Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome
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PROVIDER: PRJNA320289 | ENA |
REPOSITORIES: ENA
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Project description: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 primary breast cancer patients of the Oslo2 study was cut and blended before being divided into fractions for DNA-, RNA- and protein isolation, and metabolomics, allowing for 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 scored 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 using integrative clustering, tumors were classified into ten subtypes. The final consensus clustering incorporating all the 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 where 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 significant different outcome, and in another a trend was observed. Conclusions: The herein identified six integrated subtypes confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing the knowledge of the luminal A subtype heterogeneity may add pivotal information guiding therapeutic choices, evidently bringing us closer to more personalized treatment for this largest subgroup of breast cancer.
2017-03-01 | GSE81000 | GEO
Project description: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 primary breast cancer patients of the Oslo2 study was cut and blended before being divided into fractions for DNA-, RNA- and protein isolation, and metabolomics, allowing for 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 scored 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 using integrative clustering, tumors were classified into ten subtypes. The final consensus clustering incorporating all the 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 where 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 significant different outcome, and in another a trend was observed. Conclusions: The herein identified six integrated subtypes confirm the heterogeneity of breast cancer and show that finer subdivisions of subtypes are evident. Increasing the knowledge of the luminal A subtype heterogeneity may add pivotal information guiding therapeutic choices, evidently bringing us closer to more personalized treatment for this largest subgroup of breast cancer.
2017-03-01 | GSE80999 | GEO
Project description:BackgroundBreast 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.MethodsTumor 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.ResultsBased 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.ConclusionsThe 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.
| S-EPMC5372339 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2017-03-01 | GSE81002 | GEO
Project description:Purpose In breast cancer, specific aberrant methylation patterns have been associated with different BC histologic and molecular subtypes and data suggest that DNA methylation profiles may play an important role in the development and progression of distinct breast subtypes. However, the epigenome of the newly defined luminal B and luminal B-HER2 positive breast cancers has not yet been characterized. Therefore the main goal of the current study is to deciphered the aberrant DNA methylation profiles associated with these breast cancer subtypes. Experimental Design 29 luminal subtype breast cancer samples along with 8 control tissue were epigenetically interrogated using the HumanMethylation27 DNA Analysis BeadChip. Results Luminal B-HER2 + subtype displays the most aggressive phenotype and shows the highest number of aberrantly methylated CpG markers. On the other hand, the luminal B subtype harbours an heterogeneous DNA methylation profile that seems to be half way between the luminal A and luminalB-HER2+ subtypes. Conclusions The heterogeneous epigenetic and genetic profile of the luminal B subtype, might indicate that a further stratification has to be done for this specific breast cancer subtype.
2016-12-18 | GSE73808 | GEO
Project description:Prior to implantation, embryonic development occurs in the confinement of the reproductive tract lumen. The endometrial epithelia determines the uterine luminal composition and, consequently, the molecular milieu available to the pre-implantation embryo. This cow RNA-seq study was especially designed to (i) evaluate the impact that progesterone concentration has on the transcriptome of luminal epithelial cells, and (ii) evaluate the impact that endometrial gene expression has on pregnancy outcome. Luminal epithelial cells were collected using a cytology brush three days prior to embryo transfer, so that the molecular evaluation and the pregnancy outcome, measured 30 days after estrus, pertained to the same reproductive cycle.
2021-04-07 | GSE171577 | GEO
Project description:In-depth clinical proteomic analysis of laser-microdissected HOT lesions of five luminal B breast cancer Ki-67 high subtype.
2020-10-12 | PXD021912 | JPOST Repository
Project description:The transcription factor GATA3 is essential for luminal cell differentiation during mammary gland development and critical for formation of the luminal subtypes of breast cancer. Ectopic expression of GATA3 promoted global alterations of the transcriptome of basal triple-negative breast cancer cells resulting in molecular and cellular changes associated with a more differentiated, luminal tumor subtype and a concomitant reduction in primary tumor growth, lung metastasis, and macrophage recruitment at the metastatic site. Importantly, we demonstrate that the inhibition of metastases by GATA3 results from the suppression of lysyl oxidase (LOX) expression, a metastasis promoting matrix protein that affects cell proliferation, cross-linking of extracellular collagen types, and establishment of the metastatic niche. There are 2 samples sent in triplicates.
2011-08-31 | E-GEOD-24249 | biostudies-arrayexpress
Project description:Genome-wide methylation analysis of human breast cancer subtype group (Luminal A, Luminal B, HER2+ and TNBC)
| PRJNA480639 | ENA
Project description:Muscle invasive bladder cancer (MIBC) is a heterogeneous disease with a high recurrence rate and poor clinical outcomes. Molecular subtype provides a new framework for the study of MIBC heterogeneity. Clinically, MIBC can be classified as basal and luminal subtypes, they display different clinical and pathological characteristics, but the molecular mechanism is still unclear. Lipidomic and metabolomic molecules have recently been considered to play an important role in the genesis and development of tumors, especially as potential biomarkers. Their different expression profiles in basal and luminal subtypes provide clues for the molecular mechanism of basal and luminal subtypes and the discovery of new biomarkers. Herein, we stratified MIBC patients into basal and luminal subtype using a MIBC classifier based on transcriptome expression profiles. We qualitatively and quantitatively analyzed the lipids and metabolites of basal and luminal MIBC subtypes, and identified differential lipid and metabolite profiles of them. Our results suggest that free fatty acids (FFA) and sulfatides (SL), which are closely associated with immune and stromal cell types, can contribute to the diagnosis of basal and luminal subtypes of MIBC. Moreover, we showe that glycerophosphocholine (GCP)/imidazoles and nucleosides/imidazoles ratios can accurately distinguish the basal and luminal tumors. Overall, by integrating transcriptomic, lipidomic, and metabolomic data, our study reveals specific biomarkers to differentially diagnose basal and luminal MIBC subtypes and may provide a basis for precision therapy of MIBC.
2021-07-08 | GSE179440 | GEO