Hepatic CD4 T Cells Predict Hepatocellular Carcinoma Risk on Metabolic Dysfunction‐Associated Steatohepatitis Patients
; Fernandez, Marina Laura ; Calafat, Patricia ; Kurpis, María ; Nuñez, Nicolás ; Prieto, Jhon ; Saborowski, Anna ; Vogel, Arndt ; Debes, José Daniel ; Balderramo, Domingo Cesar ; Boonstra, Andre ; Romagnoli, Pablo Alberto 
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Fecha
12/2025
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Wiley
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United European Gastroenterology Journal
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2050-6406
eISSN
2050-6414
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Background & Aims: Metabolic dysfunction‐associated steatohepatitis (MASH) increasingly drives hepatocellular carcinoma(HCC) development. We characterized inflammatory infiltrates in liver biopsies from MASH patients who developed HCCversus controls to identify predictive immune signatures.Method: Formalin‐fixed paraffin‐embedded (FFPE) liver biopsies from MASH patients were categorized as pre‐HCC MASH(n = 10) or control MASH (n = 13) by the ESCALON consortium. Standardized histological analysis and multiplexed immunohistochemistrywere performed targeting CD4, CD8, PD1, PDL1, FoxP3, CXCR6, CD3, CD68, and CD20 using a PhenoImagerFusion scanner. Single‐cell RNA‐seq datasets characterized hepatic CD4 T cell heterogeneity. Clinical parameters measuredincluded ALT, AST, GGT, alkaline phosphatase, platelets, and INR.Results: Pre‐HCC MASH showed inflammation extending from portal to periportal areas versus portal‐only distribution incontrols. Analysis of 291,908 cells revealed significantly higher CD4þ density (p = 0.0243) and CD4þPD1þ cells (p = 0.017) inpre‐HCC patients, while CD8þ and regulatory T cell densities remained unchanged. Single‐cell RNA‐seq identified potentialphenotypic shifts from Th1 cytotoxicity toward tissue‐repair and Th17 CD4þ T cells in MASH livers. Combined immunologicaland clinical variables (sex, age, CD4þ T cell numbers, ALT, alkaline phosphatase and platelets) achieved excellent predictiveperformance (ROC‐AUC = 0.944) for HCC development.Conclusions: Increase in liver CD4þ T cell infiltration characterizes MASH‐to‐HCC progression. These immune signaturescombined with clinical parameters demonstrate remarkable predictive value for identifying high‐risk MASH patients.
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