Browsing by Subject "PROFILES"

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  • Ottka, Claudia; Vapalahti, Katariina; Puurunen, Jenni; Vahtera, Laura; Lohi, Hannes (2021)
    Background Metabolomics has been proven to be an invaluable research tool by providing comprehensive insight into systemic metabolism. However, the lack of scalable and quantitative methods with known reference intervals (RIs) and documented reproducibility has prevented the use of metabolomics in the clinical setting. Objective The objective of this study was to validate the developed quantitative nuclear magnetic resonance (NMR) spectroscopy-based metabolomics platform for canine serum and plasma samples and determine optimal sample handling conditions for its use. Methods Altogether, 8247 canine samples were analyzed using a Bruker's 500 MHz NMR spectrometer. Using statistical approaches derived from international guidelines, we studied method precision, measurand stability in various long- and short-term storage conditions, as well as the effect of prolonged contact with red blood cells (RBCs), and differences among blood collection tubes. We also screened interferences with lipemia, hemolysis, and bilirubinemia. The results were compared against routine clinical chemistry methods, and RIs were defined for all measurands. Results We determined RIs for 123 measurands, most of which were previously unpublished. The reproducibility of the results of the NMR platform appeared generally outstanding, and the integrity of the results can be ensured by following standard blood drawing and processing guidelines. Conclusions Owing to the advantages of quantitative results, high reproducibility, and scalability, this canine metabolomics platform holds great potential for numerous clinical and research applications to improve canine health and well-being.
  • Levola, Jonna M.; Sailas, Eila S.; Saamanen, Timo S.; Turunen, Leena M.; Thomson, Annika C. (2019)
    Background: The focus of emergency room (ER) treatment is on acute medical crises, but frequent users of ER services often present with various needs. The objectives of this study were to obtain information on persistent frequent ER service users and to determine reasons for their ER service use. We also sought to determine whether psychiatric diagnoses or ongoing use of psychiatric or substance use disorder treatment services were associated with persistent frequent ER visits. Methods: A cohort (n = 138) of persistent frequent ER service users with a total of 2585 ER visits during a two-year-period was identified. A content analysis was performed for 10% of these visits. Register data including International Classification of Primary Care 2 (ICPC-2) -codes and diagnoses were analyzed and multivariable models were created in order to determine whether psychiatric diagnoses and psychosocial reasons for ER service use were associated with the number of ER visits after adjusting for covariates. Results: Patients who were younger, had a psychiatric diagnosis and engaged in ongoing psychiatric and other health services, had more ER visits than those who were not. Having a psychiatric diagnosis was associated with the frequency of ER visits in the multivariable models after adjusting for age, gender and ongoing use of psychiatric or substance use disorder treatment services. Reasons for ER-service use according to ICPC-2 -codes were inadequately documented. Conclusions: Patients with psychiatric diagnoses are overrepresented in this cohort of persistent frequent ER service users. More efficient treatments paths are needed for patients to have their medical needs met through regular appointments.
  • Salmela-Aro, Katariina; Upadyaya, Katja; Vinni-Laakso, Janica; Hietajärvi, Lauri (2021)
    This longitudinal study examined school engagement and burnout profiles among early and middle adolescents before and during COVID-19, and within-class latent change and stability in students' socio-emotional skills the profiles. The longitudinal data were collected in fall 2019 and 2020 from 1381 5th to 6th, and 1374 7th to 8th grade students. Using repeated measures latent profile analyses based on school engagement and burnout we identified five study well-being change profiles in both samples showing structural similarity: normative (53% sample 1; 69% sample 2), moderate-decreasing (4%; 5%), high-decreasing (17%; 10%), low-increasing (6%;7%) and moderate-increasing (20%; 10%) groups. The groups with increasing study well-being showed simultaneous increase in intrapersonal socio-emotional competencies but showed less changes in interpersonal outcomes.
  • Aromaa, H.; Helariutta, K.; Ikonen, J.; Yli-Kaila, M.; Koskinen, L.; Siitari-Kauppi, M. (2018)
    A method for analyzing H-3, Cl-36, Na-22, Ba-133 and Cs-134 from simulated groundwater (SGW) samples was introduced. Gamma emitting radionuclides Na-22, Ba-133 and Cs-134 were measured by using an HPGe-detector. Beta emitting H-3 and Cl-36 were separated from gamma emitting Na-22, Ba-133 and Cs-134. AgCl precipitation was used for the separation of Cl-36 from SGW samples with yields of 98 +/- 2%. H-3 was separated by distillation with recoveries of 97 +/- 3%. This method was used for the determination of activity concentrations of H-3, Cl-36, Na-22, Ba-133 and Cs-134 in SGW samples collected from an in situ through diffusion experiment.
  • Cervantes, Sandra; Vuosku, Jaana; Pyhajarvi, Tanja (2021)
    Despite their ecological and economical importance, conifers genomic resources are limited, mainly due to the large size and complexity of their genomes. Additionally, the available genomic resources lack complete structural and functional annotation. Transcriptomic resources have been commonly used to compensate for these deficiencies, though for most conifer species they are limited to a small number of tissues, or capture only a fraction of the genes present in the genome. Here we provide an atlas of gene expression patterns for conifer Pinus sylvestris across five tissues: embryo, megagametophyte, needle, phloem and vegetative bud. We used a wide range of tissues and focused our analyses on the expression profiles of genes at tissue level. We provide comprehensive information of the per-tissue normalized expression level, indication of tissue preferential upregulation and tissue-specificity of expression. We identified a total of 48,001 tissue preferentially upregulated and tissue specifically expressed genes, of which 28% have annotation in the Swiss-Prot database. Even though most of the putative genes identified do not have functional information in current biological databases, the tissue-specific patterns discovered provide valuable information about their potential functions for further studies, as for example in the areas of plant physiology, population genetics and genomics in general. As we provide information on tissue specificity at both diploid and haploid life stages, our data will also contribute to the understanding of evolutionary rates of different tissue types and ploidy levels.
  • Lee, Yunsung; Haftorn, Kristine L.; Denault, William R. P.; Nustad, Haakon E.; Page, Christian M.; Lyle, Robert; Lee-Odegard, Sindre; Moen, Gunn-Helen; Prasad, Rashmi B.; Groop, Leif C.; Sletner, Line; Sommer, Christine; Magnus, Maria C.; Gjessing, Hakon K.; Harris, Jennifer R.; Magnus, Per; Haberg, Siri E.; Jugessur, Astanand; Bohlin, Jon (2020)
    BackgroundEpigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age.ResultsWe developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n=1592, age-span: 19 to 59years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n=2227, age-span: 18 to 88years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r)>0.94) in independent cohorts, including GSE111165 (n=15), GSE115278 (n=108), GSE132203 (n=795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n=470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set.ConclusionsOur ABECs predicted adults' chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.
  • Garcia-Romero, Noemi; Gonzalez-Tejedo, Carmen; Carrion-Navarro, Josefa; Esteban-Rubio, Susana; Rackov, Gorjana; Rodriguez-Fanjul, Vanessa; Oliver-De La Cruz, Jorge; Prat-Acin, Ricardo; Peris-Celda, Maria; Blesa, David; Ramirez-Jimenez, Laura; Sanchez-Gomez, Pilar; Perona, Rosario; Escobedo-Lucea, Carmen; Belda-Iniesta, Cristobal; Ayuso-Sacido, Angel (2016)
    Human gliomas harbour cancer stem cells (CSCs) that evolve along the course of the disease, forming highly heterogeneous subpopulations within the tumour mass. These cells possess self-renewal properties and appear to contribute to tumour initiation, metastasis and resistance to therapy. CSC cultures isolated from surgical samples are considered the best preclinical in vitro model for primary human gliomas. However, it is not yet well characterized to which extent their biological and functional properties change during in vitro passaging in the serum-free culture conditions. Here, we demonstrate that our CSC-enriched cultures harboured from one to several CSC clones from the human glioma sample. When xenotransplanted into mouse brain, these cells generated tumours that reproduced at least three different dissemination patterns found in original tumours. Along the passages in culture, CSCs displayed increased expression of stem cell markers, different ratios of chromosomal instability events, and a varied response to drug treatment. Our findings highlight the need for better characterization of CSC-enriched cultures in the context of their evolution in vitro, in order to uncover their full potential as preclinical models in the studies aimed at identifying molecular biomarkers and developing new therapeutic approaches of human gliomas.
