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      Fam198b as a novel biomarker for gastric cancer and a potential therapeutic target to prevent tumor cell proliferation dysregulation

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          Highlights

          • Increased Fam198b expression in GC is associated with poor prognosis.

          • The function of Fam198b in gastric cancer was testified by bioinformatics and in vitro experiments.

          • Fam198b promoted the proliferation, migration and invasion of gastric cancer cell lines.

          • Fam198b regulates Bcl-2 expression through the classical PI3K/AKT pathway to promote GC progression.

          • Fam198b is a novel biomarker for gastric cancer and a potential therapeutic target to prevent dysregulated tumor cell proliferation.

          Abstract

          Background

          It has been reported that the human family with sequence similarity 198, member B (Fam198b) play an important role in the occurrence and development of various cancers. Nevertheless, its function in gastric cancer is not completely clear. Hereby, we investigated the function and prognostic value of Fam198b in gastric cancer and further validated the results in gastric cancer through a series of in vitro experiments.

          Methods

          We used R software and online bioinformatics analysis tools-GEPIA2, TIMER2, Kaplan-Meier plotter, cBioPortal, TISIDB COSMIC, and STRING to study the characteristics and functions of Fam198b in GC, such as aberrant expression, prognostic value, genomic alterations, immune microenvironment, anticancer drug sensitivity, and related signaling pathways. In addition, in vitro experiments such as immunohistochemistry (IHC), cell function experiments, and signaling pathway experiments were performed to validate the key conclusions.

          Result

          Fam198b is obviously highly expressed in gastric cancer, and its expression is intensively correlated with tumor prognosis. The etiology of abnormal Fam198b expression was superficially investigated and validated by associating genomic alterations and the immune microenvironment. Furthermore, Fam198b is intensively correlated with the sensitivity of multiple antitumor drugs. It was demonstrated by functional enrichment analysis that Fam198b was linked to myogenesis, angiogenesis, epithelial mesenchymal transition and cytokine binding. It was observed in vitro experiments that knockdown Fam198b could significantly inhibit tumor cell proliferation and migration. These results were reversed when Fam198b was overexpressed. It was validated by signaling pathway experiments that Fam198b promoted gastric cancer progression by up-regulating the PI3K/AKT/BCL-2 signaling pathway.

          Conclusion

          As a novel biomarker to predict GC prognosis and tumor progression, Fam198b is a promising therapeutic target to reverse tumor progression.

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          Most cited references39

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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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            WGCNA: an R package for weighted correlation network analysis

            Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at .
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              STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

              Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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                Author and article information

                Contributors
                Journal
                Transl Oncol
                Transl Oncol
                Translational Oncology
                Neoplasia Press
                1936-5233
                06 November 2023
                January 2024
                06 November 2023
                : 39
                : 101824
                Affiliations
                [a ]Northern Jiangsu People's Hospital, Yangzhou 225001, PR China
                [b ]Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou 225001, PR China
                [c ]Northern Jiangsu People's Hospital , Medical School of Nanjing University, Yangzhou 225001, PR China
                [d ]Northern Jiangsu People's Hospital Affiliated to Dalian Medical University, Yangzhou 225001, PR China
                [e ]General Surgery Institute of Yangzhou, Yangzhou University, Yangzhou 225001, PR China
                [f ]Yangzhou Key Laboratory of Basic and Clinical Transformation of Digestive and Metabolic Diseases, PR China
                Author notes
                [* ]Corresponding authors at: Department of Gastrointestinal Surgery, Northern Jiangsu Peoples's Hospital, No.98 Nantong West Road, Yangzhou, Jiangsu Province 225001, China. freezingfall@ 123456163.com wdaorong666@ 123456sina.com
                [#]

                Daorong Wang and Jun Ren are co-corresponding authors.

                Article
                S1936-5233(23)00210-3 101824
                10.1016/j.tranon.2023.101824
                10652145
                37939629
                808185e7-0255-41c1-96b8-a06e78075f5e
                © 2023 Published by Elsevier Inc.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 30 June 2023
                : 2 November 2023
                : 2 November 2023
                Categories
                Original Research

                gastric cancer,fam198b,tcga,prognosis,biomarker,pi3k/akt
                gastric cancer, fam198b, tcga, prognosis, biomarker, pi3k/akt

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