Abstract：
Hepatocellular carcinoma (HCC) is a widespread primary liver cancer with a high fatality rate. Despite several genes with oncogenic effects in HCC have been identified, many remain undiscovered. In this study, we conducted a comprehensive computational analysis to explore the involvement of genes within the same families as known driver genes in HCC. Specifically, we expanded the concept beyond single-gene mutations to encompass gene families sharing homologous structures, integrating various omics data to comprehensively understand gene abnormalities in cancer. Our analysis identified 74 domains with an enriched mutation burden, 404 domain mutation hotspots, and 233 dysregulated driver genes. We observed that specific low-frequency somatic mutations may contribute to HCC occurrence, potentially overlooked by single-gene algorithms. Furthermore, we systematically analyzed how abnormalities in the ubiquitinated proteasome system (UPS) impact HCC, finding that abnormal genes in E3, E2, DUB families, and Degron genes often result in HCC by affecting the stability of oncogenic or tumor suppressor proteins. In conclusion, expanding the exploration of driver genes to include gene families with homologous structures emerges as a promising strategy for uncovering additional oncogenic alterations in HCC.
摘要：
肝细胞癌（HCC）是一种广泛存在的原发性肝癌，病死率高。尽管已经确定了一些在HCC中具有致癌作用的基因，许多仍未被发现。在这项研究中,我们进行了一项全面的计算分析,以探索与已知驱动基因在HCC中相同家族中的基因的参与。具体来说,我们将这个概念扩展到单基因突变之外，包括共享同源结构的基因家族，整合各种组学数据，以全面了解癌症中的基因异常。我们的分析确定了74个具有富集突变负担的结构域，404域突变热点，和233个失调的驱动基因。我们观察到，特定的低频体细胞突变可能有助于HCC的发生，可能被单基因算法忽视。此外，我们系统分析了泛素化蛋白酶体系统（UPS）异常如何影响HCC，发现E3，E2，DUB家族中的异常基因，和Degron基因通常通过影响致癌或肿瘤抑制蛋白的稳定性而导致HCC。总之,扩大对驱动基因的探索以包括具有同源结构的基因家族，是发现HCC中其他致癌改变的有希望的策略。
