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Screening of Hepatocellular Carcinoma Hub Genes Based on WGCNA and Its Function Prediction AnalysisObjective: Weighted gene co-Expression network analysis(WGCNA)was used to study the relationship between gene expression data and clinicopathological features of patients with hepatocellular carcinoma.The non-scale network of Hepatocellular carcinoma(HCC)gene was constructed to find the HCC Hub genes and its involved biological functions.Methods: The RNA second-generation sequencing data and corresponding clinical characteristics of hepatocellular carcinoma patients were downloaded from the TCGA database website,and the second-generation sequencing data of hepatocellular carcinoma RNA and corresponding clinical characteristics of the LIRI-JR project were downloaded from the ICGC database.Two R packages,limma and edgeR,were used to screen for differential genes common between cancerous and normal tissue samples in the two database cohorts.Then,the WGCNA function package was used to construct the scale-free co-expression network and gene module for each database,and the module with the highest correlation and the corresponding clinical features were searched in the module-feature relationship diagram.The hub gene of the target module is screened based on Gene significance and Module membership.Finally,the KEGG and GO pathway enrichment analysis of the common pivot genes in the two databases was carried out to explore their biological functions.Results:Analysis of mRNA sequencing data of TCGA database 50 for hepatocellular carcinoma and adjacent tissues,374 cases of hepatocellular carcinoma and 50 adjacent tissues and 240 cases of hepatocellular carcinoma and 197 normal tissues of the ICRI database LIRI-JR project.A total of 1672 differential genes were identified,and the common differential genes were used as target genes for WGCNA analysis.The WGCNA analysis finally obtained a researchmodule(turquoise module)and screened 40 common hub genes.GO and KEGG enrichment analysis suggested that these hub genes may be involved in cell cycle,cell senescence,mitosis,chromosome concentration and isolation,spindle microtubules,tubulin binding,DNA replication,protein serine,p53 signaling pathway,FoxO signaling pathway,The Fanconi anemia pathway is related to pathways.Conclusion: Our study shows that the gene modules found by weighted co-expression network analysis are biologically significant,and that the core genes can also be used to verify the clinical significance of the module by combining clinical pathological feature information analysis.It can be used as a methodological tool to explore the molecular mechanism of HCC,laying a foundation for the study of genetic biomarkers of hepatocellular carcinoma.Part? Construction of Cox Proportional Hazard Regression Model Based on Hub GenesObjective: Cox regression analysis and Lasso regression analysis were used to construct a cox proportional hazard regression model based on the pivotal gene obtained in the first part,and to explore the predictive value of the model for survival prognosis of patients with HCC.Methods: This study used the TCGA database hepatocellular carcinoma cohort to remove273 patient data and corresponding clinicopathological features from outlier samples as a exploration cohort.The hepatocellular carcinoma cohort of the ICRI database LIRI-JR project removed 220 patient data and corresponding clinicopathological features of the outlier samples as a validation cohort.In the exploration cohort,Univariate Cox regression analysis and Lasso regression analysis and multivariate Cox proportional hazard regression method were used to screen the most valuable hub genes for prognosis of hepatocellular carcinoma patients and establish a risk prediction model.The validation cohort was then used to validate the value and stability of the risk prediction model in predicting survival prognosis in patients with hepatocellular carcinoma.Results: Through the single factor Cox analysis and Lasso regression analysis,the 16 hub genes finally selected in the training set entered the multivariate Cox proportional hazard regression analysis,and 8 potential significant OS-related genes were screened by multi-factor Cox proportional hazard regression.We established a linear prognostic model for eight genes(CDC45,CENPA,MCM10,MELK,CDC20,ASF1 B,FANCD2,NCAPH):-0.999*ASF1B expression level +0.561*CDC45expression level+0.567*CENPA expression level-0.886*FANCD2 expression level+0.486*MCM10 expression level+0.448*MELK expression level-0.475*NCAPH expression level+0.264*CDC20 expression level.We divided patients into high-risk and low-risk groups based on prognostic indicators.Eight gene combinations are independent prognostic biomarkers for OS in patients with hepatocellular carcinoma,and the AUC of the ROC curve for predicting 3-year survival rates for 8 gene combination markers is 0.803,and the AUC of the ROC curve predicting the 3-year survival rate of the 8 gene combination in the validation cohort was 0.795,suggesting that the 8-gene combination model performed well in predicting three-year survival.Conclusion: Based on the first part of the pivot gene,a novel marker containing eight genes was constructed to strongly predict the survival of patients with hepatocellular carcinoma.In addition,the identified 8-gene combination model showed good performance in predicting three-year survival,and was an independent prognostic indicator for survival prediction of patients with hepatocellular carcinoma,which was helpful for screening high-risk groups and guiding clinicians to develop individualized treatment plans.Part ? Ferroptosis Related Genes and Related Non-coding RNAs in Hepatocellular CarcinomaObjective: Genes associated with ferroptosis from hepatocellular carcinoma and their associated non-coding RNAs were screened using the TCGA database for hepatocellular carcinoma RNA sequencing data and literature searches and the KEGG ferroptosis pathway.Methods: The genes related to ferroptosis were screened by Chinese and foreign literature search and KEGG ferroptosis pathway,and then the hub genes obtained in the first part were taken and the ferroptosis related genes of hepatocellular carcinoma were found.16329non-coding RNAs(14448 Lnc RNAs and 1881 mi RNAs)were transformed in the TCGA database hepatocellular carcinoma RNA sequencing data.We performed differential expression analysis of these non-coding RNAs,and the differentially expressed non-coding RNA was integrated with the expression profile data of hepatocellular carcinoma ferroptosis-related genes for spearman correlation analysis and WGCNA analysis.Non-coding RNAs that are closely related to hepatocellular carcinoma ferroptosis genes were identified,and the most relevant non-coding RNAs were analyzed for clinical pathology and GSEA functional enrichment.Results:103 genes related to ferroptosis were obtained by Chinese and foreign literature search and KEGG ferroptosis pathway screening.The 103 genes associated with ferroptosis and 40 hub genes were crossed and the gene associated with ferroptosis in hepatocellular carcinoma was FANCD2.1888 non-coding RNAs with significant differential expression were identified.We integrated 1888 differentially expressed non-coding RNAs(1632 Lnc RNAs and 256 mi RNAs)and FANCD2 hepatocellular carcinoma expression profiling data into spearman correlation analysis.Three non-coding RNAs(CTD-2510F5.4,DDX11-AS1,hsa-mir-139)were found to be most closely associated with FANCD2.The most relevant non-coding RNA was CTD-2510F5.4,and CTD-2510F5.4was only associated with the turquoise gene module analyzed in the first part,and the correlation coefficient was the largest.GSEA analysis indicated that Lnc RNA CTD-2510F5.4is involved in many key pathways involved in ferroptosis and is associated with tumorigenesis,including oxidoreductase activity,glutathione peroxidase activity,iron ion binding,P53 signaling pathway,NOTCH signaling pathway,ERBB signaling pathways and pathways to cancer.Conclusion: In this study,we searched for the genes associated with ferroptosis in hepatocellular carcinoma(FANCD2)through Chinese and foreign literature searches combined with the results of the first part of the study.It was found for the first time that Lnc RNA CTD-2510F5.4 was poorly expressed in HCC,and the survival rate of HCC patients was decreased.This may be a potential novel biomarker and therapeutic target for early diagnosis,pathological classification,clinical treatment and prognosis of HCC.Analysis by GSEA enrichment suggests that CTD-2510F5.4 may be associated with ferroptosis.However,these assumptions need to be further validated and validated by in vitro and in vivo experiments and larger multicenter studies. |
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