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Development of an immune-related prognostic index associated with hepatocellular carcinoma
Liver hepatocellular carcinoma (LIHC), an inflammation-associated cancer induced by a variety of etiological factors, is still one of the most prevalent and lethal cancers in human population. In this study, the expression profiles of immune-related genes (IRGs) were integrated with the overall surv...
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Published in: | Aging (Albany, NY.) NY.), 2020-03, Vol.12 (6), p.5010-5030 |
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creator | Hu, Bo Yang, Xiao-Bo Sang, Xin-Ting |
description | Liver hepatocellular carcinoma (LIHC), an inflammation-associated cancer induced by a variety of etiological factors, is still one of the most prevalent and lethal cancers in human population. In this study, the expression profiles of immune-related genes (IRGs) were integrated with the overall survival (OS) of 378 LIHC patients based on the Cancer Genome Atlas (TCGA) dataset. Moreover, the differentially expressed and survival related IRGs among LIHC patients were predicted through the computational difference algorithm and COX regression analysis. As a result, 7 genes, including HSPA4, S100A10, FABP6, CACYBP, HDAC1, FCGR2B and SHC1, were retrieved to construct a predictive model associated with the overall survival (OS) of LIHC patients. Typically, the as-constructed model performed moderately in predicting prognosis, which was also correlated with tumor grade. Functional enrichment analysis revealed that the genes of high-risk group were actively involved in mRNA binding and the spliceosome pathway. Intriguingly, the prognostic index established based on IRGs reflected infiltration by multiple types of immunocytes. Our findings screen several IRGs with clinical significance, reveal the drivers of immune repertoire, and illustrate the importance of a personalized, IRG-based immune signature in LIHC recognition, surveillance, and prognosis prediction. |
doi_str_mv | 10.18632/aging.102926 |
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In this study, the expression profiles of immune-related genes (IRGs) were integrated with the overall survival (OS) of 378 LIHC patients based on the Cancer Genome Atlas (TCGA) dataset. Moreover, the differentially expressed and survival related IRGs among LIHC patients were predicted through the computational difference algorithm and COX regression analysis. As a result, 7 genes, including HSPA4, S100A10, FABP6, CACYBP, HDAC1, FCGR2B and SHC1, were retrieved to construct a predictive model associated with the overall survival (OS) of LIHC patients. Typically, the as-constructed model performed moderately in predicting prognosis, which was also correlated with tumor grade. Functional enrichment analysis revealed that the genes of high-risk group were actively involved in mRNA binding and the spliceosome pathway. Intriguingly, the prognostic index established based on IRGs reflected infiltration by multiple types of immunocytes. Our findings screen several IRGs with clinical significance, reveal the drivers of immune repertoire, and illustrate the importance of a personalized, IRG-based immune signature in LIHC recognition, surveillance, and prognosis prediction.</description><identifier>ISSN: 1945-4589</identifier><identifier>EISSN: 1945-4589</identifier><identifier>DOI: 10.18632/aging.102926</identifier><identifier>PMID: 32191631</identifier><language>eng</language><publisher>United States: Impact Journals</publisher><subject>Biomarkers, Tumor - genetics ; Biomarkers, Tumor - immunology ; Carcinoma, Hepatocellular - diagnosis ; Carcinoma, Hepatocellular - genetics ; Carcinoma, Hepatocellular - immunology ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Kaplan-Meier Estimate ; Liver Neoplasms - diagnosis ; Liver Neoplasms - genetics ; Liver Neoplasms - immunology ; Prognosis ; Research Paper</subject><ispartof>Aging (Albany, NY.), 2020-03, Vol.12 (6), p.5010-5030</ispartof><rights>Copyright © 2020 Hu et al.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c387t-11636874338b03862125252ed7b699853915d8097cdd3e445f4cb36978875a283</citedby><cites>FETCH-LOGICAL-c387t-11636874338b03862125252ed7b699853915d8097cdd3e445f4cb36978875a283</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138589/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138589/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,733,786,790,891,27957,27958,53827,53829</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32191631$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hu, Bo</creatorcontrib><creatorcontrib>Yang, Xiao-Bo</creatorcontrib><creatorcontrib>Sang, Xin-Ting</creatorcontrib><title>Development of an immune-related prognostic index associated with hepatocellular carcinoma</title><title>Aging (Albany, NY.)</title><addtitle>Aging (Albany NY)</addtitle><description>Liver hepatocellular carcinoma (LIHC), an inflammation-associated cancer induced by a variety of etiological factors, is still one of the most prevalent and lethal cancers in human population. In this study, the expression profiles of immune-related genes (IRGs) were integrated with the overall survival (OS) of 378 LIHC patients based on the Cancer Genome Atlas (TCGA) dataset. Moreover, the differentially expressed and survival related IRGs among LIHC patients were predicted through the computational difference algorithm and COX regression analysis. As a result, 7 genes, including HSPA4, S100A10, FABP6, CACYBP, HDAC1, FCGR2B and SHC1, were retrieved to construct a predictive model associated with the overall survival (OS) of LIHC patients. Typically, the as-constructed model performed moderately in predicting prognosis, which was also correlated with tumor grade. Functional enrichment analysis revealed that the genes of high-risk group were actively involved in mRNA binding and the spliceosome pathway. Intriguingly, the prognostic index established based on IRGs reflected infiltration by multiple types of immunocytes. Our findings screen several IRGs with clinical significance, reveal the drivers of immune repertoire, and illustrate the importance of a personalized, IRG-based immune signature in LIHC recognition, surveillance, and prognosis prediction.