Establishment Of A Diagnostic And Prognostic Risk Assessment Model For LncRNA In Hepatocellular Carcinoma And Exploration Of Its Biological Significance

Objective Primary liver carcinoma(PLC),as a malignant tumor with the fourth-highest rate of morbidity and sixth-highest rate of mortality in the world,is characterized by hidden onset,easy invasion and metastasis and poor prognosis.Its diagnosis and treatment has been a worldwide problem.Hepatocellular carcinoma(HCC)is the most common type of liver cancer,since the early symptoms of HCC patients are not significant and often accompanied by chronic liver disease,which has a serious impact on the prognosis of HCC patients.Currently,prognostic models of HCC commonly used in clinical practice include TNM stage(8th edition)and Barcelona clinic liver cancer(BCLC),Cancer of the Liver Italian Program(CLIP),Chinese liver cancer staging(CIS).But each model has its own applicability and limitations,the ability to predict the prognosis of patients is limited.Therefore,it has great significance to further study the molecular mechanisms regulating the occurrence and development of HCC and explore effective therapeutic targets and prognostic markers.With the development of science and technology,long non-coding RNA(lncRNA),as functional regulators,has attracted more and more attention for cell growth,differentiation and metabolism.A lot of researches have confirmed that lncRNA can regulate gene expression at different levels in a variety of roles,actively involved in tumor growth,metastasis and recurrence,suggesting that lncRNA has the potential to guide early diagnosis and prognostic evaluation of patients.Hence,it is important to deeply study the mechanism of lncRNA on HCC and establish a new model to evaluate the prognosis of HCC.Methods In this study,HCC samples from the TCGA-LIHC database were randomly grouped into training set and validation set at 7:3.Based on Lasso regression analysis,differentially expressed lncRNAs in HCC were screened to establish a Diagnostic model for HCC(the model was named as: Diagnostic model of lncRNA by Lasso,DLL model).The classification ability of DLL model in training set and validation set was observed by Principal component analysis(PCA).Moreover,risk scores based on model feature lncRNA were obtained based on lasso regression to assess the prognostic potential of DLL models.In order to explore the relationship between model feature lncRNA and clinical characteristics,Cox regression was used to construct the Nomogram model based on DLL model,and the ROC curve,Kaplan-Meier survival curve and calibration curve were used to evaluate its prognostic performance.GO enrichment analysis and KEGG pathway enrichment analysis were used to further explore the biological processes and pathways of key lncRNAs in the DLL model in the occurrence and development of liver cancer.GO annotation and KEGG pathway enrichment analysis were used to further explore the biological processes and pathways of key lncRNAs in the DLL model for the occurrence and development of HCC.In order to determine the direct targets regulated by lncRNAs,target genes significantly activated in the enrichment pathway were selected to conduct molecular docking energy analysis with characteristic lncRNAs.Finally,the immune mechanism of DLL model regulating HCC was explored by the correlation analysis of immune infiltration.Results 751 differential expression lncRNAs were screened from the lncRNA expression profile of HCC.Seven specific lncRNAs(AC107396.1,AC010776.2,B3 GAl T5-AS1,LINC01612,PCDH9-AS2,AC092171.2 and SFTA1P)were screened by LASSO regression analysis and a diagnostic model was established.PCA analysis showed that DLL model had similar classification ability in training set and validation set.The prognostic risk score was calculated based on Lasso regression coefficient,and the Kaplan-Meier survival curve showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group(P = 0.034).Univariate Cox regression analysis was used to screen clinical features related to OS,including Metastasis,Residual tumor,Hepatitis B surface Antigen,Hepatitis C antibody and Hepatitis C virus RNA and DLL model as indicators to establish a Nomogram model.The AUC value of ROC curve tended to be flat over time.The results show that the Nomogram model has a good ability to predict the prognostic performance.According to the Kaplan-Meier survival curve,the survival rate in the high-score group was significantly lower than that in the low-score group(P <0.0001).In the calibration curve,Hosmer-Lemeshow P value is 0.154,indicating that the Nomogram model has good practical prediction performance.Enrichment analysis results showed that the biological functions of key lncRNAs in DLL model may be related to histone modification,covalent chromatin modification and cell fate commitment.The main pathways involved included cell senescence,hepatocellular carcinoma signaling pathway,transcriptional misregulation in cancer pathway,and signaling pathways regulating pluripotency of stem cells pathway.Molecular docking energy analysis showed that FOXM1 and E2F4 were the target genes of 7-lncRNA in DLL model.Immune infiltration analysis showed that Treg cells were significantly activated.Combined with pathway enrichment analysis,the immune mechanism of DLL model regulating liver cancer was mapped.Conclusion Based on LASSO regression analysis,seven lncRNAs(AC107396.1,AC010776.2,B3GALT5-AS1,LINC01612,PCDH9-AS2,AC092171.2 and SFTA1P)were screened to establish a molecular diagnostic model(DLL model)for HCC.The DLL model has good classification potential and diagnostic potential.Combining the DLL model and clinical features to establish a Nomogram model,The analysis shows that the Nomogram model has a good prognostic potential.According to GO enrichment analysis,KEGG enrichment pathway analysis and molecular docking energy analysis,DLL model 7-lncRNA is involved in the occurrence and development of HCC through the regulation of FOXM1 and E2F4 factors on cell senescence and hepatocellular carcinoma signaling pathway.The results of immune infiltration analysis combined with KEGG pathway enrichment analysis explored the potential immune mechanism of DLL model regulating HCC,that is,the specific expression of lncRNA in DLL model inhibited the Th17 differentiation pathway and the inflammatory cytokine IL-17 signaling pathway,and increased the transformation and functional stability of Treg through the PD-L1 expression and PD-1 checkpoint pathway,resulting in an imbalance of Th17/Treg balance and the progress of HCC were promoted.