Link between GRHL2 Motifs and Intratumor Heterogeneity of Cis-Regulatory Elements Results in Poor Outcome in Luminal Breast Cancer: A Single-cell Chromatin Accessibility Analysis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE198639 | GEO | 2022/03/16
REPOSITORIES: GEO
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Project description:Breast cancer is a heterogeneous disease, and breast cancer cell lines are invaluable for studying this heterogeneity. However, the epigenetic diversity across these cell lines remains poorly understood. In this study, we performed genome-wide chromatin accessibility analysis on 23 breast cancer cell lines, including 2 estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative (ER+/HER2−), 3 ER+/HER2+, 2 HER2+, and 15 triple-negative breast cancer (TNBC) lines. These cell lines were classified into three groups based on their chromatin accessibility: the receptor-positive group (Group-P), TNBC basal group (Group-B), and TNBC mesenchymal group (Group-M). Motif enrichment analysis revealed that only Group-P exhibited coenrichment of forkhead box A1 (FOXA1) and grainyhead-like 2 (GRHL2) motifs, whereas Group-B was characterized by the presence of the GRHL2 motif without FOXA1. Notably, Group-M did not show enrichment of either FOXA1 or GRHL2 motifs. Furthermore, gene ontology analysis suggested that group-specific accessible regions were associated with their unique lineage characteristics. To investigate the epigenetic landscape regulatory roles of FOXA1 and GRHL2, we performed knockdown experiments targeting FOXA1 and GRHL2, followed by assay for transposase-accessible chromatin sequencing analysis. The findings revealed that FOXA1 maintains Group-P–specific regions while suppressing Group-B–specific regions in Group-P cells. In contrast, GRHL2 preserves commonly accessible regions shared between Group-P and Group-B in Group-B cells, suggesting that FOXA1 and GRHL2 play a pivotal role in preserving distinct chromatin accessibility patterns for each group. Specifically, FOXA1 distinguishes between receptor-positive and TNBC cell lines, whereas GRHL2 distinguishes between basal-like and mesenchymal subtypes in TNBC lines.
2024-02-01 | GSE254218 | GEO
Project description:Breast cancer is a heterogeneous disease, and breast cancer cell lines are invaluable for studying this heterogeneity. However, the epigenetic diversity across these cell lines remains poorly understood. In this study, we performed genome-wide chromatin accessibility analysis on 23 breast cancer cell lines, including 2 estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative (ER+/HER2−), 3 ER+/HER2+, 2 HER2+, and 15 triple-negative breast cancer (TNBC) lines. These cell lines were classified into three groups based on their chromatin accessibility: the receptor-positive group (Group-P), TNBC basal group (Group-B), and TNBC mesenchymal group (Group-M). Motif enrichment analysis revealed that only Group-P exhibited coenrichment of forkhead box A1 (FOXA1) and grainyhead-like 2 (GRHL2) motifs, whereas Group-B was characterized by the presence of the GRHL2 motif without FOXA1. Notably, Group-M did not show enrichment of either FOXA1 or GRHL2 motifs. Furthermore, gene ontology analysis suggested that group-specific accessible regions were associated with their unique lineage characteristics. To investigate the epigenetic landscape regulatory roles of FOXA1 and GRHL2, we performed knockdown experiments targeting FOXA1 and GRHL2, followed by assay for transposase-accessible chromatin sequencing analysis. The findings revealed that FOXA1 maintains Group-P–specific regions while suppressing Group-B–specific regions in Group-P cells. In contrast, GRHL2 preserves commonly accessible regions shared between Group-P and Group-B in Group-B cells, suggesting that FOXA1 and GRHL2 play a pivotal role in preserving distinct chromatin accessibility patterns for each group. Specifically, FOXA1 distinguishes between receptor-positive and TNBC cell lines, whereas GRHL2 distinguishes between basal-like and mesenchymal subtypes in TNBC lines.
2024-02-01 | GSE254216 | GEO
Project description:Limited knowledge of the changes in estrogen receptor (ER) signaling during the transformation of the normal mammary gland to breast cancer hinders the development of effective prevention and treatment strategies. Differences in estrogen signaling between normal human primary breast epithelial cells and primary breast tumors obtained immediately following surgical excision were explored. Transcriptional profiling of normal ER+ mature luminal mammary epithelial cells and ER+ breast tumors revealed significant difference in the response to estrogen stimulation. Consistent with these differences in gene expression, the normal and tumor ER cistromes were distinct and sufficient to segregate normal breast tissues from breast tumors. The selective enrichment of the DNA binding motif GRHL2 in the breast cancer-specific ER cistrome suggests that it may play a role in the differential function of ER in breast cancer. Depletion of GRHL2 resulted in altered ER binding and differential transcriptional responses to estrogen stimulation. Furthermore, GRHL2 was demonstrated to be essential for estrogen-stimulated proliferation of ER+ breast cancer cells. DLC1 was also identified as an estrogen-induced tumor suppressor in the normal mammary gland with decreased expression in breast cancer. In clinical cohorts, loss of DLC1 and gain of GRHL2 expression are associated with breast cancer and are independently predictive for worse survival. This study suggests that normal ER signaling is lost and tumor-specific ER signaling is gained during breast tumorigenesis. Unraveling these changes in ER signaling during breast cancer progression should aid the development of more effective prevention strategies and targeted therapeutics. SIGNIFICANCE STATEMENT: Abnormal estrogen receptor (ER) signaling drives the majority of breast cancers and is targeted by endocrine therapies. However, in normal breast tissue, ER signaling has been demonstrated to promote benign functions such as development and differentiation. Using genomic techniques to characterize ER function in normal breast and breast tumors, this study reveals differential patterns of ER signaling, suggesting that normal ER signaling is lost and tumorigenic ER signaling gained during breast tumor formation. Better understanding of this process can aid the development of improved breast cancer prevention strategies and therapies.
2019-05-27 | GSE99680 | GEO
Project description:*** This submission includes RNA data, with DNA files available under a different accession number*** Purpose: Endocrine therapy resistance remains the greatest challenge for treating hormone receptor positive breast cancer patients. We aim to identify molecular mechanisms underlying endocrine therapy resistance through in-depth genomic analysis of patient samples. Experimental Design: We collected tumors from 35 estrogen receptor positive breast cancer patients receiving endocrine therapy, of which 3 patients had intrinsic resistance and 19 patients developed acquired resistance. For each patient, multiple tumor specimens were collected during the course of treatment. We performed DNA whole exome sequencing and RNA sequencing on all tumor samples. DNA mutations, copy number alterations and RNA gene expression data were analyzed through supervised analyses comparing paired sensitive and resistant tumor samples to identify molecular features related to endocrine therapy resistance. Results: We identified mutations enriched in resistant tumors including ESR1 and GATA3. ESR1 D538G variant confers endocrine therapy resistance while E380Q variant confers hypersensitivity. We demonstrate that resistant tumors had distinct gene expression profiles and elevated signaling pathways including ER, HER2, GATA3, AKT, RAS and p63 signaling. Integrated analysis for individual patient highlighted the heterogeneity of endocrine therapy resistance mechanisms. Conclusions: Our results suggest that mechanisms underlying endocrine therapy resistance are highly heterogeneous with diverse changes in genomic and transcriptomic levels.
2022-09-01 | E-MTAB-9917 | biostudies-arrayexpress
Project description:There is clinical need to predict sensitivity of metastatic hormone receptor-positive and HER2-negative (HR+/HER2-) breast cancer to endocrine therapy, and targeted RNA sequencing (RNAseq) offers diagnostic potential to measure both transcriptional activity and functional mutation. We developed the SET ER/PR index to measure gene expression microarray probe sets that were correlated with hormone receptors (ESR1 and PGR) and robust to pre-analytical and analytical influences. We tested SET ER/PR index in biopsies of metastastic HR+/HER2- breast cancer against the treatment outcomes in 140 patients. Then we customized the SETER/PR assay to measure 18 informative, 10 reference transcripts, and sequence the ligand binding domain (LBD) of ESR1 using droplet-based targeted RNAseq, and tested that in residual RNA from 53 patients. Higher SET ER/PR index in metastatic samples predicted longer progression-free (PFS) and overall survival (OS) when patients received endocrine therapy as next treatment, even after adjustment for clinical-pathologic risk factors (PFS: HR 0.534, 95% CI 0.299 to 0.955, p = 0.035; OS: HR 0.315, 95% CI 0.157 to 0.631, p = 0.001). Mutated ESR1 LBD was detected in 8/53 (15%) of metastases, involving 1% to 98% of ESR1 transcripts (all had high SETER/PR index). A signature based on probe sets with good pre-analytical and analytical performance facilitated our customization of an accurate targeted RNAseq assay to measure both phenotype and genotype of ER-related transcription. Elevated SET ER/PR was associated with prolonged sensitivity to endocrine therapy in patients with metastatic HR+/HER2- breast cancer, especially in the absence of mutated ESR1 transcript. We tested SET ER/PR index in biopsies of metastastic HR+/HER2- breast cancer against the treatment outcomes in 140 patients. Then we customized the SET ER/PR assay to measure 18 informative, 10 reference transcripts, and sequence the ligand binding domain (LBD) of ESR1 using droplet-based targeted RNAseq, and tested that in residual RNA from 53 patients. Higher SET ER/PR index in metastatic samples predicted longer progression-free (PFS) and overall survival (OS) when patients received endocrine therapy as next treatment, even after adjustment for clinical-pathologic risk factors (PFS: HR 0.485, 95% CI 0.265 to 0.889, p = 0.019; OS: HR 0.314, 95% CI 0.155 to 0.637, p = 0.001). Mutated ESR1 LBD was detected in 8/53 (15%) of metastases, involving 1% to 98% of ESR1 transcripts (all had high SET ER/PR index). A signature based on probe sets with good pre-analytical and analytical performance facilitated our customization of an accurate targeted RNAseq assay to measure both phenotype and genotype of ER-related transcription. Elevated SET ER/PR was associated with prolonged sensitivity to endocrine therapy in patients with metastatic HR+/HER2- breast cancer, especially in the absence of mutated ESR1 transcript.
2019-05-30 | GSE124647 | GEO
Project description:Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Controls: 5 cases; ER +/HER2- breast cancer patients : 11 cases
2013-12-12 | E-GEOD-53179 | biostudies-arrayexpress
Project description:In ER-positive, HER2-negative breast cancer, multiple measures of intra-tumor heterogeneity are associated with worse response to endocrine therapy. To investigate heterogeneity in response to treatment, we developed an operating room-to-laboratory pipeline for the collection of live human tumors and normal breast specimens immediately after surgical resection for processing into single-cell workflows for experimentation and genomic analyses. We demonstrate differences in tamoxifen response by cell type and identify distinctly responsive and resistant subpopulations within the malignant cell compartment of human tumors. Tamoxifen resistance signatures from 3 distinct resistant subpopulations are prognostic in large cohorts of ER-positive breast cancer patients and enriched in endocrine therapy resistant tumors. This novel ex vivo model system now provides a foundation to define responsive and resistant sub-populations within heterogeneous tumors, to develop precise single cell-based predictors of response to therapy, and to identify genes and pathways driving resistance to therapy.
