An evolutionary learning-based method for identifying a circulating miRNA signature for breast cancer diagnosis prediction.

ABSTRACT: Breast cancer (BC) is one of the most commonly diagnosed cancers worldwide. As key regulatory molecules in several biological processes, microRNAs (miRNAs) are potential biomarkers for cancer. Understanding the miRNA markers that can detect BC may improve survival rates and develop new targeted therapeutic strategies. To identify a circulating miRNA signature for diagnostic prediction in patients with BC, we developed an evolutionary learning-based method called BSig. BSig established a compact set of miRNAs as potential markers from 1280 patients with BC and 2686 healthy controls retrieved from the serum miRNA expression profiles for the diagnostic prediction. BSig demonstrated outstanding prediction performance, with an independent test accuracy and area under the receiver operating char

SUBMITTER: Sathipati SY 

PROVIDER: S-EPMC10894035 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature