What question did this study set out to answer?

To evaluate the association of AI-derived tumor-infiltrating lymphocyte metrics with treatment response and survival in early-stage triple-negative breast cancer.

May 29, 2026

AI-based assessment of tumor-infiltrating lymphocytes (TILs) in patients with triple-negative breast cancer (TNBC) receiving neoadjuvant chemotherapy versus chemo-immunotherapy.

Key Points

To evaluate the association of AI-derived tumor-infiltrating lymphocyte metrics with treatment response and survival in early-stage triple-negative breast cancer.
Analyzed H&E-stained slides for TILs using manual assessment and AI pipeline.
Evaluated pathologic complete response and event-free survival using regression models.
Included 105 patients from a multicenter TNBC registry who received neoadjuvant therapy.
61% of patients experienced a pathologic complete response, with AI TIL metrics linked to higher likelihood of pCR (RR 1.22, 95% CI 1.12-1.33, p<0.001).
Three-year event-free survival was 85.3% overall, with improved EFS associated with higher AI-TILs (q<0.10).
No significant interaction found between AI-derived metrics and treatment regimen.

Abstract

e12583 Background: Most patients with early-stage TNBC receive neoadjuvant chemotherapy and immunotherapy, yet biomarkers to guide treatment selection remain limited. Building on prior manual TIL analyses, we evaluated whether AI-derived TIL and immune spatial metrics are associated with response and survival, and whether these associations differ by treatment regimen. Methods: From the prospective DFCI Multicenter TNBC Registry, we identified patients with stage I–III TNBC who received neoadjuvant therapy. Pretreatment H chemo-immunotherapy, n=65, (62%) and included in this analysis. 12 patients (11%) presented with stage I, 44 (42%) stage II, and 49 (47%) stage III disease. 45 (43%) had lymph node involvement, 89 (85%) of patients received the KN522 regimen, and (15%) received a platinum and taxane-containing regimen. Overall, 61 (58%) patients experienced a pCR: 22 (55%) in the chemotherapy-only cohort and 39 (60%) with chemo-immunotherapy. Higher AI-derived TIL metrics were associated with increased likelihood of experiencing pCR, including AI TILs (RR per standard deviation (SD) 1.22, 95% CI 1.12-1.33, p<0.001, q<0.001), admixed immune infiltration (RR per SD 1.14, 95% CI 0.99-1.31, p=0.0625, q=0.120), immune hotspot (RR per SD 1.14, 95% CI 1.00-1.29, p=0.049, q=0.120), and immune habitat (RR per SD 1.15, 95% CI 0.99-1.33, p=0.0638, q=0.120). Associations were observed in the chemotherapy-only and chemo-immunotherapy cohorts combined, without evidence of a statistically significant interaction between AI-TIL metrics and neoadjuvant regimen. With a median follow-up of 2.6 years, the 3-year EFS was 85.3% in the overall cohort. Higher AI-TILs and immune habitat were associated with improved EFS (q<0.10), though event numbers were limited. Conclusions: These findings are consistent with prior manual TIL analyses and demonstrate that AI-TIL metrics are prognostic in early TNBC, though not predictive of benefit from adding pembrolizumab to neoadjuvant chemotherapy. Additional studies with longer follow-up are needed to validate these findings and further explore the potential role of AI-derived TIL metrics in early-stage TNBC.

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