</description><subject>Biomarkers, Tumor - genetics</subject><subject>Biomarkers, Tumor - immunology</subject><subject>Carcinoma, Hepatocellular - diagnosis</subject><subject>Carcinoma, Hepatocellular - genetics</subject><subject>Carcinoma, Hepatocellular - immunology</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Humans</subject><subject>Kaplan-Meier Estimate</subject><subject>Liver Neoplasms - diagnosis</subject><subject>Liver Neoplasms - genetics</subject><subject>Liver Neoplasms - immunology</subject><subject>Prognosis</subject><subject>Research Paper</subject><issn>1945-4589</issn><issn>1945-4589</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNpVUT1PwzAQtRCIlsLIijKypMR2_LUgofIpVWKBhcVyHKc1SuxgJwX-PaEtVdENd9I9vXvvHgDnMJtCTjG6UgvrFlOYIYHoARhDkZM0J1wc7s0jcBLje5ZRQnJ6DEYYQQEphmPwdmtWpvZtY1yX-CpRLrFN0zuTBlOrzpRJG_zC-dhZnVhXmq9Exei1Xe8-bbdMlqZVndemrvtahUSroK3zjToFR5Wqoznb9gl4vb97mT2m8-eHp9nNPNWYsy6FgxDKWY4xLzLMKYKIDGVKVlAhOMECkpJngumyxCbPSZXrAlPBOGdEIY4n4HrD2_ZFY0o9OAmqlm2wjQrf0isr_2-cXcqFX0kGMR-eMxBcbgmC_-hN7GRj468f5Yzvo0SYQ4oYy-EATTdQHXyMwVS7MzCT6zzkOg-5yWPAX-xr26H_AsA_yHKIFw</recordid><startdate>20200319</startdate><enddate>20200319</enddate><creator>Hu, Bo</creator><creator>Yang, Xiao-Bo</creator><creator>Sang, Xin-Ting</creator><general>Impact Journals</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20200319</creationdate><title>Development of an immune-related prognostic index associated with hepatocellular carcinoma</title><author>Hu, Bo ; Yang, Xiao-Bo ; Sang, Xin-Ting</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c387t-11636874338b03862125252ed7b699853915d8097cdd3e445f4cb36978875a283</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Biomarkers, Tumor - genetics</topic><topic>Biomarkers, Tumor - immunology</topic><topic>Carcinoma, Hepatocellular - diagnosis</topic><topic>Carcinoma, Hepatocellular - genetics</topic><topic>Carcinoma, Hepatocellular - immunology</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Humans</topic><topic>Kaplan-Meier Estimate</topic><topic>Liver Neoplasms - diagnosis</topic><topic>Liver Neoplasms - genetics</topic><topic>Liver Neoplasms - immunology</topic><topic>Prognosis</topic><topic>Research Paper</topic><toplevel>online_resources</toplevel><creatorcontrib>Hu, Bo</creatorcontrib><creatorcontrib>Yang, Xiao-Bo</creatorcontrib><creatorcontrib>Sang, Xin-Ting</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Aging (Albany, NY.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Bo</au><au>Yang, Xiao-Bo</au><au>Sang, Xin-Ting</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of an immune-related prognostic index associated with hepatocellular carcinoma</atitle><jtitle>Aging (Albany, NY.)</jtitle><addtitle>Aging (Albany NY)</addtitle><date>2020-03-19</date><risdate>2020</risdate><volume>12</volume><issue>6</issue><spage>5010</spage><epage>5030</epage><pages>5010-5030</pages><issn>1945-4589</issn><eissn>1945-4589</eissn><notes>ObjectType-Article-1</notes><notes>SourceType-Scholarly Journals-1</notes><notes>ObjectType-Feature-2</notes><notes>content type line 23</notes><abstract>Liver hepatocellular carcinoma (LIHC), an inflammation-associated cancer induced by a variety of etiological factors, is still one of the most prevalent and lethal cancers in human population. In this study, the expression profiles of immune-related genes (IRGs) were integrated with the overall survival (OS) of 378 LIHC patients based on the Cancer Genome Atlas (TCGA) dataset. Moreover, the differentially expressed and survival related IRGs among LIHC patients were predicted through the computational difference algorithm and COX regression analysis. As a result, 7 genes, including HSPA4, S100A10, FABP6, CACYBP, HDAC1, FCGR2B and SHC1, were retrieved to construct a predictive model associated with the overall survival (OS) of LIHC patients. Typically, the as-constructed model performed moderately in predicting prognosis, which was also correlated with tumor grade. Functional enrichment analysis revealed that the genes of high-risk group were actively involved in mRNA binding and the spliceosome pathway. Intriguingly, the prognostic index established based on IRGs reflected infiltration by multiple types of immunocytes. Our findings screen several IRGs with clinical significance, reveal the drivers of immune repertoire, and illustrate the importance of a personalized, IRG-based immune signature in LIHC recognition, surveillance, and prognosis prediction.</abstract><cop>United States</cop><pub>Impact Journals</pub><pmid>32191631</pmid><doi>10.18632/aging.102926</doi><tpages>21</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Biomarkers, Tumor - genetics Biomarkers, Tumor - immunology Carcinoma, Hepatocellular - diagnosis Carcinoma, Hepatocellular - genetics Carcinoma, Hepatocellular - immunology Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans Kaplan-Meier Estimate Liver Neoplasms - diagnosis Liver Neoplasms - genetics Liver Neoplasms - immunology Prognosis Research Paper |
title | Development of an immune-related prognostic index associated with hepatocellular carcinoma |
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