GNAI2 Is a Risk Factor for Gastric Cancer: Study of Tumor Microenvironment (TME) and Establishment of Immune Risk Score (IRS)
Purpose. Although the G protein subunit α i2 (GNAI2) is upregulated in multiple cancers, its prognostic value and exact role in the development of gastric cancer (GC) remain largely unknown. Methods. This study evaluated the effect of GNAI2 on the tumor microenvironment (TME) in GC, constructed an i...
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description | Purpose. Although the G protein subunit α i2 (GNAI2) is upregulated in multiple cancers, its prognostic value and exact role in the development of gastric cancer (GC) remain largely unknown. Methods. This study evaluated the effect of GNAI2 on the tumor microenvironment (TME) in GC, constructed an immune risk score (IRS) model based on differentially-expressed immune genes, and systematically correlated GNAI2 and epigenetic factor expression patterns with TME and IRS. Also, RT-qPCR, flow cytometry, Western blotting (WB), and transwell assays were carried out to explore the regulatory mechanism of GNAI2 in GC. Results. High GNAI2 expression was associated with poor prognosis. Cytokine activation, an increase in tumor-infiltrating immune cells (TIIC), and the accumulation of regulatory T cells in the tumor immune cycle were all promoted by the TME, which was significantly associated with GNAI2 expression. Two different differentially expressed mRNA (DER) modification patterns were determined. These two DERs-clusters had significantly different TME cell infiltrations and were classified as either noninflamed or immune-inflamed phenotypes. The IRS model constructed using differentially expressed genes (DEGs) had great potential in predicting GC prognosis. The IRS model was also used in assessing clinicopathological features, such as microsatellite instability (MSI) status, epithelial-mesenchymal transition (EMT) status, clinical stages, tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores. Low IRS scores were associated with high immune checkpoint gene expression. Cell and animal studies confirmed that GNAI2 activated PI3K/AKT pathway and promoted the growth and migration of GC cells. Conclusion. The IRS model can be used for survival prediction and GNAI2 serves as a candidate therapeutic target for GC patients. |
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Although the G protein subunit α i2 (GNAI2) is upregulated in multiple cancers, its prognostic value and exact role in the development of gastric cancer (GC) remain largely unknown. Methods. This study evaluated the effect of GNAI2 on the tumor microenvironment (TME) in GC, constructed an immune risk score (IRS) model based on differentially-expressed immune genes, and systematically correlated GNAI2 and epigenetic factor expression patterns with TME and IRS. Also, RT-qPCR, flow cytometry, Western blotting (WB), and transwell assays were carried out to explore the regulatory mechanism of GNAI2 in GC. Results. High GNAI2 expression was associated with poor prognosis. Cytokine activation, an increase in tumor-infiltrating immune cells (TIIC), and the accumulation of regulatory T cells in the tumor immune cycle were all promoted by the TME, which was significantly associated with GNAI2 expression. Two different differentially expressed mRNA (DER) modification patterns were determined. These two DERs-clusters had significantly different TME cell infiltrations and were classified as either noninflamed or immune-inflamed phenotypes. The IRS model constructed using differentially expressed genes (DEGs) had great potential in predicting GC prognosis. The IRS model was also used in assessing clinicopathological features, such as microsatellite instability (MSI) status, epithelial-mesenchymal transition (EMT) status, clinical stages, tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores. Low IRS scores were associated with high immune checkpoint gene expression. Cell and animal studies confirmed that GNAI2 activated PI3K/AKT pathway and promoted the growth and migration of GC cells. Conclusion. The IRS model can be used for survival prediction and GNAI2 serves as a candidate therapeutic target for GC patients.