基于生物信息学方法挖掘调控肾透明细胞癌发生的分子生物标志物

Mining molecular biomarkers regulating the occurrence of kidney renal clear cell carcinoma based on bioinformatics methods

摘要

目的 采用生物信息学分析筛选与肾透明细胞癌（KIRC）发生密切相关的分子生物标志物，并验证其在临床样本中的表达水平。方法 从癌症基因组图谱（TCGA）数据库获取KIRCⅠ期mRNA测序数据，用主成分分析（PCA）降维处理，筛选差异表达基因（DEGs），并对DEGs进行GO和KEGG富集分析。采用加权基因共表达网络分析（WGCNA）筛选出与KIRC显著相关的基因，构建蛋白互作（PPI）网络筛选枢纽基因。通过受试者工作特征（ROC）曲线评估枢纽基因的诊断价值，使用生存曲线图分析其预后价值，并分析枢纽基因的mRNA表达量与KIRC病理分期的相关性。纳入来自新疆维吾尔自治区人民医院的20例KIRCⅠ期患者的临床样本，采用逆转录实时定量聚合酶链式反应（RT-qPCR）、蛋白免疫印迹法、酶联免疫吸附试验（ELISA）法检测该枢纽基因在患者肾癌及癌旁组织中的表达水平。结果 共筛选出8223个DEGs，其中上调基因4092个、下调基因4131个。GO分析显示DEGs与生物粘附、质膜组成部分和转运蛋白活性等相关，KEGG分析显示DEGs与细胞粘附分子、细胞因子-细胞因子受体相互作用、病毒蛋白与细胞因子和细胞因子受体的相互作用等途径相关。WGCNA分析获得了171个与KIRCⅠ期显著相关的基因，PPI网络筛选出的枢纽基因淋巴细胞胞质蛋白2（LCP2）与KIRCⅠ期的相关性显著，ROC曲线下面积为0.96，且LCP2的表达水平与患者的总体生存率呈负相关，与患者的分期、淋巴结转移有关。临床样本验证显示，KIRCⅠ期组织中LCP2的mRNA和蛋白的相对表达水平均显著高于癌旁正常组织（P<0.000 1）。结论 LCP2在KIRCⅠ期组织中显著上调，可作为KIRC早期诊断与治疗的潜在分子生物标志物。

Abstract

Objective To identify biomolecular markers closely related to the occurrence of kidney renal clear cell carcinoma (KIRC) and verify their expression levels in clinical samples. Methods Stage Ⅰ KIRC mRNA sequencing data were obtained from The Cancer Genome Atlas (TCGA). Principal component analysis (PCA) was used for dimensionality reduction to screen differentially expressed genes (DEGs), which then underwent GO and KEGG analyses. Weighted gene co-expression network analysis (WGCNA) was used to screen genes significantly related to KIRC, and a protein-protein interaction (PPI) network was constructed to screen hub genes. The diagnostic value of hub genes was evaluated with receiver operating characteristic (ROC) curve, and their prognostic value was analyzed using survival curve plots. The correlation between the mRNA expressions of hub genes and the pathological stages of KIRC was analyzed. Clinical samples of 20 patients with stage Ⅰ KIRC treated in our hospital were included, and the expressions of the hub genes in cancerous and adjacent tissues were detected with reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR), Western blotting, and enzyme-linked immunosorbent assay (ELISA). Results A total of 8223 DEGs were screened out, including 4092 up-regulated ones and 4131 down-regulated ones. GO analysis showed that DEGs were related to bioadhesion, plasma membrane composition, and transporter activity. KEGG analysis showed that DEGs were related to pathways such as cell adhesion molecules, cytokine-cytokine receptor interactions, and interactions between viral proteins and cytokines and cytokine receptors. WGCNA analysis obtained 171 genes that were significantly related to stage Ⅰ KIRC. The hub gene, lymphocyte cytosolic protein 2 (LCP2), screened out by the PPI network, was significantly related to stage Ⅰ KIRC. The area under the ROC curve was 0.96. The expression level was negatively correlated with the overall survival rate of patients. The expression of LCP2 was related to the stage and lymph node metastasis. Clinical verification showed that the mRNA and protein relative expressions of LCP2 in KIRC tissues were significantly higher than those in adjacent tissues (P<0.000 1). Conclusion LCP2 is significantly up-regulated in stage Ⅰ KIRC tissues and can be used as a potential biomarker for the early diagnosis and treatment of KIRC.

关键词

分子生物学 / 生物信息学 / 表观遗传学 / 差异表达基因 / 肾透明细胞癌 / 加权基因共表达网络分析 / 淋巴细胞胞质蛋白2

Key words

molecular biology / bioinformatics / epigenetics / differentially expressed genes / kidney renal clear cell carcinoma / weighted gene co-expression network analysis / lymphocyte cytosolic protein 2

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基金资助

新疆维吾尔自治区自然科学基金面上项目(2021D01C189)