Glycosylation profiling of triple-negative breast cancer: clinical and immune correlations and identification of LMAN1L as a biomarker and therapeutic target.

ABSTRACT:

Introduction

Breast cancer (BC) is the most prevalent malignant tumor in women, with triple-negative breast cancer (TNBC) showing the poorest prognosis among all subtypes. Glycosylation is increasingly recognized as a critical biomarker in the tumor microenvironment, particularly in BC. However, the glycosylation-related genes associated with TNBC have not yet been defined. Additionally, their characteristics and relationship with prognosis have not been deeply investigated.

Methods

Transcriptomic analyses were used to identify a glycosylation-related signature (GRS) associated with TNBC prognosis. A machine learning-based prediction model was constructed and validated across multiple independent datasets. The model's predictive capability was extended to evaluate the progno

SUBMITTER: Yu Q 

PROVIDER: S-EPMC11759290 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature