Focal hotspot and diffuse immune subtypes of tumor-infiltrating lymphocytes: AI-powered spatial clustering classification and its clinical relevance to HER2 expression in triple-negative breast cancer.

ABSTRACT:

Purpose

This study aimed to define spatial immune subtypes of tumor-infiltrating lymphocytes (TILs) using artificial intelligence (AI)-powered analysis and investigate their association with distinct human epidermal growth factor receptor-2 (HER2) expression levels, response to neoadjuvant chemotherapy (NAC), and patient survival outcomes in triple-negative breast cancer (TNBC).

Methods

We conducted a multicenter study involving TNBC patients receiving NAC, stratified into HER2-0, HER2-ultralow, and HER2-low subgroups. An AI-based cell classifier was employed to identify TILs (AI-TILs) and extract spatial coordinates from pathology images. Using unsupervised learning of spatial clustering analysis to identify immune subtypes. The performance of the AI model was benchmarked a

SUBMITTER: Xie T 

PROVIDER: S-EPMC12836918 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature