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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, METHODS, RESULTS. Meshes: Adult, Aged, Carcinogenesis, Carcinoma, Hepatocellular, Cell Transformation, Neoplastic, Disease Progression, Female, Gene Expression Profiling, Humans, Liver Neoplasms, Male, Middle Aged, Mutation, Polymorphism, Single Nucleotide, RNA, Neoplasm, Tumor Microenvironment.
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Does sequential transcriptome analysis of human liver cancer indicate late stage acquisition of malignant traits? Context: Human hepatocarcinogenesis is as a multi-step process starting from dysplastic lesions to early carcinomas (eHCC) that ultimately progress to HCC (pHCC). However, the sequential molecular alterations driving malignant transformation of the pre-neoplastic lesions are not clearly defined. This lack of information represents a major challenge in the clinical management of patients at risk. We applied next-generation transcriptome sequencing to tumor-free surrounding liver (n = 7), low- (n = 4) and high-grade (n = 9) dysplastic lesions, eHCC (n = 5) and pHCC (n = 3) from 8 HCC patients with hepatitis B infection. Integrative analyses of genetic and transcriptomic changes were performed to characterize the genomic alterations during hepatocarcinogenesis. We report that changes in transcriptomes of early lesions including eHCC were modest and surprisingly homogenous. Extensive genetic alterations and subsequent activation of prognostic adverse signaling pathways occurred only late during hepatocarcinogenesis and were centered on TGFβ, WNT, NOTCH, and EMT-related genes highlighting the molecular diversity of pHCC. We further identify IGFALS as a key genetic determinant preferentially down-regulated in pHCC.
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Our results define new hallmarks in molecular stratification and therapy options for patients at risk for HCC, and merit larger prospective investigations to develop a modified clinical-decision making algorithm based on the individualized next-generation sequencing analyses. Final Decision: yes