a systematic evaluation of multi-gene predictors for the pathological response of breast cancer patients to chemotherapy系统评价的多基因预测乳腺癌患者对化疗的病理反应.pdfVIP

A Systematic Evaluation of Multi-Gene Predictors for the Pathological Response of Breast Cancer Patients to Chemotherapy 1.¤ 1. 2 1 1 1 Kui Shen , Nan Song , Youngchul Kim , Chunqiao Tian , Shara D. Rice , Michael J. Gabrin , W. 3 4 2 Fraser Symmans , Lajos Pusztai , Jae K. Lee * 1 Precision Therapeutics, Inc., Pittsburgh, Pennsylvania, United States of America, 2 Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, United States of America, 3 Department of Pathology, University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America, 4 Division of Breast Medical Oncology, Yale Cancer Center, New Haven, Connecticut, United States of America Abstract Previous studies have reported conflicting assessments of the ability of cell line-derived multi-gene predictors (MGPs) to forecast patient clinical outcomes in cancer patients, thereby warranting an investigation into their suitability for this task. Here, 42 breast cancer cell lines were evaluated by chemoresponse tests after treatment with either TFAC or FEC, two widely used standard combination chemotherapies for breast cancer. We used two different training cell line sets and two independent prediction methods, superPC and COXEN, to develop cell line-based MGPs, which were then validated in five patient cohorts treated with these chemotherapies. This evaluation yielded high prediction performances by these MGPs, regardless of the training set, chemotherapy, or prediction method. The MGPs were also able to predict patient clinical outcomes for the subgroup of estrogen receptor (ER)-negative patients, which has proven difficult in the past.