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Combined Treatment with Epigenetic, Differentiating, and Chemotherapeutic Agents Cooperatively Targets Tumor-Initiating Cells in Triple-Negative Breast Cancer.

ABSTRACT: Efforts to induce the differentiation of cancer stem cells through treatment with all-trans retinoic acid (ATRA) have yielded limited success, partially due to the epigenetic silencing of the retinoic acid receptor (RAR)-? The histone deacetylase inhibitor entinostat is emerging as a promising antitumor agent when added to the standard-of-care treatment for breast cancer. However, the combination of epigenetic, cellular differentiation, and chemotherapeutic approaches against triple-negative breast cancer (TNBC) has not been investigated. In this study, we found that combined treatment of TNBC xenografts with entinostat, ATRA, and doxorubicin (EAD) resulted in significant tumor regression and restoration of epigenetically silenced RAR-? expression. Entinostat and doxorubicin treatment inhibited topoisomerase II-? (TopoII-?) and relieved TopoII-?-mediated transcriptional silencing of RAR-? Notably, EAD was the most effective combination in inducing differentiation of breast tumor-initiating cells in vivo Furthermore, gene expression analysis revealed that the epithelium-specific ETS transcription factor-1 (ESE-1 or ELF3), known to regulate proliferation and differentiation, enhanced cell differentiation in response to EAD triple therapy. Finally, we demonstrate that patient-derived metastatic cells also responded to treatment with EAD. Collectively, our findings strongly suggest that entinostat potentiates doxorubicin-mediated cytotoxicity and retinoid-driven differentiation to achieve significant tumor regression in TNBC. Cancer Res; 76(7); 2013-24. ©2016 AACR.

SUBMITTER: Merino VF

PROVIDER: S-EPMC4873448 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Combined Treatment with Epigenetic, Differentiating, and Chemotherapeutic Agents Cooperatively Targets Tumor-Initiating Cells in Triple-Negative Breast Cancer.

Merino Vanessa F VF Nguyen Nguyen N Jin Kideok K Sadik Helen H Cho Soonweng S Korangath Preethi P Han Liangfeng L Foster Yolanda M N YMN Zhou Xian C XC Zhang Zhe Z Connolly Roisin M RM Stearns Vered V Ali Syed Z SZ Adams Christina C Chen Qian Q Pan Duojia D Huso David L DL Ordentlich Peter P Brodie Angela A Sukumar Saraswati S

Cancer research 20160119 7

Efforts to induce the differentiation of cancer stem cells through treatment with all-trans retinoic acid (ATRA) have yielded limited success, partially due to the epigenetic silencing of the retinoic acid receptor (RAR)-β The histone deacetylase inhibitor entinostat is emerging as a promising antitumor agent when added to the standard-of-care treatment for breast cancer. However, the combination of epigenetic, cellular differentiation, and chemotherapeutic approaches against triple-negative bre ...[more]

PMID: 26787836

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Project description:PurposeTriple-negative breast cancer (TNBC) is an aggressive tumor with poor prognosis, it has higher recurrence and metastatic rates than other breast cancer subtypes. This study aims to investigate biomarkers and potential targets for TNBC related to ferroptosis through data mining and bioinformatics analysis. The findings may provide new insights for treating TNBC.MethodsThe TNBC patients' data from the Cancer Genome Atlas (TCGA) database were extracted for differential expression and prognosis analysis. Consensus genes obtained by intersecting differential expressed and ferroptosis-related genes was used to establish the prognostic model by the univariate and multivariate Cox analyses. Besides, TNBC data from the Gene Expression Omnibus (GEO) database was used to confirm the reliability of the prognosis model. Moreover, clinical information was analyzed by multifactorial independent analysis to identify independent prognostic factors. The expression of genes constituting the prognostic model was further validated using the Human Protein Atlas (HPA) database. Finally, the Comparative Toxicogenomic Data (CTD) database was used to explore possible treatment drugs for TNBC.ResultsWe obtained 13,245 differential expressed genes, and 177 consensus genes. 98 genes with prognostic implication were obtained by univariable Cox. Then, a prognostic model including 12 ferroptosis-related genes was constructed by multivariable Cox. The area under curve (AUC) value of the prognostic model for TNBC was 0.82. The GEO database validated that the model (AUC = 0.77) could predict the patient outcomes. The staining results of 10 out of 12 prognostic model genes in HPA database showed that their expression was consistent with our predictions. Clinical risk analysis indicated that risk score of patients could act as an independent prognostic factor. Finally, six drugs that may have interaction with 12 ferroptosis-related genes were obtained using the CTD database.ConclusionThe prognostic model composed of 12 ferroptosis-related genes could predict the prognosis of TNBC patients, and seven genes (ASNS, LAMP2, CAV1, DPP4, HELLS, TF, ZFP69B) could be potential new therapeutic targets for TNBC, and two drugs (1-methyl-3-isobutylxanthine, rosiglitazone) could act as potential therapeutic drugs for the treatment of TNBC.

Dataset Information

Combined Treatment with Epigenetic, Differentiating, and Chemotherapeutic Agents Cooperatively Targets Tumor-Initiating Cells in Triple-Negative Breast Cancer.

Publications

Combined Treatment with Epigenetic, Differentiating, and Chemotherapeutic Agents Cooperatively Targets Tumor-Initiating Cells in Triple-Negative Breast Cancer.

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