  • Vihma, Timo; Kilpeläinen, Tiina; Manninen, Miina; Sjöblom, Anna; Jakobson, Erko; Palo, Timo; Jaagus, Jaak; Maturilli, Marion (2011)
  • Welsh, Paul; Rankin, Naomi; Li, Qiang; Mark, Patrick B.; Würtz, Peter; Ala-Korpela, Mika; Marre, Michel; Poulter, Neil; Hamet, Pavel; Chalmers, John; Woodward, Mark; Sattar, Naveed (2018)
    Aims/hypotheses We aimed to quantify the association of individual circulating amino acids with macrovascular disease, microvascular disease and all-cause mortality in individuals with type 2 diabetes. Methods We performed a case-cohort study (N = 3587), including 655 macrovascular events, 342 microvascular events (new or worsening nephropathy or retinopathy) and 632 all-cause mortality events during follow-up, in a secondary analysis of the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) study. For this study, phenylalanine, isoleucine, glutamine, leucine, alanine, tyrosine, histidine and valine were measured in stored plasma samples by proton NMR metabolomics. Hazard ratios were modelled per SD increase in each amino acid. Results In models investigating associations and potential mechanisms, after adjusting for age, sex and randomised treatment, phenylalanine was positively, and histidine inversely, associated with macrovascular disease risk. These associations were attenuated to the null on further adjustment for extended classical risk factors (including eGFR and urinary albumin/creatinine ratio). After adjustment for extended classical risk factors, higher tyrosine and alanine levels were associated with decreased risk of microvascular disease (HR 0.78; 95% CI 0.67, 0.91 and HR 0.86; 95% CI 0.76, 0.98, respectively). Higher leucine (HR 0.79; 95% CI 0.69, 0.90), histidine (HR 0.89; 95% CI 0.81, 0.99) and valine (HR 0.79; 95% CI 0.70, 0.88) levels were associated with lower risk of mortality. Investigating the predictive ability of amino acids, addition of all amino acids to a risk score modestly improved classification of participants for macrovascular (continuous net reclassification index [NRI] +35.5%, p <0.001) and microvascular events (continuous NRI +14.4%, p = 0.012). Conclusions/interpretation We report distinct associations between circulating amino acids and risk of different major complications of diabetes. Low tyrosine appears to be a marker of microvascular risk in individuals with type 2 diabetes independently of fundamental markers of kidney function.
  • Huvila, Jutta; Laajala, Teemu D.; Edqvist, Per-Henrik; Mardinoglu, Adil; Talve, Lauri; Ponten, Fredrik; Grenman, Seija; Carpen, Olli; Aittokallio, Tero; Auranen, Annika (2018)
    Objective. In clinical practise, prognostication of endometrial cancer is based on clinicopathological risk factors. The use of immunohistochemistry-based markers as prognostic tools is generally not recommended and a systematic analysis of their utility as a panel is lacking. We evaluated whether an immunohistochemical marker panel could reliably assess endometrioid endometrial cancer (EEC) outcome independent of clinicopathological information. Methods. A cohort of 306 EEC specimens was profiled using tissue microarray (TMA). Cost- and time-efficient immunohistochemical analysis of well-established tissue biomarkers (ER, PR, HER2, Ki-67, MLH1 and p53) and two new biomarkers (L1CAM and ASRGL1) was carried out. Statistical modelling with embedded variable selection was applied on the staining results to identify minimal prognostic panels with maximal prognostic accuracy without compromising generalizability. Results. A panel including p53 and ASRGL1 immunohistochemistry was identified as the most accurate predictor of relapse-free and disease-specific survival. Within this panel, patients were allocated into high- (5.9%), intermediate- (295%) and low- (64.6%) risk groups where high-risk patients had a 30-fold risk (P <0.001) of dying of EEC compared to the low-risk group. Conclusions. P53 and ASRGL1 immunoprofiling stratifies EEC patients into three risk groups with significantly different outcomes. This simple and easily applicable panel could provide a useful tool in EEC risk stratification and guiding the allocation of treatment modalities. (C) 2018 Elsevier Inc. All rights reserved.
  • Congdon, Eliza; Service, Susan; Wessman, Jaana; Seppanen, Jouni K.; Schönauer, Stefan; Miettunen, Jouko; Turunen, Hannu; Koiranen, Markku; Joukamaa, Matti; Jarvelin, Marjo-Riitta; Palotie, Leena; Veijola, Juha; Mannila, Heikki; Paunio, Tiina; Freimer, Nelson B. (2012)
  • Tuononen, Minttu; O'Connor, Ewan J.; Sinclair, Victoria A. (2019)
    The presence of clouds and their characteristics have a strong impact on the radiative balance of the Earth and on the amount of solar radiation reaching the Earth's surface. Many applications require accurate forecasts of surface radiation on weather timescales, for example solar energy and UV radiation forecasts. Here we investigate how operational forecasts of low and mid-level clouds affect the accuracy of solar radiation forecasts. A total of 4 years of cloud and solar radiation observations from one site in Helsinki, Finland, are analysed. Cloud observations are obtained from a ceilometer and therefore we first develop algorithms to reliably detect cloud base, precipitation, and fog. These new algorithms are widely applicable for both operational use and research, such as in-cloud icing detection for the wind energy industry and for aviation. The cloud and radiation observations are compared to forecasts from the Integrated Forecast System (IFS) run operationally and developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We develop methods to evaluate the skill of the cloud and radiation forecasts. These methods can potentially be extended to hundreds of sites globally. Over Helsinki, the measured global horizontal irradiance (GHI) is strongly influenced by its northerly location and the annual variation in cloudiness. Solar radiation forecast error is therefore larger in summer than in winter, but the relative error in the solar radiation forecast is more or less constant throughout the year. The mean overall bias in the GHI forecast is positive (8 W m(-2)). The observed and forecast distributions in cloud cover, at the spatial scales we are considering, are strongly skewed towards clear-sky and overcast situations. Cloud cover forecasts show more skill in winter when the cloud cover is predominantly overcast; in summer there are more clear-sky and broken cloud situations. A negative bias was found in forecast GHI for correctly forecast clear-sky cases and a positive bias in correctly forecast overcast cases. Temporal averaging improved the cloud cover forecast and hence decreased the solar radiation forecast error. The positive bias seen in overcast situations occurs when the model cloud has low values of liquid water path (LWP). We attribute this bias to the model having LWP values that are too low or the model optical properties for clouds with low LWP being incorrect.
  • Uotila, Riikka; Röntynen, Petteri; Pelkonen, Anna S.; Voutilainen, Helena; Kaarina Kukkonen, Anna; Mäkelä, Mika J. (2020)
  • Salvador-Martinez, Irepan; Salazar-Ciudad, Isaac (2017)
    The increase in complexity in an embryo over developmental time is perhaps one of the most intuitive processes of animal development. It is also intuitive that the embryo becomes progressively compartmentalized over time and space. In spite of this intuitiveness, there are no systematic attempts to quantify how this occurs. Here, we present a quantitative analysis of the compartmentalization and spatial complexity of Ciona intestinalis over developmental time by analyzing thousands of gene expression spatial patterns from the ANISEED database. We measure compartmentalization in two ways: as the relative volume of expression of genes and as the disparity in gene expression between body parts. We also use a measure of the curvature of each gene expression pattern in 3D space. These measures show a similar increase over time, with the most dramatic change occurring from the 112-cell stage to the early tailbud stage. Combined, these measures point to a global pattern of increase in complexity in the Ciona embryo. Finally, we cluster the different regions of the embryo depending on their gene expression similarity, within and between stages. Results from this clustering analysis, which partially correspond to known fate maps, provide a global quantitative overview about differentiation and compartmentalization between body parts at each developmental stage. (C) 2017 Elsevier B.V. All rights reserved.
  • Liu, Chengyu; Louhimo, Riku; Laakso, Marko; Lehtonen, Rainer; Hautaniemi, Sampsa (2015)
    Background: Histologically similar tumors even from the same anatomical position may still show high variability at molecular level hindering analysis of genome-wide data. Leveling the analysis to a gene regulatory network instead of focusing on single genes has been suggested to overcome the heterogeneity issue although the majority of the network methods require large datasets. Network methods that are able to function at a single sample level are needed to overcome the heterogeneity and sample size issues. Methods: We present a novel network method, Differentially Expressed Regulation Analysis (DERA) that integrates expression data to biological network information at a single sample level. The sample-specific networks are subsequently used to discover samples with similar molecular functions by identification of regulations that are shared between samples or are specific for a subgroup. Results: We applied DERA to identify key regulations in triple negative breast cancer (TNBC), which is characterized by lack of estrogen receptor, progesterone receptor and HER2 expression and has poorer prognosis than the other breast cancer subtypes. DERA identified 110 core regulations consisting of 28 disconnected subnetworks for TNBC. These subnetworks are related to oncogenic activity, proliferation, cancer survival, invasiveness and metastasis. Our analysis further revealed 31 regulations specific for TNBC as compared to the other breast cancer subtypes and thus form a basis for understanding TNBC. We also applied DERA to high-grade serous ovarian cancer (HGS-OvCa) data and identified several common regulations between HGS-OvCa and TNBC. The performance of DERA was compared to two pathway analysis methods GSEA and SPIA and our results shows better reproducibility and higher sensitivity in a small sample set. Conclusions: We present a novel method called DERA to identify subnetworks that are similarly active for a group of samples. DERA was applied to breast cancer and ovarian cancer data showing our method is able to identify reliable and potentially important regulations with high reproducibility. R package is available at http://csbi.ltdk.helsinki.fi/pub/czliu/DERA/.
  • Khan, Suleiman A.; Virtanen, Seppo; Kallioniemi, Olli P.; Wennerberg, Krister; Poso, Antti; Kaski, Samuel (2014)
  • Salmiheimo, Aino N. E.; Mustonen, Harri K.; Vainionpaa, Sanna A. A.; Shen, Zhanlong; Kemppainen, Esko A. J.; Seppanen, Hanna E.; Puolakkainen, Pauli A. (2016)
    Recent studies suggest that pro-inflammatory type M1 macrophages inhibit tumor progression and that anti-inflammatory M2 macrophages enhance it. The aim of this study was to examine the interaction of type M1 and M2 macrophages with pancreatic cancer cells. We studied the migration rate of fluorescein stained pancreatic cancer cells on Matrigel cultured alone or with Granulocyte- Macrophage Colony Stimulating Factor (GM-CSF) differentiated macrophages or with Macrophage Colony Stimulating Factor (M-CSF) differentiated macrophages, skewing the phenotype towards pro- and anti-inflammatory direction, respectively. Macrophage differentiation was assessed with flow cytometry and the cytokine secretion in cell cultures with cytokine array. Both GM-CSF and M-CSF differentiated macrophages increased the migration rate of primary pancreatic adenocarcinoma cell line (MiaPaCa-2) and metastatic cell line (HPAF-II). Stimulation with IL6 or IL4+ LPS reversed the macrophages' increasing effect on the migration rate of Mi-aPaCa-2 completely and partly of HPAF-II. Co-culture with MiaPaCa-2 reduced the inflammatory cytokine secretion of GM-CSF differentiated macrophages. Co-culture of macrophages with pancreatic cancer cells seem to change the inflammatory cytokine profile of GM-CSF differentiated macrophages and this might explain why also GM-CSF differentiated macrophages promoted the invasion. Adding IL6 or IL4+ LPS to the cell culture with MiaPaCa-2 and GM-CSF or M-CSF differentiated macrophages increased the secretion of inflammatory cytokines and this could contribute to the reversion of the macrophage induced increase of cancer cell migration rate.
