Deletion of chromosome bands 11q22-q23 in lymphoproliferative disorders and the genetics of mantle cell lymphoma Ying Zhu Department of Medical Genetics Haartman Institute University of Helsinki Helsinki, Finland Academic Dissertation To be publicly discussed with the permission of the Faculty of Medicine of the University of Helsinki, in the Small Lecture Hall of the Haartman Institute on April 10 th , 2002, at 12:00 noon. Helsinki 2002 SUPERVISED BY: Professor Sakari Knuutila, Ph.D. Department of Medical Genetics Haartman Institute University of Helsinki Professor Heikki Joensuu, M.D., Ph.D. Department of Oncology Helsinki University Central Hospital REVIEWED BY: Docent Tarja-Terttu Pelliniemi, M.D., Ph.D. Department of Haematology Turku University Central Hospital Docent Maija Wessman, Ph.D. Department of Biosciences Division of Genetics University of Helsinki OFFICIAL OPPONENT: Docent Soili Kytölä, Ph.D. Institute of Medical Technology University of Tampere ISBN 952-91-4512-8 (print) ISBN 952-10-0481-9 (pdf) http://ethesis.helsinki.fi Helsinki 2002 Yliopistopaino Table of Content 1 List of original publications................................................................................................5 2 Abbreviations........................................................................................................................6 3 Abstract.................................................................................................................................7 4 Introduction..........................................................................................................................8 5 Review of the literature.......................................................................................................9 5.1 Lymphocytic malignancies............................................................................................9 5.1.1 Classification of lymphoma.................................................................................9 5.1.2 Mantle cell lymphoma.......................................................................................12 5.1.3 Chronic lymphocytic leukemia..........................................................................13 5.2 11q and genetic aberrations in non-Hodgkin’s lymphoma.......................................15 5.2.1 Genes and abnormalities in 11q.........................................................................15 5.2.2 Chromosomal abnormalities in non-Hodgkin’s lymphoma.............................19 5.2.3 Genetic aberrations in mantle cell lymphoma...................................................22 5.2.4 Genetic aberrations in chronic lymphocytic leukemia.....................................22 5.3 Recent technological advances in molecular cytogenetics........................................24 5.3.1 Chromosome banding analysis..........................................................................24 5.3.2 FISH...................................................................................................................24 5.3.3 Other FISH-based techniques............................................................................26 5.3.4 Array technology................................................................................................27 6 Aims of the study................................................................................................................30 7 Material and methods........................................................................................................31 7.1 Patients........................................................................................................................ 31 7.2 Immunohistochemistry (study I-V) .............................................................................35 7.3 G-banding analysis (study II and III).........................................................................35 7.4 Interphase fluorescence in situ hybridization (studies I – III).........................35 7.4.1 Sample preparation............................................................................................35 7.4.2 Probes.................................................................................................................36 7.4.3 Dual-color and single-color FISH.....................................................................37 7.5 RNA and DNA extraction (study IV and V)................................................................38 7.6 RT-PCR analysis (study IV)........................................................................................39 7.7 PCR-SSCP analysis (study IV)...................................................................................39 7.8 Sequencing PCR products (study IV).........................................................................40 7.9 Southern blotting analysis (study IV).........................................................................40 7.10 PAGE analysis (study IV)...........................................................................................40 7.11 cDNA array analysis (study V)...................................................................................40 7.12 Gene expression data analysis (study V)....................................................................41 7.13 Real-time PCR analysis (study V)..............................................................................43 8 Results..................................................................................................................................43 8.1 Deletion in chromosome bands 11q22-q23 in mantle cell lymphoma (study I) .......44 8.2 Discontinuous deletion in 11q23 in chronic lymphocytic leukemia (study II)..........44 8.3 Deletion in 11q23 in different lymphoma subtypes (study III)..................................45 8.4 Mutation analysis of the PPP2R1B gene (study IV)..................................................46 8.5 The gene expression profiles of MCL and its blastoid variant (study V)..................47 9 Discussion............................................................................................................................49 9.1 Discussion of the techniques applied.........................................................................49 9.2 The minimal common region of deletion in 11q22-q23 (study I, II).........................52 9.3 The second critical region in 11q22-q23 (study I, II)................................................53 9.4 The 11q23 deletion in different lymphoma subtypes (study I, II, III)........................54 9.5 The role of the PPP2R1B gene in MCL and CLL (study IV).....................................56 9.6 Marker genes identified by array analysis in MCL (study V)...................................57 10 Concluding remarks and perspectives............................................................................60 11 Acknowledgements.............................................................................................................62 12 References...........................................................................................................................64 5 1 LIST OF ORIGINAL PUBLICATIONS This thesis is based on the following original publications: I Monni O, Zhu Y, Franssila K, Oinonen R, Höglund P, Elonen E, Joensuu H, Knuutila S. Molecular characterization of deletion at 11q22.1-23.3 in mantle cell lymphoma. Br J Haematol 1999, 104, 665-671. II Zhu Y, Monni O, El-Rifai W, Siitonen SM, Vilpo L, Vilpo J, Knuutila S. Discontinuous deletions at 11q23 in B cell chronic lymphocytic leukemia. Leukemia 1999, 13, 708-712. III Zhu Y, Monni O, Franssila K, Elonen E, Vilpo J, Joensuu H, Knuutila S. Deletions at 11q23 in different lymphoma subtypes. Haematologica 2000, 85, 908- 912. IV Zhu Y, Loukola A, Monni O, Kuokkanen K, Franssila K, Elonen E, Vilpo J, Joensuu H, Kere J, Aaltonen L, Knuutila S. PPP2R1B gene in chronic lymphocytic leukemias and mantle cell lymphomas. Leuk Lymph 2001, 41, 177-183. V Zhu Y, Hollmén J, Oinonen R, Aalto Y, Elonen E, Kere J, Mannila H, Franssila K, Knuutila S. Gene expression profiling in mantle cell lymphoma and its blastoid variant. Submitted. The publications are referred to by their Roman numerals in the text. 6 2 ABBREVIATIONS BAC bacteria artificial chromosome CLL chronic lymphocytic leukemia cDNA complementary deoxyribonucleic acid CGH comparative genomic hybridization DAPI 4', 6-diamidino-2-phenylindole dATP deoxyadenosine triphosphate dCTP deoxycytidine triphosphate DLBCL diffuse large B-cell lymphoma DNA deoxyribonucleic acid dUTP deoxyuridine triphosphate FISH fluorescence in situ hybridization FITC fluorescein-isothiocyanate FL follicular lymphoma HL Hodgkin lymphoma kb kilobase kD kilodalton LOH loss of heterozygosity MALT mucosa-associated lymphoid tissue Mb megabase MCL mantle cell lymphoma mRNA messenger ribonucleic acid MSC mechanically stretched chromosome NHL non-Hodgkin’s lymphoma NK natural killer p chromosome short arm PAC P1 artificial chromosome PAGE polyacrylamide gel electrophoresis PCA principal component analysis PCR polymerase chain reaction PGL paraganglioma q chromosome long arm RNA ribonucleic acid REAL A revised European-American classification for lymphoid neoplasms RT-PCR reverse transcription polymerase chain reaction SDS sodium dodecyl sulfate SLL small lymphocytic lymphoma SSC standard saline citrate SSCP single strand conformation polymorphism TBE Tris-borate/EDTA electrophoresis buffer TRITC tetra-rhodamine-isothiocyanate WHO World Health Organization YAC yeast artificial chromosome 7 3 ABSTRACT Chromosome bands 11q22-q23 have been found frequently deleted in a number of solid tumors and lymphoproliferative disorders, suggesting the existence of tumor suppressor gene(s) in this area. This abnormality has been found in mantle cell lymphoma (MCL) and chronic lymphocytic leukemia (CLL) by comparative genomic hybridization studies (Karhu et al., 1997; Monni et al., 1998). By using the samples from MCL and CLL patients, we wanted to identify the minimal common region of deletion in 11q22-q23 and the candidate gene in the region. We also wanted to study the occurrence of the deletion in 11q22-q23 in different types of lymphoma. Because MCL is a relatively newly identified disease entity whose molecular background is not well known, it was also our aim to study the gene expression profiles of MCL and its blastoid variant. Altogether we studied samples from 158 lymphoma or leukemia patients. One hundred and fifty-two samples were studied using fluorescence in situ hybridization (FISH) with YAC (yeast artificial chromosome) probes from 11q22.1-q23.3. Two critical regions were identified in 11q22-q23, one represented by YAC755b11 and the other by YAC785e12. The presence of the deletion in 11q23 is frequent in MCL, and the abnormality is present in a small fraction of CLL/SLL (small lymphocytic lymphoma) and diffuse large B-cell lymphoma cases. Our results showed the possible correlation of the deletion in 11q23 with the development of leukemia from localized lymphoma, and with the development of the Richter’s syndrome. One candidate gene in 11q23, the PPP2R1B gene, was examined. The mutation analysis of this gene has suggested that the pathogenic role of the PPP2R1B gene in MCL and CLL is probably minor and it is not likely to be the target of the deletion in 11q23. In study V, we used the cDNA array technology to study the gene expression profiles of common and blastoid variant MCL. We studied 18 samples from MCL patients and identified marker genes for both common and blastoid variant MCL. We also created a disease subtype (common vs blastoid variant) classifier, which might be helpful in the differential diagnosis of MCL. Some of the results obtained from this thesis work have already been utilized in the diagnosis of lymphomas. 8 4 INTRODUCTION Non-Hodgkin’s lymphoma (NHL) is a heterogeneous group of neoplasms of the immune system with distinct morphological, immunohistochemical, genetic and clinical features. To correctly classify and diagnose different subgroups of NHL is essential in order to treat the patients successfully. One of the important criteria for lymphoma classification and diagnosis is the genetic abnormality associated with different lymphoma subgroups. It is widely acknowledged that cancer is a genetic disease, resulting from the accumulation of gene mutations. At the microscopic level, it is manifested by the structural abnormalities of the chromosomes. Research conducted over the past 30 years has shown that clonal chromosomal abnormalities in tumor cells are distributed non- randomly throughout the genome. Different neoplasms have distinctive chromosomal abnormality profiles involving different chromosomes, chromosomal arms, bands and sub-band regions. On the other hand, many abnormalities are associated with certain diseases or disease subgroups only (Heim & Mitelman, 1995). In this thesis, we studied abnormalities of one particular chromosome part, namely the deletion in chromosome bands 11q22-q23, in several types of NHL, in particular mantle cell lymphoma and chronic lymphocytic leukemia. Our intention was to determine the molecular background of this abnormality and to investigate any clinical correlation it might have. We further studied mantle cell lymphoma on the gene expression level in order to understand more about the pathogenesis of this disease. Modern genetic research is characterized by the technical advancement. Various novel techniques and methods enable research on both the single-gene and the genome level. Results obtained in recent years have greatly improved our knowledge of the diseases. Today, the use of many of the techniques, such as the chromosome banding analysis and the fluorescence in situ hybridization analysis, is considered an important part in disease diagnosis and prognosis. 9 5 REVIEW OF THE LITERATURE 5.1 Lymphocytic malignancies 5.1.1 Classification of lymphoma Non-Hodgkin’s Lymphoma (NHL) is a heterogeneous group of neoplasms of the immune system. The classification of NHL is not a simple task, because many different cell types are involved. Moreover, the neoplasms can originate in virtually any organ, and patients with some types of lymphoma can develop leukemia. It is of great importance to correctly classify and diagnose the different subgroups of NHL in order to treat these diseases successfully. A common system of classification helps clinicians and pathologists all over the world to communicate and exchange information. Since 1925, at least 25 classification systems have been developed for NHL. The ones that can be regarded as milestones are the Rappaport classification (Rappaport, 1966), the Kiel classification (Lennert, 1978; Stansfeld et al., 1988), the Lukes and Collins classification (Lukes & Collins, 1974), the Work Formulation for Clinical Usage (Non-Hodgkin's Lymphoma Pathologic Classification Project, 1982), the Revised European-American Lymphoma (REAL) classification (Harris et al., 1994) and the WHO (World Health Organization) classification (Jaffe et al., 2001). The history of NHL classification clearly reflects our increasing understanding of the nature of different subgroups of NHL. The focus of the classification criteria has gradually shifted from pure morphology or clinical behavior to include neoplastic cell morphology, immunophenotype, genetic background, normal cell counterpart and clinical features. In other words, all the current information is now used collectively to define the disease entities. The development of NHL classification also reflects the amazing technical and instrumental advances in the field over the past 40 years. New technologies allow more thorough study of the diseases, leading to a more profound understanding of them [for review see (Isaacson, 2000)]. The classification systems most widely in use now are the REAL classification and its updated version - the WHO classification (Table 1), which were both jointly drawn up by experts from Europe and the United States. In both classification systems, lymphomas are classified based on five properties: morphology, immunophenotype, genotype, normal cell counterpart and clinical features. In addition to malignancies originated from B and T cells, Hodgkin’s lymphoma and 10 malignancies originated from natural killer (NK) cells are also included. The REAL classification has been proved to be highly practical and reproducible (Lymphoma Classification Project, 1997). Many specific genetic abnormalities were associated with particular lymphoma subtypes identified by the REAL/WHO classification (Jaffe et al., 2001), proving the accuracy of the classification at the molecular level. The experience gained from developing the REAL and WHO classification could also be used in the classification of other types of cancer and will be important for the future development of lymphoma classification (Harris et al., 2000). It is clear from the history of NHL classification that there has been an evolution in the process. With the development of new technologies and the acquisition of new data, new disease entities may be identified, and uncertainties will be clarified. This is already taking place. For example, new subtypes of diffuse large B-cell lymphoma (DLBCL) have been identified using the microarray technology (Alizadeh et al., 2000) and new subtypes of chronic lymphocytic leukemia (CLL) have been recognized by analyses of the Ig V gene mutation and the expression of CD38 (Damle et al., 1999; Hamblin et al., 1999). There is also more and more information being gathered on the correlation between genetic markers and patients’ clinical behavior. It is possible that, in the future new approaches based on genetics and molecular biology may play an important role in NHL classification. 11 Table 1. The World Health Organization classification of lymphoid malignancies (Jaffe et al., 2001) B-cell neoplasms Precursor B lymphoblastic leukemia/lymphoma Chronic lymphocytic leukemia/small lymphocytic lymphoma B-cell prolymphocytic leukemia Lymphoplasmacytic lymphoma Splenic marginal zone lymphoma Hairy cell leukemia Plasma cell myeloma Monoclonal gammopathy of undetermined significance Solitary plasmacytoma of bone Extraosseous plasmacytoma Primary amyloidosis Heavy chain diseases Extranodal marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALT-lymphoma) Nodal marginal zone B-cell lymphoma Follicular lymphoma Mantle cell lymphoma Diffuse large B-cell lymphoma Mediastinal (thymic) large B-cell lymphoma Intravascular large B-cell lymphoma Primary effusion lymphoma Burkitt lymphoma/leukemia T-cell and NK-cell neoplasms Precursor T lymphoblastic leukemia/lymphoma T-cell prolymphocytic leukemia T-cell large granular lymphocytic leukemia Aggressive NK cell leukemia Adult T-cell leukemia/lymphoma Mycosis fungoides Sézary syndrome Primary cutaneous anaplastic large cell lymphoma Lymphomatoid papulosis Extranodal NK/T cell lymphoma, nasal type Enteropathy-type T-cell lymphoma Subcutaneous panniculitis-like T-cell lymphoma Angioimmunoblastic T-cell lymphoma Peripheral T-cell lymphoma, unspecified Anaplastic large cell lymphoma Blastic NK cell lymphoma Hodgkin lymphoma Nodular lymphocyte predominant Hodgkin lymphoma Classical Hodgkin lymphoma Nodular sclerosis classical Hodgkin lymphoma Mixed cellularity classical Hodgkin lymphoma Lymphocyte-rich classical Hodgkin lymphoma Lymphocyte-depleted classical Hodgkin lymphoma 12 5.1.2 Mantle cell lymphoma Mantle cell lymphoma (MCL) is a malignant non-Hodgkin’s lymphoma of B cell lineage. The normal cell counterpart of the malignant cell of MCL is the immature CD5+ virgin B cell in the mantle zone of lymphoid follicles (Harris et al., 1994). MCL has been described variously since its initial recognition in the mid-1970s, such as lymphocytic lymphoma of intermediate differentiation (Berard & Dorfman, 1974), centrocytic lymphoma (Lennert & Feller, 1990) and mantle zone lymphoma (Weisenburger et al., 1981). It was later shown (Banks et al., 1992) that these lymphomas were in fact one disease entity and given the name mantle cell lymphoma. MCL accounts for 2.5% to 4.0% of all NHL cases in the United States, and 7% to 9% in Europe (Weisenburger & Armitage, 1996). MCL patients are characterized by advanced age, male predominance, presentation at advanced stages, and frequent involvement of bone marrow, peripheral blood and other external sites (Fisher et al., 1995; Norton et al., 1995; Teodorovic et al., 1995; Velders et al., 1996; Argatoff et al., 1997). The median survival of MCL patients is only 3 to 4 years in most large- scale series, even after combination chemotherapies for aggressive lymphomas (Oinonen et al., 1998), so that MCL is regarded as an incurable disease. The common form of MCL is characterized by small to medium-sized lymphocytes with scant cytoplasm. The nuclei usually have slightly irregular-contours with dispersed chromatin and inconspicuous nucleoli (Harris et al., 1994). As in chronic lymphocytic leukemia (CLL), CD5 and pan B-cell antigens (CD19, CD20, CD22, and CD24) are usually co-expressed on MCL neoplastic cells. The feature distinguishing MCL cells from CLL cells is the expression of CD23, which is positive for CLL and usually negative for MCL. CD20 and immunoglobulin light chain expression is usually strong in MCL and weak in CLL, which is also a useful distinction. However, exceptions have been identified in both diseases. In addition to the common form of MCL, a so-called large cell or blastoid variant of the disease has been identified (Jaffe et al., 1987; Fisher et al., 1995; Ott et al., 1997). Greiner et al. described three subtypes of the variant form of MCL: blastic; anaplastic; and centrocytoid-centroblastic (Greiner et al., 1996), whereas Ott et al. identified only two types of variant (lymphoblastoid and pleomorphic variant) based on morphology (Ott et al., 1997). Regardless of the morphological sub-classification, the feature distinguishing blastoid variant MCL from the common MCL is the high mitotic rate 13 (Jaffe et al., 1987; Ott et al., 1994; Fisher et al., 1995). Around 30% of MCL patients develop the more aggressive blastoid variants that progress more rapidly and shorten survival (Norton et al., 1995; Greiner et al., 1996). 5.1.3 Chronic lymphocytic leukemia Historically, chronic lymphocytic leukemia (CLL) has two subtypes: B-cell chronic lymphocytic leukemia (B-CLL) and T-cell chronic lymphocytic leukemia (T-CLL). About 97% of CLL cases are B-CLL (Bennett et al., 1989). In the WHO lymphoma classification, however, CLL is recognized as a B-cell neoplasm only. The disease previously known as T-CLL is now recognized as T-cell prolymphocytic leukemia or large granular lymphocyte leukemia (Jaffe et al., 2001). Here we will use the term CLL as defined by the WHO lymphoma classification. Small lymphocytic lymphoma (SLL) cases have the same tissue morphology and immunophenotype as CLL cases. CLL involves primarily bone marrow and peripheral blood, while SLL is usually non- leukemic, although exceptions exist in both diseases. Therefore, CLL and SLL are considered one disease entity (Harris et al., 1994; Jaffe et al., 2001). CLL is the most common leukemia in adults in western countries and accounts for one fourth of all leukemia cases (Rozman & Monserrat, 1995). CLL affects mostly elderly patients, only 10% to 15% of patients are younger than 50 years at the time of diagnosis. There is a gender bias so that the disease affects more men than women (ratio approximately 2:1). Although the cause of the disease is not completely understood, one suggestion is the failure of malignant cells to undergo apoptosis. It has been shown that CLL patients accumulate mature monoclonal CD5+ lymphocytes and that these cells are arrested in the G 0 /G 1 phase of the cell cycle (Bannerji & Byrd, 2000). The immunophenotype of typical CLL malignant cells are: weak IgM or IgM and IgD, CD5+, CD19+, weak CD20, weak CD22, CD79a+, CD23+, CD43+, weak CD11c, CD10-, cyclin D1-, and FMC7 and CD79b negative or weakly expressed. Matutes et al. (1994) developed a scoring system for differential diagnosis of CLL from other types of B-cell leukemia based on the immunophenotype. Typical CLL case has a score of five, which means CD22-, CD23+, CD5+, FMC7- and undetectable or weak Igκ/λ (Matutes et al., 1994). 14 The normal cell counterpart of the leukemia cells in CLL was originally thought to be the virgin B cell. However, recent studies have shown that the normal cell counterpart is the virgin B cell in only about 50% of cases of CLL, and that it is the memory B cell in the other cases (Damle et al., 1999; Hamblin et al., 1999). The same studies have shown that the disease is less malignant in those cases where the normal cell counterpart is the memory B cell, than when the normal cell counterpart is the virgin B cell. CLL is usually considered an incurable disease with currently available therapies. The clinical course of CLL is in general indolent, but varies a lot among patients. Some patients can live asymptomatically for many years, while others die within five years after diagnosis. There are two staging systems – Rai and Binet – in use for predicting the survival. The Rai staging system defines five stages (0-IV) with increasingly worse prognosis: lymphocytosis alone (stage 0); lymphocytosis, lymphadenopathy (stage I); lymphocytosis, spleen or liver enlargement or both (stage II); lymphocytosis, anemia with hemoglobin less than 11.0 g/dl (stage III); lymphocytosis, thrombocytopenia with platelet count less than 100,000 /mm 3 (stage IV) (Rai et al., 1975). The Binet staging system defines three stages (A-C) with increasingly worse prognosis: no anemia, no thrombocytopenia, less than three areas enlarged (A); no anemia, no thrombocytopenia, three or more areas enlarged (B); anemia with hemoglobin less than 10.0 g/dl, or thrombocytopenia with platelet count less than 100,000/mm 3 , or both (C) (Binet et al., 1981). Around 3.5% of CLL cases transform to high-grade lymphoma, a process referred to as Richter’s syndrome (Richter, 1929; Foucar, 1992). Around 3% of the Richter’s syndrome cases transform to diffuse large B-cell lymphoma, and the rest transform to lymphomas resembling Hodgkin’s lymphoma. 15 5.2 11q and genetic aberrations in non-Hodgkin’s lymphoma 5.2.1 Genes and abnormalities in 11q Chromosome 11 represents about 4.8% of the relative autosome length, is estimated to be 144 Mb in size, and has 997 genes assigned to it. The long arm of chromosome 11, 11q, is estimated at around 90 Mb and has 673 genes assigned to it (http://www.ncbi.nlm.nih.gov). Genes are non-uniformly distributed along 11q, clustering mostly in three regions, 11q13, 11q22-q23 and 11q24. Proto-oncogenes EMS1, FGF3 (INT2), FGF4 (HST), CCND1 (PRAD1), BCL1 and GSTP1 are located in 11q13. The candidate gene for MEN1 (multiple endocrine neoplasia type 1) has been localized to 11q13.1 (Chandrasekharappa et al., 1997), as has PGL2, one of the two paraganglioma (PGL) candidate genes located on chromosome 11q (Mariman et al., 1993). The translocation t(11;22)(q24;q12), present in about 90% of cases of Ewing’s sarcoma and neuroepithelioma (Turc et al., 1984), involves the oncogene FLI1 in 11q24 (Hromas et al., 1993). The gene encoding the protein kinase CHK1, a checkpoint protein for the G2 to M phase transition, is located in 11q24 (Sanchez et al., 1997). In 11q24 there is also the ETS1 gene, which is homologous to the viral ets oncogene of the E26 virus, and acts as a transcription factor in regulating cell proliferation, differentiation, lymphoid cell development, angiogenesis and apoptosis (Li et al., 1999). Chromosome bands 11q22-q23 are frequently involved in translocations and deletions in a variety of neoplasms. Figure 1 shows the schematic integrated physical map of this region (Arai et al., 1996). The most common chromosomal translocations in this region are those involving the MLL gene, of which more than 40 different ones have been described and 19 partner genes have been cloned (Osaka et al., 1999; Schreiner et al., 1999). These translocations are present in about 5% of patients with acute myeloid leukemia, and up to 10% of patients with acute lymphocytic leukemia (Kaneko et al., 1986). In addition, they are seen in up to 80% of cases of infant acute myeloid leukemia and acute lymphocytic leukemia (Heerema et al., 1994). Around 85% of patients with topoisomerase II inhibitor-related secondary leukemia have these translocations (Pedersen-Bjergaard & Rowley, 1994). Cytogenetic and loss of heterozygosity (LOH) analyses have shown that chromosome bands 11q22-q23 are frequently deleted in a number of solid tumors 16 (breast, cervical, ovarian, gastric, lung, bladder, prostate, nasopharyngeal, squamous and colorectal carcinomas; malignant melanomas and intracerebral neoplasms) (Foulkes et al., 1993; Keldysh et al., 1993; Carter et al., 1994; Hampton et al., 1994a; Hampton et al., 1994b; Bethwaite et al., 1995; Gabra et al., 1995; Herbst et al., 1995; Iizuka et al., 1995; Koreth et al., 1995; Negrini et al., 1995; Rasio et al., 1995; Shaw & Knowles, 1995; Winqvist et al., 1995; Baffa et al., 1996; Blaeker et al., 1996; Davis et al., 1996; Gabra et al., 1996; Hui et al., 1996; Tomlinson & Bodmer, 1996; Uzawa et al., 1996; Dahiya et al., 1997; Koreth et al., 1997), as well as in lymphoproliferative disorders (Heim & Mitelman, 1995). These results strongly suggest the presence of tumor suppressor gene(s) in this region. Functional evidence for the existence of tumor suppressor gene(s) in 11q has been provided by microcell fusion experiments involving the transfer of normal chromosome 11 or part of it into malignant melanoma, breast, lung, cervical and ovarian cancer cell lines. Transfer of the whole chromosome 11, the chromosome bands 11q13-q23 or their fragments suppressed the in vitro growth of the cells (Gioeli et al., 1997), and the in vivo tumorigenesis (Negrini et al., 1994; Zenklusen et al., 1995; Robertson et al., 1996; Murakami et al., 1998) and metastatic potentials (Phillips et al., 1996) of the cells in nude mice. While the length of the deleted regions varies between tumor types, two minimum common regions of deletion (common to three or more tumor types) were found in 11q22.3-q23.1 and 11q23.2-q23.3. The minimal common region of deletion in 11q22.3-q23.1 has been found to be 2-3 Mb in size, and contain the ATM gene and a region represented by YAC755b11 (Stilgenbauer et al., 1996; Koreth et al., 1999). Other studies showed that the minimal critical region was only the region represented by YAC755b11 (1.6 Mb in size) (Monni et al., 1999; Zhu et al., 1999). ATM encodes a serine-threonine kinase belonging to a protein family related to phosphoinositide kinases which includes ATR, Mec1, Tel1 and Rad53 (Elledge, 1996). ATM detects DNA damages and activates p53, Chk2 and Mdm2 to promote apoptosis or cell cycle arrest. ATM also activates c-Abl in response to stress signals. In addition, ATM is required for DNA repair and insufficient DNA repair will lead to genomic instability (Baskaran et al., 1997; Shafman et al., 1997; Banin et al., 1998; Canman et al., 1998; Matsuoka et al., 1998; Brown et al., 1999; Johnson et al., 1999). Inactivation of the ATM gene and the corresponding loss of ATM protein function result in ataxia telangiectasia, a 17 disorder characterized by atrophy of the cerebellum and thymus, immunodeficiency, premature aging, predisposition to cancer, and sensitivity to ionizing radiation (Savitsky et al., 1995). Mutations of the ATM gene have been found in CLL, MCL and T-cell prolymphocytic leukemia cases (Stilgenbauer et al., 1997; Bullrich et al., 1999; Schaffner et al., 1999; Stilgenbauer et al., 1999; Schaffner et al., 2000; Camacho et al., 2002). The PPP2R1B gene is located very close to the region represented by YAC755b11. PP2A is a regulatory enzyme that negatively regulates the MAPK cascade and has been linked to carcinogenesis (Hunter, 1995). The PPP2R1B gene has 15 exons and encodes the β isoform of the structural/regulatory A subunit of the PP2A gene. It was found to be mutated in human lung and colon cancers, and identified as a putative tumor suppressor gene (Wang et al., 1998). But no mutation was found in hereditary PGL (Baysal et al., 1998), and rarely in ovarian carcinomas (Campbell & Manolitsas, 1999; Wu et al., 1999), parathyroid hyperplasia and adenomas (Hemmer et al., 2002), CLL or MCL (Zhu et al., 2001). Therefore, its role as a tumor suppressor gene remains to be confirmed. The 11q23.2-q23.3 region was found frequently deleted in cutaneous malignant melanoma (Herbst et al., 1999), ovarian cancer (Launonen et al., 1998), cervical carcinoma (Mugica-Van Herckenrode et al., 1999), lung cancer (Wang et al., 1999), breast cancer (Launonen et al., 1999), CLL (Zhu et al., 1999) and MCL (Monni et al., 1999). A tumor suppressor gene, TSLC1 (for tumor suppressor gene in lung cancer-1), was recently identified in non-small-cell-lung cancer. This gene is located in a 100 kb area in the center of the region represented by YAC939b12 (Murakami et al., 1998; Kuramochi et al., 2001). 11q23.2 is also the region where the gene responsible for hereditary PGL is located. PGL is a rare disorder characterized by the development of mostly benign, highly vascular, slow-growing tumors in the head and neck. The succinate-ubiquinone oxidoreductase subunit D gene (SDHD) was recently identified as the hypothesized gene PGL1. SDHD is a critical component of the oxygen-sensing system of paragangliomic tissue. The loss of its function may lead to chronic hypoxic stimulation and cellular proliferation (Baysal et al., 2000). It will be interesting to examine the roles of these two genes in other types of neoplasms. A retinoid-induced class II tumor suppressor / growth regulatory gene was found to be involved in CLL and located in 11q23 (DiSepio et al., 1998). Its exact location and role in other types of cancer deserve further investigation. 18 Figure 1. Schematic physical map of the region 11q22.1-q23.3 and some important genes (below) [a modification of (Arai et al. 1996)]. 19 5.2.2 Chromosomal abnormalities in non-Hodgkin’s lymphoma Tumor cells exhibit clonal chromosomal abnormalities that are non-randomly distributed throughout the genome. It has been shown that many types of cancer have distinctive chromosomal aberration profiles, and some chromosome aberrations are unique to certain types of cancer or cancer subgroups (Heim & Mitelman, 1995). Many NHL subgroups have characteristic chromosomal translocations. For example, t(14;18)(q32;q21) is found in 70% to 90% of follicular lymphoma cases, resulting in deregulation of the oncogene BCL2 (Tsujimoto et al., 1985). MCL is characterized by t(11;14)(q13;q32), which is found in 50% to 70% of cases and involves the oncogene BCL1 (Weisenburger & Armitage, 1996). t(8;14)(q24;q32) is found in 75% to 85% of Burkitt’s lymphoma and involves the CMYC gene (Dalla- Favera et al., 1982). The translocation t(9;22)(q34;q11) creates an oncogenic fusion gene BCR-ABL, and is found in 85% of cases of chronic myeloid leukemia and 15%- 20% of cases of acute lymphocytic leukemia (Heim & Mitelman, 1995). Trisomies of chromosomes 3, 7, 12 and 18 have been found in NHL with varying frequencies (Heim & Mitelman, 1995). Other chromosomal amplifications detectable using cytogenetic analysis techniques, such as double minute chromosomes and homogeneously staining regions, are rarely detected in NHL (Ben-Yehuda et al., 1994). Comparative Genomic Hybridization (CGH) studies have revealed several highly amplified regions in NHL, and oncogenes in these regions were also found to be amplified [reviewed by (Knuutila et al., 1998)]. The most common chromosome deletion sites in NHL include 6q, 11q, 13q and 14q (Heim & Mitelman, 1995). In addition, CGH studies have found frequent chromosome deletions in 1p, 8p, 9p, 12p, 12q and 17p in NHL (Knuutila et al., 1999). The characteristic chromosomal aberrations in NHL detected by chromosome banding analysis are summarized in Table 2. Recurrent observation of deletion in a chromosome in tumor samples by cytogenetic analysis often indicates the existence of a putative tumor suppressor gene. Tumor suppressor genes encode proteins that function in cell growth regulatory or differentiation pathways, and loss of their function induces cells to develop malignant phenotypes (Vogelstein & Kinzler, 1998). The loss of function of tumor suppressor genes usually follows the “two-hit” model originally proposed to explain the 20 development of retinoblastoma by Alfred Knudson (Knudson, 1971). According to this model, two mutagenic events (hits) are required for the tumor suppressor genes to stop functioning. In familial cancers, the first hit is present in the germline and the second hit comes as a somatic mutation. In sporadic cancers, both mutagenic events are somatic. Inactivation of a tumor suppressor gene often occurs through the deletion of one allele and mutation of the other. In addition to cytogenetic analysis, tumor suppressor genes can also be identified through DNA linkage analyses attempting to locate genes involved in an inherited predisposition to cancer, and through LOH or allelic loss studies (Vogelstein & Kinzler, 1998). Examples of known and putative tumor suppressor genes have been summarized by Knuutila et al. (1999). Table 2. Characteristic chromosomal aberrations in malignant lymphoma and lymphocytic leukemia [a modification of (Heim & Mitelman, 1995)] Rearrangement Gene(s) involved Types of lymphoma / Leukemia 1p and 1q rearrangements ? Variable B- or T-cell NHL, Hodgkin lymphoma, multiple myeloma, plasma cell leukemia t(1;19)(q23;p13) E2A;PBX1 Acute lymphocytic leukemia t(2;3)(p12;q27) IGK;LAZ3/BCL6 Diffuse large B-cell or follicular lymphoma t(2;5)(p23;q35) ALK;NPM Ki-1 lymphoma t(2;8)(p12;q24) IGK;MYC Burkitt lymphoma, acute lymphocytic leukemia t(2;18)(p12;q21) IGK;FVT1 Follicular lymphoma +3 ? Variable B- or T-cell NHL 3q rearrangements ? Variable B- or T-cell NHL, Hodgkin lymphoma t(3;14)(q27;q32) LAZ3/BCL6;IGH Diffuse large B-cell or follicular lymphoma t(3;22)(q27;q11) LAZ3/BCL6;IGL Diffuse large B-cell or follicular lymphoma 6p rearrangements ? T-cell NHL del(6q) ? Variable, mostly B-cell NHL, Hodgkin lymphoma, acute lymphocytic leukemia, chronic lymphocytic leukemia, hairy cell leukemia, T-cell prolymphocytic leukemia +7 ? Variable B- or T-cell NHL 7q rearrangements ? Hodgkin lymphoma 21 t(8;14)(q24;q32) MYC;IGH Burkitt lymphoma, acute lymphocytic leukemia t(8;22)(q24;q11) MYC;IGL Burkitt lymphoma, acute lymphocytic leukemia 9q rearrangements ? Variable B- or T-cell NHL t(9;14)(p13;q32) PAX5;IGH Small lymphocytic lymphoma t(9;22)(q34;q11) BCR;ABL Acute lymphocytic leukemia t(10;14)(q24;q11) HOX11;TCRD T-cell acute lymphocytic leukemia t(10;14)(q24;q32) LYT10;IGH Variable B-cell NHL del(11q) ? Chronic lymphocytic leukemia, mantle cell lymphoma t(11;14)(q13;q32) BCL1/PRAD1;IGH Mantle cell lymphoma, chronic lymphocytic leukemia, multiple myeloma, plasma cell leukemia t(11;18)(q21;q21) ? Small lymphocytic lymphoma, mucosa-associated lymphoid tissue (MALT) lymphoma rearrangement of 11q23 MLL; multiple fusion genes Acute lymphocytic leukemia +12 ? Small lymphocytic or diffuse large B-cell lymphoma, chronic lymphocytic leukemia, B-cell prolymphocytic leukemia 12p rearrangements ? Hodgkin lymphoma 13p rearrangements ? Hodgkin lymphoma del/+(13q) ? Chronic lymphocytic leukemia 14q+ ? Chronic lymphocytic leukemia, B-cell prolymphocytic leukemia, hairy cell leukemia, multiple myeloma, plasma cell leukemia 14q11 rearrangements TCRA;TCRD T-cell NHL, T-cell prolymphocytic leukemia del(14q) ? Variable B- or T-cell NHL 14q32 rearrangements IGH Variable B-cell NHL, Hodgkin lymphoma t(14;18)(q32;q21) IGH;BCL2 Follicular or diffuse large B- cell lymphoma del(17p) ? Chronic lymphocytic leukemia +18 ? Variable B- or T-cell NHL t(18;22)(q21;q11) BCL2;IGL Follicular lymphoma -X/+X/-Y ? Variable B- or T-cell NHL 22 5.2.3 Genetic aberrations in mantle cell lymphoma Over-expression of cyclin D1 is a characteristic feature of MCL. A recent study by Yatabe et al. showed that 85% of MCL cases were cyclin D1 positive. They suggested that the cyclin D1 positive and negative cases might actually represent different disease entities, with the cyclin D1 positive cases representing typical MCL, while the cyclin D1 negative cases could be better described as “cyclin D1-negative MCL-like B-cell lymphoma” cases (Yatabe et al., 2000). The over-expression of cyclin D1 in more than 70% of the cases are caused by the t(11;14) chromosomal translocation (Williams et al., 1992). MCL was also found to be characterized by the inactivation of the ATM gene (Stilgenbauer et al., 1999; Schaffner et al., 2000; Camacho et al., 2002). P53 mutations were found in some MCL cases, and it was suggested that these mutations were correlated with a poor prognosis (Greiner et al., 1996). In the blastoid variants of MCL, abnormalities of the cyclin-dependent kinase inhibitor genes P16 INK4a and P21 Waf1 , were also found (Pinyol et al., 1997; Pinyol et al., 1998). CGH studies have shown that MCL cases have a rather different pattern of chromosomal alterations compared to ones detected in other types of NHL. The most common abnormalities were recurrent gains in 3q, 7p, 8q, 12q, 15q, 18q and 9q34, and losses in 1p, 6q, 9p, 10p14-p15, 11q14-q23, 13 and 17p (Monni et al., 1998; Beà et al., 1999). Blastoid variant MCL was found to have increased number of chromosomal imbalances, high-level DNA amplifications, and a tendency to be tetraploid (Ott et al., 1997; Beà et al., 1999). 5.2.4 Genetic aberrations in chronic lymphocytic leukemia CLL has been reported in ataxia telangiectasia families (Swift et al., 1987), although no evidence of linkage between CLL and the ATM gene was found (Bevan et al., 1999). Somatic deletion or point mutation affecting both alleles of the ATM gene have been reported (Schaffner et al., 1999). Germ line mutations of the ATM gene have also been found in one third of CLL patients (Bullrich et al., 1999), and total or partial inactivation of ATM protein in up to 40% of patients (Stankovic et al., 1999). Patients with decreased expression of the ATM protein have more aggressive disease and shorter survival (Starostik et al., 1998). In about 95% of cases of CLL there is increased expression of the BCL2 oncogene, due to DNA hypomethylation in the BCL2 promoter region (Hanada et al., 1993). Mutations of the P53 tumor suppressor 23 gene were seen in 15% of patients and patients with P53 mutations had more aggressive disease (Cordone et al., 1998). Some CLL patients have leukemic cells showing high-level expression of P27 Kip1 , whose protein product normally decreases as a cell progresses into S phase. Such patients may have shorter blood lymphocyte doubling time and shorter survival than the average CLL patient (Vrhovac et al., 1998). Chromosome banding analysis reveals clonal chromosome aberrations in around 40-50% of CLL patients (Juliusson & Gahrton, 1990; Juliusson et al., 1991). This technique is likely to underestimate the prevalence of clonal chromosome aberrations because the leukemic cells have low spontaneous mitotic activity and respond poorly to mitogenic stimulation (Autio et al., 1987). When mitogenic stimulation is optimized, clonal chromosome aberrations were found in up to 79% of CLL patients (Larramendy et al., 1998). CGH and interphase fluorescence in situ hybridization (FISH) techniques have also greatly facilitated the detection of chromosomal aberrations in CLL. The most frequent chromosomal aberrations were found to be deletions in 13q, 11q, 6q and 17p, and trisomy 12 (Döhner et al., 1999). The aberration in 13q mainly involves the chromosome band 13q14, where the retinoblastoma tumor suppressor gene (RB1) resides. It has been speculated that RB1 could have a pathogenic role in CLL, but the results so far have been contradictory. The pathogenic gene is thought more likely to be located distal to RB1 and efforts at positional cloning have been made (Liu et al., 1997; Corcoran et al., 1998; Stilgenbauer et al., 1998). Patients with the 11q deletion were shown to represent a subset of CLL characterized by extensive nodal involvement and poor prognosis (Döhner et al., 1997). Recently, cDNA microarray analysis has revealed a distinctive gene expression profile for CLL patients with the 11q23 deletion (Aalto et al., 2001). Trisomy 12 was the most frequent chromosomal aberration found using chromosome banding analysis, with the frequency ranging from approximately 7% to more than 25% (Juliusson & Gahrton, 1990). Trisomy 12 was shown to be related to atypical morphology and poor prognosis (Escidoer et al., 1993; Que et al., 1993; Criel et al., 1994; Matutes et al., 1996). Patients with deletions in chromosome 17 usually have the poorest prognosis and this aberration is the only one of independent prognostic value (Bentz et al., 1999; Döhner et al., 2000). 