</description><identifier>ISSN: 1942-0900</identifier><identifier>EISSN: 1942-0994</identifier><identifier>DOI: 10.1155/2022/1254367</identifier><language>eng</language><publisher>New York: Hindawi</publisher><subject>Algorithms ; Antigens ; Cancer therapies ; Datasets ; Gastric cancer ; Gene expression ; Genomes ; Genomics ; Immunotherapy ; Medical prognosis ; Patients ; Proteins ; Tumors</subject><ispartof>Oxidative medicine and cellular longevity, 2022-10, Vol.2022, p.1-35</ispartof><rights>Copyright © 2022 Han Yu et al.</rights><rights>Copyright © 2022 Han Yu et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2022 Han Yu et al. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c425t-cb2945f4b2128a7c70ffd9ed39ea849ba30bfa408075c8e3762b381cf843cc1e3</citedby><cites>FETCH-LOGICAL-c425t-cb2945f4b2128a7c70ffd9ed39ea849ba30bfa408075c8e3762b381cf843cc1e3</cites><orcidid>0000-0002-5074-5591 ; 0000-0003-4144-8891</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9586761/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9586761/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids></links><search><contributor>Ali Sheikh, Md Sayed</contributor><contributor>Md Sayed Ali Sheikh</contributor><creatorcontrib>Yu, Han</creatorcontrib><creatorcontrib>Liu, Sha</creatorcontrib><creatorcontrib>Wu, ZuGuang</creatorcontrib><creatorcontrib>Gao, FenFei</creatorcontrib><title>GNAI2 Is a Risk Factor for Gastric Cancer: Study of Tumor Microenvironment (TME) and Establishment of Immune Risk Score (IRS)</title><title>Oxidative medicine and cellular longevity</title><description>Purpose. Although the G protein subunit α i2 (GNAI2) is upregulated in multiple cancers, its prognostic value and exact role in the development of gastric cancer (GC) remain largely unknown. Methods. This study evaluated the effect of GNAI2 on the tumor microenvironment (TME) in GC, constructed an immune risk score (IRS) model based on differentially-expressed immune genes, and systematically correlated GNAI2 and epigenetic factor expression patterns with TME and IRS. Also, RT-qPCR, flow cytometry, Western blotting (WB), and transwell assays were carried out to explore the regulatory mechanism of GNAI2 in GC. Results. High GNAI2 expression was associated with poor prognosis. Cytokine activation, an increase in tumor-infiltrating immune cells (TIIC), and the accumulation of regulatory T cells in the tumor immune cycle were all promoted by the TME, which was significantly associated with GNAI2 expression. Two different differentially expressed mRNA (DER) modification patterns were determined. These two DERs-clusters had significantly different TME cell infiltrations and were classified as either noninflamed or immune-inflamed phenotypes. The IRS model constructed using differentially expressed genes (DEGs) had great potential in predicting GC prognosis. The IRS model was also used in assessing clinicopathological features, such as microsatellite instability (MSI) status, epithelial-mesenchymal transition (EMT) status, clinical stages, tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores. Low IRS scores were associated with high immune checkpoint gene expression. Cell and animal studies confirmed that GNAI2 activated PI3K/AKT pathway and promoted the growth and migration of GC cells. Conclusion. The IRS model can be used for survival prediction and GNAI2 serves as a candidate therapeutic target for GC patients.</description><subject>Algorithms</subject><subject>Antigens</subject><subject>Cancer therapies</subject><subject>Datasets</subject><subject>Gastric cancer</subject><subject>Gene expression</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Immunotherapy</subject><subject>Medical prognosis</subject><subject>Patients</subject><subject>Proteins</subject><subject>Tumors</subject><issn>1942-0900</issn><issn>1942-0994</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kcFuGyEQhldVIzVNcssDIPXiKHUCLOxCD5Usy3FXihspds6IZaHG3QUXdhPl0Hcvrq1IySGHESPmm59h_iw7R_AKIUqvMcT4GmFK8qL8kB0jTvAYck4-vuQQfso-x7iBsMgxQcfZ3_nPSYVBFYEE9zb-BjdS9T4Ak2IuYx-sAlPplA7fwLIfmmfgDVgNXSovrApeu0cbvOu068FotZhdAOkaMIu9rFsb1__vU0fVdYPT-xeWygcNRtX98uI0OzKyjfrscJ5kDzez1fTH-PZuXk0nt2NFMO3HqsacUENqjDCTpSqhMQ3XTc61ZITXMoe1kQQyWFLFdF4WuM4ZUoaRXCmk85Ps-153O9SdblSaKshWbIPtZHgWXlrxuuLsWvzyj4JTVpQFSgKjg0DwfwYde9HZqHTbSqf9EAUuMUOEIsoT-uUNuvFDcOl7O6okyQiGE_V1T6Udxhi0eRkGQbEzU-zMFAczE365x9fWNfLJvk__A3ainYc</recordid><startdate>20221014</startdate><enddate>20221014</enddate><creator>Yu, Han</creator><creator>Liu, Sha</creator><creator>Wu, ZuGuang</creator><creator>Gao, FenFei</creator><general>Hindawi</general><general>Hindawi