Bolin Song, Himanshu Maurya, Tianyi Xia, Naoto Tokuyama, Kamal Hammouda, Xiangxue Wang, Ibrahim Mohammad, Tilak Pathak, Xiuming Zhang, Viraj A Master, Mehmet Asim Bilen, Shilpa Gupta, Cheng Lu, Hexiang Wang, Anant Madabhushi
Automated TLS density and TSR individually showed good concordance with pathologist assessments (TLS: ICC=0.852; TSR: Spearman ρ=0.826; both p < 0.001). High TLS density and low TSR were each associated with improved progression-free survival (PFS) across cohorts. The TLS-TSR score outperformed either biomarker alone (C-index: 0.65-0.69) and remained an independent predictor of PFS in multivariable analysis. TLS density showed strong association with ICI response (AUC 0.745, 95% CI 0.607-0.864). Transcriptomic analysis further revealed enrichment of extracellular matrix organization and stromal-related pathways in the high-risk group, accompanied by selective alterations in immune cell composition, indicating coordinated remodeling of both stromal and immune components of TME.
BACKGROUND: Tumor microenvironment (TME) including stromal composition and antitumor immune responses, plays an important role in cancer progression. Tumor-stroma ratio (TSR) and tertiary lymphoid structures (TLS) both shows prognostic value, but their combined significance across urothelial carcinoma (UC) remains unclear.
METHODS: We retrospectively analyzed H&E-stained whole-slide images from 884 UC patients from five cohorts (FAHZU, n = 76; Emory, n = 94; TCGA, n = 291; QDPH, n = 330; TRRC, n = 93), encompassing both localized and advanced disease settings. TLS were identified using deep learning-based nuclei classification followed by identifying clusters of aggregated immune cells, while TSR was quantified using automated stromal segmentation. An integrated TLS-TSR risk score was trained using a Cox proportional hazards model in the FAHZU cohort and externally validated in four independent test cohorts. In the TRRC cohort, associations between these biomarkers and response to immune checkpoint inhibitor (ICI) were assessed.
FINDINGS: Automated TLS density and TSR individually showed good concordance with pathologist assessments (TLS: ICC=0.852; TSR: Spearman ρ=0.826; both p < 0.001). High TLS density and low TSR were each associated with improved progression-free survival (PFS) across cohorts. The TLS-TSR score outperformed either biomarker alone (C-index: 0.65-0.69) and remained an independent predictor of PFS in multivariable analysis. TLS density showed strong association with ICI response (AUC 0.745, 95% CI 0.607-0.864). Transcriptomic analysis further revealed enrichment of extracellular matrix organization and stromal-related pathways in the high-risk group, accompanied by selective alterations in immune cell composition, indicating coordinated remodeling of both stromal and immune components of TME.
INTERPRETATIONS: Integrating stromal composition and immune-related morphology may improve prognostic stratification across UC patients and identify histopathologic features associated with response to ICI.