| Background and purpose: Hepatocellular carcinoma(HCC)is a genetically and phenotypically heterogeneous tumor,and prognosis prediction is still a challenge.T h erefore,new biomarkers are needed to identify high-risk HCC patients with poor prog nosis.Some long noncoding RNAs(lncRNAs)are associated with cell cycle progressi on and maintenance of genomic stability.When the expression of these lncRNAs is m alregulated,it marks the generation and development of HCC.By analyzing transcript omic data and clinical sample data of HCC patients in The Cancer Genome Atlas(TC GA)database,specific cell cycle-associated lncRNAs with abnormal expression in H CC and associated with poor prognosis were obtained to establish clinical prognostic r isk scores.Clinical sample data were used to verify the predictive value of the score.At the same time,based on this risk score,different methods were used to comprehens ively analyze the immune microenvironment of HCC,so as to provide a new idea and method for immunotherapy of HCC patients.Methods: Transcriptome data and clinical sample data were downloaded from th e TCGA-HCC dataset.Cell cycle-associated gene sets were obtained from existing stu dies,and co-expression analysis was performed to identify cell cycle-associated lnc R NAs(r > 0.4,p < 0.001).Univariate analysis was performed on the screened cell cycl e-related lncRNAs to obtain a series of prognostic related lncRNAs,which were inclu ded in LASSO regression to establish the risk score,and then cross-verified the risk sc ore.HCC samples were grouped according to this risk score,Risk scores and tumor m utational burden were analyzed using R packages and different methods(TIMER,CI BERSORT,CIBERSORT-ABS,QUANTISEQ,MCP-COUNTER,XCELL,and EPI C).TMB),tumor immunoinfiltration,immune checkpoint genes,and immunotherape utic response.All the above analyses are based on R software.Results: Cell cycle-related lncRNAs: AC009549.1,AC090018.2,PKD1P6-NPI PP1 and TMCC1-AS1 were significantly up-regulated in HCC.A risk score was estab lished for lncRNAs that were ultimately identified as specific.Risk scores were established using these four cell cycle-associated lncRNAs.C-i ndex curve shows that compared with common clinical indicators,such as age,sex,tu mor node metastasis(TNM)staging and grading,this risk score has higher predictive value for prognosis in HCC patients.Compared with age,sex,TNM stage and classifi cation,ROC curve showed that the accuracy of risk score was the highest,and the AU C value was 0.738.Correlation analysis showed that B cells,CD4+T cells,macrophag es and Regulatory T cells(Tregs)were significantly enriched in high-risk groups,and the expression levels of all immune checkpoint genes were increased.Differences in T MB,partial immune response,immune cell infiltration,immune checkpoint gene expr ession levels,and drug reactivity were observed between the two risk groups.The linear-graph model,consisting of age,sex,TNM stage,grading,and risk sco res including 4 cell cycle-related lncRNAs,can intuitively reflect the 1-year,3-year,a nd 5-year overall survival(OS)outcomes of individual HCC patients.Conclusions: 1.Cell cycle-related lncRNAs AC009549.1,AC090018.2,PKD1P6-NPIPP1 and TMCC1-AS1 are significantly up-regulated in HCC,and are associate d with poor prognosis in HCC patients.They are considered potential markers of prog nostic value in establishing risk scores.2.The risk score we established(risk Score=0.491856119340748×AC009549.1+1.39032991534736×AC090018.2 +1.6216819436919×PKD1P6-NPIPP1 +0.85757931156 481×TMCC1-AS1 expression level)can better predict the prognosis of HCC p atients and identify high-risk groups with poor HCC prognosis.3.Based on this risk score,we found significant differences in TMB,partial imm une response,immune cell infiltration and immune checkpoint gene expression betwe en high-risk and low-risk groups,which may bring new thinking for immunotherapy o f HCC patients. |
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