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
551Background: 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 microenviron...
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Published in | Journal of clinical oncology Vol. 43; no. 16_suppl; p. 551 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
American Society of Clinical Oncology
01.06.2025
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Online Access | Get full text |
ISSN | 0732-183X 1527-7755 |
DOI | 10.1200/JCO.2025.43.16_suppl.551 |
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Summary: | 551Background: 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)CohortOR (95% CI)p-valueManual TILs %(10-unit inc.)All1.13 (1.04, 1.23)0.004ER-1.16 (1.02, 1.31)0.02ER+1.07 (0.95, 1.21)0.27Percentage of Lymphocyte (10-unit inc.)All2.00 (1.30, 3.07)0.002ER-1.75 (0.95, 3.21)0.07ER+1.93 (1.02, 3.62)0.04AI TILs(one-tenth inc.)All1.22 (1.06, 1.40)0.005ER-1.19 (0.98, 1.44)0.09ER+1.19 (0.97, 1.46)0.10 |
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Bibliography: | Abstract Disclosures |
ISSN: | 0732-183X 1527-7755 |
DOI: | 10.1200/JCO.2025.43.16_suppl.551 |