Integrative radiomics analyses identify universal signature for predicting prognosis and therapeutic vulnerabilities across primary and secondary liver cancers: A multi-cohort study

As the hallmark of cancer, genetic and phenotypic heterogeneity leads to biomarkers that are typically tailored to specific cancer type or subtype. This specificity introduces complexities in facilitating streamlined evaluations across diverse cancer types and optimizing therapeutic outcomes. In this study, we comprehensively characterized the radiological patterns underlying liver cancer (LC) by integrating radiomics profiles from computed tomography (CT) images of hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and colorectal cancer liver metastases (CRLM) through unsupervised clustering analysis. We identified three distinct radiomics clusters, displaying heterogeneity in prognosis. Subsequently, we formulated a shared prognosticator, the liver cancer radiomics signature (LCRS), by discovering and manifesting connectivity among radiomics phenotypes using GGI strategy. We validated that the LCRS is independent prognostic factor after adjusting for clinic-pathologic variables (all P