Screening of UBE2S interacting protein and construction of prognostic model in hepatocellular carcinoma
10.13481/j.1671-587X.20240121
- VernacularTitle:肝细胞癌中UBE2S互作蛋白的筛选及预后模型构建
- Author:
Xiaoyan WANG
1
,
2
;
Hao ZHANG
;
Zehao GUO
;
Jun CAO
;
Zhijing MO
Author Information
1. 桂林医学院智能医学与生物技术学院实验教学中心,广西 桂林 541199
2. 桂林医学院 广西高校生物化学与分子生物学重点实验室,广西 桂林 541199
- Keywords:
Ubiquitin-conjugating enzyme E2S;
Hepatocellular carcinoma;
Co-immunoprecipitation;
Liquid chromatograph mass spectrometer;
Prognostic analysis
- From:
Journal of Jilin University(Medicine Edition)
2024;50(1):168-177
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To screen the interacting protein of ubiquitin-conjugating enzyme E2S(UBE2S)and construct the hepatocellular carcinoma(HCC)based on UBE2S interacting protein prognosis model(UIPM),and to discuss the value of UIPM in assessing the prognosis of the HCC patients.Methods:Co-immunoprecipitation(Co-IP)was used to screen the protein complexes binding to Flag-UBE2S.After validation by sodium dodecyl sulphate-polyacrylamide gel electrophoresis(SDS-PAGE)and Western blotting methods;liquid chromatography-mass spectrometer(LC-MS)was used to identify the UBE2S interacting proteins;Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis were conducted on these proteins;the prognosis-related proteins from The Cancer Genome Atlas(TCGA)were cross-referenced with UBE2S interacting proteins by survival package of R software;the key proteins were extracted through LASSO regression analysis to build the UIPM;the prognostic model risk scoring formula was established.The HCC patients in TCGA were divided into high risk group and low risk group based on median value of the risk scores.The predictive accuracy of UIPM was evaluated by receiver operating characteristic curve(ROC),and the predictive accuracy was further validated by International Cancer Genome Consortium(ICGC)Database;univariate regression analysis and multivariate Cox regression analysis were used to detect whether the UIPM risk score was an independent prognostic factor for HCC.Furthermore,the nomogram model was built.Results:A total of 97 UBE2S interacting proteins were identified through Co-IP combined with LC-MS analysis.The GO functional enrichment analysis and KEGG signaling pathway enrichment analysis results showed that the interacting proteins were closely associated with cysteine-type endopeptidase activity,oxidative stress,and cell death.The TCGA revealed 5 163 HCC prognosis-related proteins;after intersecting with UBE2S interacting proteins,40 prognosis-related interacting proteins were found.Seven key proteins were determined through LASSO regression analysis,including UBE2S,heat shock protein family A member 8(HSPA8),heterogeneous nuclear ribonucleoprotein H1(HNRNPH1),chaperonin containing TCP1 subunit 3(CCT3),eukaryotic translation initiation factor 2 subunit 1(EIF2S1),receptor for activated C kinase 1(RACK1),and actin related protein 2/3 complex subunit 4(ARPC4),and the UIPM was constructed.There was significant difference in survival rate of the patients between high risk group and low risk group(P<0.05).The ROC curve analysis results showed the area under ROC curve(AUC)values of UIPM for predicting 1-year,2-year,and 3-year survival risk scores of the HCC patients were all greater than 0.7,indicating the model had high predictive accuracy.This was also confirmed by ICGC Database data.The univariate and multivariate Cox regression analysis results showed that the UIPM risk score was an independent prognostic risk factor for the HCC patients(P<0.05).The nomogram results showed good consistency between predicted survival rate and actual survival rate of the patient.Conclusion:A total of 97 interacting proteins that interact with UBE2S may promote the occurence and devolopment of HCC through oxidative stress and dysregulation of ferroptosis pathways.The UIPM risk score is an independent risk factor for the prognosis of HCC and can be used to predict the outcomes of the patients.UBE2S,HSPA8,HNRNPH1,CCT3,EIF2S1,RACK1,and ARPC4 could be regarded as the new biomarkers and therapeutic targets for HCC.
