基于生物信息学分析骨肉瘤的关键基因和qRT-PCR实验验证

Analysis of key genes in osteosarcoma based on bioinformatics and qRT-PCR experimental verifi cation

目的利用生物信息学方法筛选出与骨肉瘤(osteosarcoma,OS)相关的关键基因,以作为OS的潜在诊断标志物和新治疗靶点。方法从基因表达综合(Gene Expression Omnibus,GEO)数据库中检索下载2个符合本研究的OS相关数据集(GSE16088和GSE42572),共包括21例OS组织样本和14例正常骨组织样本。对数据集进行矫正分析鉴定出差异表达基因(differentially expressed genes,DEGs)。通过加权基因共表达网络分析方法(weighted gene co-expression network analysis,WGCNA)与DEGs筛选出交集基因。对交集基因进行疾病本体论(Disease Ontology,DO)、基因本体论(Gene Ontology,GO)、京都基因与基因组百科全书分析(Kyoto Encyclopedia of Genes and Genomes,KEGG)和蛋白互作(protein-protein interaction,PPI)网络分析。采用受试者工作特征(receiver operating characteristic,ROC)曲线评估该PPI网络degree排名前10位的Hubbe基因的表达水平对OS患者的诊断效能,并以另一个OS数据集GSE19276对Hubbe基因进行验证筛选出关键基因。分析关键基因与浸润性免疫细胞的相关性。收集2020年9月1日至2022年6月30日于广西中医药大学第一附属医院住院手术的4例OS患者的OS组织及其癌旁组织,采用实时荧光定量聚合酶链式反应(real-time quantitative polymerase chain reaction,qRT-PCR)对关键基因进行实验验证。结果在OS组织与正常骨组织中共筛选出687个DEGs(上调基因523个和下调基因164个)。WGCNA关键模块基因2338个。DEGs与WGCNA关键模块基因共有交集基因545个。DO富集分析结果表明,DEGs与WGCNA结果的交集基因主要与泌尿系统癌症、肾癌、生殖细胞癌、肌肉骨骼系统癌症和胚胎癌等癌症相关。GO富集结果表明,交集基因主要参与骨化的形成、细胞外基质组织和生物矿物组织发育等生物学过程。KEGG通路富集在磷脂酰肌醇3激酶(phosphatidylinositide 3-kinase,PI3K)/蛋白激酶B(protein kinase B,PKB,又名Akt)信号通路、过氧化物酶体增殖物激活受体(peroxisome proliferators-activated receptor,PPAR)信号通路及流体剪切应力和动脉粥样硬化等信号通路上。PPI网络分析中degree排名前10位的Hubbe基因为磷脂酰肌醇4,5-二磷酸3-激酶催化亚基α(phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha,PIK3CA)、脯氨酰4-羟化酶亚单位α1(prolyl 4-hydroxylase subunit alpha 1,P4HA1)、整合素αⅤ(integrin alphaⅤ,ITGAⅤ)、组蛋白去乙酰化酶2(histone deacetylase 2,HDAC2)、连环蛋白β1(catenin beta 1,CTNNB1)、Ⅲ型胶原蛋白α1(collagen typeⅢalpha 1,COL3A1)、Ⅰ型胶原蛋白α2(collagen typeⅠalpha 2,COL1A2)、转导蛋白β样1X相关蛋白1(transducin beta-like 1X-related protein 1,TBL1XR1)、小核核糖核蛋白多肽G(small nuclear ribonucleoprotein polypeptide G,SNRPG)和Ras相关核蛋白(Ras-related nuclear protein,RAN)。以数据集GSE19276绘制ROC曲线验证Hubbe基因表明,P4HA1和ITGAV的准确度较高(均AUC>0.8且P<0.05)。qRT-PCR实验结果显示,P4HA1和ITGAV mRNA在OS组织中高表达(均P<0.01)。结论P4HA1和ITGAV是OS的潜在生物标志物和治疗靶点。

Objective To screen out key genes associated with osteosarcoma(OS)using bioinformatic methods and find poten-tial diagnostic markers and therapeutic targets for OS.Methods Two OS-related datasets(GSE16088 and GSE42572)were re-trieved and downloaded from the Gene Expression Omnibus(GEO)database,including 21 OS tissue samples and 14 normal bone tis-sue samples.The datasets were corrected to identify differentially expressed genes(DEGs),and the intersecting genes were screened out by the weighted gene co-expression network analysis(WGCNA)and DEGs.The intersecting genes were analyzed by Disease Ontology(DO),Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG),and protein-protein interaction(PPI)net-work.The receiver operating characteristic(ROC)curve was used to analyze the diagnostic performance of the expressions of the top 10 Hubbe genes of the PPI network for OS,and the OS dataset GSE19276 was used to validate the diagnotic efficacy of the Hub-be genes and screen out the key genes.Subsequently,the correlation of the key genes with infiltrating immune cells was analyzed.The OS tissues and paracancerous tissues of four OS patients surgically treated at the First Affiliated Hospital of Guangxi Universi-ty of Traditional Chinese Medicine from September 1st,2020,to June 30th,2022,were collected,and the expression of the key genes were verified by real-time quantitative polymerase chain reaction(qRT-PCR).Results A total of 687 DEGs including 523 upreg-ulated genes and 164 downregulated genes,2338 key module genes of WGCNA,and 545 intersecting genes of DEGs and WGCNA key module genes were screened out in the OS and normal bone tissue samples.The DO enrichment analysis showed that the intersecting genes were mainly related to cancers such as urinary system cancer,kidney cancer,germ cell cancer,musculoskeletal system cancer and embryonal cancer.The GO enrichment analysis showed that the intersecting genes were mainly involved in ossification,extracel-lular matrix organization and biomineral tissue development.The KEGG pathway was enriched in the phosphatidylinositide 3-kinase(PI3K)/protein kinase B(Akt)signaling pathway,peroxisome proliferators-activated receptor(PPAR)signaling pathway,and fluid shear stress and atherosclerosis.The Hubbe genes of the top 10 degree in the PPI network analysis were phosphatidylinositol-4,5-bisphos-phate 3-kinase catalytic subunit alpha(PIK3CA),prolyl 4-hydroxylase subunit alpha 1(P4HA1),integrin alphaⅤ(ITGAⅤ),histone deacetylase 2(HDAC2),catenin beta 1(CTNNB1),collagen typeⅢalpha 1(COL3A1),collagen typeⅠalpha 2(COL1A2),transducin beta-like 1X-related protein 1(TBL1XR1),small nuclear ribonucleoprotein polypeptide G(SNRPG),and Ras-related nuclear protein(RAN).The Hubbe genes were validated by plotting ROC curves with the GSE19276 dataset,and the results showed that P4HA1 and ITGAV were more accurate(both AUC>0.8 and P<0.05).The results of qRT-PCR experiments showed that the mRNA expressions of P4HA1 and ITGAV were higher in the OS tissues(both P<0.01).Conclusions P4HA1 and ITGAV may be potential biomarkers and therapeutic targets for OS.