Artificial intelligence (AI) based spatial assessment of tumor-infiltrating lymphocytes (TIL) and pathologic complete response in early HER2+ breast cancer (BC): Secondary analysis of NSABP B-41.

551 Background: Manual quantitative assessment of stromal TILs has shown promise as a biomarker in HER2+ BC. We present an AI-powered single-cell TIL assessment. Methods: Manual TIL assessment was completed per guidelines. Zero-shot, AI-powered pipeline (Case45) was used to analyze tumor microenvironment (TME) from H&E slides, focusing on TILs and their spatial interplay with cancer cells. The algorithm identified all cells, deriving three metrics: pct_lymphocyte (lymphocytes/total cells), AI_TIL (adjacent-tumor lymphocyte to stromal cell ratio), hotspot_immune (normalized fraction of immune cell aggregates in relation to cancer/tissue). Spearman correlation coefficients evaluated correlations; logistic regression models assessed the relationship between TIL measurements and pCR, with and without gene expression adjustments. AUC assessed predictive performance, and univariate Cox models examined TILs' association with event-free survival (EFS). Results: Our analyses included tumors of 262 patients with early-stage HER2+ BC, 67% estrogen receptor (ER) positive, 51% positive lymph nodes. Poor histologic grade (p<0.001), non-luminal (p=0.006), and ER- tumors (p=0.003) were associated with higher manual TILs. Manual TILs were moderately associated with pct_lymphocyte (r= 0.34) and AI_TIL (r= 0.43). Perthe table, manual TILs were positively associated with pCR, the association was numerically stronger in ER- tumors (Interaction p=0.38). pct_lymphocyte and AI_TIL were positively associated with pCR, regardless of ER status. hotspot_immune was strongly associated with pCR (OR=1.26 for all, 1.29 in ER-, 1.22 in ER+, p=<0.001). TILs and ESR1 and ERBB2 provided complementary prognostic utility in pCR in trastuzumab-treated patients (AUC: 0.699-0.757). Among all subjects, there was no association between manual TILs and EFS (p=0.2); there was a marginal association between AI_TIL and EFS (p=0.06). Conclusions: The spatial characterization of TILs using an AI-powered tool shows promise as a prognostic biomarker in both HER2+/ER+ and HER2+/ER- BC, manual TIL assessment is prognostic in HER2+/ER- BC. The assessment of immune aggregates appears to be highly predictive of pCR. Further validation through prospective-retrospective studies, focused on the spatial immune heterogeneity in the TME, is required before integrating these biomarkers into routine clinical practice. Clinical trial information: NCT00486668 . TILs measurements and pCR. Variable (continuous) Cohort OR (95% CI) p-value Manual TILs %(10-unit inc.) All 1.13 (1.04, 1.23) 0.004 ER- 1.16 (1.02, 1.31) 0.02 ER+ 1.07 (0.95, 1.21) 0.27 Percentage of Lymphocyte (10-unit inc.) All 2.00 (1.30, 3.07) 0.002 ER- 1.75 (0.95, 3.21) 0.07 ER+ 1.93 (1.02, 3.62) 0.04 AI TILs(one-tenth inc.) All 1.22 (1.06, 1.40) 0.005 ER- 1.19 (0.98, 1.44) 0.09 ER+ 1.19 (0.97, 1.46) 0.10

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Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.551
Primary Topic
Radiomics and Machine Learning in Medical Imaging
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article
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article

Artificial intelligence (AI) based spatial assessment of tumor-infiltrating lymphocytes (TIL) and pathologic complete response in early HER2+ breast cancer (BC): Secondary analysis of NSABP B-41.

Priya Rastogi, Roberto Salgado, Haixi Yan, Brent T. Harris et al.
Journal of Clinical Oncology
Radiomics and Machine Learning in Medical Imaging
article

Artificial intelligence (AI) based spatial assessment of tumor-infiltrating lymphocytes (TIL) and pathologic complete response in early HER2+ breast cancer (BC): Secondary analysis of NSABP B-41.

