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Background  Gene expression (RNA-seq) and overall survival (OS) in TCGA were combined using chromosome accessibility (ATAC-seq) to search for key molecules affecting liver cancer prognosis.    Methods  We used the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) to analyse chromatin accessibility in the promoter regions of whole genes in liver hepatocellular carcinoma (LIHC) and then screened differentially expressed genes (DEGs) at the mRNA level by transcriptome sequencing technology (RNA-seq). We obtained genes significantly associated with overall survival (OS) by a one-way Cox analysis. The three were screened by taking intersection and further using a Kaplan–Meier (KM) for validation. A prognostic model was constructed using the obtained genes by LASSO regression analysis.The expression of these genes in hepatocellular carcinomas was then analysed. The protein expression of these genes was verified using the Human Protein Atlas(HPA) online datasets and immunohistochemistry.    Results  ATAC-seq, RNA-seq and survival analysis, combined with a LASSO prediction model, identified signatures of 15 genes ( PRDX6, GCLM, HTATIP2, SEMA3F, UCK2, NOL10, KIF18A, RAP2A, BOD1, GDI2, ZIC2, GTF3C6 SLC1A5, ERI3  and  SAC3D1 ), all of which were highly expressed in hepatocellular carcinoma. The LASSO prognostic model showed that this risk score had high predictive accuracy for the survival prognosis at 1, 3 and 5 years. A KM curve analysis showed that high expression of all 15 gene signatures was significantly associated with a poor prognosis in LIHC patients. HPA analysis of protein expression showed that  PRDX6 ,  GCLM ,  HTATIP2 ,  NOL10 ,  KIF18A ,  RAP2A  and  GDI2  were highly expressed in the hepatocellular carcinoma tissues compared with normal control tissues.    Conclusions  PRDX6, GCLM, HTATIP2, SEMA3F, UCK2, NOL10, KIF18A, RAP2A, BOD1, GDI2, ZIC2, GTF3C6, SLC1A5, ERI3 and SAC3D1 may affect the prognosis of LIHC.

frontiers in oncology

Bioinformatics Analysis Using ATAC-seq and RNA-seq for the Identification of 15 Gene Signatures Associated With the Prediction of Prognosis in Hepatocellular Carcinoma