Artificial intelligence defines spatial patterns of tumor-infiltrating lymphocytes highly associated with outcome - a pan-GI cancer study.

ABSTRACT:

Background

Gastrointestinal (GI) cancers (including esophagus, stomach, colon, rectum, pancreas and liver) account for more than one-quarter of all cancer diagnoses and 35% of cancer-related fatalities worldwide. Quantification of tumor-infiltrating lymphocytes (TILs) is a known cancer prognostic marker. In this study, we used computer vision and machine learning [artificial intelligence (AI)] approaches to evaluate the prognostic significance of computational pathology features relating to spatial arrangement and diversity in the appearance of TILs and cancer nuclei across five different types of GI cancers: colon, stomach, pancreas, and rectum adenocarcinoma and liver hepatocellular carcinoma.

Patients and methods

The study comprises >1700 patients from four different site

SUBMITTER: Chen C 

PROVIDER: S-EPMC12514508 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature