Automating tumor-stroma ratio quantification in colon cancer patients from the UNITED study.

ABSTRACT:

Background

Colon cancer is a leading cause of cancer-related death worldwide, making accurate prognostic tools crucial. The tumor-stroma ratio (TSR) quantifies the proportion of stromal to tumor epithelial tissue and is a prognosticator in colon cancer. Stroma-high tumors are associated with worse outcomes and less benefit from adjuvant chemotherapy (ACT). Transitioning from visual to automated TSR scoring coincides with digital pathology advancements.

Materials and methods

In this study, we validated a fully automated artificial intelligence-based TSR quantification algorithm in hematoxylin-eosin-stained slides from the UNITED cohort, including 853 stage II and III colon cancer patients who had not received neoadjuvant therapy. The algorithm segmented 11 tissue classes on w

SUBMITTER: Heilijgers F 

PROVIDER: S-EPMC12804037 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature