Abstract Introduction: Microvascular invasion (MVI) is a well-known prognostic factor in predicting cancer relapse after curative resection of resectable hepatocellular carcinoma (HCC).Therefore, there is a clear unmet need for a precision strategy based on cancer-specific multi-omics features to predict the MVI feature at the initial diagnosis of HCC. Methods: Using gene expression profiling for resected human HCC (Discovery cohort, n=240), we identified the transcriptomic signature predicting the MVI feature. Comprehensive analyses were performed using the dataset from the cancer dependency map (DepMap) project, including cancer-specific molecular characterization with multi-omics data, and drug sensitivity with compound screening, and integrative in-silico prediction methods to uncover MVI. The transcriptomic signature predicting the MVI feature were validated in independent translational cohorts (TCGA-LIHC; n=373, KOREA; n=188, TOKYO; n=183, MODENA; n=78, ZHONGSHAN; n=159). Results: The MVI signature with 1028 genes was identified from robust statistical testing from the discovery cohort, and robust validation for the prediction performance of the MVI signature showed significant accuracy in the validation cohort (AUC=0.865, p<0.01). Multi-omics analysis revealed aggressive tumor biology associated with the MVI signature and specified biomarkers. Conclusions: Integrative multi-omics profiling for resectable HCC uncovers biomarkers to predict MVI. A novel combination of biomarkers performs in sorting out the tumor with aggressive tumor biology. A precision strategy to discover resectable tumors beneficial from surgical resection can be established from consecutive clinical trials based on this translational study. Citation Format: Incheon Kang, Woo Young Kwon, Sung Hwan Lee. Comprehensive multi-omics analysis for resectable hepatocellular carcinoma uncovers biomarkers to predict microvascular invasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7364.
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