24 5.3 Recent technological advances in molecular cytogenetics 5.3.1 Chromosome banding analysis The chromosome banding technique was first introduced in 1968 (Caspersson et al., 1968), and has ever since played a central role in genetic research and clinical applications (Heim & Mitelman, 1995). However, cytogenetic analysis is sometimes very problematic due to the difficulties in obtaining high quality metaphase or prometaphase spreads of dividing neoplastic cells, in order to fix and stain the chromosomes properly before the microscopic examination, especially in solid tumors. Consequently, chromosome banding analysis data for neoplasms are the most abundant for leukemias (63%), followed by solid tumors (27%) and lymphomas (10%) (Mitelman, 1994). In addition, chromosome structural rearrangement involving segments smaller than a band (around 10 Mb) cannot be detected using the banding analysis (Heim & Mitelman, 1995, page 24). 5.3.2 FISH The FISH analysis utilizes the specific base pairing of two complementary nucleic acid sequences, one from the probe and the other from the target that is fixed on a microscopic slide. The interaction between the probe and the target can be visualized under the microscope through direct or indirect fluorescence labeling of the probe. The FISH technique is widely used in chromosome structure studies and for genome mapping. Probes The probes used in FISH can be broadly assigned to two groups: the probes for repetitive sequences and the locus-specific probes. Examples of probes for repetitive sequences are the centromere specific probes. Chromosome centromere specific probes have been developed for all human chromosomes except chromosomes 13 and 21. Other locations that provide good hybridization targets using probes for repetitive sequences are the distal end of chromosome 1p (Buroker et al., 1987) and the long arm of the Y chromosome (Lau & Schonberg, 1984). Locus-specific probes identify unique sequences of individual genes or genomic loci. These probes are available in vectors of plasmid, phage, cosmid (Feiss 25 et al., 1982), P1 (Sternberg, 1990), PAC (P1 derived artificial chromosome) (Ioannou et al., 1994), BAC (bacterial artificial chromosome) (Shizuya et al., 1992), or YAC (yeast artificial chromosome) clones (Burke et al., 1987). These host vectors allow inserts of different sizes to be conveniently incorporated, from a few kb of plasmid or phage clones, to 35-40 kb of cosmid clones, to 80-100 kb of P1 clones, to 100-200 kb of PAC clones, to 100-300 kb of BAC clones, and up to 300-2000 kb of YAC clones. These large-sized locus-specific probes have greatly facilitated the physical mapping of the genome. YAC contig maps covering the whole human genome have been constructed. However, YAC probes are relatively unstable, having low cloning efficiencies and a high degree of chimerism (Cohen et al., 1993). A transformation associated recombination method that utilizes Alu and LINE repetitive elements of the human genome has been used in the production of YAC probes to lower the level of chimerism (Larionov et al., 1996). P1, PAC and BAC probes also provide more stable alternatives to YAC probes. In addition to physical mapping, the locus-specific probes have been widely used in molecular genetic studies (discussed below), as well as for constructing bar code systems (Uhrig et al., 1999) and matrix-CGH systems (Solinas- Toldo et al., 1997). Targets The relaxation level of the target DNA affects the detection resolution. DNA is mostly tightly packed at metaphase and can be resolved to 1-2 Mb (Pinkel, 1999). Mechanically stretched chromosomes (MSCs) have a better resolution of approximately 200 kb (Laan et al., 1995). However, the resolution of MSCs is not uniform across different chromosomes and chromosome regions (Laan et al., 1995). Different methods have been used to produce free DNA fibers on microscopic slides as targets and they are termed as fiber-FISH techniques (Florijn et al., 1995). The resolution using fiber-FISH is around 1 kb (Heiskanen et al., 1996). Another important use of FISH is to obtain information from interphase nuclei where metaphase spreads are difficult to obtain. Interphase FISH has a resolution level of 50 kb-1 Mb (Trask et al., 1989). Studies using FISH Centromere specific probes are often used to detect the chromosome copy number in interphase nuclei (Cremer et al., 1986) or in prenatal diagnosis where numerical 26 aberrations are the most common abnormalities (Klinger et al., 1992). FISH technique has been used to study the interphase chromosome topography (Emmerich et al., 1989), the spatial relationship between different satellite regions within a chromosome (Rocchi et al., 1991), different models of chromosome aberrations (Lucas & Sachs, 1993), the DNA replication (Rosenberg et al., 1995), numerical aberrations and translocations in metaphase and interphase nuclei (Tkachuk et al., 1990; Losada et al., 1991; Ried et al., 1992), the non-disjunction in sperm (Williams et al., 1993), and the aneusomy in sperm (Spriggs et al., 1995; Martin et al., 1996; Spriggs et al., 1996). The FISH technique has also been applied to determine the location of YAC and cosmid clones by using metaphase, prophase and interphase chromosomes (Lichter et al., 1990; Inazawa et al., 1994; Windle et al., 1995). The location and structure of many genes have been studied using FISH on MSCs and DNA fibers (Vrolijk et al., 1996; Wang et al., 1996). 5.3.3 Other FISH-based techniques CGH To cope with the shortcomings of the banding analysis, the CGH technique was invented in 1992 (Kallioniemi et al., 1992; du Manoir et al., 1993). CGH is used to measure the relative abundance of tumor DNA along each chromosome. DNA copy number changes of 10-20 Mb in size can be detected accurately using CGH (Kallioniemi et al., 1994). Amplifications of smaller regions can be detected if they are at least 1 Mb in size and are more than 5-10 fold amplified. Loss of a region 10-12 Mb in size is also detectable if the loss is present in a large portion of the cell population (Bentz et al., 1998). CGH has been successfully utilized in both research and diagnosis [reviewed in (Knuutila et al., 1998; Knuutila et al., 1999)]. The main advantage of the CGH technique is that one does not need to culture the tumor cells. It helps to avoid the potential genetic alterations developed during long-term culturing and the problems associated with the low metaphase yield of malignant cells. CGH can also reveal the genetic composition of marker chromosomes, homogeneous staining regions and double minutes. The disadvantage of CGH is that balanced translocations, inversions, small deletions and polyploid karyotypes are not detectable. In addition, a DNA copy number change has to be present in at least 50% of the cells in the sample for it to be detected (Kallioniemi et 27 al., 1994). This may cause problems in heterogeneous tumors and tumors with normal cell infiltration. Multicolor fluorescence in situ hybridization To increase the sensitivity of the chromosome banding analysis, several multicolor fluorescence in situ hybridization systems were developed in the mid-90s to identify all 24 human chromosomes by different colors. The multiplex-fluorescence in situ hybridization (M-FISH) system (Speicher et al., 1996), the spectral karyotyping (SKY) system (Schröck et al., 1996) and the COmbined Binary RAtio (COBRA) labeling system (Tanke et al., 1999) utilize different labeling and detection methods to visualize each chromosome in its own color. The multicolor analysis has been successfully applied to elucidate complex chromosome rearrangements (Veldman et al., 1997). The resolution limit of these systems has not been well established. The current consensus is that aberrations smaller than 2.6 Mb in size are difficult to be detected (Haddad et al., 1998; Uhrig et al., 1999; Azofeifa et al., 2000). In addition to whole chromosome paints, multicolor analysis using locus- specific DNA probes can create artificially banded chromosomes (bar code) (Lengauer et al., 1993; Chudoba et al., 1999). The bar code system is able to increase the detection sensitivity and accuracy, yield information on mosaicism, and reveal structural rearrangements undetectable by other methods. The combined use of chromosome banding analysis, CGH, and multicolor fluorescence in situ hybridization together with the bar code system will give us the maximum cytogenetic information (Uhrig et al., 1999). 5.3.4 Array technology The array technology is a variation of in situ hybridization where hundreds or thousands of targets are attached to a small solid support. The solid support can be either filter or glass (DNA chip). The technology was developed in the late 1990s to make full use of the huge number of gene specific sequences identified by the Human Genome Project, and the abundant information on disease-related gene mutations. In the past few years, the array technology has quickly evolved into a highly technical field involving miniaturization, automation, multicolor fluorescent labeling, and database driven sample and data management (Wilgenbus & Lichter, 1999). 28 Oligonucleotide array and cDNA array In an oligonucleotide array, oligonucleotides are either synthesized directly on the surface of the chip, or pre-synthesized and then deposited onto the chip. Several in situ synthesis methods have been developed for this purpose and usually synthesize oligonucleotides of less than 25 bases long [reviewed by (Watson et al., 1998)]. In the printing method, pre-synthesized oligonucleotides are covalently attached to chemically treated glasses (Chu et al., 1983; Guo et al., 1994; Joos et al., 1997). The oligonucleotide array is suitable for comparing complementary targets with single base mismatched sequences, such as in the analysis of mutations or single-nucleotide polymorphisms and in mini-sequencing analysis. To study gene expression, multiple oligonucleotides for one gene are needed. The cDNA array technique is used to study the expression levels of a gene population. cDNA clone inserts are amplified by polymerase chain reaction (PCR) and attached to the solid support utilizing non-covalent charge interactions [reviewed by (Watson et al., 1998)]. The non-covalent nature of the interaction between the target and the solid support may result in the loss of the target clones during the hybridization reaction, leading to reduced sensitivity and inconsistency. However, because the cDNA array is relatively easy to prepare, it is widely in use nowadays. A variety of applications have been developed using oligonucleotide array and cDNA array, such as the detection of disease-relevant genes and mutations (Hacia et al., 1996; Su et al., 2000), and the characterization of single-nucleotide polymorphisms for linkage analysis (Cargill et al., 1999; Halushka et al., 1999). The technology has also been widely used in gene expression profiling of different physiological status (Ross et al., 2000), linking gene expression patterns to clinical information and cytogenetic abnormalities (Martin et al., 2000; Virtaneva et al., 2000), disease class discovery and prediction (Golub et al., 1999; Alizadeh et al., 2000; Bittner et al., 2000; Kihara et al., 2001), and profiling of the pharmacological and toxicological properties (Nuwaysir et al., 1999; Scherf et al., 2000). Matrix-CGH To overcome the limitation of the resolution in conventional CGH, the matrix-based CGH was developed, where hundreds or even thousands of genomic DNA target clones are immobilized on a solid support. The immobilized targets can be cosmid, 29 P1, PAC, BAC or YAC clones. Matrix CGH has significantly better resolution than conventional CGH. High copy number amplifications can be detected at a resolution of 10 kb and the smallest detectable low copy number gains or losses are approximately 100 kb in size (Solinas-Toldo et al., 1997; Wilgenbus & Lichter, 1999). One can also hybridize the genomic DNA directly onto cDNA arrays, which increases sensitivity to a single gene level (Heiskanen et al., 2000). The matrix CGH technique has been used in gene hunting projects (Albertson et al., 2000) and the detection of disease-relevant genomic imbalances (Bruder et al., 2001). Tissue array Another new development in the array field is the tissue array technology. Kononen et al. (1998) described a method to attach up to 1,000 tissue sections onto a slide. The tissue array can be used to study genomic DNA deletions and amplifications (Bubendorf et al., 1999), mRNA expression (Kononen et al., 1998) and tissue immunohistochemistry (Sallinen et al., 2000). The tissue array technique is often used in combination with the oligonucleotide or cDNA array technique. Genes identified in the expression profiling analysis using the oligonucleotide or cDNA microarray techniques can be verified on a tissue array composed of a large number of tumor samples (Moch et al., 1999). Data management An essential pre-requisite for the optimal use of microarray data is the development of sufficient tools for collecting, storing, retrieving and querying data, regardless of the technology platform used to generate it (Ermolaeva et al., 1998). The Microarray Gene Expression Database (MGED) group (http://www.mged.org) aims to promote the adoption of standards in array experiments and data. The group has developed recommendations for microarray data annotations. A number of different statistical methods have been investigated for array data analysis. To date, hierarchical clustering analysis has been the most commonly used algorithm applied to array analysis data (Eisen et al., 1998). Other analysis algorithms that have been applied include k-means clustering, Bayesian clustering (Golub et al., 1999), self-organizing maps (Tamayo et al., 1999) and principal component analysis (Hilsenbeck et al., 1999). 30 6 AIMS OF THE STUDY • To characterize the deletion in chromosome bands 11q22-q23 • narrowing down the minimal common region of deletion • examining the occurrence of the deletion in different lymphoma subtypes • testing of one candidate gene in the region • To study the gene expression profiles of mantle cell lymphoma and its blastoid variant 31 7 MATERIAL AND METHODS 7.1 Patients Altogether samples from 158 lymphoma or leukemia patients were included in this thesis study. Thirty-six CLL samples came from patients attending the CLL out- patient clinic at Tampere University Hospital, and the rest of the samples came from Helsinki University Central Hospital. There were altogether 53 MCL samples, 68 CLL/SLL (small lymphocytic lymphoma) samples, 17 DLBCL (diffuse large B-cell lymphoma) samples, 9 FL (follicular lymphoma) samples and 11 HL (Hodgkin lymphoma) samples. Some of the MCL and CLL/SLL samples were used in more than one study. The patient information is summarized in Table 3. One pathologist classified all the lymphoma samples according to the REAL classification (Harris et al., 1994). The diagnosis and staging of CLL were based on standard clinical, morphological and immunophenotyping criteria (Rai et al., 1975; Binet et al., 1981; Bennett et al., 1989; BCSH, 1994). The histology of the samples and methods used in each study are summarized in Table 4. Table 3. Patient information Disease type No. cases Age (average) Sex (F/M)* mantle cell lymphoma 53 45-90 (65) 20/33 chronic lymphocytic leukemia/ small lymphocytic lymphoma 68 38-84 (64) 20/48 diffuse large B-cell lymphoma 17 40-83 (65) 9/8 follicular lymphoma 9 41-75 (59) 6/3 Hodgkin lymphoma 11 10-76 (37) 7/4 *F, female; M, male. In study I, paraffin embedded samples from 41 MCL patients were studied by FISH analysis. The samples consisted of 34 primary lymphomas and eight recurrent ones. In one case, both the primary tumor and a recurrent tumor were examined. The samples were from 24 men and 17 women. The patient age at the time of the biopsy ranged from 45 to 87 years (median, 63 years). Four patients had stage I lymphoma at diagnosis, five stage II, one stage III, and 31 stage IV, according to the Ann Arbor classification (Carbone et al., 1971). Seven of the lymphomas were regarded as blastoid variants and two samples contained a mixture of blastoid morphology cells 32 and typical morphology cells. Nuclei extracted from paraffin-embedded tissue of reactive lymphatic tissues from two individuals were used as the control. In study II, heparinized peripheral blood specimens were collected from 30 CLL patients and studied by FISH analysis. Twenty-two of the patients were men and eight were women. The age of the patients ranged from 48 to 79 years (median, 64 years). The CLL-scores (Matutes et al., 1994) ranged from 3 to 5. Peripheral blood from two healthy persons was used as the control. In study III, FISH analysis was performed on 161 samples, comprising 47 MCL samples, 62 CLL/SLL samples, 17 DLBCL samples, 9 FL samples, 11 HL samples and 15 reactive or normal lymph node samples (used as controls). Forty-one MCL and 29 CLL/SLL samples were embedded in paraffin and all the others were either peripheral blood or fresh tissue samples. In study IV, 36 CLL samples and 37 MCL samples were included. Mutation analysis of the PPP2R1B gene was carried out on these samples. DNA and RNA extracted from the peripheral blood of two healthy individuals were used as controls. In study V, samples from 18 MCL patients were investigated by cDNA array analysis. The age of the patients at diagnosis ranged from 51 to 87 years (median, 65 years). There were 11 men and seven women. Fourteen of the patients (78%) were at Ann Arbor stage III-IV (Carbone et al., 1971) at diagnosis. All the samples used in this study were taken at diagnosis before any treatment. Nine lymphomas were classified as common MCL and nine as the blastoid variant. Total RNA was extracted from deep-frozen tumor tissue specimens. B-cells were purified from adenoid palatine tonsil samples from six healthy children, using microbeads conjugated to monoclonal CD 19 antibodies (Miltenyi Biotec, Bergisch Gladbach, Germany). The pooled total RNA was extracted and used as the control. 33 Table 4. Histology of the samples and the methods used in studies I – V. Disease type Total case no. Immuno- phenotypes No. of positive cases / no. of cases studied Methods Study I MCL 41 CD5+ CD19+ CD20+ CD23- IgM+ IgD+ κ+ λ+ cyclin D1+ 38/40 27/27 39/39 28/28 31/31 29/32 12/33 21/33 39/41 FISH Study II CLL 30 CD5+ CD22- CD23+ FMC7- undetectable or weak lgκ/λ 26/29 28/29 28/29 29/29 16/29 G-banding analysis, FISH Study III MCL 47 CD5+ CD20+ CD23- cyclin D1+ 44/46 45/45 30/30 43/47 G-banding analysis, FISH CLL/SLL 62 CD5+ CD20+ CD23+ 54/57 27/27 52/53 DLBCL 17 CD20+ 14/14 FL 9 CD20+ Bcl-2+ 6/6 6/7 Classic Hodgkin’s lymphoma 7 CD30+ CD15+ CD3+ 7/7 7/7 7/7 34 Lymphocyte predominant Hodgkin’s lymphoma 4 CD20+ CD15- CD30- CD3+ CD20+ (small cells in nodules) 4/4 3/4 3/4 4/4 2/4 Study IV CLL 36 CD5+ CD22- CD23+ FMC7- undetectable or weak Igκ/λ 31/35 34/35 34/35 35/35 19/35 RT-PCR, Sequencing, Single Strand Conformation Polymorphism (SSCP), MCL 37 CD5+ CD19+ CD20+ CD23- IgM+ IgD+ κ+ λ+ cyclin D1+ 34/36 27/27 35/35 25/25 30/30 28/31 12/32 20/32 35/37 Southern blotting, Polyacrylamide gel electrophoresis (PAGE) Study V MCL 18 CD5+ CD19+ CD20+ CD23- IgM+ IgD+ κ+ λ+ cyclin D1+ 16/17 15/15 16/16 9/9 17/17 15/18 3/11 14/17 16/18 cDNA array analysis, Real-time PCR 35 7.2 Immunohistochemistry (study I-V) The immunohistochemistry was performed on paraffin and / or fresh sections using either the biotin-avidin method or the streptavidin-biotin method. The work was done by the pathologist’s laboratory at the time of diagnosis. 7.3 G-banding analysis (study II and III) G-banding analysis of the samples in study II and III was performed at the time of diagnosis in the Chromosome and Molecular Cytogenetic Laboratory at the Helsinki University Central Hospital. The cells were detached mechanically from fresh lymph biopsies in 5 ml RPMI 1640 medium (Gibco) supplemented with 20% calf fetal serum, 1% glutamine, and 1% penicillin-streptomycin. The cell suspension was treated with colcemid (0.1 µg/ml) in 5% CO 2 at +37˚C for 4 to 12 hours. After hypotonic treatment with 75 mM KCl, the cells were fixed three times in methanol- acetic acid (3:1). Heparinized peripheral blood from leukemia patients was collected and mononuclear cells were isolated and cultured with optimal mitogenic stimulation. After harvesting, the cells were treated hypotonically (0.075 M KCl, 15 minutes, +37˚C) and fixed with methanol-acetic acid (3:1). The cell suspension was spread on slides and air-dried for a couple of days. G-banding analysis was performed according to standard protocols. Images of the metaphase spreads were generated by IKAROS programme (MetaSystems GmbH, Altlussheim, Germany) and ten metaphase spreads of each sample were analyzed. Karyotypes were determined according to the International System for Human Cytogenetic Nomenclature 1995 (Mitelman, 1995). 7.4 Interphase fluorescence in situ hybridization (studies I – III) 7.4.1 Sample preparation Paraffin embedded samples We extracted the nuclei from paraffin embedded tissues according to protocols described by others (Heiden et al., 1991; Hyytinen et al., 1994) with slight modifications. The sections were deparaffinized with xylene 4 times at +55°C and once at +67°C, which was followed by treatment in 100%, 95%, 70% and 50% ethanol series and in H 2 O at room temperature. After deparaffinization, sections were digested in 1 ml of Carlsberg's solution (0.1% Sigma protease XXIV, 0.1 M Tris, 0.07 M NaCl, pH 7.2) for 1 hour at +37°C and vigorously shaken in a vortex machine for 20 minutes. The nuclear suspension was filtered through a nylon net (pore size 55 µm) and spread on slides. The nuclei preparations were deparaffinized 36 again just before the reaction, to ensure high quality hybridization, by incubating the slides at +65°C for 15 minutes and washing them 3 times in xylene at room temperature, followed by dehydration in 100%, 85%, 70% and 50% ethanol series. Fresh tissue and peripheral blood samples Cells from fresh tumor tissues were separated and cultured overnight in RPMI media [80%RPMI 1640, 20% fetal calf serum, 0.29 mg/ml L-glutamine, 100 mg/ml streptomycin, 100 U/ml penicillin, 0,1 µg/ml Colcemid (all from Gibco, Grand Island, NY, USA)]. Heparinized peripheral blood of leukemia patients was collected and mononuclear cells were isolated and cultured with optimal mitogenic stimulation as described elsewhere (Larramendy et al., 1998). After harvesting, cells were treated hypotonically (0.075 M KCl, 15 minutes, 37˚C) and fixed with methanol-acetic acid (3:1). The cell suspension was then spreaded on slides. 7.4.2 Probes In study I, 20 YAC probes covering the region 11q22.1-q23.3 contiguously (Figure 1. on page 18) were obtained from the Centre d'Etude Polymorphisme d'Humain (CEPH, Paris, France). All probes were screened with the corresponding markers using PCR and FISH analysis to confirm their identities and locations. None of the probes showed chimerism, as all hybridized only to 11q22-q23. YAC probes 808c6 and 953e4, hybridizing to 11p13, were used as controls of hybridization efficiency and for evaluating the chromosome copy number. Seventeen MCL cases were tested with all 20 probes. Twenty-four MCL cases were screened with probe 755b11 first. Cases found to have the 11q23 deletion were tested with a wider set of probes from the YAC contig to determine the extent of the deletion. Probe 981g12, which represents the region containing the ATM gene, was tested on cases that did not show the deletion of the region represented by YAC755b11 to eliminate the possibility that the deletion in 11q23 was not uniformly detected by YAC755b11. In study II, based on the results from study I, eight YAC clones (793d9, 755b11, 913g9, 957e4, 771d4, 939b12, 785e12, and 911f2) were used. These YAC probes constitute a contig of 7.8 Mb in size spanning the region 11q23.1-q23.3 (Figure 1. on page 18). All of the YAC probes hybridized only to 11q22-q23 and none of them showed chimerism. YAC 953a4 (CEPH-Généthon), mapped to 11p13, was 37 used as the chromosome copy number control. The identities of the YAC probes were confirmed by PCR with their corresponding markers. In study III, YAC probe 755b11 was used. The yeast cells containing the probes were grown in AHC medium for 4-6 days and DNA was extracted from the yeast by using a glass bead and phenol based procedure (Hoffman & Winston, 1987). 7.4.3 Dual-color and single-color FISH In dual color FISH, the control and test DNA were labeled with digoxigenin-dUTP and biotin-14-dATP, respectively, by nick-translation according to the standard procedure. In single color FISH, the DNA was labeled with biotin-14-dATP. The probe mixture contained approximately 1 µg labeled DNA, 25 µg human Cot-1 DNA (Gibco) and 25 µg herring sperm DNA (Sigma Chemical Co., Bornem, Belgium) dissolved in 50% formamide and 10% dextran sulfate in 2×SSC. The probe mixture was denatured at +75˚C for 5 minutes before the hybridization. The nuclei preparations extracted from paraffin embedded samples were first deparaffinized as described on page 35-36. In order to increase the hybridization efficiency, the slides were treated in 1 M sodium thiocyanate at +70°C for 15 minutes, followed by treatment in 0.05 N HCl at +37°C for 10 minutes and in 5 mg / ml pepsin dissolved in 0.05 N HCl at +37°C for 20 minutes. The slides were then denatured in 70% formamide / 2 × SSC (pH 7) at +75°C for 5 minutes. The fresh tissue or blood samples preparations were treated with 0.01 N HCl at +37°C for 5 minutes and with 5 mg / ml pepsin dissolved in 0.01 N HCl at +37°C for 7 minutes, and then denatured in 70% formamide / 2 × SSC (pH 7) at +65°C for 2 minutes. The denatured probe mixture was hybridized onto the slides and the reaction continued for at least two days in a moist chamber at +37°C. After the hybridization reaction, the slides were rinsed once in 2 × SSC and twice in 0.1 × SSC at +45°C for 5 minutes each. In dual-color FISH, the biotinylated test DNA was detected by incubating the slides at +37°C with the avidin-TRITC solution (1:5000, Vector laboratories, Burlingame, CA, USA), the biotinylated anti- avidin solution (1:1000, Vector) and the avidin-TRITC solution (1:5000) for 40, 45, and 40 minutes, respectively. Simultaneously, the digoxigenin-labeled control DNA was visualized with the mouse-anti-digoxigenin solution (1:100, Boehringer 38 Mannheim, Germany), the rabbit-anti-mouse FITC solution (1:300, Sigma, St. Louis, MO, USA) and the goat-anti-rabbit FITC solution (1:200, Sigma) for 60, 40, and 40 minutes, respectively. In single-color FISH, the biotinylated DNA was detected by incubation at +37°C with the avidin-FITC solution (1:200, Vector), the biotinylated anti-avidin solution (1:1000, Vector) and the avidin-FITC solution (1:200) for 40, 45, and 40 minutes, respectively. The preparations were counter-stained in 2 µg/ml of DAPI for 10 minutes. From each preparation a minimum of 200 morphologically intact and non- overlapping nuclei were checked using a Leitz fluorescence microscope (Laborlux D, Germany). The locus was considered deleted if the frequency of cells with only one signal was higher than the cut-off value. The cut-off value for deletion was obtained by experiments on normal reactive lymphoid tissue samples. The cut-off level was defined as the mean value of the frequencies of nuclei exhibiting one signal plus three times the standard deviation. 7.5 RNA and DNA extraction (study IV and V) Total RNA of mononuclear cells collected from heparinized blood of CLL patients was isolated using the TRIzol Reagent (Life Technologies Inc., Grand Island, NY, USA) according to the manufacturer's instruction (study IV). Total RNA was isolated from lymphoma specimens preserved at –120 ˚C using the RNeasyMini Kit from QIAGEN (Valencia, CA, USA) according to the manufacturer’s instruction (study V). For array analysis, the total RNA was treated with DNase according to the manufacturer’s instruction (Clontech Laboratories Inc., Palo Alto, CA, USA). The purity and the integrity of the RNA were examined by electrophoresis on 1% agarose gel. Only high quality RNA was used for gene expression analysis. DNA was extracted from deep-frozen tissue, blood or bone marrow samples from CLL and MCL patients, using the phenol-chloroform extraction method (study IV). In four cases of MCL, DNA was extracted from archival paraffin-embedded material according to the protocol described elsewhere (Isola et al., 1994). The RNA and DNA of the control samples were extracted using the same method as the patient samples in each study. 39 7.6 RT-PCR analysis (study IV) We used RT-PCR to detect mutations in the PPP2R1B gene using total RNA from ten CLL patient samples in study IV. 0.8 µg RNA was reverse-transcribed to cDNA in a 20 µl reaction mixture using the standard random priming method with M-MLV reverse transcriptase (Promega, Madison, WI, USA) and RNAse inhibitor (Promega) according to the manufacturer’s instruction. The subsequent PCR analysis was usually performed using 3 µl cDNA, 1 × PCR buffer (Perkin-Elmer, Branchburg, NJ, USA), 250 µM dNTPs (Finnzymes, Espoo, Finland), 0.8 µM forward and reverse primers, and 2 units of AmpliTaqGOLD polymerase (Perkin-Elmer) in a final volume of 50 µl. The MgCl 2 concentration was 1.5 mM. Primers were designed using the primer 3 program (http://www-genome.wi.mit.edu/). 7.7 PCR-SSCP analysis (study IV) PCR-SSCP is a method to detect mutations, polymorphisms and sequence variants, utilizing the property that the electrophoretic mobility of single-stranded nucleic acid depends both on the length and the sequence of the target. We used PCR-SSCP to detect genomic mutations in the PPP2R1B gene in study IV. Primers for PCR analysis on genomic DNA were designed using the primer 3 program (http://www- genome.wi.mit.edu/). The reactions were carried out in a 50 µl reaction volume containing 100 ng of genomic DNA, 1 × PCR buffer (Perkin Elmer), 250 µM dNTPs (Finnzymes), 0.6 µM forward and reverse primers, and 2 units of AmpliTaqGOLD polymerase (Perkin Elmer). The concentration of MgCl 2 was optimized to 1-2.5 mM in the reaction mixture for each exon and 6% DMSO was used in reactions for exon 1. In reactions for exon 8, the concentrations of the forward and reverse primers were 0.5 µM and 1µM, respectively. After PCR, equal volumes of the reaction mixture and the denaturing loading buffer (95% formamide, 20 mM EDTA, 0.05% bromphenol blue and 0.05% xylene cyanole) were mixed. The mixture was denatured for 5 minutes at +95°C and loaded onto a 0.4 mm × 30 cm × 45 cm gel. The gel contained 0.5 × mutation detection enhancement gel solution (FMC Bioproduct, Rockland, ME, USA) and 1 × TBE buffer. The gels were electrophoresized at 3-6 W overnight and then stained with silver according to the standard protocol. 40 7.8 Sequencing PCR products (study IV) In order to determine the nucleic acid sequences in mutated samples, we sequenced PCR products showing aberrant bands in either the RT-PCR analysis or the PCR- SSCP analysis in study IV. The PCR product was purified using a QIAquick PCR purification kit (Qiagen) and DNA fragments were sequenced using an ABI PRISM Dye Terminator (Perkin Elmer) according to the manufacturer’s instruction. Cycle sequencing products were then electrophoresized on 6% Long Ranger gels (FMC Bioproduct) and identified using an Applied Biosystems model 373A automated DNA sequencer (Perkin Elmer). The DNA fragments were sequenced using both forward and reverse primers. 7.9 Southern blotting analysis (study IV) In some samples PCR-SSCP analysis was not successful in consecutive exons. In order to see if this was due to deletions spanning more than one exon in the samples, we performed the Southern blotting analysis. EcoR I (New England Biolabs, Beverly, MA, USA) and TaqI (New England Biolabs) restriction enzymes were used to digest genomic DNA (10 µg). The digested DNA was fractionated according to size in 0.8% agarose gel (Bio-Rad, Hercules, CA, USA). After denaturation and neutralization treatment, DNA fragments were blotted onto Hybond-C extra filters (Amersham, Piscataway, NJ, USA). A cDNA probe containing PPP2R1B exons 1-9 was labeled radioactively with [α 32 P] dCTP using standard methods and hybridized to the DNA on the filters. After hybridization, the filters were washed at least twice in 3 × SSC and 0.1% SDS at +65°C for 20 minutes each. 7.10 PAGE analysis (study IV) After PCR-SSCP analysis, we found abnormal bands in exon 1 of the PPP2R1B gene in some samples. To confirm this finding, we performed the PAGE analysis. PAGE was performed using Ultrapure Sequagel (National Diagnostics, Atlanta, GA, USA). The gels were silver-stained. The reactions were performed according to the standard protocol. 7.11 cDNA array analysis (study V) In order to study the gene expression profiles of common and blastoid variant MCL, we performed cDNA array analyses using the Atlas Human Hematology/Immunology 41 cDNA expression array (7737-1) (Clontech Laboratories Inc). The array includes 406 human genes and nine housekeeping genes immobilized in duplicate dots on a nylon membrane. The 406 genes included were previously shown to be involved in various hematological and immunological disorders or in the normal functions of the human immune system. The names of the genes and their coordinates on the filter are available on-line (http://www.clontech.com/atlas/genelists/index.shtml). Total RNA (3 - 4 µg) was reverse-transcribed into cDNA with primers provided with the reaction kit by Clontech Laboratories Inc. and was labeled with 33 P-dATP. Probe purification and hybridization to the array were performed according to the manufacturer’s instruction. After the post-hybridization washes, the array was exposed to an imaging plate (BAS-MP 2040S; Fuji, Tokyo, Japan) at room temperature for 3-5 days and scanned by a phosphorimager (Bio-Imaging Analyzer, BAS-2500; Fuji). The image was analyzed and the intensity of each spot was quantified using the Atlas Image 1.5 software (Clontech Laboratories Inc.). The background was determined as the average intensity of the blank space between the different panels of the array. Saturation of the hybridization signal was not observed. All filters used were from the same batch to minimize printing variation between batches. 7.12 Gene expression data analysis (study V) Three statistical analysis methods were used to analyze the array data: the regression analysis, the principal component analysis (PCA) and the naive Bayes classifier. The first two methods focused on identifying deregulated genes and the third one provided a model for the differential diagnosis of common MCL and its blastoid variant. In regression analysis, Microsoft Excel 2000 software was used to generate the xy-scatterplot of expression data from array experiments on one sample and the control. The same software was used to determine the least-squared regression line and the Pearson correlation coefficient of the scatterplot. The 95% confidence interval around the regression line was determined. Spots beyond this area were identified as abnormally expressed (Smid-Koopman et al., 2000). If a gene was found abnormally expressed in more than 3 samples, it was considered deregulated in MCL. By comparing the frequencies at which a gene was identified as abnormally expressed in 42 common and blastoid variant MCL samples, we were able to identify genes that were differentially deregulated in the two types of MCL. The Principal Component Analysis (PCA) method combined the expression data from all 18 samples and compared it to the control. Each gene was given a score. Genes with a score around zero were considered normal and genes with big positive or negative scores were considered deregulated. Technically, from the absolute intensity of each gene, the background intensity was first subtracted, followed by the subtraction of the control intensity, then the mean value of the data set of an array was subtracted from each data point. To give equal weighting to all cases, the data in each case was standardized to unit variance by dividing all the values by the standard deviation. The covariance matrix is estimated from the data and the principal components are given by eigenvectors and associated eigenvalues of the covariance matrix. The first principal component is the eigenvector that has the largest eigenvalue of the covariance matrix. The first principal component is interpreted as the average expression level of each gene (Hilsenbeck et al., 1999). The gene were scored based on their first principal component projections. The naive Bayes classifier has been widely used in diagnostic applications (Duda et al., 2001). In this method, we assume that the expression level of each differentially deregulated gene in each class is distributed according to a normal distribution. We may estimate the parameters of the normal distribution. The parameters for each class distribution are the mean vector and the diagonal covariance matrix. The parameters were estimated by the method of maximum likelihood by assigning the average value and the diagonal covariance matrix of the sample to the mean vector and the covariance matrix of the class densities, respectively. Once the parameters of the classifier have been estimated, the model can be used for classification. In order to assess how well the classifier would operate in a clinical setting, where cases with unknown diagnosis are encountered, we applied the leave- one-out cross-validation method (Golub et al., 1999). In this case, we calibrated a new classifier based on data from 17 samples and assessed its accuracy with the 18th sample, and repeated this effort 18 times with all possible combinations to assess the accuracy of the classifier. The cross-validated test error is the average of all errors made during the testing phase. To check whether the classification results are significant, we performed a randomization experiment. The class labels of the 43 observations were randomly permuted, and a new classifier was derived using the same method as for the original data. The accuracy of the new classifier is compared to the original classifier. This procedure was repeated 10.000 times. 7.13 Real-time PCR analysis (study V) Real-time PCR utilizes fluorescence labels to detect PCR products. Thus, the reaction process (in terms of PCR product amount) can be followed at real time and the product can be quantified. In study V, we used real-time PCR to confirm the array results. Four genes were tested, namely AF17, ADA, RGS2 and CMYC, by the real- time PCR analysis. 820 ng purified RNA was reverse-transcribed using the 1st strand cDNA synthesis kit for RT-PCR (AMV) (Roche Diagnostics Corp., Indianapolis, IN, USA). The cDNA was diluted 10-fold prior to PCR amplification. Real-time PCR was performed using the LightCycler rapid thermal cycler system (Roche Molecular Biochemicals, Mannheim, Germany) according to the manufacturer’s instruction. The primers were designed by TIB Molbiol (Berlin, Germany). Reactions were performed in a 10 µl volume with primer concentrations of 0.5 µM each, Mg 2+ concentration optimized between 2-5 mM, and 1 µl of cDNA. The LightCycler-FastStart DNA Master SYBR Green I kit was used (Roche Diagnostics GmbH, Mannheim, Germany). To confirm amplification specificity, the PCR products from each primer pair were subjected to the melting curve analysis and subsequently gel electrophoresis analysis. 8 RESULTS In this thesis study, we first tried to identify the critical regions in 11q22-q23 using FISH analysis on samples of MCL and CLL. We identified two critical regions, one of which was the minimal common region of deletion in 11q22-q23. We then used the probe representing this minimal common region of deletion to study the occurrence of the deletion in 11q22-q23 in different lymphoma subtypes. In study IV, we performed mutation analysis on one candidate gene in 11q23. Finally in study V, we investigated the gene expression profiles of common and blastoid variant MCL using the cDNA array analysis. 44 8.1 Deletion in chromosome bands 11q22-q23 in mantle cell lymphoma (study I) We studied 41 MCL samples by FISH analysis in study I. We first screened 17 MCL samples with 20 YAC probes covering the whole area of 11q22.1-q23.3. We found deletions in this area in nine samples (53%). The deletion was usually large, spanning several megabases, although in one sample, only the region represented by YAC755b11 (1.6 Mb) in 11q23.1 was deleted. We then screened additional 24 MCL samples with the probe 755b11 and found deletions in 11 samples, yielding an overall frequency of deletion of 49% in all samples (20/41). The deletion was present in at least 25% of the nuclei examined and in most samples it occurred in more than 60% of the nuclei. In one case, a large biallelic deletion was detected. Two signals were seen with a control probe in more than 78% of the cells. The region represented by the YAC probes 785e12 and 911f2, at the distal end of 11q22-q23, seemed to be rather critical, because the deletion ended here in most of the informative cases (12/19, 63%). In two cases, the end point of the deletion occurred between the region represented by probes 911f2 and 822g8. In one case, it was between the region represented by probes 939b12 and 785e12. The proximal end point of the deletion was not determined, because the deletion usually extended beyond 11q22.1. In some lymphoma samples, two or three signals were found by probes 711d4 and 939b12 while the flanking regions were deleted. We studied the association between the presence of a deletion in this region and clinical parameters. No association was found between the presence of a deletion and median age, gender, International Prognostic Index, or Ann Arbor stage of the patients. 8.2 Discontinuous deletion in 11q23 in chronic lymphocytic leukemia (study II) No numerical abnormality or translocation involving chromosome 11 was found in any of the CLL cases. Standard cytogenetic analysis revealed deletions in 11q in six samples (nos 1, 2, 9, 11, 18 and 20). Five of these samples had other chromosome abnormalities. FISH analysis confirmed these cytogenetic findings and revealed three more samples (nos 3, 25 and 30) with the deletion in 11q23. The overall frequency of 11q deletion was therefore 30% (9/30). In each of the samples with the deletion in 45 11q23, the percentage of cells showing deletions ranged from 22% to 93% (mean, 77%). Five samples had discontinuous deletions. The genomic region represented by the YAC probes 793d9, 755b11 and 913g9 was deleted in all the samples that had the deletion. The region represented by YAC 785e12, located about 4 Mb distal from 755b11, was deleted in all but one of the samples (no. 2). The area in between, represented by YAC probes 957e4, 771d4 and 939b12, was deleted discontinuously in five samples (case nos 3, 9, 18, 20 and 30). In sample nos 3, 9 and 30, the region represented by YAC 785e12 was deleted while both of flanking regions were not. In sample nos 3 and 9, two signals were seen at their normal positions in 11q when probes 771d4, 939b12 and 911f2 were hybridized to the metaphase spreads of the samples, confirming that there was no deletion of these regions in these samples. The same was true when sample no. 24 was hybridized with probes 771d4 and 939b12. Dual-color FISH on metaphase spreads from sample nos 3, 9, 18 and 30, with probes 755b11 and 785e12, showed that the deletions in these regions affected the same chromosome. No signal splitting was found in sample nos 3, 9 and 30 when dual-color FISH was performed on interphase cells with probes 939b12 and 911f2, suggesting that there were no translocations involving these regions. 8.3 Deletion in 11q23 in different lymphoma subtypes (study III) We studied 146 lymphoma or leukemia samples and 15 control samples by FISH analysis in study III and found deletion of the region represented by YAC755b11 in 40 samples (25%). MCL had the highest deletion frequency with 23 out of 47 samples (49%) having the deletion. No significant difference in frequencies were found between common and blastoid variant MCL. Out of the 62 CLL/SLL samples studied, 13 (21%) had the deletion. The deletion is more common in the blood specimens of CLL/SLL (9 out of 30, 30%) than the lymph node specimens of CLL/SLL (4 out of 32, 13%). Four out of the 17 (24%) DLBCL samples were found to have the deletion. There were three cases of Richter’s syndrome among the CLL/SLL and the DLBCL patients, and they all had the deletion. None of the nine FLs, 11 HLs or the 15 reactive or normal lymph node specimens had the deletion. The percentage of cells showing the deletion ranged from 22% to 95% (mean, 72%). 