Abstract 3317: IFITM3: A predictive biomarker for therapeutic outcomes in advanced hepatocellular carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) is a major global health challenge, with China bearing a significant burden due to its high incidence and mortality rates. Vascular invasion (VI), particularly microvascular invasion (MVI), is a critical prognostic factor in HCC , profoundly influencing treatment decisions. Despite its clinical importance, reliable and non-invasive biomarkers for stratified prediction and therapeutic response remain scarce. Extracellular vesicles (EVs) are emerging as promising tools in cancer progression and therapy assessment. Methods: Sixty-five patients with China Liver Cancer (CNLC) stage III HCC treated with hepatic artery infusion chemotherapy (HAIC) plus sintilimab and a bevacizumab biosimilar (IBI305) were stratified based on RECIST criteria and surgical status for survival analysis and Kaplan-Meier (KM) curve construction. Univariate and multivariate regression analyses were employed to identify independent predictors of surgical eligibility. Cellular and molecular investigations followed to uncover potential biomarkers. scRNA-seq data (GEO: GSE242889), bulk RNA-seq data (GEO: GSE19977, TCGA), and hdWGCNA analysis were utilized to identify hub genes linked to MVI. TCGA data were divided into training and validation sets at a 7:3 ratio. Machine learning algorithms (LASSO regression, SVM-RFE, random forest) identified high-risk MVI genes. A prognostic nomogram model was constructed and significant predictors were explored with its performance assessed via ROC curves. Immunohistochemical staining and exosomal IFITM3 analysis were applied to evaluate gene expression across treatment stages. Results: Data from 65 patients (April 2021 to July 2023) with a median age of 57 years, predominantly male (83.1%), were analyzed. Patients who underwent surgery (30.8%) or achieved partial response (PR) per RECIST (38.5%) demonstrated significantly improved overall survival. Multivariate regression indicated that patients with VI, distant metastasis, ascites, and Child-Pugh grade B as factors reducing surgical eligibility, with VI as an independent predictor. Six MVI high-risk genes (VTN, DYNC1I2, HABP2, IFT43, IFITM3, NDUFS4) were identified, among which IFITM3 emerged as a key prognostic marker. High IFITM3 expression was associated with shorter survival (P < 0.001). The nomogram model showed strong predictive accuracy for survival (AUC1=0.641, AUC2=0.613, AUC2.5=0.579). Immunohistochemical analysis and exosomal analysis further validated IFITM3's role in influencing therapeutic outcomes. Conclusions: In summary, IFITM3 levels are closely linked to therapeutic outcomes in HCC patients. Non-invasive blood-based detection of IFITM3 holds promise for enhancing therapeutic stratification. Further research may refine prediction models and deepen understanding of IFITM3's role in poor therapeutic outcomes in cancer. Citation Format: Yinchao Zhang, Linze Xu, Jin Zhang, Dandan Wu, Huikai Li, Yueguo Li, Yang Liu. IFITM3: A predictive biomarker for therapeutic outcomes in advanced hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3317.