Limited</general><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-5074-5591</orcidid><orcidid>https://orcid.org/0000-0003-4144-8891</orcidid></search><sort><creationdate>20221014</creationdate><title>GNAI2 Is a Risk Factor for Gastric Cancer: Study of Tumor Microenvironment (TME) and Establishment of Immune Risk Score (IRS)</title><author>Yu, Han ; Liu, Sha ; Wu, ZuGuang ; Gao, FenFei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c425t-cb2945f4b2128a7c70ffd9ed39ea849ba30bfa408075c8e3762b381cf843cc1e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Antigens</topic><topic>Cancer therapies</topic><topic>Datasets</topic><topic>Gastric cancer</topic><topic>Gene expression</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Immunotherapy</topic><topic>Medical prognosis</topic><topic>Patients</topic><topic>Proteins</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Han</creatorcontrib><creatorcontrib>Liu, Sha</creatorcontrib><creatorcontrib>Wu, ZuGuang</creatorcontrib><creatorcontrib>Gao, FenFei</creatorcontrib><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Oxidative medicine and cellular longevity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Han</au><au>Liu, Sha</au><au>Wu, ZuGuang</au><au>Gao, FenFei</au><au>Ali Sheikh, Md Sayed</au><au>Md Sayed Ali Sheikh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>GNAI2 Is a Risk Factor for Gastric Cancer: Study of Tumor Microenvironment (TME) and Establishment of Immune Risk Score (IRS)</atitle><jtitle>Oxidative medicine and cellular longevity</jtitle><date>2022-10-14</date><risdate>2022</risdate><volume>2022</volume><spage>1</spage><epage>35</epage><pages>1-35</pages><issn>1942-0900</issn><eissn>1942-0994</eissn><abstract>Purpose. Although the G protein subunit α i2 (GNAI2) is upregulated in multiple cancers, its prognostic value and exact role in the development of gastric cancer (GC) remain largely unknown. Methods. This study evaluated the effect of GNAI2 on the tumor microenvironment (TME) in GC, constructed an immune risk score (IRS) model based on differentially-expressed immune genes, and systematically correlated GNAI2 and epigenetic factor expression patterns with TME and IRS. Also, RT-qPCR, flow cytometry, Western blotting (WB), and transwell assays were carried out to explore the regulatory mechanism of GNAI2 in GC. Results. High GNAI2 expression was associated with poor prognosis. Cytokine activation, an increase in tumor-infiltrating immune cells (TIIC), and the accumulation of regulatory T cells in the tumor immune cycle were all promoted by the TME, which was significantly associated with GNAI2 expression. Two different differentially expressed mRNA (DER) modification patterns were determined. These two DERs-clusters had significantly different TME cell infiltrations and were classified as either noninflamed or immune-inflamed phenotypes. The IRS model constructed using differentially expressed genes (DEGs) had great potential in predicting GC prognosis. The IRS model was also used in assessing clinicopathological features, such as microsatellite instability (MSI) status, epithelial-mesenchymal transition (EMT) status, clinical stages, tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores. Low IRS scores were associated with high immune checkpoint gene expression. Cell and animal studies confirmed that GNAI2 activated PI3K/AKT pathway and promoted the growth and migration of GC cells. Conclusion. The IRS model can be used for survival prediction and GNAI2 serves as a candidate therapeutic target for GC patients.</abstract><cop>New York</cop><pub>Hindawi</pub><doi>10.1155/2022/1254367</doi><tpages>35</tpages><orcidid>https://orcid.org/0000-0002-5074-5591</orcidid><orcidid>https://orcid.org/0000-0003-4144-8891</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Antigens Cancer therapies Datasets Gastric cancer Gene expression Genomes Genomics Immunotherapy Medical prognosis Patients Proteins Tumors |
title | GNAI2 Is a Risk Factor for Gastric Cancer: Study of Tumor Microenvironment (TME) and Establishment of Immune Risk Score (IRS) |
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