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      Construction of CDKN2A-related competitive endogenous RNA network and identification of GAS5 as a prognostic indicator for hepatocellular carcinoma

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          Abstract

          BACKGROUND

          Competitive endogenous RNA (ceRNA) is an innovative way of gene expression modulation, which plays a crucial part in neoplasia. However, the intricacy and behavioral characteristics of the ceRNA network in hepatocellular carcinoma (HCC) remain dismal.

          AIM

          To establish a cyclin dependent kinase inhibitor 2A (CDKN2A)-related ceRNA network and recognize potential prognostic indicators for HCC.

          METHODS

          The mutation landscape of CDKN2A in HCC was first explored using the cBioPortal database. Differential expression analysis was implemented between CDKN2A high and CDKN2A low expression HCC samples. The targeted microRNAs were predicted by lncBasev3.0, and the targeted mRNAs were predicted by miRDB, and Targetscan database. The univariate and multivariate analysis were utilized to identify independent prognostic indicators.

          RESULTS

          CDKN2A was frequently mutated and deleted in HCC. The single-cell RNA-sequencing analysis revealed that CDKN2A participated in cell cycle pathways. The CDKN2A-related ceRNA network-growth arrest specific 5 (GAS5)/miR-25-3p/SRY-box transcription factor 11 (SOX11) was successfully established. GAS5 was recognized as an independent prognostic biomarker, whose overexpression was correlated with a poor prognosis in HCC patients. The association between GAS5 expression and methylation, immune infiltration was explored. Besides, traditional Chinese medicine effective components targeting GAS5 were obtained.

          CONCLUSION

          This CDKN2A-related ceRNA network provides innovative insights into the molecular mechanism of HCC formation and progression. Moreover, GAS5 might be a significant prognostic biomarker and therapeutic target in HCC.

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          Most cited references47

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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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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              clusterProfiler: an R package for comparing biological themes among gene clusters.

              Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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                Author and article information

                Contributors
                Journal
                World J Gastrointest Oncol
                WJGO
                World Journal of Gastrointestinal Oncology
                Baishideng Publishing Group Inc
                1948-5204
                15 April 2024
                15 April 2024
                : 16
                : 4
                : 1514-1531
                Affiliations
                Department of Infectious Disease, Zhoushan Hospital, Wenzhou Medical University, Zhoushan 316021, Zhejiang Province, China
                Department of Infectious Disease, Zhoushan Hospital, Wenzhou Medical University, Zhoushan 316021, Zhejiang Province, China
                State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital of Zhejiang University, Hangzhou 310003, Zhejiang Province, China
                Department of Infectious Disease, Zhoushan Hospital, Wenzhou Medical University, Zhoushan 316021, Zhejiang Province, China
                State Key Laboratory for the Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital of Zhejiang University, Hangzhou 310003, Zhejiang Province, China
                Department of Infectious Disease, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325035, Zhejiang Province, China
                Department of Infectious Disease, Zhoushan Hospital, Wenzhou Medical University, Zhoushan 316021, Zhejiang Province, China
                Department of Infectious Disease, Zhoushan Hospital, Wenzhou Medical University, Zhoushan 316021, Zhejiang Province, China
                Department of Infectious Disease, Zhoushan Hospital, Wenzhou Medical University, Zhoushan 316021, Zhejiang Province, China. lsb0398@ 123456126.com
                Author notes

                Author contributions: Pan Y and Zhang YR initiated the study and organized it; Wang LY, Ma YQ, and Fang Z designed and carried out bioinformatics analyses, statistical analyses, and drew figures; Pan Y and Wu LN drafted the manuscript; Li SB contributed to the review and editing; all authors have read and agreed to the published version of the manuscript.

                Supported by the Zhejiang Province Major Science and Technology Project for Medicine and Health, No. WKJ-ZJ-2329.

                Corresponding author: Shi-Bo Li, Doctor, Department of Infectious Disease, Zhoushan Hospital, Wenzhou Medical University, No. 739 Dingshen Road, Zhoushan 316021, Zhejiang Province, China. lsb0398@ 123456126.com

                Article
                jWJGO.v16.i4.pg1514 90123
                10.4251/wjgo.v16.i4.1514
                11037068
                38660664
                a2aa1c2a-9542-4643-8440-a4347e888cd4
                ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.

                This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.

                History
                : 24 November 2023
                : 16 January 2024
                : 4 February 2024
                Categories
                Basic Study

                hepatocellular carcinoma,competitive endogenous rna,molecular mechanism,prognosis,biomarker

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