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Genome-wide analysis of the three-way interplay among gene expression, estrogen receptor expression and chemotherapeutic sensitivity in breast cancer.

ABSTRACT: The expression of estrogen receptor ? (ER) in breast cancers may be indicative of a favorable prognosis and most of these cancers respond to anti-estrogens or aromatase inhibitors. However, ER-positive (ER+) breast cancers receiving anti-hormone and/or chemotherapy sometimes lose their ER expression, which leads to the evolution of the disease to higher aggressiveness and drug resistance. In the present study, an ER-modified signature (EMS) was developed from the expression profile of a chemoresistant MCF-7 breast cancer cell line that lost ER expression during long-term treatment with a chemotherapeutic agent. The EMS could discriminate the ER-negative (ER-) breast cancer cells from the ER+ ones, which included seven pathways essential for the ER- cell development. Furthermore, the EMS indicated a more malignant subgroup of the ER- cells by discriminating the chemoresistant ER- cells from the chemosensitive ones. In addition, the classified chemoresistant ER- patients demonstrated worse prognosis. In conclusion, we developed a new method to discriminate subgroups of ER- breast cancer cells.

SUBMITTER: He DX

PROVIDER: S-EPMC5783585 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Genome-wide analysis of the three-way interplay among gene expression, estrogen receptor expression and chemotherapeutic sensitivity in breast cancer.

He Dong-Xu DX Wu Xiao-Li XL Lu Chun-Xiao CX Gu Xiao-Ting XT Zhang Guang-Yuan GY Ma Xin X Liu De-Quan DQ

Oncology reports 20171012 6

The expression of estrogen receptor α (ER) in breast cancers may be indicative of a favorable prognosis and most of these cancers respond to anti-estrogens or aromatase inhibitors. However, ER-positive (ER+) breast cancers receiving anti-hormone and/or chemotherapy sometimes lose their ER expression, which leads to the evolution of the disease to higher aggressiveness and drug resistance. In the present study, an ER-modified signature (EMS) was developed from the expression profile of a chemores ...[more]

PMID: 29039577

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Project description:BACKGROUND: Chemosensitivity and tumor metastasis are two primary issues in cancer management. Cancer cells often exhibit a wide range of sensitivity to anti-cancer compounds. To gain insight on the genetic mechanism of drug sensitivity, one powerful approach is to employ the panel of 60 human cancer cell lines developed by the National Cancer Institute (NCI). Cancer cells also show a broad range of invasion ability. However, a genome-wide portrait on the contributing molecular factors to invasion heterogeneity is lacking. METHODS: Our lab performed an invasion assay on the NCI-60 panel. We identified invasion-associated (IA) genes by correlating our invasion profiling data with the Affymetrix gene expression data on NCI-60. We then employed the recently released chemosensitivity data of 99 anti-cancer drugs of known mechanism to investigate the gene-drug correlation, focusing on the IA genes. Afterwards, we collected data from four independent drug-testing experiments to validate our findings on compound response prediction. Finally, we obtained published clinical and molecular data from two recent adjuvant chemotherapy cohorts, one on lung cancer and one on breast cancer, to test the performance of our gene signature for patient outcome prediction. RESULTS: First, we found 633 IA genes from the invasion-gene expression correlation study. Then, for each of the 99 drugs, we obtained a subset of IA genes whose expression levels correlated with drug-sensitivity profiles. We identified a set of eight genes (EGFR, ITGA3, MYLK, RAI14, AHNAK, GLS, IL32 and NNMT) showing significant gene-drug correlation with paclitaxel, docetaxel, erlotinib, everolimus and dasatinib. This eight-gene signature (derived from NCI-60) for chemosensitivity prediction was validated by a total of 107 independent drug tests on 78 tumor cell lines, most of which were outside of the NCI-60 panel. The eight-gene signature predicted relapse-free survival for the lung and breast cancer patients (log-rank P = 0.0263; 0.00021). Multivariate Cox regression yielded a hazard ratio of our signature of 5.33 (95% CI = 1.76 to 16.1) and 1.81 (95% CI = 1.19 to 2.76) respectively. The eight-gene signature features the cancer hallmark epidermal growth factor receptor (EGFR) and genes involved in cell adhesion, migration, invasion, tumor growth and progression. CONCLUSIONS: Our study sheds light on the intricate three-way interplay among gene expression, invasion and compound-sensitivity. We report the finding of a unique signature that predicts chemotherapy survival for both lung and breast cancer. Augmenting the NCI-60 model with in vitro characterization of important phenotype-like invasion potential is a cost-effective approach to power the genomic chemosensitivity analysis.

Dataset Information

Genome-wide analysis of the three-way interplay among gene expression, estrogen receptor expression and chemotherapeutic sensitivity in breast cancer.

Publications

Genome-wide analysis of the three-way interplay among gene expression, estrogen receptor expression and chemotherapeutic sensitivity in breast cancer.

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