Definition of clinically distinct molecular subtypes in estrogen receptor positive breast carcinomas using genomic grade
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE6532 | GEO | 2007/03/01
SECONDARY ACCESSION(S): PRJNA98807
REPOSITORIES: GEO
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Project description:Purpose: A number of microarray studies have reported distinct molecular profiles of breast cancers (BC): basal-like, ErbB2-like and two to three luminal-like subtypes. These were associated with different clinical outcomes. However, although the basal and the ErbB2 subtypes are repeatedly recognized, identification of estrogen receptor (ER)-positive subtypes has been inconsistent. Refinement of their molecular definition is therefore needed. Materials and methods: We have previously reported a gene-expression grade index (GGI) which defines histological grade based on gene expression profiles. Using this algorithm, we assigned ER-positive BC to either high or low genomic grade subgroups and compared these to previously reported ER-positive molecular classifications. As further validation, we classified 666 ER-positive samples into subtypes and assessed their clinical outcome. Results: Two ER-positive molecular subgroups (high and low genomic grade) could be defined using the GGI. Despite tracking a single biological pathway, these were highly comparable to the previously described luminal A and B classification and significantly correlated to the risk groups produced using the 21-gene recurrence score. The two subtypes were associated with statistically distinct clinical outcome in both systemically untreated and tamoxifen-treated populations. Conclusions: The use of genomic grade can identify two clinically distinct ER-positive molecular subtypes in a simple and highly reproducible manner across multiple datasets. This study emphasizes the important role of proliferation-related genes in predicting prognosis in ER-positive BC. Experiment Overall Design: dataset of microarray experiments from primary breast tumors used to assess the reationship between GGI, molecular subtypes, and tamoxifen resistance. Experiment Overall Design: No replicate, no reference sample.
2008-06-20 | E-GEOD-6532 | biostudies-arrayexpress
Project description:Background: We have previously shown that the Gene expression Grade Index (GGI) was able to identify two subtypes of estrogen receptor (ER)-positive tumors that were associated with statistically distinct clinical outcomes in both untreated and tamoxifen-treated patients. Here, we aim to investigate the ability of the GGI to predict relapses in postmenopausal women who were treated with tamoxifen (T) or letrozole (L) within the BIG 1-98 trial. Methods: We generated gene expression profiles (Affymetrix) and computed the GGI for a matched, case-control sample of patients enrolled in the BIG 1-98 trial from the two hospitals where frozen samples were available. All relapses (cases) were identified from patients randomized to receive monotherapy or from the switching treatment arms for whom relapse occurred before the switch. Each case was randomly matched with four controls based upon nodal status and treatment (T or L). The prognostic value of GGI was assessed as a continuous predictor and divided at the median. Predictive accuracy of GGI was estimated using time-dependent area under the curve (AUC) of the ROC curves. Results: Frozen samples were analyzable for 48 patients (10 cases and 38 controls). Seven of the 10 cases had been assigned to receive L. Cases and controls were comparable with respect to menopausal and nodal status, local and chemotherapy, and HER2 positivity. Cases were slightly older than controls and had a larger proportion of large, poorly differentiated ER+/PgR- tumors. The GGI was significantly and linearly related to risk of relapse: each 10-unit increase in GGI resulted in an increase of approximately 11% in the hazard rate (p=0.02). Within the subgroups of patients with node-positive disease or who were treated with L, the hazard of relapse was significantly greater for patients with GGI at or above the median. AUC reached a maximum of 78% at 27 months. Conclusions: This analysis supports the GGI as a good predictor of relapse for ER-positive patients, even among patients who receive L. Validation of these results, in a larger series from BIG 1-98, is planned using the simplified GGI represented by a smaller set of genes and tested by qRT-PCR on paraffin-embedded tissues. Test whether the Gene expression Grade Index (GGI) is a potential predictor of relapse for endocrine-treated breast cancer patients in the BIG 1-98 trial. 55 microarray experiments from primary breast tumors of endocrine-treated patients. No replicate, no reference sample.
2009-07-09 | E-GEOD-16391 | biostudies-arrayexpress
Project description:Background: We have previously shown that the Gene expression Grade Index (GGI) was able to identify two subtypes of estrogen receptor (ER)-positive tumors that were associated with statistically distinct clinical outcomes in both untreated and tamoxifen-treated patients. Here, we aim to investigate the ability of the GGI to predict relapses in postmenopausal women who were treated with tamoxifen (T) or letrozole (L) within the BIG 1-98 trial. Methods: We generated gene expression profiles (Affymetrix) and computed the GGI for a matched, case-control sample of patients enrolled in the BIG 1-98 trial from the two hospitals where frozen samples were available. All relapses (cases) were identified from patients randomized to receive monotherapy or from the switching treatment arms for whom relapse occurred before the switch. Each case was randomly matched with four controls based upon nodal status and treatment (T or L). The prognostic value of GGI was assessed as a continuous predictor and divided at the median. Predictive accuracy of GGI was estimated using time-dependent area under the curve (AUC) of the ROC curves. Results: Frozen samples were analyzable for 48 patients (10 cases and 38 controls). Seven of the 10 cases had been assigned to receive L. Cases and controls were comparable with respect to menopausal and nodal status, local and chemotherapy, and HER2 positivity. Cases were slightly older than controls and had a larger proportion of large, poorly differentiated ER+/PgR- tumors. The GGI was significantly and linearly related to risk of relapse: each 10-unit increase in GGI resulted in an increase of approximately 11% in the hazard rate (p=0.02). Within the subgroups of patients with node-positive disease or who were treated with L, the hazard of relapse was significantly greater for patients with GGI at or above the median. AUC reached a maximum of 78% at 27 months. Conclusions: This analysis supports the GGI as a good predictor of relapse for ER-positive patients, even among patients who receive L. Validation of these results, in a larger series from BIG 1-98, is planned using the simplified GGI represented by a smaller set of genes and tested by qRT-PCR on paraffin-embedded tissues.