  • Neiman, Maja; Hellstrom, Cecilia; Just, David; Mattsson, Cecilia; Fagerberg, Linn; Schuppe-Koistinen, Ina; Gummesson, Anders; Bergström, Göran; Kallioniemi, Olli; Achour, Adnane; Sallinen, Riitta; Uhlen, Mathias; Nilsson, Peter (2019)
    In the era towards precision medicine, we here present the individual specific autoantibody signatures of 193 healthy individuals. The self-reactive IgG signatures are stable over time in a way that each individual profile is recognized in longitudinal sampling. The IgG autoantibody reactivity towards an antigen array comprising 335 protein fragments, representing 204 human proteins with potential relevance to autoimmune disorders, was measured in longitudinal plasma samples from 193 healthy individuals. This analysis resulted in unique autoantibody barcodes for each individual that were maintained over one year's time. The reactivity profiles, or signatures, are person specific in regards to the number of reactivities and antigen specificity. Two independent data sets were consistent in that each healthy individual displayed reactivity towards 0-16 antigens, with a median of six. Subsequently, four selected individuals were profiled on in-house produced high-density protein arrays containing 23,000 protein fragments representing 14,000 unique protein coding genes. Based on a unique, broad and deep longitudinal profiling of autoantibody reactivities, our results demonstrate a unique autoreactive profile in each analyzed healthy individual. The need and interest for broad-ranged and high-resolution molecular profiling of healthy individuals is rising. We have here generated and assessed an initial perspective on the global distribution of the self-reactive IgG repertoire in healthy individuals, by investigating 193 well-characterized healthy individuals.
  • Aure, Miriam Ragle; Vitelli, Valeria; Jernstrom, Sandra; Kumar, Surendra; Krohn, Marit; Due, Eldri U.; Haukaas, Tonje Husby; Leivonen, Suvi-Katri; Vollan, Hans Kristian Moen; Luders, Torben; Rodland, Einar; Vaske, Charles J.; Zhao, Wei; Moller, Elen K.; Nord, Silje; Giskeodegard, Guro F.; Bathen, Tone Frost; Caldas, Carlos; Tramm, Trine; Alsner, Jan; Overgaard, Jens; Geisler, Jurgen; Bukholm, Ida R. K.; Naume, Bjorn; Schlichting, Ellen; Sauer, Torill; Mills, Gordon B.; Karesen, Rolf; Maelandsmo, Gunhild M.; Lingjaerde, Ole Christian; Frigessi, Arnoldo; Kristensen, Vessela N.; Borresen-Dale, Anne-Lise; Sahlberg, Kristine K.; OSBREAC (2017)
    Background: Breast cancer is a heterogeneous disease at the clinical and molecular level. In this study we integrate classifications extracted from five different molecular levels in order to identify integrated subtypes. Methods: Tumor tissue from 425 patients with primary breast cancer from the Oslo2 study was cut and blended, and divided into fractions for DNA, RNA and protein isolation and metabolomics, allowing the acquisition of representative and comparable molecular data. Patients were stratified into groups based on their tumor characteristics from five different molecular levels, using various clustering methods. Finally, all previously identified and newly determined subgroups were combined in a multilevel classification using a "cluster-of-clusters" approach with consensus clustering. Results: Based on DNA copy number data, tumors were categorized into three groups according to the complex arm aberration index. mRNA expression profiles divided tumors into five molecular subgroups according to PAM50 subtyping, and clustering based on microRNA expression revealed four subgroups. Reverse-phase protein array data divided tumors into five subgroups. Hierarchical clustering of tumor metabolic profiles revealed three clusters. Combining DNA copy number and mRNA expression classified tumors into seven clusters based on pathway activity levels, and tumors were classified into ten subtypes using integrative clustering. The final consensus clustering that incorporated all aforementioned subtypes revealed six major groups. Five corresponded well with the mRNA subtypes, while a sixth group resulted from a split of the luminal A subtype; these tumors belonged to distinct microRNA clusters. Gain-of-function studies using MCF-7 cells showed that microRNAs differentially expressed between the luminal A clusters were important for cancer cell survival. These microRNAs were used to validate the split in luminal A tumors in four independent breast cancer cohorts. In two cohorts the microRNAs divided tumors into subgroups with significantly different outcomes, and in another a trend was observed. Conclusions: The six integrated subtypes identified confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing knowledge of the heterogeneity of the luminal A subtype may add pivotal information to guide therapeutic choices, evidently bringing us closer to improved treatment for this largest subgroup of breast cancer.