Machine Learning-Based Enhanced MRI Radiomics for PDCD1 Prognostication and Expression Prediction in Breast Cancer.

ABSTRACT:

Background

Programmed cell death 1 (PDCD1) is an immune checkpoint inhibitor that plays an important role in immune evasion in breast cancer (BC). In this study, we aimed to evaluate the correlation between PDCD1 expression, immune cell tumor infiltration, and prognosis. In addition, we also developed a predictive model to determine PDCD1 expression levels in patients with BC based on radiomics features extracted from magnetic resonance imaging (MRI).

Methods

Clinical data of 1082 patients with BC extracted from The Cancer Genome Atlas (TCGA) and MRI data of 108 patients with BC extracted from The Cancer Imaging Archive (TCIA) were used to determine the correlation between PDCD1 expression levels and the prognosis, clinical stage, survival, and levels of

SUBMITTER: Gao Y 

PROVIDER: S-EPMC12663040 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature