■喉鳞状细胞癌(LSCC)是头颈部突出的癌症,这极大地影响了患者的生活质量。LSCC的发病机制尚不清楚。目前,LSCC治疗包括化疗,手术和放射治疗;然而,这些方法对复发和持续癌症患者的疗效较差.因此,这项研究确定了伴有LSCC的hub基因,这可能是未来潜在的治疗目标。
■我们从癌症基因组图谱(TCGA)和基因表达综合(GEO)数据库中提取了全转录组高通量测序(HTS)LSCC数据,并使用统计软件RStudio计算LSCC和正常样品之间的差异表达基因(DEGs)。通过加权基因共表达网络分析(WGCNA),基因和基因组(KEGG)途径和基因本体论(GO)功能的京都百科全书的富集检查,并检查蛋白质-蛋白质相互作用(PPI)网络,我们获得了网络hub基因,并验证了hub基因的预后价值和蛋白表达水平。
■通过对差异基因表达的分析,从GEO和TCGA数据库获得了2,139和2,774个DEG,分别,通过WGCNA从TCGA-LSCC和GSE127165数据集中筛选了13和15个模块,分别。WGCNA和DEG列表中最显著的正相关和负相关模块重叠,检索到总共36个共表达的重叠基因。通过对GO和KEGG的富集分析,发现基因功能高度集中在细胞连接组装中,基底膜,细胞外基质(ECM)结构成分等。,这些途径主要集中在ECM受体相互作用中,病灶粘连,小细胞肺癌,和弓形虫病.通过对PPI网络分析,10个网络集线器基因(SNAI2,ITGA6,LAMB3,LAMC2,CAV1,COL7A1,GJA1,EHF,OAT,和GPT)获得。最后,这些基因的生存分析和蛋白表达验证证实,低OAT表达和高CAV1表达显著影响LSCC患者的生存预后。
■我们认识到与LSCC几乎相关的hub基因和关键模块,这些基因通过生存分析和人类蛋白质图谱(HPA)数据库进行了验证,这对于揭示LSCC的发病机制和探索新的精确生物学标志物和潜在的治疗靶标非常重要。
UNASSIGNED: Laryngeal squamous cell carcinoma (LSCC) is the prominent cancer in head and neck, which greatly affects life quality of patients. The pathogenesis of LSCC is not clear. Presently, the LSCC treatments include chemotherapy, surgery and radiotherapy; however, these methods have poor efficacy in patients with recurrent and persistent cancer. Therefore, the study identified the hub genes accompanied with LSCC, which may be a potential therapeutic target in the future.
UNASSIGNED: We extracted whole transcriptome high-throughput sequencing (HTS) LSCC data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and calculate differentially expressed genes (DEGs) between LSCC and normal samples using statistical software RStudio. Through weighted gene co-expression network analysis (WGCNA), enrichment examination of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) functions, and examination of protein-protein interaction (PPI) network, we obtained network hub genes and validated the hub genes prognostic value and expression levels of protein.
UNASSIGNED: Through analysis of differential gene expression, from the GEO and TCGA databases 2,139 and 2,774 DEGs were obtained, respectively, 13 and 15 modules were screened from TCGA-LSCC and GSE127165 datasets by WGCNA, respectively. The most significant positive and negative correlation modules in the WGCNA and DEG lists were overlapped, and overall 36 co-expressed overlapping genes were retrieved. Through enrichment analysis of GO and KEGG, it was found that the gene functions were highly concentrated in cell junction assembly, basement membrane, extracellular matrix (ECM) structural constituent etc., and the pathways were mainly concentrated in ECM receptor interaction, focal adhesion, small cell lung cancer, and toxoplasmosis. Through analysis of PPI network analysis, 10 network hub genes (SNAI2, ITGA6, LAMB3, LAMC2, CAV1, COL7A1, GJA1, EHF, OAT, and GPT) were obtained. Finally, survival analysis and protein expression validation of these genes confirmed that low OAT expression and high CAV1 expression remarkably influenced the survival of patient\'s prognosis with LSCC.
UNASSIGNED: We recognized the hub genes and key modules nearly associated to LSCC and these genes were validated by survival analysis and the database of Human Protein Atlas (HPA), which is of high importance for unveiling the pathogenesis of LSCC and probing for new precise biological marker and potential therapeutic targets.