Priya Rastogi, Roberto Salgado, Haixi Yan, Brent T. Harris, Ilana Schlam, Gong Tang, Ingrid Hook, Tanner J. Freeman, Sai Maley, Norman Wolmark, Sandra M. Swain, Khalid AbdulJabbar
article en

Abstract

551 Background: Manual quantitative assessment of stromal TILs has shown promise as a biomarker in HER2+ BC. We present an AI-powered single-cell TIL assessment. Methods: Manual TIL assessment was completed per guidelines. Zero-shot, AI-powered pipeline (Case45) was used to analyze tumor microenvironment (TME) from H&E slides, focusing on TILs and their spatial interplay with cancer cells. The algorithm identified all cells, deriving three metrics: pct_lymphocyte (lymphocytes/total cells), AI_TIL (adjacent-tumor lymphocyte to stromal cell ratio), hotspot_immune (normalized fraction of immune cell aggregates in relation to cancer/tissue). Spearman correlation coefficients evaluated correlations; logistic regression models assessed the relationship between TIL measurements and pCR, with and without gene expression adjustments. AUC assessed predictive performance, and univariate Cox models examined TILs' association with event-free survival (EFS). Results: Our analyses included tumors of 262 patients with early-stage HER2+ BC, 67% estrogen receptor (ER) positive, 51% positive lymph nodes. Poor histologic grade (p<0.001), non-luminal (p=0.006), and ER- tumors (p=0.003) were associated with higher manual TILs. Manual TILs were moderately associated with pct_lymphocyte (r= 0.34) and AI_TIL (r= 0.43). Perthe table, manual TILs were positively associated with pCR, the association was numerically stronger in ER- tumors (Interaction p=0.38). pct_lymphocyte and AI_TIL were positively associated with pCR, regardless of ER status. hotspot_immune was strongly associated with pCR (OR=1.26 for all, 1.29 in ER-, 1.22 in ER+, p=<0.001). TILs and ESR1 and ERBB2 provided complementary prognostic utility in pCR in trastuzumab-treated patients (AUC: 0.699-0.757). Among all subjects, there was no association between manual TILs and EFS (p=0.2); there was a marginal association between AI_TIL and EFS (p=0.06). Conclusions: The spatial characterization of TILs using an AI-powered tool shows promise as a prognostic biomarker in both HER2+/ER+ and HER2+/ER- BC, manual TIL assessment is prognostic in HER2+/ER- BC. The assessment of immune aggregates appears to be highly predictive of pCR. Further validation through prospective-retrospective studies, focused on the spatial immune heterogeneity in the TME, is required before integrating these biomarkers into routine clinical practice. Clinical trial information: NCT00486668 . TILs measurements and pCR. Variable (continuous) Cohort OR (95% CI) p-value Manual TILs %(10-unit inc.) All 1.13 (1.04, 1.23) 0.004 ER- 1.16 (1.02, 1.31) 0.02 ER+ 1.07 (0.95, 1.21) 0.27 Percentage of Lymphocyte (10-unit inc.) All 2.00 (1.30, 3.07) 0.002 ER- 1.75 (0.95, 3.21) 0.07 ER+ 1.93 (1.02, 3.62) 0.04 AI TILs(one-tenth inc.) All 1.22 (1.06, 1.40) 0.005 ER- 1.19 (0.98, 1.44) 0.09 ER+ 1.19 (0.97, 1.46) 0.10

Journal of Clinical OncologyVol. 43(16_suppl)
University of Pittsburgh (US), Georgetown University (US), MedStar Georgetown University Hospital (US), GZA Ziekenhuizen Campus Sint-Augustinus (BE), Dana-Farber Cancer Institute (US), UPMC Hillman Cancer Center (US), NRG Oncology (US), NSABP Foundation (US)
Breast Cancer Research Foundation
Openalex Percentile: Top 82%
Radiomics and Machine Learning in Medical Imaging
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