46 No significant difference was found in the deletion frequencies between men and women (MCL, p=0.86; CLL/SLL, p=0.74; DLBCL, p=1.00). Neither was there difference in age at diagnosis between the cases with or without the deletion in any of the subtypes of lymphoma (MCL, p=0.89; CLL/SLL, p=0.17; DLBCL, p=0.82). The deletion was more common in MCL than in other types of lymphoma (MCL vs CLL/SLL: p=0.0021; MCL vs DLBCL: p=0.069). The difference in deletion frequencies between CLL/SLL and DLBCL was not statistically significant (p=1.00). Although the deletion frequency is higher in blood samples than in lymph node samples of CLL/SLL (30% vs 13%), the difference is not statistically significant (P = 0.045). 8.4 Mutation analysis of the PPP2R1B gene (study IV) Ten CLL samples were subjected to the RT-PCR and sequencing analysis. Exon 3 of the PPP2R1B gene was found deleted in sample no. 16. We performed PCR-SSCP analysis on the genomic DNA of 26 additional CLL samples and 37 MCL samples. Ninety-six percent of the PCR experiments were successful. After the SSCP analysis, no abnormality was found in exons 2-15 in any of the samples. One CLL sample (No. 52) showed abnormal bands in the analysis of exon 1, which was confirmed by the PAGE analysis. The sequencing analysis showed that this abnormality was a silent mutation CTA (Leu)- CTG (Leu) at codon 22. To see if there were large deletions spanning several exons, we did Southern blotting analysis on 20 MCL samples and 18 CLL samples (two of the CLL samples studied by the RT-PCR analysis, nos 16 and 41, were also included in the RT-PCR analysis). Experiments on DNA digested by TaqI yielded informative results from 8 MCL samples and 17 CLL samples. Experiments on DNA digested by EcoRI yielded informative results from seven MCL samples but failed in all CLL cases because of the poor quality of the DNA. A structural rearrangement of the PPP2R1B gene was found in one MCL sample (no. 33). Details of this rearrangement could not be studied because RNA was not available. Altogether, therefore, we found two abnormalities in the PPP2R1B gene, a deletion of exon 3 in one CLL sample (no. 16) and a structural rearrangement in one MCL sample (no. 33). 47 8.5 The gene expression profiles of MCL and its blastoid variant (study V) The regression analysis identified 46 deregulated genes. Thirty-four of them were found to be deregulated in both common and blastoid variant MCL at frequencies ranging from 22% to 100%. The remaining 12 genes were found to be differentially deregulated in common and blastoid variant MCL. In PCA, we chose 20 genes with the highest scores and 20 genes with the lowest scores as the deregulated genes for MCL. Genes identified by both the regression analysis and PCA were considered deregulated in both common and blastoid variant MCL. There were 18 such genes (Table 5). Table 5. Genes deregulated in both common and blastoid variant MCL Gene name Chromosome location Status Suggested role in MCL SCYA21 9p13 Up Normal body function GPR13 3p21.3 Up Not known BCL1 11q13 Up Oncogene AF17 17q21 Up Not known MIG 4q21 Up Normal body function CD5 11q13 Up Not known ANX2 15q21-q22 Up Tumor metastasis promoter CD44H 11p13 Up Tumor metastasis promoter TP12/CD6 11q13 Up Not known TCF7 5q31.1 Up Not known GRN 17q21.32 Up Oncogene GZMK 5q11-q12 Up Normal body function EBI2 13 Down Not known ADA 20q12-q13.11 Down Not known CALLA/CD10 3q25.1-q25.2 Down Oncogene CD66D 19q13.2 Down Tumor suppressor RGS1 1q31 Down Tumor metastasis promoter RGS2 1q31 Down Tumor metastasis promoter The expression data of the 12 genes differentially deregulated for common and blastoid variant MCL were used to calibrate the naive Bayes classifier. The leave-one- 48 out cross-validation tests showed correct classification in 14 out of the 18 cases. Therefore, the cross-validated test error for the classifier was 0.222. The randomization experiments yielded a significance level of 0.028. To improve the classification, we used subsets of the 12 genes to calibrate the classifier. This had not only the potential to provide a more accurate classifier, but was also a way to choose and confirm the differentially deregulated genes. We tested gene sets consisting of one to eleven genes with different gene composites. It turned out that the best classifier is a gene set consisting of eight genes. The mean classification error was 0.111. Randomization results yielded a significance level of 0.018. Therefore, we conclude that these eight genes are significant in separating the blastoid variant from common MCL and they are differentially deregulated in common and blastoid variant MCL (Table 6). Table 6. Genes differentially deregulated in common and blastoid variant MCL Gene Name Chromosome location Status Deregulated in common MCL Deregulated in MCL blastoid variant Suggested role in MCL CMYC 8q24.12- q24.13 Up 0 44% Oncogene BCL2 18q21.33 Up 33% 56% Oncogene TOP1 20q12-q13.1 Up 67% 11% Not known CD45 1q31-q32 Up 56% 0 Tumor suppressor CD70 19p13 Up 22% 56% Oncogene NFATC 18q23 Up 56% 11% Functions through downstream targets. PIM1 6p21.2 Up 0 56% Oncogene CD23 19p13.3 Down 33% 67% Not known To confirm the cDNA array results, we did real-time PCR analysis on four genes, AF-17, ADA, RGS2 and CMYC. The results were in accordance with the array analysis results. 49 9 DISCUSSION 9.1 Discussion of the techniques applied Control samples We used lymph node biopsy specimens from two healthy individuals as controls in study I, and peripheral blood specimens from two healthy individuals as controls in study II. The control samples were tested by 20 YAC probes in study I and 8 in study II. In each experiment, a total of 200 nuclei were analyzed. The frequency of normal nuclei with one-signal in each experiment was determined. The average frequency and the standard deviation were calculated, and the cut-off level was determined as the average frequency plus three times the standard deviation. If the frequency of nuclei with one-signal in a FISH experiment on one patient sample is higher than the cut-off level, we consider the region represented by the probe is deleted in the sample. We studied 15 normal or reactive lymph node specimens with YAC755b11 in study III. In addition to determine the cut-off level, these samples were used to determine the occurrence of the deletion in 11q23 in normal lymph node tissues. In study IV, we used DNA and RNA extracted from the peripheral blood of two healthy individuals as controls. To determine whether a point mutation is a polymorphism, one usually needs a larger series of normal samples. In this study, no point mutation was found. Therefore, we think two control samples are sufficient. Choosing the proper control is perhaps the most difficult part of the array analysis. In many cancer types, the normal cell counterparts are still unknown or controversial. In addition, to get enough amount of the normal cell counterpart from healthy individuals is often difficult. In study V, we used the B-cells purified with CD19-coupled microbeads from adenoid palatine tonsil samples from six healthy children as the control. Whether this control is the most suitable normal cell counterpart of MCL malignant cells can be argued. Theoretically, the normal cell counterpart of MCL malignant cells is the CD5+ B-cell from the mantle zone of lymph nodes. The B-cells extracted from tonsils are normally CD5-. The CD19 is a pan-B-cell marker, which is expressed not only on mantle zone B-cells, but also on germinal center and marginal zone B-cells. In addition, the patients were mostly over 60 years old, while the control samples were extract from children. However, to get enough CD5+ cells from the mantle zone of lymph nodes from healthy old men is 50 practically impossible. The alternative could be CD5+ B-cells enriched from the blood. But a recent study by Rosenwald et al. (2001) (Rosenwald et al., 2001) has shown that there is no similarity in gene expression profiles between CD5+ B-cells enriched from blood and CLL malignant cells. CLL is another disease whose normal cell counterpart is proposed to be the CD5+ B-cell. Rosenwald et al. (2001) suggested that the gene expression profile in CLL might be a manifestation of oncogenic properties and therefore might not be a feature of any normal B-cell population. Although the same kind of study has not been conducted in MCL, we think that similar conclusions can be drawn for MCL as well. Based on these facts, we think our choice of the control is suitable for this study. We were, however, careful when interpreting the deregulated genes. We used two statistical analysis methods to confirm the genes identified as deregulated: regression analysis and PCA in identifying genes deregulated in both common and blastoid variant MCL; regression analysis and naive Bayes classifier in identifying genes differentially deregulated in common and blastoid variant MCL. The stringent selection criteria guaranteed that the genes chosen by both methods were indeed deregulated. However, we should be aware that this selection process might have eliminated genes with low degree of abnormality but of biological importance. Therefore, genes chosen by one statistical analysis method as deregulated but not by the other also deserve attention. Interphase FISH Either dual-color or single-color interphase FISH was applied in studies I, II and III. One of the biggest advantages of interphase FISH is that we can utilize the paraffin- embedded archival material. Since the paraffin-embedded material is much more abundant than the fresh or deep-frozen one, interphase FISH enables us to conduct the research on larger series of patient material. The disadvantage of interphase FISH is that it is rather labor-intensive, especially when multiple probes are tested on large sample series. Over 700 FISH experiments were performed in this thesis study, which has been both time and money consuming. Therefore, it is necessary to combine interphase FISH with other high-throughput methods, such as the tumor array technology, in order to increase the efficiency. 51 Mutation analysis We used PCR-SSCP as the main method for detecting mutations in the PPP2R1B gene. PCR-SSCP is a popular electrophoretic method for the detection of mutations. It is technically simple, with high capacity and relatively high sensitivity. There are a number of factors affecting the sensitivity of PCR-SSCP: choice of matrix, electrophoretic conditions, presence of additives, and the fragment size and GC content of the sample. It has been shown that the sensitivity of PCR-SSCP is between 70% and 95% depending strongly on the factors described above (Moore et al., 2000). Except the sample’s fragment size and GC content, we optimized all the other factors for each exon before the experiments. Mutation of one nucleotide was detected in our study, proving the sensitivity of our experiments. However, we can not exclude the possibility that some mutations were not detected because PCR-SSCP experiment conditions were not optimal for some exon sequences. Perhaps the most sensitive method for mutation detection is the sequencing of the cDNA transcribed from RNA. However, the availability of RNA has often been the restricting factor. Direct sequencing of the genomic DNA (including exons and exon-intron boundaries) is also a very sensitive method. However, it is very costly to conduct such analysis on large series of samples, especially when the gene under investigation has many exons. In addition, direct sequencing of genomic DNA cannot detect large deletions spanning more than one exon. Thus, assisting methods, such as Southern blotting analysis, have to be used to make the investigation complete. Statistical methods used in the array analysis In most of the array studies, the ratio of a gene’s expression level in tumor samples to its expression level in the control sample plays an important role (Eisen et al., 1998). The glass-based array system is very convenient and accurate, because both the tumor RNA and the control RNA are simultaneously hybridized onto the array, leading to minimal inter-experimental variations. The inter-experimental variations are considerably higher using the filter-based array system, because the tumor and control RNA are hybridized to the array in two independent experiments. Therefore we needed analysis methods that could best solve the normalization problem. The regression analysis treats the expression levels of all genes in an array experiment as a population and compares it with another population. The coefficients a and b in the 52 regression function y = ax + b should, in principle, explain the major inter- experimental variants, namely the overall intensity variation caused by the different amounts of RNA used, and the background variation caused by different exposure time. In PSA, we subtracted the average value of all gene expression data on an array from the expression data of each gene, then divided this figure with the variance. This is also a powerful way to normalize the expression data. The regression analysis is, however, rather laborious, especially if there are a large number of samples. Another disadvantage was the use of frequencies, which are sensitive to the choice of thresholds. The PCA is less labor intensive. It is also more powerful in treating the sample set as a group. There are enormous interests in the tumor class prediction and classification field. Most impressively, many creative statistical analysis strategies are being applied. In our study, we used the naive Bayes classifier. This method and its variants have been applied to the classification of cancer before (Golub et al., 1999; Dudoit et al., 2000). We were able to verify the accuracy of this classifier by the cross validation tests. Although it is statistically sufficient, the true value of this classifier will only be shown when new MCL cases are correctly diagnosed. It is conceivable that with more samples and an array containing more genes, we will be able to gain much more information about the disease and generate a more accurate classifier. 9.2 The minimal common region of deletion in 11q22-q23 (study I, II) By utilizing the YAC-contig, we wanted to narrow down the critical regions in 11q22-q23. In study I, the minimal common region of deletion in 11q22-23 was found to be the region represented by YAC755b11. In study II, the same genomic region was involved in all cases with the deletion. In one case, the region represented by YAC755b11 was deleted more frequently (63%) than the flanking regions (42% and 31%, respectively). This suggested that part of the cell population had the deletion only in the region represented by YAC755b11. Similar results have been obtained by others (Stilgenbauer et al., 1996). The YAC755b11 probe was also used to screen 214 CLL cases. Deletions were found in the cases that had an inferior prognosis (Döhner et al., 1997). These data suggested that 11q23.1 might contain a tumor suppressor gene that could be important in the pathogenesis of both MCL and CLL. Our results support the conclusion that this tumor suppressor gene is located in the region represented by YAC755b11. However, the study by Stilgenbauer et al. (1999) on 81 53 MCL cases showed that the minimal common region of deletion in 11q23 was the one represented by YAC801e11, a region more proximal than the region represented by YAC755b11 (Stilgenbauer et al., 1999). This is the region where the ATM gene is located. Subsequent analysis of the same samples confirmed the inactivation of the ATM gene, leading to the conclusion that the ATM gene was the proposed tumor suppressor gene in 11q23 (Schaffner et al., 2000). Nevertheless, the significance of the region represented by YAC755b11 should not be neglected. It is highly possible that there is one yet unknown tumor suppressor gene in this region, as was evidenced by our results and the translocations found by Stilgenbauer et al. (1996) in this region. Additional evidences came from the mutation analysis of the ATM gene in CLL, where mutation was not found in a fraction of CLL cases that had the monoallelic 11q23 deletion (Schaffner et al., 1999). 9.3 The second critical region in 11q22-q23 (study I, II) In addition to the region represented by YAC 755b11, we found another critical region in 11q23. In study I, the distal end point of the 11q22-q23 deletion was found to be between the regions represented by YACs 785e12 and 911f2 in the majority of samples studied (63%). Interestingly, the two regions were found deleted in cases where the deletion was discontinuous. In study II, the region represented by YAC785e12 was deleted in eight out of the 30 samples studied (27%), and in three samples this region was deleted while the flanking regions remained intact. Our results suggested that the region represented by YAC785e12 and its vicinity were the second critical region in 11q22-q23. The region might contain another yet unknown tumor suppressor gene. YACs 785e12 and 911f2 are mapped to 11q23.3, the region that often contains structural aberrations and rearrangements in hematological malignancies (Heim & Mitelman, 1995). This region also contains inherited and constitutionally fragile sites, which makes it susceptible to chromosome breakage and rearrangements (Sutherland et al., 1983; Yunis & Soreng, 1984). In addition to hematological diseases, loss of heterozygosity of the marker APOC-3 that is located in the region represented by 785e12 has been found frequently in breast carcinomas (Laake et al., 1997) and cervical carcinomas (Hampton et al., 1994b) (frequencies of 45% and 43%, respectively), suggesting the existence of a tumor suppressor gene in this region. 54 In our study, the deletion in 11q23 in one sample did not involve the region represented by YAC 785e12. Similarly, Stilgenbauer et al. (1996) have reported that seven out of 18 CLL samples in their study did not have the deletion of this region. One explanation might be that a part of this region could have been deleted but was beyond the resolution limit of FISH. In study II, dual-color FISH on metaphase spreads with YACs 785e12 and 755b11 showed that the deletion of the two regions occurred in the same chromosome, implying that the deletion of the region represented by YAC785e12 might be a secondary event associated with the deletion of the region represented by YAC755b11. The deletion of the region represented by YAC785e12 might therefore be a late event in the disease progression and might not be present in cases at early stages of the disease. A tumor suppressor gene, TSLC1, was identified recently in non-small-cell-lung cancer. This gene is located in the central 100-kb fragment of the region represented by YAC939b12, which is very close to the region represented by YAC785e12 (Murakami et al., 1998; Kuramochi et al., 2001). It will be interesting to see if this gene has a role in the pathogenesis of MCL and CLL. 9.4 The 11q23 deletion in different lymphoma subtypes (study I, II, III) Our results have shown that the deletion in 11q23 is not uniformly present in NHL. We studied 47 MCL samples in studies I and III, and the deletion in 11q23 was found in 49% of them. Similar results were obtained by Stilgenbauer et al. (1999), who found that 37 out of 81 MCL samples (46%) had the deletion in 11q23. Nine out of 30 blood samples of CLL/SLL (30%) were found to have the deletion in 11q23, while only 13% (4 out of 32 samples) of the lymph node biopsies of CLL/SLL had the deletion (study II & III). The combined frequency in CLL/SLL is therefore 21% and it is similar to the 20% deletion frequency obtained by others (Döhner et al., 1997). The deletion was found in 24% (4 out of 17) of DLBCL samples, and was absent in FL and HL. For HL, however, we ought to consider that the analysis was not conducted exclusively on the Reed-Stenberg cells that are the malignant cell population in HL (Teerenhovi et al., 1988). The occurrence of the deletion in 11q23 in DLBCL, FL and HL has not been reported before. The deletion in 11q23 is significantly more frequent in MCL than in any other lymphoma subtypes. We think the deletion in 11q23 could be used as a diagnostic 55 marker of MCL in addition to the cyclin D1 overexpression. The prognostic value of this abnormality has been shown in CLL (Döhner et al., 1997). Therefore, the 11q23 status is routinely examined using the YAC755b11 probe in the Chromosome and Molecular Cytogenetic Laboratory at the Helsinki University Central Hospital. About 3% of the CLL/SLL cases progress to DLBCL, which is referred to as the Richter's syndrome (Jaffe et al., 2001). We had three Richter's syndrome cases in our study. One was diagnosed as CLL at the time of the study; clinical follow-up showed that this patient later developed DLBCL. The other two were diagnosed as DLBCL at the time of the study and their records showed that they had previously been CLL patients. Interestingly, all of them had the deletion in 11q23. Although the sample number was small, the current result suggested that the deletion was associated with the development of the Richter’s syndrome. CLL patients whose tumor cells have this lesion might be more prone to develop Richter’s syndrome and have a poor prognosis. The genes involved in the transformation might reside in this particular region. CLL and SLL are considered one disease entity in the WHO classification. CLL affects primarily the bone marrow and peripheral blood, and SLL lymph nodes. In our study, we have found that the frequencies of the deletion in 11q23 tend to be different in the blood and lymph node specimens of CLL/SLL, although the difference is not statistically significant. Because of difficulty obtaining the clinical data, we did not know the lymph node involvement status of the patients whose blood samples were tested. Out of the 32 patient whose lymph node samples were tested, 25 patients had the bone marrow infiltration. Although pair-wise comparison is not possible, our results do suggest that the malignant cells with 11q23 deletion may have impaired homing ability to the lymph node and therefore may be more likely to be in the blood circulations. Our hypothesis is supported by a recent study, which demonstrated that functionally relevant adhesion molecules and cell signaling receptors on CLL cells are differentially expressed according to the 11q22.3-q23.1 deletion status (Sembries et al., 1999). Sembries et al. (1999) suggested that the 11q deletion might have impaired several cellular pathways in CLL cells, changing the migratory properties of these cells within lymphoid organs and in peripheral blood. Studies have also shown that typical CLL (Karhu et al., 1997) and typical SLL (Autio et al., 1998) have rather different CGH profiles. All these results urged us to question 56 whether CLL and SLL are different forms of one disease or if they are actually two distinct disease entities. This matter deserves further investigations. We also need to bear in mind that CLL itself is a heterogeneous disease, which can be divided into two subgroups based on the Ig V gene mutation and the CD38 expression status. Patients with unmutated Ig V gene and higher percentage of CD38+ cells have poorer prognosis (Damle et al., 1999; Hamblin et al., 1999). On the other hand, 11q23 deletion has been found to define a subset of CLL with poor prognosis (Döhner et al., 1997). It will be interesting to see if the patients with unmutated Ig V gene and higher percentages of Cd38+ cells also have the 11q23 deletion. Or perhaps 11q23 deletion is an independent marker that helps to divide CLL into even more subtypes. 9.5 The role of the PPP2R1B gene in MCL and CLL (study IV) Since it was cloned in 1998, the PPP2R1B gene has been found to be mutated in human lung and colon cancer (Wang et al., 1998), but not in hereditary paraganglioma (Baysal et al., 1998), ovarian carcinoma (Campbell & Manolitsas, 1999; Wu et al., 1999) or parathyroid hyperplasia and adenoma (Hemmer et al., 2002). In study IV, we found the deletion of exon 3 of the PPP2R1B gene in one CLL sample and the structural rearrangement of this gene in one MCL sample. In both cases, FISH analysis had already revealed deletions in 11q23, which could be considered in accordance with the two-hit theory of tumor suppressor genes. There were, indeed, some imperfections in our analyses. First, the methylation status of the promoter region was not studied. Second, due to the limited information on the intron sequencies available from the Genebank, none of the PCR primers designed for SSCP analysis allowed the investigation of splice-sites. Third, the Southern-blotting analysis was not complete due to the lack of high quality DNA material. So we cannot exclude the possibility that abnormalities in the PPP2R1B gene are in fact more common than is revealed by our study. However, the mutation frequencies of the PPP2R1B gene were too low (2.7% in CLL cases and 2.6% in MCL cases) to explain the frequent deletion in 11q23 in CLL and MCL found by the FISH analyses (30% in CLL cases and 49% in MCL cases). In particular, the RT-PCR analysis carried out on 10 CLL samples revealed only one mutation, while 9 of the 10 samples had the deletion in 11q23. Therefore, we 57 assume that the role of the PPP2R1B gene in the pathogenesis of CLL and MCL is probably minor. There might be another gene or genes in the 11q23 region that play more important roles. The ATM gene has been shown to have a pathogenic role in MCL (Stilgenbauer et al., 1999; Schaffner et al., 2000) and CLL (Schaffner et al., 1999). Recently, a retinoid-induced class II tumor suppressor / growth regulatory gene was found to be involved in CLL and located in 11q23 (DiSepio et al., 1998). Its exact location and its role in other types of cancer deserve further investigation. In addition, as was discussed in section 9.2, there might be a yet unknown tumor suppressor gene in the region represented by YAC755b11. 9.6 Marker genes identified by array analysis in MCL (study V) In study V, we identified eight genes that were differentially deregulated in common and blastoid variant MCL using the regression analysis and the naive Bayes classifier. The most important finding is the possible involvement of the gp130 mediated STAT3 signaling pathway in the MCL blastoid variant transformation. Three genes in the pathway, CMYC, PIM1 and BCL2 were all up-regulated in the blastoid variant, but not in common MCL. The product of CMYC is a major regulator of cell growth and the deregulation of CMYC plays a central role in the pathogenesis of lymphoid malignancies as well as other types of cancer [reviewed by (Dang et al., 1999)]. The regulation of CMYC is coordinated via multiple signaling pathways and one of them is the gp130-mediated STAT3 signaling pathway (Kiuchi et al., 1999). PIM1 is frequently up-regulated in human hematopoietic cell lines as well as in tumor cells from leukemia patients (Amason et al., 1989). It is also a target of the gp130- mediated STAT3 signal and cooperates with CMYC to promote cell proliferation and to prevent apoptosis. BCL2 is the downstream target of both CMYC and PIM1 (Shirogane et al., 1999). The simultaneous up-regulation of the CMYC, PIM1 and BCL2 gene in our study demonstrates the close relationship between them, and suggests that the gp130-mediated STAT3 signaling pathway might be involved in the blastoid variant transformation of MCL. Abnormalities in CD45 and CD70 have been found in other types of lymphoma. Reduced levels of CD45 expression has been found in CLL patients with poorer prognosis (Sembries et al., 1999). Expression of CD70 was found in CLL, FL, DLBCL and MCL, although CD70 was infrequently expressed in normal human B cells in vivo (Lens et al., 1999). 58 Although we are not sure of the mechanism behind the frequent up-regulation of TOP1 in common MCL, we may be able to utilize this piece of information in clinical trials. It will be interesting to test whether topoisomerase I inhibitors will be effective in the treatment of common MCL. Marker genes of both common and blastoid variant MCL were identified using the regression analysis and PCA. All but two samples showed up-regulation of BCL1, which is in accordance with the immunohistochemistry study. The role of cyclin D1 in MCL is well established and will not be discussed further here. The annexin II (encoded by ANX2) heterotetramer is known to interact with a number of tumor related proteins, e.g. tissue-type plasminogen activator (Cesarman et al., 1994), cystein protease cathepsin B (Mai et al., 2000a), collagen-I and tenascin-C (Chung et al., 1996). The interaction and collaboration between them may enhance tumor cell detachment, invasion and motility (Mai et al., 2000b). The cell surface molecule CD44 has been implicated in tumor metastasis (Sy et al., 1997). It has also been shown that, in mammary epithelial cells, vast majority of CD44 interacts with annexin II in lipid rafts (Oliferenko et al., 1999). Our results further demonstrated the close relationship between annexin II and CD44, and their possible roles as promoters of tumor metastasis. Regulators of G protein signaling (RGS) inhibit the downstream signaling of the G protein (Kehrl, 1998). They are shown to inhibit the migration and adhesion of lymphoid cells (Bowman et al., 1998; Moratz et al., 2000; Reif & Cyster, 2000). Two members of the RGS family, RGS1 and RGS2, were found to be down-regulated in our study, suggesting a role in preventing tumor cell invasion and metastasis. The carcinoembryonic antigen CGM1 precursor (CD66d) belongs to the CD66 family, whose members appear to have roles in various biological processes including tumorigenesis (Thompson et al., 1991; Obrink, 1997). One of the family members, CD66a, was shown to act as a tumor suppressor in several cancer models (Skubitz et al., 2000). CD66d was found to be down-regulated in our study and it might also have tumor suppressing functions. We should be careful in interpreting the roles of three genes: T cell surface glycoprotein CD5 precursor gene (CD5), T cell differentiation antigen CD6 precursor gene (TP12/CD6) and T cell specific transcription factor 1 gene (TCF7). We used 59 purified B cells as the reference, whereas the samples were unpurified lymphoma specimens. The proportion of reactive T cells in mantle cell lymphoma samples may range from 5% to 20%. It is possible that the up-regulation of these three gene was due to the T-cell contamination. In addition to identify marker genes in common and blastoid variant MCL, the purpose of study V was to look for candidate genes for the proposed tumor suppressor gene in 11q23. No candidate gene was found, partly due to the relatively small number of genes (406) included in the array. However, we should consider this study as a pilot study, preparing us for a larger scale array study in the future. 60 10 CONCLUDING REMARKS AND PERSPECTIVES More and more evidences coming from studies by both us and others have shown that the 11q23 region harbors more than one tumor suppressor gene. These genes play important roles in the pathogenesis and progression of a number of different types of cancer, including MCL and CLL. To identify and characterize them will improve our knowledge of these diseases as well as the general knowledge of cancer biology. It is also the starting point of inventing new pharmaceuticals and diagnostic tools. Since we showed that the PPP2R1B gene is unlikely to be the tumor suppressor gene we are looking for, attention should be turned to other genes in the area. Besides ATM and TSLC1, other, as yet unknown, tumor suppressor genes could be found in the critical regions we identified. We could utilize the positional cloning strategy to try to identify them: constructing cosmid contigs over the critical regions; narrowing down the critical regions by FISH using cosmid probes; constructing a CpG island map of the critical regions; sequencing; and so on. On the other hand, the advancement of the array technology might offer better solutions to this problem. We could construct a chromosome or site-specific CGH-matrix array and examine the patient genomic DNA with it. We could also construct a chromosome or site-specific cDNA array and directly study the abnormality in gene expression in the patient material. The deletion in 11q23 is now widely accepted as a chromosomal abnormality that has diagnostic and prognostic value. It is also evident that CLL patients with this abnormality represent a distinct disease subgroup, with a unique disease progression path and genetic profile. Whether this is true for MCL patients is still unknown and deserves further study. The role of the 11q23 deletion in the development of the Richter’s syndrome and its molecular background also deserves more investigation. If a correlation could be established between the 11q23 deletion and the development of the Richter’s syndrome, the deletion will be an important prognostic factor. The difference in the frequencies of the 11q23 deletion in lymph node specimens and the peripheral blood specimens in CLL/SLL is also an interesting subject. We ought to look more closely at the genetic profiles of both CLL and SLL. The cDNA array analysis has been used to identify separate disease groups, previously considered as one disease entity (Alizadeh et al., 2000). With careful planning and sample selection, we could also get more insights into the nature of these two diseases by utilizing the array technology. 61 Not only enormous quantities of biological data, but also new technologies, are emerging with high speed in the fields of cytogenetics, molecular genetics and cell biology. We have gained valuable biological information from our successful utilization of various techniques throughout the studies in this thesis, as well as experience in using the techniques. We hope that this knowledge and experience will be beneficial to our future investigations. 62 11 ACKNOWLEDGEMENTS This thesis work has been carried out in the Department of Medical Genetics, University of Helsinki during 1997-2002. I would like to express my sincere gratitude to all the people that have made this thesis possible. Special thanks go to my supervisors, Sakari Knuutila and Heikki Joensuu, who have introduced me to the world of science and guided me through my first journey as a scientific researcher. Sakari is particularly thanked for creating a friendly working environment. The former and present heads of the Department of Medical Genetics, Albert de la Chapelle, Juha Kere, Leena Palotie, Pertti Aula and Anna-Elina Lehesjoki, are warmly thanked for providing excellent research facilities. I would like to thank the thorough and expert work the official referees of this thesis, Tarja-Terttu Pelliniemi and Maija Wessman, have done. The reviewing process has been crucial to this thesis and is very educational to me. All my co-authors are thanked for the pleasant and fruitful collaboration: Outi Monni, Kaarle Franssila, Riikka Räty, Pia Höglund, Erkki Elonen, Wa’el El-Rifai, Sanna Siitonen, Leena Vilpo, Juhani Vilpo, Anu Loukola, Katja Kuokkanen, Juha Kere, Lauri Aaltonen, Jaakko Hollmén, Yan Aalto, Balint Nagy and Heikki Mannila. In particular, I want to thank Outi Monni for being not only the most important collaborator of this thesis work, but also a true friend. In addition, I want to thank the staff of the routine lab at the 4 th floor for their assistance over the years. Pirjo Pennanen is thanked for the assistance in practical matters and language revision of all my articles. Anne Hand is thanked for the language revision of this thesis. It could have been a very long and boring five-years, if it were not with all my former and present colleagues. Outi, Maija Wolf and Anna-Maria Björkqvist, thank you for helping me through the initial clumsiness and all the fun we had together. My P-floor folks, Yan, Tarja, Anna, Sílvia, Eeva, Haiju, Florence and Kowan, we have become so close together, it feels very hard to leave now. In particular, I want to thank Yan for her kindness and friendship, and all the girlie talks we shared. Special 64 12 REFERENCES Aalto Y, El-Rifai W, Vilpo L, Ollila J, Nagy B, Vihinen M, Vilpo J, Knuutila S (2001) Distinct gene expression profiling in chronic lymphocytic leukemia with 11q23 deletion. Leukemia, 15, 1721-1728. Albertson DG, Ylstra B, Segraves R, Collins C, Dairkee SH, Kowbel D, Kuo WL, Gray JW, Pinkel D (2000) Quantitative mapping of amplicon structure by array CGH identifies CYP24 as a candidate oncogene. Nat Genet, 25, 144-146. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, Powell JI, Yang L, Marti GE, Moore T, Hudson J, Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Levy R, Wilson W, Grever MR, Byrd JC, Botstein D, Brown PO, Staudt LM (2000) Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature, 403, 503-511. Amason R, Sigaux F, Frzedborski S, Flandrin G, Givol D, Telerman A (1989) The human protooncogene product p33pim is expressed during fetal hematopoiesis and in diverse leukemias. Proc Natl Acad Sci USA, 86, 8857-8861. Arai Y, Hosoda F, Nakayama K, Ohki M (1996) A yeast artificial contig and NotI restriction map that spans the tumor suppressor gene(s) locus, 11q22.2-q23.3. Genomics, 35, 196-206. Argatoff LH, Connors JM, Klasa RJ, Horsman DE, Gascoyne RD (1997) Mantle cell lymphoma: a clinicopathologic study of 80 cases. Blood, 89, 2067-2078. Autio K, Aalto Y, Franssila K, Elonen E, Joensuu H, Knuutila S (1998) Low number of DNA copy number changes in small lymphocytic lymphoma. Haematologica, 83, 690-692. Autio K, Elonen E, Teerenhovi L, Knuutila S (1987) Cytogenetic and immunologic characterization of mitotic cells in chronic lymphocytic leukemia. Eur J Haematol, 39, 289-298. Azofeifa J, Fauth C, Kraus J, Maierhofer C, Langer S, Bolzer A, Reichman J, Schuffenhauer S, Speicher MR (2000) An optimized probe set for the detection of small interchromosomal aberrations by 24-color FISH. Am J Hum Genet, 66, 1684- 1688. Baffa R, Negrini M, Mandes B, Rugge M, Ranzani GN, Hirohashi s, Croce CM (1996) Loss of heterozygosity for chromosome 11 in adenocarcinoma of the stomach. Cancer Res, 56, 268-272. Banin S, Moyal L, Shieh S, Taya Y, Anderson CW, Chessa L, Smorodinsky NI, Prives C, Reiss Y, Shiloh Y, Ziv Y (1998) Enhanced phosphorylation of p53 by ATM in response to DNA damage. Science, 281, 1674-1677. Banks PM, Chan J, Cleary ML, Delsol G, De Wolf-Peeters C, Gatter K, Grogan TM, Harris NL, Isaacson PG, Jaffe ES, Mason D, Pileri S, Ralfkiaer E, Stein H, Warnke RA (1992) Mantle cell lymphoma: A proposal for unification of morphologic, immunologic, and molecular data. Am J Pathol, 16, 637-640. Bannerji R, Byrd JC (2000) Update on the biology of chronic lymphocytic leukemia. Curr Opin Oncol, 12, 22-29. 65 Baskaran R, Wood LD, Whitaker LL, Canman CE, Morgan SE, Xu Y, Barlow C, Baltimore D, Wynshaw-Boris A, Kastan MB, Wang JY (1997) Ataxia telangiectasia mutant protein activates c-Abl tyrosine kinase in response to ionizing radiation (see comments). Nature, 387, 516-519. Baysal BE, Farr JE, Goss JR, Devlin B, Richard CWI (1998) Genomic organization and precise physical location of protein phosphatase 2A regulatory subunit A beta isoform gene on chromosome band 11q23. Gene, 217, 107-116. Baysal BE, Ferrell RE, Willett-Brozick JE, Lawrence EC, Myssiorek D, Bosch A, van der Mey A, Taschner PEM, Rubinstein WS, Myers EN, Richard CWI, Cornelisse CJ, Devilee P, Devlin B (2000) Mutation in SDHD, a mitochondrial complex II gene, in hereditary paraganglioma. Science, 287, 848-851. General Haematologic Task Force of BCSH (1994) Immunophenotyping in the diagnosis of chronic lymphoproliferative disorders. J Clin Pathol, 47, 871-875. Beà S, Ribas M, Hernández JM, Bosch F, Pinyol M, Hernández L, García JL, Flores T, González M, López-Guillermo A, Piris MA, Cardesa A, Montserrat E, Miró R, Campo E (1999) Increased number of chromosomal imbalances and high-level DNA amplifications in mantle cell lymphoma are associated with blastoid variants. Blood, 93, 4365-4374. Ben-Yehuda D, Houldsworth J, Parsa NZ, Chaganti RSK (1994) Gene amplification in non-Hodgkin's lymphoma. Br J Haematol, 86, 792-797. Bennett JM, Catovsky D, Daniel M-T, Flanderin G, Galton DAG, Gralnick HR, Sultan C (1989) Proposals for the classification of chronic (mature) B and T lymphoid leukaemias. J Clin Pathol, 42, 567-584. Bentz M, Plesch A, Stilgenbauer S, Döhner H, Lichter P (1998) Minimal sizes of deletions detected by comparative genomic hybridization. Genes Chromosomes Cancer, 21, 172-175. Bentz M, Stilgenbauer S, Lichter P, Dähner H (1999) Interphase FISH in chronic lymphoproliferative disorders and comparative genomic hybridisation in the study of lymphomas. Haematologica, 84, 102-106. Berard CW, Dorfman RF (1974) Histopathology of malignant lymphomas. Clin Hematol, 3, 39. Bethwaite PB, Koreth J, Herrington CS, McGee JOD (1995) Loss of heterozygosity occurs at the D11S29 locus on chromosome 11q23 in invasive cervical carcinoma. Br J Cancer, 71, 814-818. Bevan S, Catovsky D, Marossy A, Matutes E, Popat S, Antonovic P, Bell A, Berrebi A, Gaminara EJ, Quabeck K, Ribeiro I, Mauro FR, Stark P, Sykes H, van Dongen J, Wimperis J, Wright S, Yuille MR, Houlston RS (1999) Linkage analysis for ATM in familial B cell chronic lymphocytic leukaemia. Leukemia, 13, 1497-1500. Binet JL, Auquier A, Digihiero G, Chastang C, Piguet H, Goasguen J, Vaugier G, Potron G, Colona P, Oberling F, Thomas M, Tchernia G, Jacquillat C, Boivin P, Lesty C, Duault MT, Monconduit M, Belabbes S, Gremy F (1981) A new prognostic classification of chronic lymphocytic leukemia derived from a multivariate survival analysis. Cancer, 48, 198-206. 66 Bittner M, Meltzer P, Chen Y, Jiang Y, Seftor E, Hendrix M, Radmacher M, Simon R, Yakhini Z, Ben-Dor A, Sampas N, Dougherty E, Wang E, Marincola F, Gooden C, Lueders J, Glatfelter A, Pollock P, Carpten J, Gillanders E, Leja D, Dietrich K, Beaudry C, Berens M, Alberts D, Sondak V, Hayward N, Trent J (2000) Molecular classification of cutaneous malignant melanoma by gene expression profiling. Nature, 406, 536-540. Blaeker H, Rasheed BK, McLendon RE, Friedman HS, Batra SK, Fuchs HE, Bigner SH (1996) Microsatellite analysis of childhood brain tumors. Genes Chromosomes Cancer, 15, 54-63. Bowman EP, Campbell JJ, Druey KM, Scheschonka A, Kehrl JH, Butcher EC (1998) Regulation of chemotactic and proadhesive responses to chemoattractant receptors by RGS (regulator of G-protein signaling) family members. J Biol Chem, 273, 28040- 28048. Brown AL, Lee CH, Schwarz JK, Mitiku N, Piwnica-Worms H, Chung JH (1999) A human Cds1-related kinase that function downstream of ATM protein in the cellular response to DNA damage. Proc Natl Acad Sci USA, 96, 3745-3750. Bruder CEG, Hirvelä C, Tapia-Paez I, Fransson I, Segraves R, Hamilton G, Zhang XX, Evans DG, Wallace AJ, Baser ME, Zucman-Rossi J, Hergersberg M, Boltshauser E, Papi L, Rouleau GA, Poptodorov G, Jordanova A, Rask-Andersen H, Kluwe L, Mautner V, Sainio M, Hung G, Mathiesen T, Möller C, Pulst SM, Harder H, Heiberg A, Honda M, Niimura M, Sahlén S, Blennow E, Albertson DG, Pinkel D, Dumanski JP (2001) High resolution deletion analysis of constitutional DNA from neurofibromatosis type 2 (NF2) patients using microarray-CGH. Hum Mol Genet, 10, 271-282. Bubendorf L, Kononen J, Koivisto P, Schraml P, Moch H, Gasser TC, Willi N, Mihatsch MJ, Sauter G, Kallioniemi O-P (1999) Survey of gene amplification during prostate cancer progression by high-throughput fluorescence in situ hybridization on tissue microarray. Cancer Res, 59, 803-806. Bullrich F, Rasio D, Kitada S, Starostik P, Kipps T, Keating M, Albitar M, Reed JC, Croce CM (1999) ATM Mutations in B-cell chronic lymphocytic leukemia. Cancer Res, 59, 24-27. Burke DT, Carle GF, Olson MV (1987) Cloning of large segments of exogenous DNA into yeast by means of articifial chromosome vectors. Science, 236, 806-812. Buroker N, Bestwick R, Haight G, Magenis RE, Litt M (1987) A hypervariable repeated sequence on human chromosome 1p36. Hum Genet, 77, 175-181. Camacho E, Hernández L, Hernández S, Tort F, Bellosillo B, Beà S, Bosch F, Montserrat E, Cardesa A, Fernández PL, Campo E (2002) ATM gene inactivation in mantle cell lymphoma mainly occurs by truncating mutations and missense mutations involving the phosphatidylinositol-3 kinase domain and is associated with increasing numbers of chromosomal imbalances. Blood, 99, 238-244. Campbell IG, Manolitsas T (1999) Absence of PPP2R1B gene alterations in primary ovarian cancers. Oncogene, 18, 6367-6369. Canman CE, Lim DS, Cimprich KA, Taya Y, Tamai K, Sakaguchi K, Appella E, Kastan MB, Siliciano JD (1998) Activation of the ATM kinase by ionizing radiation and phosphorylation of p53. Science, 281, 1677-1679. 