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Introduction: Thyroid cancer is a malignant disease which could hardly be prognosticated. The PI3K/Akt/mTOR and Cyclin-DependentKinase 4 (CDK4) pathways are vital regulators of tumor cell proliferation and survival. The present study was accordingly designed to use dual inhibition of such pathways to kill thyroid cancer cells. Methods and materials: The effects of each inhibitors on human ATC and BCPAP cell lines wereevaluated by MTT assay. The right concentrations of inhibitors were determined and synergistic effects of such inhibitors were evaluated by 3,and Caspase-9 activity assay as well as Akt, mTOR,and CDK4. Results:Our finding showed thatboth ATC and BCPAP cell proliferation is significantly inhibited by PD-332991(PD) and NVP dependent manner (P<0.05), however, the BCPAP cells were more sensitive than ATC cells. Our data also revealed that NVP treatment significantly decreasedthe phosphorylation state of both AKT and mTOR. Nonetheless, PD tre and mTORwhereascombination treatment of NVP and PD1 significantly decreased AKT and mTOR phosphorylation (P<0.001). NVP and PD treatment either alone or in a combination also decreased Retinoblastoma phosphoryl decreased Cyclin D1 expression.In addition, our data of Caspase 8 and Caspase 3 as well as Bax/Bcl-2 ratio indicated that the combinationof NVP and PD induced cell apoptosis significantly (P<0.05). Conclusion:The present study suggests thatinhibition ofPI3K and CDK4 is the effective treatment for bothresistant and sensitivethyroid cancer cell line.

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.