Prognostic value of tumor-infiltrating lymphocytes (TILs) in Luminal breast cancer: A novel computational method for assessing TILs abundance and spatial distribution patterns.

The prognostic significance of tumor-infiltrating lymphocytes (TILs) in Luminal-type breast cancer remains controversial, primarily due to typically low TIL infiltration levels, methodological inconsistencies in assessment, and insufficient consideration of spatial distribution patterns. To overcome these limitations, we developed an advanced artificial intelligence (AI)-driven computational TIL assessment (CTA) system, compliant with international visual assessment guidelines, which enables precise quantification of both TIL abundance (automatic TILs, aTILs) and spatial distribution patterns (aggregated: aTILs-agg; distributed: aTILs-dis) in Luminal-type breast cancer. Our comprehensive analysis suggests that elevated TIL levels were significantly associated with improved overall survival (OS) and progression-free survival (PFS) outcomes. Notably, Luminal B subtype demonstrated significantly higher TIL infiltration compared to Luminal A. In the Luminal A cohort, the aggregated spatial pattern (aTILs-agg) emerged as a favorable prognostic indicator for both OS and PFS, while in Luminal B cases, overall TIL abundance (aTILs) and distributed patterns (aTILs-dis) were associated with enhanced survival outcomes. Multivariate Cox regression analysis confirmed the independent prognostic value of aTILs, aTILs-agg, and aTILs-dis for PFS in Luminal A patients, though no significant associations were observed in the Luminal B subgroup. This study demonstrates the clinical utility of AI-powered TIL assessment as a promising prognostic indicator for predicting clinical outcomes in Luminal breast cancer patients, offering new insights into tumor-immune interactions within this molecular subtype.