Literature DB >> 30225582

Copy number profiling of Oncotype DX genes reveals association with survival of breast cancer patients.

Washaakh Ahmed1,2, Muhammad Faraz Arshad Malik2, Muhammad Saeed2, Farhan Haq3.   

Abstract

Copy number variations (CNVs) are key contributors in breast cancer initiation and progression. However, to date, no CNV-based gene signature is developed for breast cancer. 21-gene Oncotype DX, a clinically validated signature, was identified using only RNA expression data in breast cancer patients. In this study, we evaluated whether CNVs of Oncotype DX genes can be used to predict the prognosis of breast cancer patients. Transcriptomic data of 547 and genomic data of 816 of breast cancer patients were downloaded from The Cancer Genome Atlas database. To establish the prognostic relevance between the CNVs of Oncotype DX genes and clinicopathological features, statistical analysis including Pearson Correlation, Fisher-exact, Chi square, Kaplan-Meier survival and Cox regression analyses were performed. 86% genes showed positive CNV-expression correlation. CNVs in 52% and 47.6% genes showed association with ER+ and PR+ status, respectively. 71% of the genes (including ERBB2, CTSV, CD68, GRB7, MKI67, MMP1, PGR, RPLP0, TFRC, BAG1, BCL2, BIRC5, FLNB, GSTM1 and SCUBE2) showed association with poor overall survival. 14% of the genes (including CTSV, RPLP0 and BIRC5) genes showed association with disease free survival. Cox regression analysis revealed ESR1, metastasis and node stage as independent prognostic factors for overall survival of breast cancer patients. The results suggested that CNV-based assay of Oncotype DX genes can be used to predict the survival of breast cancer patients. In future, identifying new gene signatures for better breast cancer prognosis using CNV level information will be worth investigating.

Entities:  

Keywords:  Amplification; Deletion; Gene signatures; Oncotype DX; Survival

Mesh:

Substances:

Year:  2018        PMID: 30225582     DOI: 10.1007/s11033-018-4379-1

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


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