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Triple-negative breast cancer: bridging the gap from cancer genomics to predictive biomarkers.

ABSTRACT: Triple-negative breast cancer (TNBC) represents a challenge clinically due to a lack of response to hormonal and HER2-targeted agents coupled with an aggressive disease course. As the biology of this breast cancer subtype is better understood, it is clear that TNBC is a heterogeneous disease and one targeted therapy is unlikely to be active in all patients. Biomarkers predictive of response to treatment are thus of great importance in TNBC. This review outlines studies evaluating biomarkers predictive of response to neoadjuvant chemotherapy and to targeted therapies in the advanced setting. The development of validated biomarkers in conjunction with novel targeted therapies represents an opportunity to improve patient outcomes in TNBC.

SUBMITTER: Davis SL

PROVIDER: S-EPMC3987651 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Triple-negative breast cancer: bridging the gap from cancer genomics to predictive biomarkers.

Davis S Lindsey SL Eckhardt S Gail SG Tentler John J JJ Diamond Jennifer R JR

Therapeutic advances in medical oncology 20140501 3

Triple-negative breast cancer (TNBC) represents a challenge clinically due to a lack of response to hormonal and HER2-targeted agents coupled with an aggressive disease course. As the biology of this breast cancer subtype is better understood, it is clear that TNBC is a heterogeneous disease and one targeted therapy is unlikely to be active in all patients. Biomarkers predictive of response to treatment are thus of great importance in TNBC. This review outlines studies evaluating biomarkers pred ...[more]

PMID: 24790649

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Project description:Triple‑negative breast cancer (TNBC) accounts for the worst prognosis of all types of breast cancers due to a high risk of recurrence and a lack of targeted therapeutic options. Extensive effort is required to identify novel targets for TNBC. In the present study, a robust rank aggregation (RRA) analysis based on genome‑wide gene expression datasets involving TNBC patients from the Gene Expression Omnibus (GEO) database was performed to identify key genes associated with TNBC. A total of 194 highly ranked differentially expressed genes (DEGs) were identified in TNBC vs. non‑TNBC. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was utilized to explore the biological functions of the identified genes. These DEGs were mainly involved in the biological processes termed positive regulation of transcription from RNA polymerase II promoter, negative regulation of apoptotic process, response to drug, response to estradiol and negative regulation of cell growth. Genes were mainly involved in the KEGG pathway termed estrogen signaling pathway. The aberrant expression of several randomly selected DEGs were further validated in cell lines, clinical tissues and The Cancer Genome Atlas (TCGA) cohort. Furthermore, all the top‑ranked DEGs underwent survival analysis using TCGA database, of which overexpression of 4 genes (FABP7, ART3, CT83, and TTYH1) were positively correlated to the life expectancy (P<0.05) of TNBC patients. In addition, a model consisting of two genes (FABP7 and CT83) was identified to be significantly associated with the overall survival (OS) of TNBC patients by means of Cox regression, Kaplan‑Meier, and receiver operating characteristic (ROC) analyses. In conclusion, the present study identified a number of key genes as potential biomarkers involved in TNBC, which provide novel insights into the tumorigenesis of TNBC at the gene level and may serve as independent prognostic factors for TNBC prognosis.

Dataset Information

Triple-negative breast cancer: bridging the gap from cancer genomics to predictive biomarkers.

Publications

Triple-negative breast cancer: bridging the gap from cancer genomics to predictive biomarkers.

Similar Datasets

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