2009-07-09 | GSE16391 | 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:Cross talk between the Estrogen Receptor (ER) and ErbB2/HER-2 pathways have long been implicated in breast cancer aetiology and drug response1, yet no direct connection at a transcriptional level has been shown. We now show that estrogen-ER and tamoxifen-ER complexes directly repress ErbB2 transcription via a cis-regulatory element within the ERBB2 gene. We implicate the Paired Box 2 gene product (Pax2), in a novel role, as a crucial mediator of ER repression of ErbB2 by the anti-cancer drug tamoxifen. We show that Pax2 and the ER co-activator AIB-1/SRC-3 compete for binding and regulation of ErbB2 transcription, the outcome of which determines tamoxifen response in breast cancer cells. The repression of ErbB2 by ER-Pax2 links these two important breast cancer subtypes and suggests that aggressive ErbB2 positive tumours can originate from ER positive luminal tumours by circumventing this repressive mechanism. These data provide mechanistic insight into the molecular basis of endocrine resistance in breast cancer.
2008-09-27 | E-TABM-563 | biostudies-arrayexpress
Project description:Previous studies successfully revealed molecular characteristics of bladder cancers, dealing with non-muscle invasive bladder cancer and muscle invasive bladder cancer, separately. At the molecular level, however, there is a great need to aggregate these subtypes, which may share biological characteristics. This study aimed to identify distinct molecular subtypes of BC and the clinical and/or biological characteristics of each subtype. We used seven gene expression data sets for bladder cancer, which included data from 118 primary bladder cancer samples and 27 recurrent bladder tumor tissues from the Yonsei University Severance Hospital. Hierarchical clustering revealed four molecular subtypes of BC with different clinical outcomes: class 1 with low-grade NMIBC and the best prognosis; class 2 characterized by active FGFR3 and inhibited immune response pathways; class 3 with high-grade NMIBC and the worst progression-free survival; and class 4 mainly comprised of MIBC along with EMT activation. By applying the classifier based on these characteristics, we stratified all BC samples into newly identified molecular subtypes. When comparing previously reported subtypes, our subtypes well agreed with their molecular characteristics regardless of breast cancer-based biology, and showed a strong prognostic relevance in class 3. Integrative analysis of mutation and gene expression suggested that class 3 may have the potential benefit from anti-PD-L1 immunotherapy. Our classifier, constructed by NMIBC and MIBC integration, successfully stratified BC patients into distinct subtypes with different clinical outcomes and a possible treatment option.
2018-10-03 | GSE120736 | GEO
Project description:Breast cancer is a heterogeneous disease classified into 3 major subtypes based on the presence or absence of molecular markers for oestrogen receptors (ER), progesterone receptors (PR) and human epidermal growth factor-2 (Her2) . Hormone receptor-positive BC (ER+, PR+ and Her-2-), accounts for approximately 70% of patients. Patients with ER- BC account for approximately 30 % of all cases and commonly have a worse prognosis than ER+ patients (9). However, a significant proportion of ER- cases have good outcomes and could potentially benefit from a less aggressive therapy. Triple negative breast cancer (TNBC, ER-, PR- and Her-2-) accounts for approximately 15% of breast cancers and has the poorest outcomes. An hypoxic microenvironment is an important intrinsic component of solid tumours that can result in rapid proliferation of cancer cells and is associated with the lack of oxgyen and abnormal tumour blood vessels. Hypoxia stimulates the hypoxia inducible factor-1α (HIF-1α) that transactivates genes associated with angiogenesis, tumour growth, metastasis, metabolic reprogramming, and treatment resistance. HIF-1α is recognised to induce the expression of carbonic anhydrase IX (CAIX), an enzyme that has been attributed a central role in pH regulation and cancer progression and is particularly pronounced in peri necrotic tumour areas, high-grade BCs. The adaption to hypoxia is governed by multiple transcriptional and post-transcriptional changes in gene expression. Up to 1.5 % of the human genome is estimated to be transcriptionally responsive to hypoxia. Genes and pathways which have been identified as being responsive to hypoxia may have the potential to be used as prognostic or predictive markers, and furthermore, can help identify novel therapeutic targets. The aim of the present study was to gain a better understanding of the transcriptomic and protein pathways associated with CAIX in ER- BC to identify potential therapeutic targets against this aggressive phenotype.
