Work

Deep learning-based quantification of tumor-infiltrating lymphocytes as a prognostic indicator in nasopharyngeal carcinoma: multicohort findings

Year: 2025

Type: article

Abstract: Background Nasopharyngeal carcinoma (NPC) features a tumor-immune microenvironment rich in tumor-infiltrating lymphocytes (TILs), important for prognosis but labor-intensive to quantify. This study evaluates a deep learning model to quantify TILs (TIL DL ) in hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) of NPC and explores the association of TIL DL percentage with patient outcomes and response to immune checkpoint blockade (ICB). Methods We retrospectively analyzed 435 nonmetastatic NPC patients from two centers, divided into a training cohort ( n = 220) and a validation cohort ( n = 215). An additional cohort of de novo metastatic NPC patients receiving ICB therapy ( n = 63) was included. The deep learning model calculated TIL DL percentages from H&E-stained WSIs. Correlations between TIL DL percentages and immunohistochemistry (IHC)-derived TIL densities were assessed. Survival analyses evaluated their prognostic significance. Results TIL DL percentages showed strong correlations with IHC-derived TIL densities (CD3+ T cells R = 0.46, CD8+ T cells R = 0.33, CD20+ B cells R = 0.57; all P < 0.001). Higher TIL DL percentages (median ≥45.7%) were associated with better 5-year disease-free survival (DFS) and overall survival (OS) in both training (DFS: 80.6% versus 62.5%, P = 0.016; OS: 84.4% versus 71.8%, P = 0.025) and validation cohorts (DFS: 87.3% versus 74.3%, P = 0.016; OS: 93.7% versus 82.6%, P = 0.010). In the ICB-treated metastatic cohort, higher TIL DL percentages predicted better 3-year progression-free survival (PFS: 40.5% versus 25.0%, P = 0.022). Multivariate analyses confirmed TIL DL percentage as an independent prognostic factor in both settings. Conclusions The TIL DL percentage derived from H&E-stained WSIs effectively stratifies risk in nonmetastatic NPC and may serve as a biomarker in metastatic NPC treated with ICB, aiding in patient selection for individualized treatment.

Source: ESMO Open

DOI: 10.1016/j.esmoop.2025.105494