Prediction of chemo-response in serous ovarian cancer.

ABSTRACT:

Background

Nearly one-third of serous ovarian cancer (OVCA) patients will not respond to initial treatment with surgery and chemotherapy and die within one year of diagnosis. If patients who are unlikely to respond to current standard therapy can be identified up front, enhanced tumor analyses and treatment regimens could potentially be offered. Using the Cancer Genome Atlas (TCGA) serous OVCA database, we previously identified a robust molecular signature of 422-genes associated with chemo-response. Our objective was to test whether this signature is an accurate and sensitive predictor of chemo-response in serous OVCA.

Methods

We first constructed prediction models to predict chemo-response using our previously described 422-gene signature that was associated with response

SUBMITTER: Gonzalez Bosquet J 

PROVIDER: S-EPMC5070116 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature