Development of a Machine Learning-Based Prognostic Model for Hormone Receptor-Positive Breast Cancer Using Nine-Gene Expression Signature.

ABSTRACT:

Background

Determining the prognosis of hormone receptor positive (HR⁺) breast cancer (BC), which accounts for 80% of all BCs, is critical in improving survival outcomes. Stratifying individuals at high risk of BC-related mortality and improving prognosis has been the focus of research for over a decade. However, these tools are not universal as they are limited to clinical factors. We hypothesized that a new framework for predicting prognosis in HR⁺ BC patients can develop using artificial intelligence.

Methods

A total of 2,338 HR⁺ human epidermal growth factor receptor 2 negative (HER2^-) BC cases were analyzed from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), The Cancer Genome Atlas (TCGA), and Gene Ex

SUBMITTER: Takeshita T 

PROVIDER: S-EPMC10588506 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature