A chemotherapy response classifier based on support vector machines for high-grade serous ovarian carcinoma.

ABSTRACT: Long-term outcome of high-grade serous epithelial ovarian carcinoma (HGSOC) remains poor as a result of recurrence and the emergence of drug resistance. Almost all the patients were given the same platinum-based chemotherapy after debulking surgery even though some of them are naturally resistant to the first-line chemotherapy. No method could verify this part of patients right after the surgery currently. In this study, we used 156 paraffin-embedded high-grade HGSOC specimens for immunohistochemical analysis with 37 immunology markers, and association between the expression levels of these markers and the chemoresponse were evaluated. A support vector machine (SVM)-based HGSOC prognostic classifier was then established, and was validated by a 95-patient independent cohort. The classifier

SUBMITTER: Sun CY 

PROVIDER: S-EPMC4823103 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature