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  • Louhimo, Riku i; Laakso, Marko; Belitskin, Denis; Klefstrom, Juha; Lehtonen, Rainer; Hautaniemi, Sampsa (2016)
    Background: Genomic alterations affecting drug target proteins occur in several tumor types and are prime candidates for patient-specific tailored treatments. Increasingly, patients likely to benefit from targeted cancer therapy are selected based on molecular alterations. The selection of a precision therapy benefiting most patients is challenging but can be enhanced with integration of multiple types of molecular data. Data integration approaches for drug prioritization have successfully integrated diverse molecular data but do not take full advantage of existing data and literature. Results: We have built a knowledge-base which connects data from public databases with molecular results from over 2200 tumors, signaling pathways and drug-target databases. Moreover, we have developed a data mining algorithm to effectively utilize this heterogeneous knowledge-base. Our algorithm is designed to facilitate retargeting of existing drugs by stratifying samples and prioritizing drug targets. We analyzed 797 primary tumors from The Cancer Genome Atlas breast and ovarian cancer cohorts using our framework. FGFR, CDK and HER2 inhibitors were prioritized in breast and ovarian data sets. Estrogen receptor positive breast tumors showed potential sensitivity to targeted inhibitors of FGFR due to activation of FGFR3. Conclusions: Our results suggest that computational sample stratification selects potentially sensitive samples for targeted therapies and can aid in precision medicine drug repositioning. Source code is available from
  • Koli, Katri; Sutinen, Eva; Ronty, Mikko; Rantakari, Pia; Fortino, Vittorio; Pulkkinen, Ville; Greco, Dario; Sipila, Petra; Myllarniemi, Marjukka (2016)
    Idiopathic pulmonary fibrosis (IPF) is characterized by activation and injury of epithelial cells, the accumulation of connective tissue and changes in the inflammatory microenvironment. The bone morphogenetic protein (BMP) inhibitor protein gremlin-1 is associated with the progression of fibrosis both in human and mouse lung. We generated a transgenic mouse model expressing gremlin-1 in type II lung epithelial cells using the surfactant protein C (SPC) promoter and the Cre-LoxP system. Gremlin-1 protein expression was detected specifically in the lung after birth and did not result in any signs of respiratory insufficiency. Exposure to silicon dioxide resulted in reduced amounts of lymphocyte aggregates in transgenic lungs while no alteration in the fibrotic response was observed. Microarray gene expression profiling and analyses of bronchoalveolar lavage fluid cytokines indicated a reduced lymphocytic response and a downregulation of interferon-induced gene program. Consistent with reduced Th1 response, there was a downregulation of the mRNA and protein expression of the anti-fibrotic chemokine CXCL10, which has been linked to IPF. In human IPF patient samples we also established a strong negative correlation in the mRNA expression levels of gremlin-1 and CXCL10. Our results suggest that in addition to regulation of epithelial-mesenchymal crosstalk during tissue injury, gremlin-1 modulates inflammatory cell recruitment and anti-fibrotic chemokine production in the lung.
  • Zhou, Wenjing; Jirstrom, Karin; Johansson, Christine; Amini, Rose-Marie; Blomqvist, Carl; Agbaje, Olorunsola; Warnberg, Fredrik (2010)
    Background: Microarray gene-profiling of invasive breast cancer has identified different subtypes including luminal A, luminal B, HER2-overexpressing and basal-like groups. Basal-like invasive breast cancer is associated with a worse prognosis. However, the prognosis of basal-like ductal carcinoma in situ (DCIS) is still unknown. Our aim was to study the prognosis of basal-like DCIS in a large population-based cohort. Methods: All 458 women with a primary DCIS diagnosed between 1986 and 2004, in Uppland and Vastmanland, Sweden were included. TMA blocks were constructed. To classify the DCIS tumors, we used immunohistochemical (IHC) markers (estrogen-, progesterone-, HER2, cytokeratin 5/6 and epidermal growth factor receptor) as a surrogate for the gene expression profiling. The association with prognosis was examined for basal-like DCIS and other subtypes using Kaplan-Meier survival analyses and Cox proportional hazards regression models. Results: IHC data were complete for 392 women. Thirty-two were basal-like (8.2%), 351 were luminal or HER2-positive (89.5%) and 9 unclassified (2.3%). Seventy-six women had a local recurrence of which 34 were invasive. Another 3 women had general metastases as first event. Basal-like DCIS showed a higher risk of local recurrence and invasive recurrence 1.8 (Confidence interval (CI) 95%, 0.8-4.2) and 1.9 (0.7-5.1), respectively. However, the difference was not statistically significant. Also, no statistically significant increased risk was seen for triple-negative or high grade DCIS. Conclusions: Basal-like DCIS showed about a doubled, however not statistically significant risk for local recurrence and developing invasive cancer compared with the other molecular subtypes. Molecular subtyping was a better prognostic parameter than histopathological grade.
  • Huusko, P; Ponciano-Jackson, D; Wolf, Maija; Kiefer, J A; Azorsa, D O; Tuzmen, S; Weaver, D; Robbins, C; Moses, T; Allinen, M; Hautaniemi, S; Chen, Y D; Elkahloun, A; Basik, M; Bova, G S; Bubendorf, L; Lugli, A; Sauter, G; Schleutker, J; Ozcelik, H; Elowe, S; Pawson, T; Trent, J M; Carpten, J D; Kallioniemi, O P; Mousses, S (2004)