肝细胞癌（HCC）是全球癌症相关死亡的第三大原因。为了降低 HCC 相关死亡率，早期诊断和治疗改进至关重要。 Hub差异表达基因（HubGs）可以作为潜在的诊断和预后生物标志物，也为精确治疗提供治疗靶点。因此，我们的目的是确定用于 HCC 诊断、预后和治疗的顶级 Hub 基因。通过系统文献综述，从 59 项研究中得出了 202 个 HCC 相关 HubG，但这些基因之间缺乏一致的检测。然后，我们通过综合生物信息学分析确定了排名靠前的 HubG（tHubG），突出显示它们的功能、通路和调节因子，这些可能更能代表 HCC 的诊断、预后和治疗。在本研究中，八个 HubG（CDK1、AURKA）通过蛋白质-蛋白质相互作用（PPI）网络和生存分析，将（CDC20、CCNB2、TOP2A、PLK1、BUB1B 和 BIRC5）确定为 tHubG。它们在 HCC 不同阶段的差异表达经癌症基因组图谱 (TCGA) 计划数据库验证，表明它们作为早期 HCC 标志物的潜力。富集分析揭示了 HCC 相关生物过程 (BP)、分子功能 (MF)、细胞成分 (CC) 和信号通路中的一些重要作用。此外，基因调控网络分析强调了在转录和转录后调节这些 tHubG 的关键转录因子 (TF) 和 microRNA (miRNA)。最后，我们选择了三种药物（CD437、avrainvillamide 和 LRRK2-IN-1）作为 HCC 治疗的候选药物，因为它们与我们提出的和已发表的所有蛋白质受体均表现出强结合。这项研究的结果可能为早期治疗提供宝贵的资源。 HCC 的诊断、预后和治疗。

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths globally. To reduce HCC-related mortality, early diagnosis and therapeutic improvement are essential. Hub differentially expressed genes (HubGs) may serve as potential diagnostic and prognostic biomarkers, also offering therapeutic targets for precise therapies. Therefore, we aimed to identify top-ranked hub genes for the diagnosis, prognosis, and therapy of HCC.Through a systematic literature review, 202 HCC-related HubGs were derived from 59 studies, yet consistent detection across these was lacking. Then, we identified top-ranked HubGs (tHubGs) by integrated bioinformatics analysis, highlighting their functions, pathways, and regulators that might be more representative of the diagnosis, prognosis, and therapies of HCC.In this study, eight HubGs (CDK1, AURKA, CDC20, CCNB2, TOP2A, PLK1, BUB1B, and BIRC5) were identified as the tHubGs through the protein-protein interaction (PPI) network and survival analysis. Their differential expression in different stages of HCC, validated using The Cancer Genome Atlas (TCGA) Program database, suggests their potential as early HCC markers. The enrichment analyses revealed some important roles in HCC-related biological processes (BPs), molecular functions (MFs), cellular components (CCs), and signaling pathways. Moreover, the gene regulatory network analysis highlighted key transcription factors (TFs) and microRNAs (miRNAs) that regulate these tHubGs at transcriptional and post-transcriptional. Finally, we selected three drugs (CD437, avrainvillamide, and LRRK2-IN-1) as candidate drugs for HCC treatment as they showed strong binding with all of our proposed and published protein receptors.The findings of this study may provide valuable resources for early diagnosis, prognosis, and therapies for HCC.