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Identification of potential core genes in hepatoblastoma via bioinformatics analysis
medRxiv - Genetic and Genomic Medicine Pub Date : 2020-12-26 , DOI: 10.1101/2020.12.22.20248756
Basavaraj Vastrad , Chanabasayya Vastrad , Iranna Kotturshetti

Hepatoblastoma is the childhood liver cancer. Profound efforts have been made to illuminate the pathology, but the molecular mechanisms of hepatoblastoma are still not well understood. To identify the candidate genes in the carcinogenesis and progression of hepatoblastoma, microarray dataset GSE131329 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and pathway and Gene Ontology (GO) enrichment analysis were performed. The protein-protein interaction network (PPI), module analysis, target gene - miRNA regulatory network and target gene - TF regulatory network were constructed and analyzed. A total of 996 DEGs were identified, consisting of 499 up regulated genes and 497 down regulated genes. The pathway and Gene Ontology (GO) enrichment analysis of the DEGs include proline biosynthesis, superpathway of tryptophan utilization, chromosome organization and organic acid metabolic process. Twenty-four hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell cycle, chromosome organization, lipid metabolic process and oxidation-reduction process. Validation of hub genes showed that TP53, PLK1, AURKA, CDK1, ANLN, ESR1, FGB, ACAT1, GOT1 and ALAS1 may be involved in the carcinogenesis, invasion or recurrence of hepatoblastoma. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of hepatoblastoma, and provide candidate targets for diagnosis and treatment of hepatoblastoma.

中文翻译:

通过生物信息学分析鉴定肝母细胞瘤中潜在的核心基因

肝母细胞瘤是儿童肝癌。已经做出了深刻的努力来阐明病理学,但是肝母细胞瘤的分子机制仍然没有被很好地理解。为了鉴定肝母细胞瘤的致癌性和进展中的候选基因,从基因表达综合(GEO)数据库下载了微阵列数据集GSE131329。鉴定差异表达基因(DEG),并进行途径和基因本体论(GO)富集分析。构建并分析了蛋白质-蛋白质相互作用网络(PPI),模块分析,目标基因-miRNA调控网络和目标基因-TF调控网络。共鉴定出996个DEG,包括499个上调基因和497个下调基因。DEG的途径和基因本体论(GO)富集分析包括脯氨酸生物合成,色氨酸利用的超途径,染色体组织和有机酸代谢过程。鉴定出24个毂基因,生物学过程分析表明,这些基因主要富集于细胞周期,染色体组织,脂质代谢过程和氧化还原过程。集线器基因的验证表明TP53,PLK1,AURKA,CDK1,ANLN,ESR1,FGB,ACAT1,GOT1和ALAS1可能参与肝母细胞瘤的癌变,侵袭或复发。总之,在本研究中确定的DEG和枢纽基因有助于我们了解肝母细胞瘤致癌和进展的分子机制,并为肝母细胞瘤的诊断和治疗提供候选靶点。色氨酸利用,染色体组织和有机酸代谢过程的超途径。鉴定出24个毂基因,生物学过程分析表明,这些基因主要富集于细胞周期,染色体组织,脂质代谢过程和氧化还原过程。集线器基因的验证表明TP53,PLK1,AURKA,CDK1,ANLN,ESR1,FGB,ACAT1,GOT1和ALAS1可能参与肝母细胞瘤的癌变,侵袭或复发。总之,在本研究中确定的DEG和枢纽基因有助于我们了解肝母细胞瘤致癌和进展的分子机制,并为肝母细胞瘤的诊断和治疗提供候选靶点。色氨酸利用,染色体组织和有机酸代谢过程的超途径。鉴定出24个毂基因,生物学过程分析表明,这些基因主要富集于细胞周期,染色体组织,脂质代谢过程和氧化还原过程。集线器基因的验证表明TP53,PLK1,AURKA,CDK1,ANLN,ESR1,FGB,ACAT1,GOT1和ALAS1可能参与肝母细胞瘤的癌变,侵袭或复发。总之,在本研究中确定的DEG和枢纽基因有助于我们了解肝母细胞瘤致癌和进展的分子机制,并为肝母细胞瘤的诊断和治疗提供候选靶点。鉴定出24个毂基因,生物学过程分析表明,这些基因主要富集于细胞周期,染色体组织,脂质代谢过程和氧化还原过程。集线器基因的验证表明TP53,PLK1,AURKA,CDK1,ANLN,ESR1,FGB,ACAT1,GOT1和ALAS1可能参与肝母细胞瘤的癌变,侵袭或复发。总之,在本研究中确定的DEG和枢纽基因有助于我们了解肝母细胞瘤致癌和进展的分子机制,并为肝母细胞瘤的诊断和治疗提供候选靶点。鉴定出24个毂基因,生物学过程分析表明,这些基因主要富集于细胞周期,染色体组织,脂质代谢过程和氧化还原过程。集线器基因的验证表明TP53,PLK1,AURKA,CDK1,ANLN,ESR1,FGB,ACAT1,GOT1和ALAS1可能参与肝母细胞瘤的癌变,侵袭或复发。总之,在本研究中确定的DEG和枢纽基因有助于我们了解肝母细胞瘤致癌和进展的分子机制,并为肝母细胞瘤的诊断和治疗提供候选靶点。集线器基因的验证表明TP53,PLK1,AURKA,CDK1,ANLN,ESR1,FGB,ACAT1,GOT1和ALAS1可能参与肝母细胞瘤的癌变,侵袭或复发。总之,在本研究中确定的DEG和枢纽基因有助于我们了解肝母细胞瘤致癌和进展的分子机制,并为肝母细胞瘤的诊断和治疗提供候选靶点。集线器基因的验证表明TP53,PLK1,AURKA,CDK1,ANLN,ESR1,FGB,ACAT1,GOT1和ALAS1可能参与肝母细胞瘤的癌变,侵袭或复发。总之,在本研究中确定的DEG和枢纽基因有助于我们了解肝母细胞瘤致癌和进展的分子机制,并为肝母细胞瘤的诊断和治疗提供候选靶点。
更新日期:2020-12-26
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