Gene signature-based prediction of triple-negative breast cancer patient response to Neoadjuvant chemotherapy.

Cancer Medicine
Yanding ZhaoChao Cheng

Abstract

Neoadjuvant chemotherapy is the current standard of care for large, advanced, and/or inoperable tumors, including triple-negative breast cancer. Although the clinical benefits of neoadjuvant chemotherapy have been illustrated through numerous clinical trials, more than half of the patients do not experience therapeutic benefit and needlessly suffer from side effects. Currently, no clinically applicable biomarkers are available for predicting neoadjuvant chemotherapy response in triple-negative breast cancer; the discovery of such a predictive biomarker or marker profile is an unmet need. In this study, we introduce a generic computational framework to calculate a response-probability score (RPS), based on patient transcriptomic profiles, to predict their response to neoadjuvant chemotherapy. We first validated this framework in ER-positive breast cancer patients and showed that it predicted neoadjuvant chemotherapy response with equal performance to several clinically used gene signatures, including Oncotype DX and MammaPrint. Then, we applied this framework to triple-negative breast cancer data and, for each patient, we calculated a response probability score (TNBC-RPS). Our results indicate that the TNBC-RPS achieved the high...Continue Reading

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Citations

Nov 17, 2021·Journal of Biochemical and Molecular Toxicology·Shengcui LiuRuikui Zhang

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Datasets Mentioned

BETA
GSE25055
GSE20271

Methods Mentioned

BETA
biopsies

Software Mentioned

R
sva
ESTIMATE
randomForest
ComBat
genefu R
endoPredict
PROSIGNA

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