Cancer Grade Model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer.

ABSTRACT:

Background

Prognostic stratification of breast cancers remains a challenge to improve clinical decision making. We employ machine learning on breast cancer transcriptomics from multiple studies to link the expression of specific genes to histological grade and classify tumours into a more or less aggressive prognostic type.

Materials and methods

Microarray data of 5031 untreated breast tumours spanning 33 published datasets and corresponding clinical data were integrated. A machine learning model based on gradient boosted trees was trained on histological grade-1 and grade-3 samples. The resulting predictive model (Cancer Grade Model, CGM) was applied on samples of grade-2 and unknown-grade (3029) for prognostic risk classification.

Results

A 70-gene signature for ass

SUBMITTER: Amiri Souri E 

PROVIDER: S-EPMC8405688 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature