Construction Of A CENPM-based Prognostic Risk Assessment Signature For Hepatocellular Carcinoma Using Multi-Omics Big Data Integration Analysis

Objective: Hepatocellular carcinoma(HCC)is a malignant tumor with high morbidity and mortality.Most patients are prone to recurrence and metastasis,and the prognosis is poor.Deeply elucidating the molecular mechanism of HCC occurrence and development will help to identify novel and efficient biomarkers for establishing risk models for predicting the prognosis of HCC,which is of great significance for the treatment and diagnosis of HCC.Centromeric protein M(CENPM)belongs to the centromeric protein family.Studies have shown that abnormal expression of CENPM is closely related to the occurrence and development of various cancers,but its role and function in liver cancer are poorly understood.Methods: The function of CENPM in the occurrence and development of hepatocellular carcinoma was integrated and analyzed using multiple tumor databases;the protein HCC prognostic risk prediction model and the RNA-binding protein HCC prognostic risk prediction model were constructed based on CENPM co-expressed proteins;The function in the occurrence and development of HCC and construct a HCC prognostic risk model;based on CENPM-related immune infiltration changes,single-sample gene set enrichment analysis(ss GSEA)was used to explore the changes of tumor microenvironment in HCC patients.Results: CENPM was highly expressed in HCC,and survival analysis showed that high CENPM expression predicted worse prognosis than low CENPM expression.At the same time,the expression of CENPM was significantly correlated with tumor grade,tumor stage and T stage.Multivariate Cox regression analysis showed that CENPM was an independent prognostic factor for HCC patients.High CENPM expression was mainly enriched in cell cycle,DNA replication,RNA degradation,cancer,phagocytosis,P53 signaling and purine metabolism.Multivariate Cox regression analysis screened eight proteins(MCM3,MCM7,PCNA,SLC39A1,SMC2,TOP2 A,UBE2C and UHRF1)to construct a protein prognostic risk model,and the AUC values of these eight proteins were all higher than 0.7.The construction of nomogram It can improve the sensitivity and specificity of predicting the 1-,3-,and 5-year survival rates of HCC patients.Multivariate Cox regression analysis screened eight RBPs(SNRPD1,IARS,BRCA1,EZH2,RUVBL1,TST,TCOF1,and AZGP1),and the ROC results showed that the AUC value of the training set was 0.786,and the AUC value of the validation set was 0.689,suggesting this prognosis The sensitivity and specificity of the model were moderate.The results of survival analysis indicated that the survival rate of the high-risk group was lower than that of the low-risk group in both the training set and the validation set.A total of 33pyroptosis-related genes were extracted,and 53 of the 364 liver cancer samples in TCGA-HCC were mutated,with a mutation frequency of 14.56%.Among them,NLRP2 and NLRP3 had the highest mutation frequencies,and most of the mutation types were nonsense mutations.CNV alterations were common in 33 PRGs,and most of them focused on copy number amplification,with GSDMC,AIM2,and GSDMD mainly showing CNV gain,while CASP9 showed CNV loss.LASSO regression screened nine lnc RNAs(AL031985.3,NRAV,OSMR-AS1,AC073611.1,MKLN1-AS,AL137186.2,AL049840.4,MIR4435-2HG,and AL118511.1)as independent prognostic risk factors.The high-risk group is mainly enriched in tumor-related and immune-related pathways,and the low-risk group is mainly enriched in metabolic-related pathways;the high-risk group is related to the 50% inhibitory concentration(IC50)of docetaxel,and the low-risk group is mainly enriched in the metabolism-related pathways.Group correlates with IC50 of chemotherapeutic drugs such as bortezomib.Immune infiltrates in liver cancer samples were classified into low,medium and high abundance clusters using the ss GSEA scoring method.The results showed that the expression of immune cells increased with the increase of immune activity.Stromal score,immune score and ESTIMATE score were positively correlated with immune activity and negatively correlated with tumor purity.There were significant differences in the expression of 23 HLA-related genes between different immune groups.The expression levels of PD-L1 and CTLA-4 increased with the increase of immune activity.Conclusion: CENPM is highly expressed in HCC and is highly correlated with poor prognosis,suggesting that CENPM may play an important role in the occurrence and development of liver cancer.Screening identified CENPM-based proteins MCM3,MCM7,PCNA,SLC39A1,SMC2,TOP2 A,UBE2C and UHRF1 and RNA-binding proteins SNRPD1,IARS,BRCA1,EZH2,RUVBL1,TST,TCOF1,and AZGP1 that can be used to efficiently predict the prognosis of liver cancer patients.A set of pyroptosis-related lnc RNAs and their potential impact mechanisms on the tumor microenvironment were characterized based on CENPM function.Using ss GSEA,the immune infiltration pattern of HCC based on the function of CENPM was analyzed,and the changes of the tumor immune microenvironment during the progression of HCC were revealed.