| Research background and purposeHepatocellular carcinoma(HCC)remains a global health challenge.Autophagy,as a conservative cellular physiological process,maintains cell homeostasis under physiological or pathological conditions by degradation of damaged and mutated cytoplasmic substances.Previous studies have shown that autophagy plays a role in different phases of development of HCC.Some autophagy-related genes(ARGs),such as LC3 and ULK1,have become new HCC prognostic biomarkers.However,low tissue specificity and instability in vivo and in vitro affect the wide applicability of those genes’ m RNA as prognostic biomarkers.Therefore,the development of new autophagy-related biomarkers to predict the prognosis of HCC is still very important.In recent years,the regulatory mechanism of long non-coding RNA(lncRNA)on autophagy has been revealed,and autophagy-related lncRNAs(AR-lncRNAs)have been reported as prognostic markers of HCC.In this study,bioinformatics analysis was used to comprehensively analyze the gene sequencing data from the The Cancer Genome Atlas(TCGA),in order to explore a more accurate HCC prognostic signature based on multiple AR-lncRNA expression levels and integrate it into the nomogram to provide prognostic information for clinic.At the same time,the relationship between autophagy level and drug sensitivity of hepatocellular carcinoma cells was briefly explored in view of the current lack of indicators to guide patients to choose drugs,which provides a basis for the selection of clinical treatment.Method1.The transcriptome sequencing data of 370 HCC samples with prognostic information in the TCGA database was included in the study.The weighted correlation network analysis(WGCNA)divides lncRNAs expressed in HCC sample into different modules with similar expression patterns.The AR-lncRNA module was identified according to the correlation analysis between modules and clinical traits.2.Univariate Cox regression and LASSO regression with 10-fold cross-validation were used to screen the AR-lncRNAs which related to the overall survival rate(OS)(OS related AR-lncRNAs)in the AR-lncRNA module.The patients with HCC were randomly divided into a "training set" and a "testing set".In the "training set",the multivariate Cox analysis with forward conditional stepwise regression was used to establish the HCC prognosis signature,and the high-and low-risk groups of HCC patients were divided according to the risk score.The signature was applied to the "testing set",all HCC samples and patients stratified according to clinical characteristics.The relationship between the expression of OS related AR-lncRNA and survival time was analyzed by Kaplan-Meier survival curve.The accuracy of prediction by the signature was evaluated by the area under the curve(AUC)of the subject working curve(ROC)and the consistency index(C-index)of the restricted mean survival time(RMS).3.The independent prognostic factors of HCC were identified by multivariate Cox regression and integrated into the nomogram for the 3-and 5-year survival rates of HCC patients,and the C-index was used to evaluate the prediction accuracy of the nomogram.4.Analyze the gene enrichment,somatic mutation,immune cell infiltration,chemotherapy and immunotherapy response of high-and low-risk HCC patients divided in order to preliminarily explain the predictive effectiveness of the signature.5.Construct the co-expression network between AR-lncRNAs and ARGs.The Kyoto encyclopedia of genes and genomes(KEGG)and Gene ontology(GO)analysis were used to analyze other biological pathways and processes these ARGs involved in.6.Western blotting was used to detect the level of autophagy of two kinds of hepatoma cells,Hep G2 and SMMC7721.The sensitivity of cells to Cisplatin and autophagy inhibitor 3-MA were detected by Cell Counting Kit-8(CCK-8).Results1.WGCNA clustered the lncRNAs with reasonable expression(average raw read count>1)in HCC samples into 9 modules with similar expression pattern,and the module significantly related to the patients’ autophagy gene expression level represented by gene set variation analysis(GSVA)score was defined as "AR-lncRNA module",which contained 1023AR-lncRNA.2.Univariate Cox regression showed that 354 lncRNA in AR-lncRNA module were associated with HCC prognosis(p<0.05).Seven OS related AR-lncRNAs(LNC01063,MKLN1-AS,TMCC1-SA1,CYTOR,MIR210 HG,NRAV,PLBD1-AS1)were screened by LASSO regression.The Kaplan-Meier survival curve showed that their high expression was related to shorter survival time.In the training set,multivariate Cox analysis with forward conditional stepwise regression established an HCC prognostic signature based on expression levels of five AR-lncRNAs: risk score=CYTOR expression×0.17456 + LINC01063expression×0.30093 + MKLN1-AS expression×0.27462 + PLBS1-AS1 expression×0.17218 +TMMC1-AS1 expression×0.28974.There was a significant difference in survival between high-and low-risk HCC patients divided by median risk score,and these five AR-lncRNAs were highly expressed in the high-risk group.The signature also showed high AUC of ROC in the "testing set",all HCC samples,and patients which were stratified according to clinical characteristics.Compared with three recently published HCC prognostic signatures,this model reached a higher C-index of RMS.3.Multivariate Cox regression confirmed that "TMN stage" and "risk score" were independent factors for the prognosis of HCC.A prognostic nomogram was constructed with these independent factors to predict the 3-and 5-year survival for HCC patients and the Cindex reached 0.745(95% confidence interval,0.686-0.805).4.Gene enrichment analysis(GSEA),somatic mutation analysis and immune cell infiltration analysis showed that compared with the low-risk group,HCC patients in the highrisk group showed abundant gene enrichment in cell cycle and purine metabolic pathway,increased mutation frequency of TP53 gene,and the infiltration of M1,M2 macrophages and regulatory T cells significantly increased(p<0.05).The results of chemotherapy and immunotherapy response showed that the high-risk HCC patients had poorer treatment response than the low-risk group(p<0.02).5.The co-expression network of AR-lncRNAs and ARGS showed that there were 162 ARGs correlated with the 5 AR-lncRNAs(p<0.05,|correlation coefficient|>0.3),and ARGs that promoted autophagy were positively correlated with the 5 AR-lncRNAs.KEGG and GO enrichment showed that these ARGs were also involved in cancer pathway and energy metabolism pathway.6.Western blotting assay showed that the LC3II/I level of Hep G2 cells was higher than that of SMMC7721 cells.The CCK-8 assay showed that Hep G2 cells were less sensitive to Cisplatin than SMMC7721 cells,but more sensitive to autophagy inhibitor 3-MA.Combined use of 3-MA could enhance the cytotoxicity of cisplatin to SMMC7721 cells(p < 0.001).Conclusion and significanceIn this study,an HCC prognostic signature based on the expression level of AR-lncRNAs was established,which can predict the survival of HCC patients.A prognostic nomogram provides a more intuitive and accurate prognosis estimation tool for clinic.The differences in gene enrichment,somatic mutation,immune cell infiltration and treatment response may be the reasons for the different survival between high-and low-risk HCC patients,which provided clues for the study of AR-lncRNAs in regulating the occurrence and development of HCC.The co-expression relationship between AR-lncRNAs and ARGs reflected the different autophagy levels in patients in high-and low-risk HCC patients.Cell experiments showed that hepatoma cells with different autophagy levels have different sensitivity to Cisplatin and autophagy inhibitor 3-MA,which suggested that AR-lncRNAs may affect the level of autophagy and drug sensitivity of HCC patients by regulating the expression of autophagyrelated genes,which provides targets for improving drug sensitivity and new reference information for drug selection of HCC patients. |
