肝细胞癌(HCC)起源于肝细胞,占肝癌的90%。该研究旨在基于TCGA和GSE14520队列确定用于预测HCC患者预后的新型预后生物标志物。
差异分析用于获得TCGA-LIHC-TPM群组的DEGs(差异表达基因)。以TCGA队列为训练组,以GSE14520队列为试验组,应用Lasso回归分析建立预后模型。接下来,基于预后模型,我们进行了以下分析:生存分析,独立预后分析,临床特征分析,突变分析,免疫细胞浸润分析,肿瘤微环境分析,和药物敏感性分析。最后,通过构建列线图预测HCC患者的生存时间。
通过套索回归分析,我们获得了10个基因的预后模型,包括BIRC5(含5个杆状病毒IAP重复序列),CDK4(细胞周期蛋白依赖性激酶4),DCK(脱氧胞苷激酶),HSPA4(热休克蛋白家族A成员4),HSP90AA1(热休克蛋白90α家族A类成员1),PSMD2(蛋白酶体26S亚基泛素受体,非ATP酶2),IL1RN(白细胞介素1受体拮抗剂),PGF(胎盘生长因子),SPP1(分泌磷蛋白1),和STC2(stiniocalcin2)。首先,我们发现风险评分是一个独立的预后因素,并且与HCC患者的临床特征有关,涵盖AFP(甲胎蛋白)和阶段。第二,我们观察到p53突变是高危和低危组中最明显的突变.第三,我们还发现风险评分与一些免疫细胞有关,覆盖B细胞,T细胞,树突状,巨噬细胞,中性粒细胞,等。第四,高危人群的TIDE评分较低,免疫检查点的表达更高,和更高的估计分数。最后,列线图包括临床特征和风险特征,显示特征在HCC患者生存预测中的临床实用性。
通过综合分析,我们构建了一个免疫相关的预后模型来预测HCC患者的生存率。除了预测肝癌患者的生存时间,该模型与肿瘤微环境显著相关。此外,我们得出结论,这十个免疫相关基因(BIRC5,CDK4,DCK,HSPA4,HSP90AA1,PSMD2,IL1RN,PGF,SPP1和STC2)可作为抗肿瘤免疫的新靶标。因此,本研究对探索免疫相关基因的临床应用具有重要意义。
Hepatocellular carcinoma (HCC) originates from the hepatocytes and accounts for 90% of liver cancer. The study intends to identify novel prognostic biomarkers for predicting the prognosis of HCC patients based on TCGA and GSE14520 cohorts.
Differential analysis was employed to obtain the DEGs (Differentially Expressed Genes) of the TCGA-LIHC-TPM cohort. The lasso regression analysis was applied to build the prognosis model through using the TCGA cohort as the training group and the GSE14520 cohort as the testing group. Next, based on the prognosis model, we performed the following analyses: the survival analysis, the independent prognosis analysis, the clinical feature analysis, the mutation analysis, the immune cell infiltration analysis, the tumor microenvironment analysis, and the drug sensitivity analysis. Finally, the survival time of HCC patients was predicted by constructing nomograms.
Through the lasso regression analysis, we obtained a prognosis model of ten genes including BIRC5 (baculoviral IAP repeat containing 5), CDK4 (cyclin-dependent kinase 4), DCK (deoxycytidine kinase), HSPA4 (heat shock protein family A member 4), HSP90AA1 (heat shock protein 90 α family class A member 1), PSMD2 (Proteasome 26S Subunit Ubiquitin Receptor, Non-ATPase 2), IL1RN (interleukin 1 receptor antagonist), PGF (placental growth factor), SPP1 (secreted phosphoprotein 1), and STC2 (stanniocalcin 2). First, we found that the risk score is an independent prognosis factor and is related to the clinical features of HCC patients, covering AFP (α-fetoprotein) and stage. Second, we observed that the p53 mutation was the most obvious mutation between the high-risk and low-risk groups. Third, we also discovered that the risk score is related to some immune cells, covering B cells, T cells, dendritic, macrophages, neutrophils, etc. Fourth, the high-risk group possesses a lower TIDE score, a higher expression of immune checkpoints, and higher ESTIMATE score. Finally, nomograms include the clinical features and risk signatures, displaying the clinical utility of the signature in the survival prediction of HCC patients.
Through the comprehensive analysis, we constructed an immune-related prognosis model to predict the survival of HCC patients. In addition to predicting the survival time of HCC patients, this model significantly correlates with the tumor microenvironment. Furthermore, we concluded that these ten immune-related genes (BIRC5, CDK4, DCK, HSPA4, HSP90AA1, PSMD2, IL1RN, PGF, SPP1, and STC2) serve as novel targets for antitumor immunity. Therefore, this study plays a significant role in exploring the clinical application of immune-related genes.