2023-10-19 | GSE245601 | GEO
Project description:Purpose HER2 gene amplification or protein overexpression (HER2+) defines a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. We aimed to investigate the heterogeneous biological appearance and clinical behavior of HER2+ tumors using molecular profiling. Materials and Methods Hierarchical clustering of gene expression data from 58 HER2-amplified tumors of various stage, histological grade and estrogen receptor (ER) status was used to construct a HER2-derived prognostic predictor that was further evaluated in several large independent breast cancer data sets. Results Unsupervised analysis identified three subtypes of HER2+ tumors with mixed stage, histological grade and ER-status. One subtype had a significantly worse clinical outcome. A prognostic predictor was created based on differentially expressed genes between the subtype with worse outcome and the other subtypes. The predictor was able to define patient groups with better and worse outcome in HER2+ breast cancer across multiple independent breast cancer data sets and identify a sizable HER2+ group with long disease-free survival and low mortality. Significant correlation to prognosis was also observed in basal-like, ER−, lymph node positive or high-grade tumors, irrespective of HER2-status. The predictor included genes associated to immune response, tumor invasion and metastasis. Conclusion The HER2-derived prognostic predictor provides further insight into the heterogeneous biology of HER2+ tumors and may become useful for improved selection of patients that need additional treatment with new drugs targeting the HER2 pathway. Array comparative genomic hybridization (aCGH) identified 58 breast tumors with amplification of HER2 from a larger cohort of approx 500 tumors breast. Global gene expression profiles were obtained using 70-mer oligonucleotide microarrays. Unsupervised hierarchical clustering of the 58 tumors, using Pearson correlation and complete linkage, identified three main clusters. One cluster showed significantly poorer clinical outcome. Significance of microarray (SAM) analysis was performed to identify 158 genes separating the poor outcome cluster compared to the other two clusters. Gene expression centroids, based on the 158 genes, were created for each cluster for validation in independent breast cancer data sets.
2010-03-16 | E-GEOD-18328 | biostudies-arrayexpress
Project description:Purpose: The biological subtypes of breast cancer designated as Luminal A, Luminal B, HER2+/ER-, and Basal-like are clinically important for prognosis and planning treatment strategies. Recognizing that there is a continuum in both the spectrum of breast cancer disease and the risk of survival, we sought to develop a clinical test for the biological subtypes using a supervised risk classier.Methods: Microarray and real-time quantitative RT-PCR (qRT-PCR) data from 189 samples, procured as fresh-frozen and formalin-fixed, paraffin-embedded tissues, were used to statistically select prototypical samples and genes for the biological subtypes of breast cancer. Predictions for biological subtype and risk of recurrence were determined for different stages of disease, treatments, and across analytical platforms. Results: The biological subtype predictions on a large combined microarray test set showed prognostic significance across all patients (1244 subjects; p<0.0001), on node negative patients with no adjuvant systemic therapy (738 subjects; p<0.0001), and on patients treated with endocrine therapy (404 subjects; p=0.001). Analysis of a neoadjuvant chemotherapy study revealed a high pathologic complete response (pCR) rate in HER2+/ER- and Basal-like patients. The subtype and risk predications were also highly significant when using the qRT-PCR assay from archived FFPE breast cancers. Conclusion: Our risk predictor based on distance to biological subtype centroids provides a continuous risk score that applies to all stages of breast cancer given current therapies. The assay can be performed using archived breast tissues and a real-time qRT-PCR assay, thus facilitating application to retrospective cohorts and clinical samples. Keywords: reference x sample Comparison of reference samples against treatment
2010-06-24 | E-GEOD-10886 | biostudies-arrayexpress
Project description:Recent analyses have identified heterogeneity in estrogen receptor (ER)-positive breast cancer. There are so-called luminal A and luminal B subtypes, and the characteristics, such as response to endocrine therapy and chemotherapy and prognosis, are different in these two subtypes of breast cancer. In this study, expression profiles of microRNAs (miRNAs) and mRNAs in ER-positive breast cancer tissues were compared between highly and incompletely endocrine responsive tumors by miRNA and mRNA microarrays. Unsupervised hierarchical clustering analyses revealed distinct expression patterns of miRNAs and mRNAs in these two groups. We identified one miRNA that was downregulated in highly endocrine responsive tumors and 8 miRNAs that were downregulated in incompletely endocrine responsive tumors, and target genes of these miRNAs were predicted using TargetScan and MiRanda. Protein expression patterns of the predicted target genes and the genes that were identified by mRNA expression profiling were analyzed in ER-positive breast cancer samples by immunohistochemistry. We identified a novel protein that might be associated with characteristics of ER-positive breast cancer.
2013-03-04 | GSE38279 | GEO