| Background: Hepatocellular carcinoma(HCC)is the most common malignant liver tumor with high morbidity and mortality.Tumor stemness plays a crucial role in the tumorigenesis and treatment resistance of HCC,but the prognostic biomarkers and therapeutic targets related to tumor stemness have not been fully determined in HCC.In recent years,computer technology deep learning methods have been used to evaluate tumor dedifferentiation and the stemness characteristics.The m RNA expression-based stemness index(m RNAsi)can evaluate the stemness expression of transcriptome.Although m RNAsi has been implicated in tumor initiation and tumor staging,its role in HCC remains unclear.In this project,the relationship between m RNAsi and liver cancer stem cells(LCSCs)in liver cancer tissue samples was analyzed by bioinformatics.The aim of this project is to screen the key prognostic stemness-related genes(PSRGs)that promote the progression of HCC,and provide new therapeutic targets for HCC treatment.Methods: Bioinformatics analysis of RNA sequencing data retrieved from The Cancer Genome Atlas(TCGA)databases including HCC patient tissue samples and normal tissue samples was used to investigate novel stem cell-related genes in HCC.Differential expressed genes(DEGs)in HCC tissue samples and normal tissue samples as well as in different stages of HCC patients were evaluated,and m RNAsi was associated with tumorigenesis,clinical stage and overall survival(OS),respectively.The key PSRGs were identified by Lasso regression,and prognostic models were built based on these prognostic stemness related genes.In addition,to explore key regulatory networks,Pearson correlation analysis was used to determine the relationship between the differential expression of transcription factors(TFs)and PSRGs and the absolute quantification of 50 cancer markers.The functional analysis of PSRGs in vitro and in vivo was performed to verify the function and regulatory signaling pathways between PSRGs and HCC.Immunohistochemistry was used to determine the expression of PSRG and the prognosis of patients in HCC group.At the same time,lentivirus was used to construct HCC tumor cell lines that knocked out and overexpressed the PSRG.CCK8 assay and colony formation assay were used to detect the proliferation of HCC tumor cell lines after knocked out and overexpressed PSRG.Transwell assay was used to detect the migration and invasion ability of HCC tumor cell lines after knocking out and overexpressing PSRG.Flow cytometry was used to detect tumor stemness markers in HCC tumor cell lines after knocking out and overexpressing the PSRG.In vivo experiments were performed to verify the effect of knockout and overexpression of PSRG on the tumorigenic ability of mice.To further clarify the key molecular mechanism of PSRG in HCC tumorigenesis,Western blotting and co-IP experiments were used to identify the downstream molecular signals regulated by PSRG and the proteins bound by PSRG.Finally,the CMap database was used to predict the bioactive small molecule drugs targeting the PSRG,and the effect of the drugs on HCC progression was clarified by in vitro and in vivo experiments.Results: Through bioinformatics analysis,78 PSRGs were identified to construct a prediction nomogram,and the AUC was 0.799.In the column chart,the risk score was identified as an independent prognostic factor,indicating significant applicability.Finally,we predict that SAPCD2 is a key PSRG in the progression of HCC resistance and a potential therapeutic target for HCC.Immunohistochemical results showed that SAPCD2 was highly expressed in HCC tissue samples and positively correlated with poor prognosis of patients.The role of the key PSRGs SAPCD2 in HCC tumorigenesis and the related molecular mechanisms were further evaluated by in vitro and in vivo functional experiments.We found that overexpression of SAPCD2 significantly promoted the proliferation,migration,and stemness of HCC tumor cells,while SAPCD2 knockout inhibited this effect.Mechanistically,we found that SAPCD2 promoted the expression of E2F7 and upregulated the expression of cycle-related proteins p21 and CDC2 by binding to E2F7.Overexpression of E2F7 significantly promoted the proliferation,migration and cancer stemness of HCC tumor cells,and this effect could be reversed after SAPCD2 was knocked out,suggesting that SAPCD2 promoted the expression of E2F7 by binding to E2F7,thus promoting the progression of HCC cells.Finally,through CMap database,we found that Naringenin and Lomustine,two drugs targeting SAPCD2,had the highest scores in HCC,significantly inhibited the proliferation,migration and cancer stemness of HCC tumor cells,promoted the apoptosis of HCC tumor cells.Conclusion: Our data suggested SAPCD2-mediated E2F7up-regulation contributes to HCC development,indicating SAPCD2 may be a promising target for the diagnosis and treatment of HCC.Besides,Naringenin and Lomustine,were targeting SAPCD2,which adding more evidence to further clarify the therapeutic effect of SAPCD2 against HCC. |