67 Carbone PP, Kaplan HS, Musshoff K, Smithers DW, Tubiana M (1971) Report of the committee on Hodgkin's disease staging. Cancer Res, 31, 1860-1861. Cargill M, Altshuler D, Ireland J, Sklar P, Ardlie K, Patil N, Lane CR, Lim EP, Kalayanaraman N, Nemesh J, Ziaugra L, Friedland L, Rolfe A, Warrington J, Lipshutz R, Daley GQ, Lander ES (1999) Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nat Genet, 22, 231-238. Carter SL, Negrini M, Baffa R, Gillum DR, Rosenberg AL, Schwartz GF, Croce CM (1994) Loss of heterozygosity at 11q22-q23 in breast cancer. Cancer Res, 54, 6270- 6274. Caspersson T, Farber S, Foley GD, Kudynoski J, Modest EJ, Simonsson E, Wagh U, Zech L (1968) Chemical differentiation along metaphase chromosomes. Exp Cell Res, 49, 219-222. Cesarman GM, Guevara CA, Hajjar KA (1994) An endothelial cell receptor for plasminogen/tissue plasminogen activator (t-PA). II. Annexin II-mediated enhancement of t-PA-dependent plasminogen activation. J Biol Chem, 269, 21198- 21203. Chandrasekharappa SC, Guru SC, Manickam P, al. e (1997) Positional cloning of the gene for multiple endocrine neoplasia-type 1. Science, 276, 404-407. Chu BCF, Wahl GM, Orgel LE (1983) Derivitization öf unprotected polynucleotides. Nucleic Acids Res, 11, 6513-6529. Chudoba I, Plesch A, Lörch T, Lemke J, Claussen U, Senger G (1999) High resolution multicolor-banding: a new technique for refined FISH analysis of human chromosomes. Cytogenet Cell Genet, 84, 156-160. Chung CY, Murphy-Ullrich JE, Erickson HP (1996) Mitogenesis, cell migration, and loss of focal adhesions induced by tenascin-C interacting with its cell surface receptor, annexin II. Mol Biol Cell, 7, 883-892. Cohen D, Chumakov I, Weissenbach J (1993) A first-generation physical map of the human genome. Nature, 366, 698-701. Corcoran MM, Rasool O, Liu Y, Iyengar A, Grander D, Ibbotson RE, Merup M, Wu X, Brodyansky V, Gardiner AC, Juliussion G, Chapman RM, Ivanova G, Tiller M, Gahrton G, Yankovsky N, Zabarovsky E, Oscier DG, Einhorn S (1998) Detailed molecular delineation of 13q14.3 loss in B-cell chronic lymphcytic leukemia. Blood, 91, 1382-1390. Cordone I, Masi S, Mauro FR (1998) p53 expression in B cell chronic lymphocytic leukemia. Blood, 91, 4342-4349. Cremer T, Landegent J, Bruckner A, Scholl HP, Schardin M, Hager HD, Devilee P, Pearson P, van der Ploeg M (1986) Detection of chromosome aberrations in the human interphase nucleus by visualization of specific target DNAs with radioactive and non-radioactive in situ hybridization techniques: Diagnosis of trisomy 18 with probe L.184. Hum Genet, 74, 346-352. Criel A, Wlodarska I, Meeus P, Stul M, Louwagie A, van Hoof A, Hidajat M, Mecucci C, van den Berghe H (1994) Trisomy 12 is uncommon in typical chronic lymphocytic leukaemias. Br J Haematol, 87, 523-528. 68 Dahiya R, McCarville J, Lee C, Hu W, Kaur G, Carroll P, Deng G (1997) Deletion of chromosome 11p15, p12, q22, q23-24 loci in human prostate cancer. Int J Cancer, 72, 283-288. Dalla-Favera R, Bregni M, Erikson J, Patterson D, Gallo RC, Croce CM (1982) Human c-myc onc gene is located on the region of chromosome 8 that is translocated in Burkitt lymphoma cells. Proc Natl Acad Sci USA, 79, 7824-7827. Damle RN, Wasil T, Fais F, Ghiotto F, Valetto A, Allen SL, Buchbinder A, Budman D, Dittmar K, Kolitz J, Lichtman SM, Schulman P, Vinciguerra VP, Rai KR, Ferrarini M, Chiorazzi N (1999) Ig V gene mutation status and CD38 expression as novel prognostic indicators in chronic lymphocytic leukemia. Blood, 94, 1840-1847. Dang CV, Resar LMS, Emison E, Kim S, Li Q, Prescott JE, Wonsey D, Zeller K (1999) Function of the c-Myc oncogenic transcription factor. Exp Cell Res, 253, 63- 77. Davis M, Hitchcock A, Foulkes WD, Campbell IG (1996) Refinement of two chromosome 11q regions of loss of heterozygosity in ovarian cancer. Cancer Res, 56, 741-744. DiSepio D, Ghosn C, Eckert RL, Deucher A, Robinson N, Duvic M, Chandraratna RAS, Nagpal S (1998) Identification and characterization of a retinoid-induced class II tumor supporessor / growth regulatory gene. Proc Natl Acad Sci USA, 95, 14811- 14815. du Manoir S, Speicher MR, Joos S, Schrock E, Popp S, Dohner H, Kovacs G, Robert Nicoud M, Lichter P, Cremer T (1993) Detection of complete and partial chromosome gains and losses by comparative genomic in situ hybridization. Hum Genet, 90, 590-610. Duda RO, Peter EH, Stork DG (2001) Pattern classification. 2nd ed. John Wiley & Sons, New York. Dudoit S, Fridlyand J, Speed TP (2000) Comparison of discrimination methods for the classification of tumors using gene expression data. Technical Report from the Department of Statistics at the University of California, Berkeley. Döhner H, Stilgenbauer S, Benner A, Leupolt E, Kröber A, Bullinger L, Döhner K, Bentz M, Lichter P (2000) Genomic aberrations and survival in chronic lymphocytic leukemia. N Engl J Med, 343, 1910-1916. Döhner H, Stilgenbauer S, Döhner K, Bentz M, Lichter P (1999) Chromosome aberrations in B-cell chronic lymphocytic leukemia: reassessment based on molecular cytogenetic analysis. J Mol Med, 77, 266-281. Döhner H, Stilgenbauer S, James MR, Benner A, Weilguni T, Bentz M, Fischer K, Hunstein W, Lichter P (1997) 11q deletions identify a new subset of B-cell chronic lymphocytic leukemia characterized by extensive nodal involvement and inferior prognosis. Blood, 89, 2516-2522. Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA, 95, 14863-14868. Elledge SJ (1996) Cell cycle checkpoints: preventing an identity crisis. Science, 274, 1664-1672. 69 Emmerich P, Loos P, Jauch A, Hopman AHN, Wiegant J, Higgins MJ, White BN, van der Ploeg M, Cremer C, Cremer T (1989) Double in situ hybridization in combination with digital image analysis: a new approach to study interphase chromosome topography. Exp Cell Res, 181, 126-140. Ermolaeva O, Rastogi M, Pruitt KD, Schuler GD, Bittner ML, Chen Y, Simon R, Meltzer P, Trent JM, Boguski MS (1998) Data management and analysis for gene expression arrays. Nat Genet, 20, 19-23. Escidoer SM, Pereira-Leahy JM, Drach JW, Weier HU, Goodacre AM, Cork MA, Trujillo JM, Keating MJ, Andreeff M (1993) Fluorescence in situ hybridization and cytogenetic studies of trisomy 12 in chronic lymphocytic leukemia. Blood, 81, 2702- 2707. Feiss M, Siegele DA, Rudolph CF, Frackman S (1982) Cosmid DNA packaging in vivo. Gene, 17, 123-130. Fisher RI, Dahlberg S, Nathwani BN, Banks PM, Miller TP, Grogan TM (1995) A clinical analysis of two indolent lymphoma entities: mantle cell lymphoma and marginal zone lymphoma (including the mucosa-associated lymphoid tissue and monocytoid B-cell subcategories): a Southwest Oncology Group study. Blood, 85, 1075-1082. Florijn RJ, Bonden LAJ, Vrolijk H, Wiegant J, Vaandrager J-W, Baas F, den Dunnen JT, Tanke HJ, B. vOG-J, Raap AK (1995) High-resolution DNA fiber-fish for genomic DNA mapping and colour bar-coding of large genes. Hum Mol Genet, 4, 831-836. Foucar K (1992) B cell chronic lymphocytic and prolymphocytic leukemia Neoplastic Hematopathology, (ed. by Knowles DM), Williams & Wilkins, Baltimore. Foulkes WD, Campbell IG, Stamp GWH, Trowsdale J (1993) Loss of heterozygosity and amplification on chromosome 11q in human ovarian cancer. Br J Cancer, 67, 268-273. Gabra H, Taylor L, Cohen BB, Lessels A, Eccles DM, Leonard RC, Smyth JF, Steel CM (1995) Chromosome 11 allele imbalance and clinicopathological correlates in ovarian tumours. Br J Cancer, 72, 367-375. Gabra H, Watson JE, Taylor KJ, Mackay J, Leonard RC, Steel CM, Porteous DJ, Smyth JF (1996) Definition and refinement of a region of loss of heterozygosity at 11q23.3-q24.3 in epithelial ovarian cancer associated with poor prognosis. Cancer Res, 56, 950-954. Gioeli D, Conway K, Weissman BE (1997) Localization and characterization of a chromosome 11 tumor suppressor gene using organotypic raft cultures. Cancer Res, 57, 1157-1165. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh MH, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science, 286, 531-537. Greiner TC, Moynihan MJ, Chan WC, Lytle DM, Pedersen A, Anderson JR, Weisenburger DD (1996) p53 mutations in mantle cell lymphoma are associated with variant cytology and predict a poor prognosis. Blood, 87, 4302-4310. 70 Guo Z, Guilfoyle RA, Thiel AJ, Wang R, Smith LM (1994) Direct fluorescence analysis of genetic polymorphisms by hybridization with oligonucleotide arrays on glass supports. Nucleic Acids Res, 22, 5456-5465. Hacia GH, Brody LC, Chee MS, Fodor SPA, Collins FS (1996) Detection of heterozygous mutations in BRCA1 using high-density oligonucleotide arrays and two color fluorescence analysis. Nat Genet, 14, 441-447. Haddad BR, Schröck E, Meck J, Cowan J, Young H, Ferguson-Smith MA, du Manoir S, Ried T (1998) Identification of de novo chromosomal markers and derivatives by spectral karyotyping. Hum Genet, 103, 619-625. Halushka MK, Fan J-B, Bentley K, Hsie L, Shen N, Weder A, Cooper R, Lipshutz R, Chakravarti A (1999) Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis. Nat Genet, 22, 239-247. Hamblin TJ, Davis Z, Gardiner A, Oscier DG, Stevenson FK (1999) Unmutated Ig VH genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood, 94, 1848-1854. Hampton GM, Mannermaa A, Winquist R, Alavaikko M, Blanco G, Taskinen PJ, Kiviniemi H, Newsham I, Cavenee WK, Evans GA (1994a) Loss of heterozygosity in sporadic human breast carcinoma: A common region between 11q22 and 11q23.3. Cancer Res, 54, 4586-4589. Hampton GM, Penny LA, Baergen RN, Larson A, Brewer C, Liao S, Busby-Earle RMC, Williams AWR, Steel CM, Bird CC, Stanbridge EJ, Evans GA (1994b) Loss of heterozygosity in cervical carcinoma: Subchromosomal localization of a putative tumor-suppressor gene to chromosome 11q22-q24. Proc Natl Acad Sci USA, 91, 6953-6957. Hanada M, Delia D, Aiello A, Stadtmauer E, Reed J (1993) bcl-2 gene hypothemylation and high-level expression in B-cell chronic lymphocytic leukemia. Blood, 82, 1820-1828. Harris NL, Jaffe ES, Diebold J, Flandrin G, Muller-Hermelink H-K, Vardiman J (2000) Lymphoma Classification-from controversy to consensus: the REAL and WHO classification of lymphoid neoplasms. Anal Oncol, 11 (Suppl. 1), S3-S10. Harris NL, Jaffe ES, Stein H, Banks PM, Chan JKC, Cleary ML, Delsol G, De Wolf- Peeters C, Falini B, Gatter KC, Grogan TM, Isaacson PG, Knowles DM, Mason DY, Muller-Hermelink HK, Pileri SA, Piris MA, Ralfkiaer E, Warnke RA (1994) A revised European-American classification of lymphoid neoplasms: A proposal from the international lymphoma study group. Blood, 84, 1361-1392. Heerema NA, Arthur DC, Sather H, Albo V, Feusner J, Lange BJ, Steinherz PG, Zeltzer P, Hammond D, Reaman GH (1994) Cytogenetic features of infants less than 12 months of age at diagnosis of acute lymphoblastic leukemia: impact of the 11q23 breakpoint on outcome: a report of the Children's Cancer Group. Blood, 83, 2274- 2284. Heiden T, Wang N, Bernhard T (1991) An improved Hedley method for preparation for paraffin-embedded tissues for flow-cytometric analysis of ploidy and S-phase. Cytometry, 12, 614-621. Heim S, Mitelman F (1995) Cancer cytogenetics. 2 ed. Wiley-Liss, New York. 71 Heiskanen M, Peltonen L, Palotie A (1996) Visual mapping by high resolution FISH. Trends Genet, 10, 379-382. Heiskanen MA, Bittner ML, Chen Y, Khan J, Adler KE, Trent JM, Meltzer PS (2000) Detection of gene amplification by genomic hybridization to cDNA microarrays. Cancer Res, 60, 799-802. Hemmer S, Wasenius V-M, Haglund C, Zhu Y, Knuutila S, Franssila K, Joensuu H (2002) Alterations in the suppressor gene PPP2R1B in parathyroid hyperplasia and adenoma. Cancer Genet Cytogenet, in press. Herbst RA, Gutzmer R, Matiaske F, Mommert S, Casper U, Kapp A, Weiss J (1999) Identification of two distinct deletion targets at 11q23 in cutaneous malignant melanoma. Int J Cancer, 80, 205-209. Herbst RA, Larson A, Weiss J, Cavenee WK, Hampton GM, Arden KC (1995) A defined region of loss of heterozygosity at 11q23 in cutaneous malignant melanoma. Cancer Res, 55, 2494-2496. Hilsenbeck SG, Friedrichs WE, Schiff R, O'Connell P, Hansen RK, Osborne CK, Fuqua SAW (1999) Statistical analysis of array expression data as applied to the problem of tamoxifen resistance. J Natl Cancer Inst, 91, 453-459. Hoffman C, Winston F (1987) A ten minute DNA preparation from yeast efficiently releases autonomous plasmids for transformation of Escherichia coli. Gene, 57, 267- 272. Hromas R, May W, Denny C, al. e (1993) Human FLI-1 localizes to chromosome 11Q24 and has an aberrant transcript in neuroepithelioma. Biochim Biophy, 1172, 155-158. Hui AB, Lo KW, Leung SF, Choi PH, Fong Y, Lee JC, Huang DP (1996) Loss of heterozygosity on the long arm of chromosome 11 in nasopharyngeal carcinoma. Cancer Res, 56, 3225-3229. Hunter T (1995) Protein kinases and phosphatases: the yin and yang of protein phosphorylation and signaling. Cell, 80, 225-236. Hyytinen E, Visakorpi T, Kallioniemi A, Kallioniemi OP, Isola JJ (1994) Improved technique for analysis of formalin-fixed, paraffin-embedded tumors by fluorescence in situ hybridization. Cytometry, 16, 93-99. Iizuka M, Sugiyama Y, Shiraishi M, Jones C, Sekiya T (1995) Allelic losses in human chromosome 11 in lung cancers. Genes Chromosomes Cancer, 13, 40-46. Inazawa J, Ariyama T, Tokino T, Tanigami A, Nakamura Y, Abe T (1994) High resolution ordering of DNA markers by multi-color fluorescence in situ hybridization of prophase chromosomes. Cytogenet Cell Genet, 65, 130-135. Ioannou PA, Amemiya CT, Garnes J, Kroisel PM, Shizuya H, Chen C, Batzer MA, de Jong PJ (1994) A new bacteriophage P1-derived vector for the propagation of large human DNA fragments. Nat Genet, 6, 84-89. Isaacson PG (2000) The current status of lymphoma classification. Br J Haematol, 109, 258-266. Isola J, DeVries S, Chu L, Ghazvini S, Waldman F (1994) Analysis of changes in DNA sequence copy number by comparative genomic hybridization in archival paraffin-embedded tumor samples. Am J Pathol, 145, 1301-1308. 72 Jaffe ES, Bookman MA, Longo DL (1987) Lymphocytic lymphoma of intermediate differentiation-mantle zone lymphoma: A distinct subtype of B-cell lymphoma. Hum Pathol, 18, 877-880. Jaffe ES, Harris NL, Stein H, Vardiman JW (2001) Pathology and genetics of tumours of haematopoietic and lymphoid tissues. IARCPress, Lyon. Johnson RT, Gotoh E, Mullinger AM, Ryan AJ, Shiloh Y, Ziv Y, Squires S (1999) Targeting double-strand breaks to replicating DNA identifies a subpathway of DSB repair that is defective in ataxia-telangiectasia cells. Biochem Biophy Res Commun, 261, 317-325. Joos B, Kuster H, Cone R (1997) Covalent attachment of hybridizable oligonucleotides to glass supports. Anal Biochem, 247, 96-101. Juliusson G, Gahrton G (1990) Chromosome aberrations in B-cell chronic lymphocytic leukemia. Pathogenetic and clinical implications. Cancer Genet Cytogenet, 45, 143-160. Juliusson G, Oscier D, Gahrton G, for the International Working Party of Chromosomes in CLL (IWCCLL) (1991) Cytogenetic findings and survival in B-cell chronic lymphocytic leukemia. Second IWCCLL compilation of data on 662 patients. Leuk Lymph, 5, 21-25. Kallioniemi A, Kallioniemi OP, Sudar D, Rutovitz D, Gray JW, Waldman F, Pinkel D (1992) Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors. Science, 258, 818-821. Kallioniemi OP, Kallioniemi A, Piper J, Isola J, Waldman FM, Gray JW, Pinkel D (1994) Optimizing comparative genomic hybridization for analysis of DNA sequence copy number changes in solid tumors. Genes Chromosomes Cancer, 10, 231-43. Kaneko Y, Maseki N, Takasaki M, Sakurai T, Hayashi Y, Nakazawa S, Mori T, Sakurai M, Takeda T, Shikano T (1986) Clinical and hematologic characteristics in acute leukemia with 11q23 translocations. Blood, 67, 484-491. Karhu R, Knuutila S, Kallioniemi OP, Siitonen S, Aine R, Vilpo L, Vilpo J (1997) Frequent loss of the 11q14-q24 region in chronic lymphocytic leukemia: a study by comparative genomic hybridization. Genes Chromosomes Cancer, 19, 286-290. Kehrl JH (1998) Heterotrimeric G protein signaling: roles in immune function and fine-tuning by RGS proteins. Immunity, 8, 1-10. Keldysh PL, Dragani TA, Fleischman EW, Konstantinova LN, Perevoschikov AG, Pierotti MA, Della Porta G, Kopnin BP (1993) 11q deletions in human colorectal carcinomas: cytogenetics and restriction fragment length polymorphism analysis. Genes Chromosomes Cancer, 6, 45-50. Kihara C, Tsunoda T, Tanaka T, Yamana H, Furukawa Y, Ono K, Kitahara O, Zembutsu H, Yanagawa R, Hirata K, Takagi T, Nakamura Y (2001) Predication of sensitivity of esophageal tumors to adjuvant chemotherapy by cDNA microarray analysis of gene-expression profiles. Cancer Res, 61, 6474-6479. Kiuchi N, Nakajima K, Ichiba M, Fukada T, Narimatsu M, Mizuno K, Hibi M, Hirano T (1999) STAT3 is required for the gp130-mediated full activation of the c-myc gene. J Exp Med, 189, 63-73. 73 Klinger K, Landes G, Shook D, Harvey R, Lopez L, Locke P, Lerner T (1992) Rapid detection of chromosome aneuploidies in uncultured amniocytes by using fluorescence in situ hybridization (FISH). Am J Hum Genet, 51, 55-65. Knudson AGJ (1971) Mutation and cancer: Statistical study of retinoblastoma. Proc Natl Acad Sci USA, 68, 820-823. Knuutila S, Aalto Y, Autio K, Björkqvist A-M, El-Rifai W, Hemmer S, Huhta T, Kettunen E, Kiuru-Kuhlefelt S, Larramendy ML, Lushnikova T, Monni O, Pere H, Tapper J, Tarkkanen M, Varis A, Wasenius V-M, Wolf M, Zhu Y (1999) DNA copy number losses in human neoplasms. Am J Pathol, 155, 683-694. Knuutila S, Björkqvist A-M, Autio K, Tarkkanen M, Wolf M, Monni O, Szymanska J, Larramendy ML, Tapper J, Pere H, El-Rifai W, Hemmer S, Wasenius V-M, Vidgren V, Zhu Y (1998) DNA copy number amplification in human neoplasms. Am J Pathol, 152, 1107-1123. Kononen J, Bubendorf L, Kallioniemi A, Barlund M, Schraml P, Leighton S, Torhorst J, Mihatsch MJ, Sauter G, Kallioniemi OP (1998) Tissue microarrays for high- throughput molecular profiling of tumor specimens. Nat Med, 4, 844-847. Koreth J, Bakkenist C, Larin Z, Hunt N, James M, McGee J (1999) 11q23.1 and 11q25-qter YACs suppress tumour growth in vivo. Oncogene, 18, 1157-1164. Koreth J, Bakkenist CJ, McGee JO (1997) Allelic deletions at chromosome 11q22- q23.1 and 11q25-qterm are frequent in sporadic breast but not colorectal cancers. Oncogene, 14, 431-437. Koreth J, Bethwaite PB, McGee JO (1995) Mutation at chromosome 11q23 in human non-familial breast cancer: a microdissection microsatellite analysis. J Pathol, 176, 11-18. Kuramochi M, Fukuhara H, Nobukuni T, Kanbe T, Maruyama T, Ghosh HP, Pletcher M, Isomura M, Onizuka M, Kitamura T, Sekiya T, Reeves RH, Murakami Y (2001) TSLC1 is a tumor-suppressor gene in human non-small-cell lung cancer. Nat Genet, 27, 427-430. Laake K, Ødegård Å, Andersen TI, Bukholm IK, Kåresen R, Nesland JM, Ottestad L, Shiloh Y, Børresen-Dale A-L (1997) Loss of heterozygosity at 11q23.1 in breast carcinomas: indication for involvement of a gene distal and close to ATM. Genes Chromosome Cancer, 18, 175-180. Laan M, Kallioniemi OP, Hellsten E, Alitalo K, Peltonen L, Palotie A (1995) Mechanically stretched chromosomes as targets for high-resolution FISH mapping. Genome Res, 5, 13-20. Larionov V, Kouprina N, Graves J, Chen XN, Korenberg JR, Resnick MA (1996) Specific cloning of human DNA as yeast artificial chromosomes by transformation- associated recombination. Proc Natl Acad Sci USA, 93, 491-496. Larramendy ML, Siitonen SM, Zhu Y, Hurme M, Vilpo L, Vilpo JA, Knuutila S, for the Tampere CLL group (1998) Optimized mitogen stimulation induces proliferation of neoplastic B-cells in chronic lymphocytic leukemia - significance for cytogenetic analysis. Cytogenet Cell Genet, 82, 215-221. Lau C, Schonberg S (1984) A male-specific DNA probe detects heterochromatin sequences in a familial Yq-chromosome. Am J Hum Genet, 36, 1394-1396. 74 Launonen V, Laake K, Huusko P, Niederacher D, Beckman MW, Barkardottir RB, Geirsdottir EK, Gudmundsson J, Rio P, Bignon YJ, Seitz S, Scherneck S, Bieche I, Champeme MH, Birnbaum D, White G, Varley J, Sztan M, Olah E, Osorio A, Benitez J, Spurr N, Velikonja N, Peterlin B, Winqvist R (1999) European multicenter study on LOH of APOC3 at 11q23 in 766 breast cancer patients: relation to clinical variables. Breast Cancer Somatic Genetics Consortium. Br J Cancer, 80, 879-882. Launonen V, Stenback F, Puistola U, Bloigu R, Huusko P, Kytola S, Kauppila A, Winqvist R (1998) Chromosome 11q22.3-q25 LOH in ovarian cancer: association with a more aggressive disease course and involved subregions. Gynecol Oncol, 71, 299-304. Lengauer C, Speicher MR, Popp S, Jauch A, Taniwaki M, Nagaraja R, Riethman RC, Donis-Keller H, D'Urso M, Schlessinger D (1993) Chromosome bar codes constructed by fluoresce in situ hybridization wiht Alu-PCR products of multiple YAC clones. Hum Mol Genet, 2, 505-512. Lennert K (1978) Malignant Lymphomas: Other Than Hodgkin's Disease; Histology, Cytology, Ultrastructure, Immunology. Springer-Verlag, New York. Lennert K, Feller AC (1990) Histology of Non-Hodgkin's Lymphomas (Based on the Updated Kiel Classification). Springer-Verlag, Berlin. Lens SMA, Drillenburg P, den Drijver BFA, van Schijndel G, Pals ST, van Lier RAW, van Oers MHJ (1999) Aberrant expression and reverse signalling of CD70 on malignant B cells. Br J Haematol, 106, 491-503. Li R, Pei H, Papas T (1999) The p42 variant of ETS1 protein rescues defective Fas- induced apoptosis in colon carcinoma cells. Proc Natl Acad Sci USA, 96, 3876-3881. Lichter P, Tang C-JC, Call K, Hermanson G, Evans GA, Housman D, Ward DC (1990) High-resolution mapping of human chromosome 11 by in situ hybridization with cosmid clones. Science, 247, 64-69. Liu Y, Corcoran M, Rasool O, Ivanova G, Ibbotson R, Grandér D, Iyengar A, Baranova A, Kashuba V, Merup M, Wu X, Gardiner A, Mullenbach R, Poltaraus A, Hultström AL, Juliusson G, Chapman R, Tiller M, Cotter F, Gahrton G, Yankovsky N, Zabarovsky E, Einhorn s, Oscier D (1997) Cloning of two candidate tumor suppressor genes within a 10kb region on chromosome 13q14, frequently deleted in chronic lymphocytic leukemia. Oncogene, 15, 2463-2473. Losada AP, Wessman M, Tiainen M, Hopman AH, Willard HF, Sole F, Caballin MR, Woessner S, Knuutila S (1991) Trisomy 12 in chronic lymphocytic leukemia: an interphase cytogenetic study. Blood, 78, 775-779. Lucas JN, Sachs RK (1993) Using three-color chromosome painting to test chromosome aberration models. Proc Natl Acad Sci USA, 90, 1484-1487. Lukes RJ, Collins RD (1974) Immunologic characterization of human malignant lymphomas. Cancer, 34, 1488-1503. Lymphoma Classification Project (1997) A clinical evaluation of the International Lymphoma Study Group classification of non-Hodgkin's lymphoma. Blood, 89, 3909- 3918. 75 Mai J, Finley RLJ, Waisman DM, Sloane BF (2000a) Human procathepsin B interacts with the annexin II tetramer on the surface of tumor cells. J Biol Chem, 275, 12806- 12812. Mai J, Waisman DM, Sloane BF (2000b) Cell surface complex of cathepsin B/annexin II tetramer in malignant progression. Biochim Biophys Acta, 1477, 215- 230. Mariman EC, van Beersum SE, Cremers CW, van Baars FM, Ropers HH (1993) Analysis of a second family with hereditary non-chromaffin paragangliomas locates the underlying gene at the proximal region of chromosome 11q. Hum Genet, 91, 357- 361. Martin KJ, Kritzman BM, Price LM, Koh B, Kwan C-P, Zhang X, Mackay A, O'Hare MJ, Kaelin CM, Mutter GL, Pardee AB, Sager R (2000) Linking gene expression patterns to therapeutic groups in breast cancer. Cancer Res, 60, 2232-2238. Martin RH, Spriggs EL, Rademaker AW (1996) Multicolor fluorescence in situ hybridization analysis of aneuploidy and diploidy frequencies in 225 846 sperm from 10 normal men. Biol Reprod, 54, 394-398. Matsuoka S, Huang M, Elledge SJ (1998) Linkage of ATM to cell cycle regulation by the Chk2 protein kinase. Science, 282, 1893-1897. Matutes E, Oscier D, Garcia-Marco J, Ellis J, Copplestone A, Gillingham R, Hamblin T, Lens D, Swansbury GJ, Gatovsky D (1996) Trisomy 12 defines a group of CLL with atypical morphology: correlation between cytogenetic, clinical and laboratory features in 544 patients. Br J Haematol, 92, 382-388. Matutes E, Owusu-Ankomah K, Morilla R, Garcia Marco J, Houlihan A, Que TH, Catovsky D (1994) The immunological profile of B-cell disorders and proposal of a scoring system for the diagnosis of CLL. Leukemia, 8, 1640-1645. Mitelman F (1994) Catalog of Chromosome Aberrations in Cancer. 5th ed. Wiley- Liss, New York. Mitelman F (1995) An International System for Human Cytogenetic Nomenclature (1995). Karger, Memphis, TN. Moch H, Schraml P, Bubendorf L, Mirlacher M, Kononen J, Gasser T, Mihatsch MJ, Kallioniemi OP, Sauter G (1999) High-throughput tissue microarray analysis to evaluate genes uncovered by cDNA microarray screening in renal cell carcinoma. Am J Pathol, 154, 981-986. Monni O, Oinonen R, Elonen E, Franssila K, Teerenhovi L, Joensuu H, Knuutila S (1998) Gain of 3q and deletion of 11q are frequent aberrations in mantle cell lymphoma. Genes Chromosomes Cancer, 21, 298-307. Monni O, Zhu Y, Franssila K, Oinonen R, Elonen E, Höglund P, Joensuu H, Knuutila S (1999) Molecular characterization of the deletion at 11q22.1-q23.3 in mantle cell lymphoma. Br J Haematol, 104, 665-671. Moore L, Godfrey T, Eng C, Smith A, Ho R, Waldman FM (2000) Validation of fluorescent SSCP analysis for sensitive detection of p53 mutations. Biotechniques, 28, 986-992. 76 Moratz C, Kang VH, Druey KM, Shi CS, Scheschonka A, Murphy PM, Kozasa T, Kehrl JH (2000) Regulator of G protein signaling 1 (RGS1) markedly impairs Gi alpha signaling responses of B lymphocytes. J Immunol, 164, 1829-1838. Mugica-Van Herckenrode C, Rodriguez JA, Iriarte-Campo V, Carracedo A, Barros F (1999) Definition of a region of loss of heterozygosity at chromosome 11q in cervical carcinoma. Diag Mol Pathol, 8, 92-96. Murakami Y, Nobukuni T, Tamura K, Maruyama T, Sekiya T, Arai Y, Gomyou H, Tanigami A, Ohki M, Cabin D, Frischmeyer P, Hunt P, Reeves RH (1998) Localization of tumor suppressor activity important in nonsmall cell lung carcinoma on chromosome 11. Proc Natl Acad Sci USA, 95, 8153-8158. Negrini M, Rasio D, Hampton GM, Sabbioni S, Rattan S, Carter SL, Rosenberg AL, Schwartz GF, Shiloh Y, Cavenee WK, Croce CM (1995) Definition and refinement of chromosome 11 regions of loss of heterozygosity in breast cancer: Identification of a new region at 11q23.3. Cancer Res, 55, 3003-3007. Negrini M, Sabbioni S, Possati L, Rattan S, Corallini A, Barbanti-Brodano G, Croce CM (1994) Suppression of tumorigenicity of breast cancer cells by microcell- mediated chromosome transfer: studies on chromosome 6 and 11. Cancer Res, 54, 1331-1336. Non-Hodgkin's Lymphoma Pathologic Classification Project (1982) National Cancer Institute sponsored classificaitons of non-Hodgkin's lymphomas: summary and description of a Working Formulation for clinical useage. Cancer, 49, 2112-2135. Norton AJ, Matthews J, Pappa V, Shamash J, Love S, Rohatiner AZ, Lister TA (1995) Mantle cell lymphoma: natural history defined in a serially biopsied population over a 20-year period. Anal Oncol, 6, 249-256. Nuwaysir EF, Bittner M, Trent J, Barrett JC, Afshari CA (1999) Microarrays and toxicology: the advent of toxicogenomics. Mol Carcinog, 24, 153-159. Obrink B (1997) CEA adhesion molecules - multifunctional proteins with signal- regulatory properties. Curr Opin Cell Biol, 9, 616-626. Oinonen R, Franssila K, Teerenhovi L, Lappalainen K, Elonen E (1998) Mantle cell lymphoma: clinical features, treatment and prognosis of 94 patients. Eur J Cancer, 34, 329-336. Oliferenko S, Paiha K, Harder T, Gerke V, Schwarzler C, Schwarz H, Beug H, Gunthert U, Huber LA (1999) Analysis of CD44-containing lipid rafts: Recruitment of annexin II and stabilization by the actin cytoskeleton. J Cell Biol, 146, 843-854. Osaka M, Rowley JD, Zeleznik-Le NJ (1999) MSF (MLL septin-like fusion), a fusion partner gene of MLL, in a therapy-related acute myeloid leukemia with a t(11;17)(q23;q25). Proc Natl Acad Sci USA, 96, 6428-6433. Ott G, Kalla J, Ott MM, Schryen B, Katzenberger T, Muller JG, Muller-Hermelink HK (1997) Blastoid variants of mantle cell lymphoma: frequent bcl-1 rearrangements at the major translocation cluster region and tetraploid chromosome clones. Blood, 89, 1421-1429. Ott MM, Ott G, Kuse R, Porowski P, Gunzer U, Feller AC, Müller-Hermelink HK (1994) The anaplastic variant of centrocytic lymphoma is marked by frequent 77 rearrangements of the bcl-1 gene and high proliferation indices. Histopathology, 24, 329-334. Pedersen-Bjergaard J, Rowley JD (1994) The balanced and the unbalanced chromosome aberrations of acute myeloid leukemia may develop in different ways and may contribute differently to malignant transformation. Blood, 83, 2780-2786. Phillips KK, Welch DR, Miele ME, Lee JH, Wei LL, Weissman BE (1996) Suppression of MDA-MB-435 breast carcinoma cell metastasis following the introduction of human chromosome 11. Cancer Res, 56, 1222-1227. Pinkel D (1999) Fluorescence in situ hybridization Introduction to fluorescence in situ hybridization Principles and Clinical Applications, (ed. by Andreeff M, Pinkel D), Wiley-Liss, New York. Pinyol M, Cobo F, Bea S, Jares P, Nayach I, Fernandez PL, Montserrat E, Cardesa A, Campo E (1998) p 16INK4a gene in activation by deletions, mutations, and hypermethylation is associated with transformed and aggressive variants of non- Hodgkin's lymphomas. Blood, 91, 2977-2984. Pinyol M, Hernandez L, Cazorla M, Balbin M, Jares P, Fernandez PL, Montserrat E, Cardesa A, Lopez-Otin C, Campo E (1997) Deletions and loss of expression of p16INK4a and p21Waf1 genes are associated with aggressive variants of mantle cell lymphomas. Blood, 89, 272-280. Que TH, Marco JG, Ellis J, Matutes E, Babapulle VB, Boyle S, Catovsky D (1993) Trisomy 12 in chronic lymphocytic leukemia detected by fluorescence in situ hybridization: analysis by stage, immunophenotype, and morphology. Blood, 82, 571- 575. Rai KR, Sawitsky A, Chronkite EP, Chanana AD, Levy RN, Pasternack BS (1975) Clinical staging of chronic lymphocytic leukemia. Blood, 46, 219-234. Rappaport H (1966) Tumors of the hematopoietic system. Atlas of Tumor Pathology, Section III, (ed. by Armed Forces Institute of Pathology), Washington, DC. Rasio D, Negrini M, Manenti G, Dragani TA, Croce CM (1995) Loss of heterozygosity at chromosome 11q in lung adenocarcinoma: Identification of three independent regions. Cancer Res, 55, 3988-3991. Reif K, Cyster JG (2000) RGS molecule expression in murine B lymphocytes and ability to down-regulate chemotaxis to lymphoid chemokines. J Immunol, 164, 4720- 4729. Richter MN (1929) Generalized reticular cell sarcoma of lymph nodes associated with lymphatic leukemia. Am J Pathol, 4, 285-292. Ried T, Lengauer C, Cremer T, Wiegant J, Raap AK, van der Ploeg M, Groitl P, Lipp M (1992) Specific metaphase and interphase detection of the breakpoint region in 8q24 of Burkitt lymphoma cells by triple-color fluorescence in situ hybridization. Genes Chromosomes Cancer, 4, 69-74. Robertson G, Coleman A, Lugo TG (1996) A malignant melanoma tumor suppressor on human chromosome 11. Cancer Res, 56, 4487-4492. Rocchi M, Archidiacono N, Ward DC, Baldini A (1991) A human chromosome 9- specific alphoid DNA repeat spatially resovable from satellite 3 DNA by fluorescence in situ hybridization. Genomics, 9, 517-523. 78 Rosenberg C, Florijn RJ, van de Rijke FM, Blonden LA, Raap AK, van Ommen G- JB, den Dunnen JT (1995) High resolution DNA fiber-FISH on yeast artificial chromosomes: direct visualization of DNA replication. Nat Genet, 10, 477-479. Rosenwald A, Alizadeh AA, Widhopf G, Simon R, Davis RE, Yu X, Yang L, Pickeral OK, Rassenti LZ, Powell J, Botstein D, Byrd JC, Grever MR, Cheson BD, Chiorazzi N, Wilson WH, Kipps TJ, Brown PO, Staudt LM (2001) Relation of gene expression phenotype to immunoglobulin mutation genotype in B cell chronic lymphocytic leukemia. J Exp Med, 194, 1639-1647. Ross DT, Scherf U, Eisen MB, Perou CM, Rees C, Spellman P, Iyer V, Jeffrey SS, Van de Rijn M, Walthan M, Pergamenschikov A, Lee JCF, Lashkari D, Shalon D, Myers TG, Weinstein JN, Botstein D, Brown PO (2000) Systematic variation in gene expression patterns in human cancer cell lines. Nat Genet, 24, 227-235. Rozman C, Monserrat E (1995) Chronic lymphocytic leukemia. N Engl J Med, 333, 1052-1057. Sallinen S-L, Sallinen PK, Haapasalo HK, Helin HJ, Helén PT, Schraml P, Kallioniemi O-P, Kononen J (2000) Identification of differentially expressed genes in human gliomas by DNA microarray and tissue chip techniques. Cancer Res, 60, 6617-6622. Sanchez Y, Wong C, Thoma RS, Richman R, Wu Z, Piwnica-Worms H, Elledge SJ (1997) Conservation of the Chk1 checkpoint pathway in mammals: linkage of DNA damage to Cdk regulation through Cdc25. Science, 277, 1497-1501. Savitsky K, Bar-Shira A, Gilad S, Rotman G, Ziv Y, Vanagaite L, Tagle DA, Smith S, Uziel T, Sfez S (1995) A single ataxia telangiectasia gene with a product similar to P1-3 kinase. Science, 268, 1700-1701. Schaffner C, Idler I, Stilgenbauer S, Döhner H, Lichter P (2000) Mantle cell lymphoma is characterized by inactivation of the ATM gene. Proc Natl Acad Sci USA, 97, 2773-2778. Schaffner C, Stilgenbauer S, Rappold GA, Döhner H, Lichter P (1999) Somatic ATM mutations indicate a pathogenic role of ATM in B-cell chronic lymphocytic leukemia. Blood, 94, 748-753. Scherf U, Ross DT, Walthan M, Smith LH, Lee JK, Tanabe L, Kohn KW, Reinhold WC, Myers TG, Andrews DT, Scudiero DA, Eisen MB, Sausville EA, Pommier Y, Botstein D, Brown PO, Weinstein JN (2000) A gene expression database for the molecular pharmacology of cancer. Nat Genet, 24, 236-244. Schreiner SA, García-Cuéllar MP, Fey GH, Slany RK (1999) The leukemogenic fusion of MLL with ENL creates a novel transcriptional transactivator. Leukemia, 13, 1525-1533. Schröck E, du Manoir S, Veldman T, Schoell B, Wienberg J, Ferguson-Smith MA, Ning Y, Ledbetter DH, Bar-Am I, Soenksen D, Garini Y, Ried T (1996) Multicolor spectral karyotyping of human chromosomes. Science, 273, 494-497. Sembries S, Pahl H, Stilgenbauer S, Döhner H, Schriever F (1999) Reduced expression of adhesion molecules and cell signaling receptors by chronic lymphocytic leukemia cells with 11q-deletion. Blood, 93, 624-631. 79 Shafman T, Khanna KK, Kedar P, Spring K, Kozlov S, Yen T, Hobson K, Gatei M, Zhang N, Watters D, Egerton M, Shiloh Y, Kharbanda S, Kufe D, Lavin MF (1997) Interaction between ATM protein and c-Abl in response to DNA damage (see comments). Nature, 387, 520-523. Shaw ME, Knowles MA (1995) Deletion mapping of chromosome 11 in carcinoma of the bladder. Genes Chromosomes Cancer, 13, 1-8. Shirogane T, Fukada T, Muller JMM, Shima DT, Hibi M, Hirano T (1999) Synergic roles for Pim-1 and c-Myc in STAT3-mediated cell cycle progression and antiapopotosis. Immunity, 11, 709-719. Shizuya H, Birren B, Kim UJ, Mancino V, Slepak T, Tachiiri Y, Simon M (1992) Cloning and stable maintenance of 300-kilo-pair fragments of human DNA in Escherichia coli using a F-factor-based vector. Proc Natl Acad Sci USA, 89, 8794- 8797. Skubitz KM, Campbell KD, Skubitz APN (2000) Synthetic peptides of CD66a stimulate neutrophil adhesion to endothelial cells. J Immunol, 164, 4257-4264. Smid-Koopman E, Blok LJ, Chadha-Ajwani S, Helmerhorst TJM, Brinkmann AO, Huikeshoven FJ (2000) Gene expression profiles of human endometrial cancer samples using a cDNA-expression array technique: assessment of an analysis method. Br J Cancer, 83, 246-251. Solinas-Toldo S, Lampel S, Stilgenbauer S, Nickolenko J, Benner A, Döhner H, Cremer T, Lichter P (1997) Matrix-based comparative genomic hybridization: biochips to screen for genomic imbalances. Genes Chromosomes Cancer, 20, 399- 407. Speicher MR, Gwyn Ballard S, Ward DC (1996) Karyotyping human chromosomes by combinatorial multi-fluor FISH. Nat Genet, 12, 368-375. Spriggs EL, Rademaker AW, Martin RH (1995) Aneuploidy in human sperm: results of two- and three-color fluorescence in situ hybridization using centromeric probes for chromosomes 1, 12, 15, 18, X, and Y. Cytogenet Cell Genet, 71, 47-53. Spriggs EL, Rademaker AW, Martin RH (1996) Aneuploidy in human sperm: the use of multicolor FISH to test various theories of nondisjunction. Am J Hum Genet, 58, 356-362. Stankovic T, Weber P, Stewart G, Bedenham T, Murray J, Byrd PJ, Moss PAH, Taylor AMR (1999) Inactivation of ataxia telangiectasia mutated gene in B-cell chronic lymphocytic leukaemia. Lancet, 353, 26-29. Stansfeld AG, Diebold J, Kapanci Y, Kelenyi G, Lennert K, Mioduszewska O, Noel H, Rilke F, Sundström C, Van Unnik JAM, Wright DH (1988) Updated Kiel classification for lymphomas. Lancet, 1, 292-293. Starostik P, Manshouri T, O'Brien S, Freireich E, Kantarjian H, Haidar M, al. e (1998) Deficiency of the ATM protein expression defines an aggressive subgroup of B-cell chronic lymphocytic leukemia. Cancer Res, 58, 4552-4557. Sternberg NL (1990) Bacteriophage P1 cloning system for the isolation, amplification and recover of DNA fragments as large as 100 kilobases pairs. Proc Natl Acad Sci USA, 87, 103-107. 80 Stilgenbauer S, Liebisch P, James MR, Schröder M, Schlegelberger B, Fischer K, Bentz M, Lichter P, Döhner H (1996) Molecular cytogenetic delineation of a novel critical genomic region in chromosome bands 11q22.3-q23.1 in lymphoproliferative disorders. Proc Natl Acad Sci USA, 93, 11837-11841. Stilgenbauer S, Nickolenko J, Wilhelm J, Wolf S, Weitz S, Döhner K, Boehm T, Döhner H, Lichter P (1998) Expressed sequences as candidates for a novel tumor suppressor gene at band 13q14 in B-cell chronic lymphocytic leukemia and mantle cell lymphoma. Oncogene, 16, 1891-1897. Stilgenbauer S, Schaffner C, Litterst A, Liebisch P, Gilad S, Bar-Shira A, James MR, Lichter P, Döhner H (1997) Biallelic mutations in the ATM gene in T-prolymphocytic leukemia. Nature Medicine, 3, 1155-1159. Stilgenbauer S, Winkler D, Ott G, Schaffner C, Leupolt E, Bentz M, Möller P, Müller-Hermelink HK, James MR, Lichter P, Döhner H (1999) Molecular characterization of 11q deletions points to a pathogenic role of the ATM gene in mantle cell lymphoma. Blood, 94, 3262-3264. Su YA, Bittner ML, Chen Y, Tao L, Jiang Y, Zhang Y, Stephan DA, Trent JM (2000) Identification of tumor-suppressor genes using human melanome cell lines UACC903, UACC903(+6), and SRS3 by comparison of expression profiles. Mol Carcinog, 28, 119-127. Sutherland GR, Jacky PB, Baker E, Manuel A (1983) Heritable fragile sites on human chromosomes. X. New folate-sensitive fragile sites: 6p23, 9p21, 9q32, and 11q23. Am J Hum Genet, 35, 432-437. Swift M, Reitnauer PJ, Morrell D, L. CC (1987) Breast and other cancers in families with ataxia-telangiectasia. N Engl J Med, 316, 1289-1294. Sy MS, Mori H, Liu D (1997) CD44 as a marker in human cancers. Curr Opin Oncol, 9, 108-112. Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander ES, Golub TR (1999) Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proc Natl Acad Sci USA, 96, 2907-2912. Tanke HJ, Wiegant J, van Gijlswijk RPM, Bezrookove V, Pattenier H, Heetebrij RJ, Talman EG, Raap AK, Vrolijk J (1999) New strategy for multi-colour fluorescence in situ hybridisation: COBRA: COmbined Binary RAtio labelling. Eur J Hum Genet, 7, 2-11. Teerenhovi L, Lindholm C, Pakkala A, Franssila K, Stein H, Knuutila S (1988) Unique display of a pathologic karyotype in Hodgkin's disease by Reed-Sternberg cells. Cancer Genet Cytogenet, 34, 305-311. Teodorovic I, Pittaluga S, Kluin-Nelemans JC, Meerwaldt JH, Hagenbeek A, van Glabbeke M, Somers R, Bijnens L, Noordijk EM, Peeters CD (1995) Efficacy of four different regimens in 64 mantle-cell lymphoma cases: clinicopathologic comparison with 498 other non-Hodgkin's lymphoma subtypes. European Organization for the Research and Treatment of Cancer Lymphoma Cooperative Group. J Clin Oncol, 13, 2819-2826. Thompson JA, Grunert F, Zimmerman W (1991) Carcinoembryonic antigen gene family: molecular biology and clinical perspectives. J Clin Lab Anal, 5, 344-366. 81 Tkachuk DC, Westbrook CA, Andreeff M, Donlon TA, Cleary ML, Suryanarayan K, Homge M, Redner A, Gray J, Pinkel D (1990) Detection of bcr-abl fusion in chronic myelogenous leukemia by in situ hybridization. Science, 250, 559-562. Tomlinson IP, Bodmer WF (1996) Chromosome 11q in sporadic colorectal carcinoma: patterns of allele loss and their significance for tumorigenesis. J Clin Pathol, 49, 386-390. Trask BJ, Pinkel D, van den Engh G (1989) The proximity of DNA sequences in interphase cell nuclei is correlated to genomic distance and permits ordering of cosmids spanning 250 kilobase pairs. Genomics, 5, 710-717. Tsujimoto Y, Cossman J, Jaffe E, Croce CM (1985) Involvement of the bcl-2 gene in human follicular lymphoma. Science, 228, 1440-1443. Turc CC, Philip I, Berger MP, Philip T, Lenoir GM (1984) Chromosome study of Ewing's sarcoma (ES) cell lines. Consistency of a reciprocal translocation t(11;22)(q24;q12). Cancer Genet Cytogenet, 12, 1-19. Uhrig S, Schuffenhauer S, Fauth C, Wirtz A, Daumer-Haas C, Apacik C, Cohen M, Muller-Navia J, Cremer T, Murken J, Speicher MR (1999) Multiplex-FISH for pre- and postnatal diagnostic applications. Am J Hum Genet, 65, 448-462. Uzawa K, Suzuki H, Komiya A, Nakanishi H, Ogawara K, Tanzawa H, Sato K (1996) Evidence for two distinct tumor-suppressor gene loci on the long arm of chromosome 11 in human oral cancer. Int J Cancer, 67, 510-514. Velders GA, Kluin-Nelemans JC, De Boer CJ, Hermans J, Noordijk EM, Schuuring E, Kramer MH, Van Deijk WA, Rahder JB, Kluin PM, Van Krieken JH (1996) Mantle-cell lymphoma: a population-based clinical study. J Clin Oncol, 14, 1269- 1274. Veldman T, Vignon c, Schrock E, Rowley JD, Ried T (1997) Hidden chromosome abnormalities in haematological malignancies detected by multicolour spectral karyotyping. Nat Genet, 15, 406-410. Virtaneva K, Wright FA, Tanner SM, Yuan B, Lemon WJ, Caligiuri MA, Bloomfield CD, de la Chapelle A, Krahe R (2000) expression profiling reveals fundamental biological differences in acute myeloid leukemia with isolated trisomy and normal cytogenetics. Proc Natl Acad Sci USA, 98, 1124-1129. Vogelstein B, Kinzler KW (1998) The Genetic Basis of Human Cancer. McGraw-Hill Companies, Inc., Vrhovac R, Delmer A, Tang R, Marie JP, Zittoun R, Ajchenbaum-Cymbalista F (1998) Prognostic significance of the cell cycle inhibitor p27 kip1 in chronic B-cell lymphocytic leukemia. Blood, 91, 4694-4700. Vrolijk H, Florijn RJ, van de Rijke FM, van Ommen G-JB, den Dunnen T, Raap AK, Tanke HJ (1996) Microscopy and image analysis of fibre-FISH. Bioimaging, 4, 84- 92. Wang M, Duell T, Gray JW, Weier G-UG (1996) High sensitivity, high resolution physical mapping by fluorescence in situ hybridization on to individual straightened DNA molecules. Bioimaging, 4, 73-83. Wang S, Esplin E, Li J, Huang L, Gazdar A, Minna J, Evans G (1998) Alterations of the PPP2R1B gene in human lung and colon cancer. Science, 282, 284-287. 82 Wang SS, Virmani A, Gazdar AF, Minna JD, Evans GA (1999) Refined mapping of two regions of loss of heterozygosity on chromosome band 11q23 in lung cancer. Genes Chromosomes Cancer, 25, 154-159. Watson A, Mazumder A, Stewart M, Balasubramanian S (1998) Technology for microarray analysis of gene expression. Curr Opin Biotech, 9, 609-614. Weisenburger DD, Armitage JO (1996) Mantle cell lymphoma- an entity comes of age. Blood, 87, 4483-4494. Weisenburger DD, Nathwani BN, Diamond LW, Winberg CD, Rappaport H (1981) Malignant lymphoma, intermediate lymphocytic type: a clinicopathologic study of 42 cases. Cancer, 48, 1415-1425. Wilgenbus KK, Lichter P (1999) DNA chip technology ante portas. J Mol Med, 77, 761-768. Williams BJ, Ballenger CA, Malter HE, Bishop F, Tucker M, Zwingman TA, Hassold TJ (1993) Non-disjunction in human sperm: results of fluorescence in situ hybridization studies using two and three probes. Hum Mol Genet, 2, 1929-1936. Williams ME, Swerdlow SH, Rosenberg CL, Arnold A (1992) Characterization of chromosome 11 translocation breakpoints at the bcl-1 and PRAD1 loci in centrocytic lymphoma. Cancer Res, 52, 5541-5544. Windle B, Silvas E, Parra I (1995) High resolution microscopic mapping of DNA using multicolor fluorescent hybridization. Electrophoresis, 16, 273-278. Winqvist R, Hampton GM, Mannermaa A, Blanco G, Alavaikko M, Kiviniemi H, Taskinen PJ, Evans GA, Wright FA, Newsham I, Cavenee WK (1995) Loss of heterozygosity for chromosome 11 in primary human breast tumors is associated with poor survival after metastasis. Cancer Res, 55, 2664-2669. Wu R, Connolly DC, Ren X, Fearon ER, Cho KR (1999) Somatic mutations of the PPP2R1B candidate tumor suppressor gene at chromosome 11q23 are infrequent in ovarian carcinomas. Neoplasia, 1, 311-314. Yatabe Y, Suzuki R, Tobinai K, Matsuno Y, Ichinohasama R, Okamoto M, Yamaguchi M, Tamaru J, Uike N, Hashimoto Y, Morishima Y, Suchi T, Seto M, Nakamura S (2000) Significance of cyclin D1 overexpression for the diagnosis of mantle cell lymphoma: a clinicopathologic comparison of cyclin D1-positive MCL and cyclin D1-negative MCL-like-B-cell lymphoma. Blood, 95, 2253-2261. Yunis JJ, Soreng AL (1984) Constitutive fragile sites and cancer. Science, 226, 1199- 1204. Zenklusen JC, Oshimura M, Barrett JC, Conti CJ (1995) Human chromosome 11 inhibits tumorigenicity of a murine squamous cell carcinoma cell line. Genes Chromosomes Cancer, 13, 47-53. Zhu Y, Loukola A, Monni O, Kuokkanen K, Franssila K, Elonen E, Vilpo J, Joensuu H, Kere J, Aaltonen L, Knuutila S (2001) PPP2R1B gene in mantle cell lymphomas and chronic lymphocytic leukemias. Leuk Lymph, 41, 177-183. Zhu Y, Monni O, El-Rifai W, Siitonen SM, Vilpo L, Vilpo J, Knuutila S (1999) Discontinuous deletions at chromosome band 11q23 in B-cell chronic lymphocytic leukemia. Leukemia, 13, 708-712.