Refinement of histologic subtypes and identification of biomarkers linked to unfavorable prognosis in cholangiocarcinoma: The ENSCCA registries' framework for digital twin advancement

胆管癌组织学亚型细化及与不良预后相关的生物标志物鉴定:ENSCCA注册库的数字孪生技术发展框架

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Abstract

BACKGROUND AND AIMS: Cholangiocarcinoma (CCA) displays remarkable anatomical and histological heterogeneity. Besides diagnosis confirmation, histology currently does not have a major role in the management of CCA. We aimed to study the clinical relevance of histological heterogeneity of CCA and putative tissue biomarkers by creating a multicentric digitalized European CCA Histology Registry. APPROACH AND RESULTS: Nine referral centers, participating in the International Cholangiocarcinoma Clinical Registry, shared samples and data from 293 patients. Histological and immunohistochemistry stains (n=10) were performed. Computed tomography (CT) scans (n=112 cases) were analyzed by morphological and radiomics techniques. A selection of cases (n=18) was processed for spatial transcriptomics analysis. No significant differences in 5-year overall survival (OS) were found in perihilar CCA versus intrahepatic (i) CCA, and in small bile duct (SBD) versus large bile duct (LBD) iCCA. When cases were classified by Periodic acid of Schiff (PAS) positivity (mucin content), PAS HIGH LBD iCCA showed a significantly worse 5-year OS compared to PAS LOW iCCA. Multivariate Cox regression identified PAS HIGH LBD iCCA phenotype as an independent predictor of worse OS. PAS HIGH LBD iCCA subtype showed specific molecular characteristics at spatial transcriptomics and immunohistochemistry; CT scans and serology could distinguish PAS HIGH LBD iCCA phenotype with excellent accuracy. CONCLUSIONS: Our data underline the importance of identifying morphological subclasses with a significant prevalence in CCA as a tool for risk stratification and prognosis. The European CCA Histology Registry represents a valuable platform for integrating digital pathology with clinical, radiological, and molecular information as a framework for digital twin advancement.

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