AI-powered immune profiling from histopathology slides for chemo-radiotherapy outcome prediction in rectal cancer: a study using clinical trial and real-world cohorts

Abstract

BACKGROUND: The impact of the tumour-immune microenvironment on locally advanced rectal cancer (LARC) outcomes remains unclear. This study quantitatively assesses the synergistic influence of tumour-infiltrating lymphocytes (TILs), tumour-associated macrophages (TAMs), mitotic activity, and DNA mutations in predicting outcomes for LARC patients undergoing neoadjuvant chemo-radiotherapy (nCRT). METHODS: Three cohorts (ARISTOTLE-RC, UCLH-RC, TCGA-CRC) were stratified by densities of AI-quantified TILs, TAMs, and mitotic figures with cut-offs identified on a hold-out subset and integrated with DNA mutations to assess correlations with disease-free survival (DFS) and overall survival (OS). Immune cell dynamics pre- and post-CRT were also evaluated. FINDINGS: had improved DFS (HR = 0.70, 95% CI: 0.50-0.97, p = 0.028) and exhibited a significantly higher pre-treatment mitotic index (mean difference = 9.36, 95% CI: 1.87-16.85, p = 0.0385). INTERPRETATION: These findings suggest the potential utility of AI-driven immune profiling for clinical decision-making in LARC patients undergoing nCRT. FUNDING: Cancer Research UK (RRNPSF-Jan21/100001, A18745, C7893/A2899), UK Research and Innovation (MR/T040785/1).

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