2023-07-31 | E-MTAB-11955 | biostudies-arrayexpress
Project description:Today, Radiation therapy (RT) regimens are often used for many types of cancer including breast cancer (BC) disease. BC is an heterogeneous disease, at both clinical and molecular levels, presenting distinct subtypes associated with different clinical outcomes. This variability response may be caused by some factors linked to radiation or dependent to BC specific features such as tumor stage and hormone receptor (HR) status. We analyze and compare molecular responses, in term of gene expression profile (GEP) changes, induced by 9 and 23Gy of ionizing radiation (IR) in immortalized and primary cell cultures grouped according their Estrogen (ER) and Progesteron (PR) receptors positive or negative expression. Our explorative study gives some comprehensive hallmarks of the effects of the irradiation in BC cells. We trust that this study could have a role in driving RT towards personalised treatments, based also on the molecular characterization in BC.
2018-06-06 | GSE108962 | GEO
Project description:Breast cancer is a genetically and phenotypically complex disease. To understand the role of microRNAs in this molecular complexity, we performed miRNA expression analysis in a cohort of molecularly well-characterized human breast cancer (BC) cell lines to discover miRNAs associated with the most common molecular subtypes and the most frequent genetic aberrations.Using a microarray carrying LNA™ modified oligonucleotide capture probes (Exiqon), expression levels of 725 human miRNAs were measured in 51 BC cell lines. MiRNA expression was explored by unsupervised cluster analysis and then associated with the molecular subtypes and genetic aberrations commonly present in breast cancer. Unsupervised cluster analysis using the most variably expressed miRNAs divided the 51 BC cell lines into a major and a minor cluster predominantly mirroring the luminal and basal intrinsic subdivision of BC cell lines. One hundred and thirteen miRNAs were differentially expressed between these two main clusters of which half were related to the ER-status of the cell lines. Forty miRNAs were differentially expressed between basal-like and normal-like/claudin-low cell lines. Within the luminal-group of cell lines, 39 miRNAs were associated with ERBB2 overexpression and 24 miRNAs with E-cadherin gene mutations, which are frequent in this subtype of BC cell lines. In contrast, 31 different miRNAs were associated with E-cadherin promoter hypermethylation, which, contrary to E-cadherin mutation, is exclusively observed in BC cell lines that are not of luminal origin. The differential expression of 30 miRNAs were associated with p16INK4 status while only a few differentially expressed miRNAs were associated with BRCA1, or PIK3CA/PTEN, TP53 mutation status of the cell lines (P-value < 0.05). Twelve miRNAs were associated with DNA copy number variation of the respective locus. Luminal-basal and epithelial-mesenchymal associated miRNAs determine the overall subdivision of miRNA transcriptome of BC cell lines. Specific sets of miRNAs were associated with ERBB2 overexpression, p16INK4aor E-cadherin mutation or E-cadherin methylation status, which implies that these miRNAs may contribute to the driver role of the genetic aberrations. Additionally, miRNAs, which are located in a genomic region showing recurrent genetic aberrations, may themselves play a driver role in breast carcinogenesis or contribute to a driver gene in their vicinity. In short, our study provides detailed molecular miRNA portraits of BC cell lines, which can be exploited for functional studies of clinically important miRNAs. Affymetrix plus2PM arrays were hybridized according to the manufacturer's procedure using RNA extracted from 52 cultured breast cancer cell lines. Most cellines were analyzed in triplicate. Gene expression data in log2 scale arrays were calculated and associated with diverse characteristics. This submission represents the gene expression component of the study only
2013-04-22 | E-GEOD-41313 | biostudies-arrayexpress
Project description:Estrogen receptor (ER) signaling–dependent cancer cell growth is one of the major features of ER-positive breast cancer (BC). Inhibition of ER function is a standard and effective treatment for ER-positive tumors; however, ~20% of patients with ER-positive BC experience early or late recurrence. In this study, we examined intertumor heterogeneity from an epigenetic perspective based on the hypothesis that the intrinsic difference in epigenetic states around ER signaling pathway underlies endocrine therapy resistance. We profiled chromatin accessibility data from 42 BC samples, including 35 ER-positive human epidermal growth factor receptor 2 (HER2)-negative and 7 triple-negative tumors, identifying a subgroup of ER-positive BCs with a distinctive chromatin accessibility pattern including reduced accessibility to ER-responsive elements (EREs). The same subgroup was also observed in The Cancer Genome Atlas BC cohort. Despite the reduced accessibility to EREs, the expression of ER and potential ER target genes were not decreased in these tumors. Our findings highlight the existence of a subset of ER-positive BCs with unchanged ER expression but reduced EREs accessibility that cannot be distinguished by conventional immunostaining for ER. Future studies should determine whether these tumors are associated with resistance to endocrine therapy.
2023-01-09 | GSE222116 | GEO