Long noncoding RNA landscape in breast cancer [Mexico]
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE134359 | GEO | 2020/08/12
REPOSITORIES: GEO
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Project description:Triple negative breast cancer (TNBC) represents a challenging tumor type due to their poor prognosis and limited treatment options. It is well recognize that clinical and molecular heterogeneity of TNBC is driven in part by mRNA and lncRNAs. To stratify TNBCs, we profiled mRNAs and lncRNA in 158 adjuvant TNBC tumors using an Affymetrix microarray platform. Lehmann clustering analysis allowed us to identify TNBC subtypes featuring unique lncRNA expression patterns, disease free and overall survival rates and particular gene ontology enrichments (performed with GSEA algorithm).
2018-08-31 | GSE86946 | GEO
Project description:Microarrays have revolutionized breast cancer (BC) research by enabling studies of gene expression on a transcriptome-wide scale. Recently, RNA-Sequencing (RNA-Seq) has emerged as an alternative for precise readouts of the transcriptome. To date, no study has compared the ability of the two technologies to quantify clinically relevant individual genes and microarray-derived gene expression signatures (GES) in a set of BC samples encompassing the known molecular BC's subtypes. To accomplish this, the RNA from 57 BCs representing the four main molecular subtypes (triple negative, HER2 positive, luminal A, luminal B), was profiled with Affymetrix HG-U133 Plus 2.0 chips and sequenced using the Illumina HiSeq 2000 platform. The correlations of three clinically relevant BC genes, six molecular subtype classifiers, and a selection of 21 GES were evaluated. 58 tumors representing the different molecular subtypes [triple negative (ER-/PgR-/HER2-); HER2 positive (HER2+); luminal A (ER+/HER2-/histological grade 1), luminal B (ER+/HER2-/histological grade 3)] were obtained from patients recruited between 2007 and 2011 at the Institut Jules Bordet. RNA was profiled using the Affymetrix HG-U133 Plus 2.0 chips and sequenced on the Illumina platform, producing ~30 million 50 bp paired-end reads per sample. The reads alignment and expression quantification were performed using the Tophat/Cufflinks pipeline and the Ensembl genome version hg19. The Affymetrix microarray data were normalized using fRMA and probesets were selected based on the JetSet reannotation package. This submission represents the gene expression component of the study only.
2014-11-21 | E-GEOD-43358 | biostudies-arrayexpress
Project description:Genome wide DNA methylation profiling of non-tumoral and infiltrating ductal breast cancer (tumoral) samples. The HumanMethylation450 BeadChip was used to obtain DNA methylation profiles across approximately 450,000 CpG in non-tumoral and tumoral samples. Non-tumoral samples included six frozen non-neoplastic breast tissues from reduction mammoplasties and tumoral samples included eight frozen tumors from each BC subtype, i.e. luminal A (LA), luminal B (LB), luminal-HER2 (LH), HER2 (H) and triple-negative (TN) (Total: 40 tumors).
2020-02-17 | GSE141338 | GEO
Project description:Clinical management of breast cancer (BC) metastasis remains an unmet need as it accounts for 90% of BC-associated mortality. Although the luminal subtype, which represents >70% of BC cases, is generally associated with a favorable outcome, it is susceptible to metastatic relapse as late as 15 years after treatment discontinuation. Seeking therapeutic approaches as well as screening tools to properly identify those patients with a higher risk of recurrence is therefore essential. Here, we report that the lipid-degrading enzyme fatty acid amide hydrolase (FAAH) is a predictor of long-term survival in patients with luminal BC, and that it blocks tumor progression and lung metastasis in cell and mouse models of BC. Together, our findings highlight the potential of FAAH as a biomarker with prognostic value in luminal BC and as a therapeutic target in metastatic disease.
2022-03-09 | GSE197984 | GEO
Project description:Background: DSCAM-AS1 is a cancer-related long noncoding RNA with higher expression levels in Luminal A, B and HER2-positive Breast Cancer (BC), where its expression is strongly dependent on Estrogen Receptor Alpha (ERα). Method: To decipher its function, DSCAM-AS1 expression was measured by qRT-PCR in tissue samples from 93 BC patients in addition to a meta-analysis of 30 gene expression datasets, together with the evaluation of its association with clinical data. By computational analyses of our RNA-Seq in MCF-7 cells, we investigated the DSCAM-AS1 knock-down effects at both gene and isoform levels Results: We confirmed DSCAM-AS1 overexpression in high grade Luminal A, B and HER2+ BCs and found a significant correlation with disease relapse. 908 genes were regulated by DSCAM-AS1-silencing, primarily involved in cell cycle and inflammatory response. Noteworthy, the analysis of alternative splicing and isoform regulation revealed 2,085 splicing events regulated by DSCAM-AS1, enriched in differential polyadenylation sites and 3’UTR shortening events. Finally, the DSCAM-AS1-interacting splicing factor hnRNPL was predicted as the most enriched RBP for exon skipping and 3’UTR events. Conclusion: The relevance of DSCAM-AS1 overexpression in BC is confirmed by clinical data and further enhanced by its possible involvement in the regulation of RNA processing, which is emerging as one of the most important dysfunctions in cancer.
2020-05-15 | GSE150591 | GEO
Project description:Continuous cell lines are important and commonly used in vitro models in breast cancer (BC) research. Selection of the appropriate model cell line is crucial and requires consideration of their molecular characteristics. To characterize BC cell line models in depth, we profiled a panel of 29 authenticated and publicly available BC cell lines by mRNA-sequencing, mutation analysis, and immunoblotting. Gene expression profiles separated BC cell lines in two major clusters that represent basal-like (mainly triple-negative BC) and luminal BC subtypes, respectively. HER2-positive cell lines were located within the luminal cluster. Mutation calling highlighted the frequent aberration of TP53 and BRCA2 in BC cell lines, which, therefore, share relevant characteristics with primary BC. Furthermore, we showed that the data can be used to find novel, potential oncogenic fusion transcripts, e.g., FGFR2::CRYBG1 and RTN4IP1::CRYBG1 in cell line MFM-223, and to elucidate the regulatory circuit of IRX genes and KLF15 as novel candidate tumor suppressor genes in BC. Our data indicated that KLF15 was activated by IRX1 and inhibited by IRX3. Moreover, KLF15 inhibited IRX1 in cell line HCC-1599. Each BC cell line carries unique molecular features. Therefore, the molecular characteristics of BC cell lines described here might serve as a valuable resource to improve the selection of appropriate models for BC research. Raw fastq files are also published at BioStudies: S-BSST1200.
2024-12-03 | E-MTAB-14655 | biostudies-arrayexpress
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:The clinical relevance of tumor infiltrating lymphocytes (TILs) in breast cancer (BC) is not firmly established. We aimed to validate previous prognostic findings in triple negative breast cancer (TNBC) and investigate predictive associations with trastuzumab benefit in HER2 overexpressing disease (HER2+).
2022-07-16 | GSE47994 | GEO
Project description:Microarrays have revolutionized breast cancer (BC) research by enabling studies of gene expression on a transcriptome-wide scale. Recently, RNA-Sequencing (RNA-Seq) has emerged as an alternative for precise readouts of the transcriptome. To date, no study has compared the ability of the two technologies to quantify clinically relevant individual genes and microarray-derived gene expression signatures (GES) in a set of BC samples encompassing the known molecular BC's subtypes. To accomplish this, the RNA from 57 BCs representing the four main molecular subtypes (triple negative, HER2 positive, luminal A, luminal B), was profiled with Affymetrix HG-U133 Plus 2.0 chips and sequenced using the Illumina HiSeq 2000 platform. The correlations of three clinically relevant BC genes, six molecular subtype classifiers, and a selection of 21 GES were evaluated.
2014-11-21 | GSE43358 | GEO
Project description:Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings. Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29-3.13; p=0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response. Conclusions: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen. Experiment Overall Design: dataset of microarray experiments from primary breast tumors of patients treated by Tamoxifen in adjuvant setting. No replicate, no reference sample.
2008-06-20 | E-GEOD-9195 | biostudies-arrayexpress