Background/Objectives: The molecular heterogeneity and metabolic flexibility of Hepatocellular Carcinoma (HCC) pose significant challenges to the efficacy of systemic therapy for advanced cases. Early screening difficulties often delay diagnosis, leading to more advanced stages at presentation. Combined with the inconsistent responses to current systemic therapies, HCC continues to have one of the highest mortality rates among cancers. Thus, this paper seeks to contribute to the development of systemic therapy options through the consideration of HCC’s metabolic vulnerabilities and lay the groundwork for future in vitro studies.Methods: Transcriptomic data were used to calculate single and double knockout options for HCC using genetic Minimal Cut Sets. Furthermore, using QSAR modeling, drug repositioning opportunities were assessed to inhibit the selected genes.Results: Two single knockout options that were also annotated as essential pairs were found within the pyrimidine metabolism pathway of HCC, wherein the knockout of either DHODH or TYMS is potentially disruptive to proliferation. The result of the flux balance analysis and gene knockout simulation indicated a significant decrease in biomass production. Three machine learning algorithms were assessed for their performance in predicting the pIC50 of a given compound for the selected genes. SVM-rbf performed the best on unseen data achieving an R2of 0.82 for DHODH and 0.81 for TYMS. For DHODH, the drugs Oteseconazole, Tipranavir, and Lusutrombopag were identified as potential inhibitors. For TYMS, the drugs Tadalafil, Dabigatran, Baloxavir Marboxil, and Candesartan Cilexetil showed promise as inhibitors.Conclusions: Overall, this study suggests in vitro testing of the identified drugs to assess their capabilities in inducing pyrimidine starvation on HCC.
背景/目的：肝细胞癌（HCC）的分子异质性和代谢灵活性对晚期病例的系统性治疗疗效构成重大挑战。早期筛查困难常导致诊断延迟，使患者就诊时已处于较晚期阶段。加之当前系统性治疗反应不一，HCC的死亡率在各类癌症中仍居高不下。因此，本文旨在通过探讨HCC的代谢脆弱性，为系统性治疗方案的发展作出贡献，并为未来的体外研究奠定基础。 方法：利用转录组数据，通过遗传最小割集计算HCC的单基因与双基因敲除方案。此外，采用QSAR建模评估药物重定位机会，以抑制所选基因。 结果：在HCC的嘧啶代谢通路中发现了两个单基因敲除方案，它们同时被注释为必需基因对，其中敲除DHODH或TYMS均可能显著抑制细胞增殖。通量平衡分析与基因敲除模拟结果显示，生物量产生显著下降。评估了三种机器学习算法在预测给定化合物对所选基因pIC50值方面的性能，SVM-rbf在未见数据上表现最佳，对DHODH和TYMS的R²分别达到0.82和0.81。针对DHODH，奥替康唑、替拉那韦和芦曲波帕被鉴定为潜在抑制剂；针对TYMS，他达拉非、达比加群、巴洛沙韦酯和坎地沙坦酯显示出作为抑制剂的潜力。 结论：总体而言，本研究建议对已鉴定的药物进行体外测试，以评估其在HCC中诱导嘧啶饥饿的能力。
肿瘤(癌症)患者之家