A Subset of Secreted Proteins in Ascites Can Predict Platinum-Free Interval in Ovarian Cancer

ABSTRACT:

Simple Summary

Identifying proteins that correlate with better or worse outcomes may help to identify new treatment approaches for advanced high-grade serous ovarian cancer. Here, we utilize a machine learning technique to correlate the levels of 58 secreted proteins in tumor ascites with the time to disease recurrence after chemotherapy, which is known clinically as the platinum-free interval. We identify several candidate proteins correlated to shorter or longer platinum-free intervals and describe model analysis methods that may be useful for other studies aiming to identify factors impacting patient outcomes. Future validation of these factors in a prospective cohort would confirm their clinical utility, whereas a study of the mechanisms that they impact may identify new thera

SUBMITTER: Carroll M 

PROVIDER: S-EPMC9454800 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature