AI-powered immune profiling from histopathology slides for chemo-radiotherapy outcome prediction in rectal cancer: a study using clinical trial and real-world cohorts
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Published on: February 7, 2021
Zhuoyan Shen1, Douglas Brand2, Mikaël Simard1
1Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
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:
In ARISTOTLE-RC, TIL+ patients had significantly improved DFS (HR = 0.59, 95% CI: 0.39-0.90, p = 0.013) and OS (HR = 0.42, 95% CI: 0.24-0.73, p < 0.005), while TAM+ was associated with shorter DFS (HR = 1.65, 95% CI: 1.00-2.72, p = 0.045). Similar patterns were observed in UCLH-RC and TCGA-CRC. TIL+/KRAS- patients had significantly improved DFS (HR = 0.41, 95% CI: 0.22-0.75, p < 0.005) and OS (HR = 0.28, 95% CI: 0.13-0.62, p < 0.005). In TP53-mutated patients, TAM+ group showed shorter DFS (HR = 1.46, 95% CI: 1.07-2.01, p = 0.0151), while among TP53-wild-type patients, no difference in DFS (HR = 1.00, 95% CI: 0.66-1.52, p = 0.9930) was observed between the two subgroups. Patients who transitioned after nCRT from TIL- to TIL+ 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).
