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      Anti-malarial drug dihydroartemisinin downregulates the expression levels of CDK1 and CCNB1 in liver cancer

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          Abstract

          Liver cancer is the third leading cause of cancer-associated mortality worldwide. By the time liver cancer is diagnosed, it is already in the advanced stage. Therefore, novel therapeutic strategies need to be identified to improve the prognosis of patients with liver cancer. In the present study, the profiles of GSE84402, GSE19665 and GSE121248 were used to screen differentially expressed genes (DEGs). Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for DEGs were conducted using the Database for Annotation, Visualization and Integrated Discovery. The protein-protein interaction network was established to screen the hub genes associated with liver cancer. Additionally, the expression levels of hub genes were validated using the Gene Expression Profiling Interactive Analysis and Oncomine databases. In addition, the prognostic value of hub genes in patients with liver cancer was analyzed using Kaplan-Meier Plotter. It was demonstrated that 132 and 246 genes were upregulated and downregulated, respectively, in patients with liver cancer. Among these DEGs, 10 hub genes with high connected node values were identified, which were AURKA, BIRC5, BUB1B, CCNA2, CCNB1, CCNB2, CDC20, CDK1, DLGAP5 and MAD2L1. CDK1 and CCNB1 had the most connection nodes and the highest score and were therefore, the most significantly expressed. In addition, it was demonstrated that high expression levels of CDK1 and CCNB1 were associated with poor overall survival time of patients with liver cancer. Dihydroartemisinin (DHA) is a Food and Drug Administration-approved drug, which is derived from the traditional Chinese medicine Artemisia annua Linn. DHA inhibits cell proliferation in numerous cancer types, including liver cancer. In our previous study, it was revealed that DHA inhibited the proliferation of HepG2215 cells. In the present study, it was further demonstrated that DHA reduced the expression levels of CDK1 and CCNB1 in liver cancer. Overall, CDK1 and CCNB1 were the potential therapeutic targets of liver cancer, and DHA reduced the expression levels of CDK1 and CCNB1, and inhibited the proliferation of liver cancer cells.

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          Most cited references40

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

            The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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              Challenges in liver cancer and possible treatment approaches

              Globally, liver cancer is the most frequent fatal malignancy; in the United States, it ranks fifth. Patients are often diagnosed with liver cancer in advanced stages, contributing to its poor prognosis. Of all liver cancer cases, >90% are hepatocellular carcinomas (HCCs) for which chemotherapy and immunotherapy are the best options for therapy. For liver cancer patients, new treatment options are necessary. Use of natural compounds and/or nanotechnology may provide patients with better outcomes with lower systemic toxicity and fewer side effects. Improved treatments can lead to better prognoses. Finally, in this review, we present some of the problems and current treatment options contributing to the poor outcomes for patients with liver cancer.
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                Author and article information

                Journal
                Oncol Lett
                Oncol Lett
                OL
                Oncology Letters
                D.A. Spandidos
                1792-1074
                1792-1082
                September 2021
                09 July 2021
                09 July 2021
                : 22
                : 3
                : 653
                Affiliations
                Department of Pathobiology and Immunology, Hebei University of Chinese Medicine, Shijiazhuang, Hebei 050200, P.R. China
                Author notes
                Correspondence to: Professor Xinli Shi, Department of Pathobiology and Immunology, Hebei University of Chinese Medicine, 3 Xingyuan Road, Shijiazhuang, Hebei 050200, P.R. China, E-mail: shixinli@ 123456hebcm.edu.cn
                Article
                OL-0-0-12914
                10.3892/ol.2021.12914
                8299009
                34386075
                0973c0b3-8faf-4ef6-8f98-5564759faa4b
                Copyright: © Hao et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

                History
                : 17 March 2021
                : 21 June 2021
                Funding
                Funded by: National Natural Science Foundation of China, open-funder-registry 10.13039/501100001809;
                Award ID: 81873112
                Funded by: Talent Engineering Training Funding Project of Hebei Province
                Award ID: A201902015
                Funded by: The Project to Support Hundreds of Outstanding Innovative Talents from the Universities in Hebei Province
                Award ID: SLRC2019043
                The present study was financially supported by the National Natural Science Foundation of China (grant no. 81873112), Talent Engineering Training Funding Project of Hebei Province (grant no. A201902015), and The Project to Support Hundreds of Outstanding Innovative Talents from the Universities in Hebei Province (grant no. SLRC2019043).
                Categories
                Articles

                Oncology & Radiotherapy
                liver cancer,bioinformatics analysis,dihydroartemisinin,cdk1,ccnb1
                Oncology & Radiotherapy
                liver cancer, bioinformatics analysis, dihydroartemisinin, cdk1, ccnb1

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