Dataset Information

Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer.

ABSTRACT:

Background

Existing studies have demonstrated that the integrative analysis of histopathological images and genomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, since the development of pathological phenotypes are influenced by a variety of complex biological processes, complete understanding of the underlying gene regulatory mechanisms for the cell and tissue morphology is still a challenge. In this study, we explored the relationship between the chromatin accessibility changes and the epithelial tissue proportion in histopathological images of estrogen receptor (ER) positive breast cancer.

Methods

An established whole slide image processing pipeline based on deep learning was used to perform global segmentation of epithelial and stromal tissues. We then used canonical correlation analysis to detect the epithelial tissue proportion-associated regulatory regions. By integrating ATAC-seq data with matched RNA-seq data, we found the potential target genes that associated with these regulatory regions. Then we used these genes to perform the following pathway and survival analysis.

Results

Using canonical correlation analysis, we detected 436 potential regulatory regions that exhibited significant correlation between quantitative chromatin accessibility changes and the epithelial tissue proportion in tumors from 54 patients (FDR?ConclusionThis integrative analysis is a useful strategy for identifying potential regulatory regions in the human genome that are associated with tumor tissue quantification. This study will enable efficient prioritization of genomic regulatory regions identified by ATAC-seq data for further studies to validate their causal regulatory function. Ultimately, identifying epithelial tissue proportion-associated regulatory regions will further our understanding of the underlying molecular mechanisms of disease and inform the development of potential therapeutic targets.

SUBMITTER: Xu S

PROVIDER: S-EPMC7771206 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer.

Xu Siwen S Lu Zixiao Z Shao Wei W Yu Christina Y CY Reiter Jill L JL Feng Qianjin Q Feng Weixing W Huang Kun K Liu Yunlong Y

BMC medical genomics 20201228 Suppl 11

<h4>Background</h4>Existing studies have demonstrated that the integrative analysis of histopathological images and genomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, since the development of pathological phenotypes are influenced by a variety of complex biological processes, complete understanding of the underlying gene regulatory mechanisms for the cell and tissue morphology is still a ...[more]

PMID: 33371906

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Project description:BackgroundAmong women, breast cancer is the leading cause of cancer-related death worldwide. Estrogen receptor α-positive (ERα+) breast cancer accounts for 70% of all breast cancer subtypes. Although ERα+ breast cancer initially responds to estrogen deprivation or blockade, the emergence of resistance compels the use of more aggressive therapies. While ERα is a driver in ERα+ breast cancer, ERβ plays an inhibitory role in several different cancer types. To date, the lack of highly selective ERβ agonists without ERα activity has limited the exploration of ERβ activation as a strategy for ERα+ breast cancer.MethodsWe measured the expression levels of ESR1 and ESR2 genes in immortalized mammary epithelial cells and different breast cancer cell lines. The viability of ERα+ breast cancer cell lines upon treatments with specific ERβ agonists, including OSU-ERb-12 and LY500307, was assessed. The specificity of the ERβ agonists, OSU-ERb-12 and LY500307, was confirmed by reporter assays. The effects of ERβ agonists on cell proliferation, cell cycle, apoptosis, colony formation, cell migration, and expression of tumor suppressor proteins were analyzed. The expression of ESR2 and genes containing ERE-AP1 composite response elements was examined in ERα+ human breast cancer samples to determine the correlation between ESR2 expression and overall survival and that of putative ESR2-regulated genes.ResultsIn this study, we demonstrate the efficacy of highly selective ERβ agonists in ERα+ breast cancer cell lines and drug-resistant derivatives. ERβ agonists blocked cell proliferation, migration, and colony formation and induced apoptosis and S and/or G2/M cell-cycle arrest of ERα+ breast cancer cell lines. Also, increases in the expression of the key tumor suppressors FOXO1 and FOXO3a were noted. Importantly, the strong synergy between ERβ agonists and ERα antagonists suggested that the efficacy of ERβ agonists is maximized by combination with ERα blockade. Lastly, ESR2 (ERβ gene) expression was negatively correlated with ESR1 (ERα gene) and CCND1 RNA expression in human metastatic ERα+/HER2- breast cancer samples.ConclusionOur results demonstrate that highly selective ERβ agonists attenuate the viability of ERα+ breast cancer cell lines in vitro and suggest that this therapeutic strategy merits further evaluation for ERα+ breast cancer.

Dataset Information

Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer.

Background

Methods

Results

Publications

Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer.

Similar Datasets

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