Li Bin, Zeng Tao, Chen Cui, Wu Yuankai, Huang Shuying, Deng Jing, Pang Jiahui, Cai Xiang, Lin Yuxi, Sun Yina, Chong Yutian, Li Xinhua, Gong Jiao, Tang Guofang
Department of Infectious Diseases, Key Laboratory of Liver Disease of Guangdong Province, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, China.
Department of Thyroid and Breast Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou, 510630, China.
Funct Integr Genomics. 2025 Jan 11;25(1):11. doi: 10.1007/s10142-024-01521-w.
Hepatocellular carcinoma (HCC) remains a malignant and life-threatening tumor with an extremely poor prognosis, posing a significant global health challenge. Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming. This study aimed to construct a model based on PPP-related Genes for risk assessment and prognosis prediction in HCC patients. We integrated RNA-seq and microarray data from TCGA, GEO, and ICGC databases, along with single-cell RNA sequencing (scRNA-seq) data obtained from HCC patients via GEO. Based on the "Seurat" R package, we identified distinct gene clusters related to the PPP within the scRNA-seq data. Using a penalized Cox regression model with least absolute shrinkage and selection operator (LASSO) penalties, we constructed a risk prognosis model. The validity of our risk prognosis model was further confirmed in external cohorts. Additionally, we developed a nomogram capable of accurately predicting overall survival in HCC patients. Furthermore, we explored the predictive potential of our risk model within the immune microenvironment and assessed its relevance to biological function, particularly in the context of immunotherapy. Subsequently, we performed in vitro functional validation of the key genes (ATAD2 and SPP1) in our model. A ten-gene signature associated with the PPP was formulated to enhance the prediction of HCC prognosis and anti-tumor treatment response. Following this, the ROC curve, nomogram, and calibration curve outcomes corroborated the model's robust clinical predictive capability. Functional enrichment analysis unveiled the engagement of the immune system and notable variances in the immune infiltration landscape across the high and low-risk groups. Additionally, tumor mutation frequencies were observed to be elevated in the high-risk group. Based on our analyses, the IC50 values of most identified anticancer agents demonstrated a correlation with the RiskScore. Additionally, the high-risk and low-risk groups exhibited differential sensitivity to various drugs. Cytological experiments revealed that silencing ATAD2 or SPP1 suppresses malignant phenotypes, including viability and migration, in liver cancer cells. In this study, a novel gene signature related to the PPP was developed, demonstrating favorable predictive performance. This signature holds significant guiding value for assessing the prognosis of HCC patients and directing individualized treatment strategies.
肝细胞癌(HCC)仍然是一种恶性且危及生命的肿瘤,预后极差,对全球健康构成重大挑战。尽管新型治疗药物不断涌现,但患者对抗肿瘤药物的反应和总体预后存在很大异质性。磷酸戊糖途径(PPP)在各种肿瘤细胞中高度激活,在肿瘤代谢重编程中起关键作用。本研究旨在构建一个基于PPP相关基因的模型,用于HCC患者的风险评估和预后预测。我们整合了来自TCGA、GEO和ICGC数据库的RNA测序和微阵列数据,以及通过GEO从HCC患者获得的单细胞RNA测序(scRNA-seq)数据。基于“Seurat”R包,我们在scRNA-seq数据中识别出与PPP相关的不同基因簇。使用带有最小绝对收缩和选择算子(LASSO)惩罚的惩罚Cox回归模型,我们构建了一个风险预后模型。我们的风险预后模型的有效性在外部队列中得到进一步证实。此外,我们开发了一种能够准确预测HCC患者总生存期的列线图。此外,我们探讨了我们的风险模型在免疫微环境中的预测潜力,并评估了其与生物学功能的相关性,特别是在免疫治疗背景下。随后,我们对模型中的关键基因(ATAD2和SPP1)进行了体外功能验证。制定了一个与PPP相关的十基因特征,以增强对HCC预后和抗肿瘤治疗反应的预测。在此之后,ROC曲线、列线图和校准曲线结果证实了该模型强大的临床预测能力。功能富集分析揭示了免疫系统的参与以及高风险和低风险组之间免疫浸润格局的显著差异。此外,观察到高风险组的肿瘤突变频率升高。基于我们的分析,大多数已鉴定的抗癌药物的IC50值与风险评分相关。此外,高风险组和低风险组对各种药物表现出不同的敏感性。细胞学实验表明,沉默ATAD2或SPP1可抑制肝癌细胞的恶性表型,包括活力和迁移。在本研究中,开发了一种与PPP相关的新型基因特征,显示出良好的预测性能。该特征对于评估HCC患者的预后和指导个体化治疗策略具有重要的指导价值。