Machine learning-based detoxification enzymes-related genes prognosis model in breast cancer: immune landscape and clinical significance.

ABSTRACT:

Background

Breast cancer is one of the most common malignant tumors, threatening women's health and life globally. Despite significant treatment advances, its prognosis still faces great challenges. With the rapid development of molecular biology and genomics, the role of detoxification enzymes in breast cancer occurrence, development, and prognosis has gained increasing attention. This paper aims to establish a prognostic model based on detoxification enzymes-related genes to predict breast cancer patient survival.

Methods

Unsupervised clustering was used to analyze breast cancer samples based on detoxification enzymes-related genes expression. Lasso cox regression analysis and univariate and multivariate Cox analysis were used to process the data, and machine learning algo

SUBMITTER: Zhang J 

PROVIDER: S-EPMC12185839 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature