Chen Guanqiao, Hong Xiaoshan, He Wanshan, Ou Lingling, Chen Bin, Zhong Weitao, Lin Yu, Luo Xiping
Guangzhou Medical University, Guangzhou, China.
Department of Gynecology, Guangdong Women and Children Medical Hospital, Guangzhou, China.
Front Genet. 2023 Mar 9;14:1092276. doi: 10.3389/fgene.2023.1092276. eCollection 2023.
Cervical cancer (CC) is the fourth most common malignant tumor in term of in incidence and mortality among women worldwide. The tricarboxylic acid (TCA) cycle is an important hub of energy metabolism, networking one-carbon metabolism, fatty acyl metabolism and glycolysis. It can be seen that the reprogramming of cell metabolism including TCA cycle plays an indispensable role in tumorigenesis and development. We aimed to identify genes related to the TCA cycle as prognostic markers in CC. Firstly, we performed the differential expressed analysis the gene expression profiles associated with TCA cycle obtained from The Cancer Genome Atlas (TCGA) database. Differential gene list was generated and cluster analysis was performed using genes with detected fold changes >1.5. Based on the subclusters of CC, we analysed the relationship between different clusters and clinical information. Next, Cox univariate and multivariate regression analysis were used to screen genes with prognostic characteristics, and risk scores were calculated according to the genes with prognostic characteristics. Additionally, we analyzed the correlation between the predictive signature and the treatment response of CC patients. Finally, we detected the expression of ench prognostic gene in clinical CC samples by quantitative polymerase chain reaction (RT-qPCR). We constructed a prognostic model consist of seven TCA cycle associated gene (ACSL1, ALDOA, FOXK2, GPI, MDH1B, MDH2, and MTHFD1). Patients with CC were separated into two groups according to median risk score, and high-risk group had a worse prognosis compared to the low-risk group. High risk group had lower level of sensitivity to the conventional chemotherapy drugs including cisplatin, paclitaxel, sunitinib and docetaxel. The expression of ench prognostic signature in clinical CC samples was verified by qRT-PCR. There are several differentially expressed genes (DEGs) related to TCA cycle in CC. The risk score model based on these genes can effectively predict the prognosis of patients and provide tumor markers for predicting the prognosis of CC.
宫颈癌（CC）是全球女性中发病率和死亡率排名第四的常见恶性肿瘤。三羧酸（TCA）循环是能量代谢的重要枢纽，连接着一碳代谢、脂肪酰代谢和糖酵解。可以看出，包括TCA循环在内的细胞代谢重编程在肿瘤发生和发展中起着不可或缺的作用。我们旨在鉴定与TCA循环相关的基因作为CC的预后标志物。首先，我们对从癌症基因组图谱（TCGA）数据库获得的与TCA循环相关的基因表达谱进行差异表达分析。生成差异基因列表，并使用检测到的倍数变化>1.5的基因进行聚类分析。基于CC的亚群，我们分析了不同亚群与临床信息之间的关系。接下来，使用Cox单变量和多变量回归分析筛选具有预后特征的基因，并根据具有预后特征的基因计算风险评分。此外，我们分析了预测特征与CC患者治疗反应之间的相关性。最后，我们通过定量聚合酶链反应（RT-qPCR）检测临床CC样本中每个预后基因的表达。我们构建了一个由七个与TCA循环相关的基因（ACSL1、ALDOA、FOXK2、GPI、MDH1B、MDH2和MTHFD1）组成的预后模型。CC患者根据中位风险评分分为两组，高风险组的预后比低风险组更差。高风险组对包括顺铂、紫杉醇、舒尼替尼和多西他赛在内的传统化疗药物的敏感性较低。通过qRT-PCR验证了临床CC样本中每个预后特征的表达。CC中有几个与TCA循环相关的差异表达基因（DEG）。基于这些基因的风险评分模型可以有效预测患者的预后，并为预测CC的预后提供肿瘤标志物。
