Introduction: The goal of this study was to look at changes in pseudogene genes level as oncogenes and tumor suppressors in hepatocellular carcinoma (HCC) by large-scale analysis and to develop a survival prediction model based on their expression.Methods: The cancer genome data were applied to evaluate the expression alternations of all pseudogene in HCC and their correlation with patients' prognosis. Also, a risk model was computed based on the expression of pseudogenes and their predictive power in patient mortality rates. The co-expression network and RT-qPCR method were utilized to discover pathways related and confirmed the outcomes, respectively.Results: The results revealed that 12 pseudogenes were down-regulated in HCC, and their increased expression was associated with good prognosis. Also, 11 pseudogenes were overexpressed and associated with patients' poor prognoses. The multivariate Cox regression test indicated that overexpression of AKR1B10P1, RP11-465B22.3, WASH8P, and downregulation of NPM1P25 could predict the survival rate of patients independent of clinical parameters. The risk score model based on mentioned pseudogenes could considerably distinguish patients based on their fatality rate. Also, the co-expression network shown that the identified pseudogene genes can play a role in fatty acid metabolism, proliferation, and mTOR. RT-qPCR results also showed that the expression level of WASH8P was significantly increased in cancer specimens compared to normal.Conclusion: Our results revealed that change expression of AKR1B10P1, RP11-465B22.3, WASH8P, and NPM1P25 was independently associated with prognosis and the patient mortality risk model based on these four pseudogenes can reasonably predict the survival rate of patients.

Introduction: The goal of this study was to look at changes in pseudogene genes level as oncogenes and tumor suppressors in hepatocellular carcinoma (HCC) by large-scale analysis and to develop a survival prediction model based on their expression. Methods The cancer genome data were applied to evaluate the expression alternations of all pseudogene in HCC and their correlation with patients' prognosis. Also, a risk model was computed based on the expression of pseudogenes and their predictive power in patient mortality rates. The co-expression network and RT-qPCR method were utilized to discover pathways related and confirmed the outcomes, respectively. Results The results revealed that 12 pseudogenes were down-regulated in HCC, and their increased expression was associated with good prognosis. Also, 11 pseudogenes were overexpressed and associated with patients' poor prognoses. The multivariate Cox regression test indicated that overexpression of AKR1B10P1, RP11-465B22.3, WASH8P, and downregulation of NPM1P25 could predict the survival rate of patients independent of clinical parameters. The risk score model based on mentioned pseudogenes could considerably distinguish patients based on their fatality rate. Also, the co-expression network shown that the identified pseudogene genes can play a role in fatty acid metabolism, proliferation, and mTOR. RT-qPCR results also showed that the expression level of WASH8P was significantly increased in cancer specimens compared to normal. Conclusion Our results revealed that change expression of AKR1B10P1, RP11-465B22.3, WASH8P, and NPM1P25 was independently associated with prognosis and the patient mortality risk model based on these four pseudogenes can reasonably predict the survival rate of patients.