The value of a metabolic reprogramming-related gene signature for pancreatic adenocarcinoma prognosis prediction
Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. Extensive enhancement of glycolysis and reprogramming of lipid metabolism are both associated with the development and progression of PDAC. Previous studies have suggested that various gene signatures could conv...
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Veröffentlicht in: | Aging (Albany, NY.) NY.), 2020-11, Vol.12 (23), p.24228-24241 |
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description | Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. Extensive enhancement of glycolysis and reprogramming of lipid metabolism are both associated with the development and progression of PDAC. Previous studies have suggested that various gene signatures could convey prognostic information about PDAC. However, the use of these signatures has some limitations, perhaps because of a lack of knowledge regarding the genetic and energy supply backgrounds of PDAC. Therefore, we conducted multi-mRNA analysis based on metabolic reprogramming to identify novel signatures for accurate prognosis prediction in PDAC patients. In this study, a three-gene signature comprising MET, ENO3 and CD36 was established to predict the overall survival of PDAC patients. The three-gene signature could divide patients into high- and low-risk groups by disparities in overall survival verified by log-rank test in two independent validation cohorts and could differentiate tumors from normal tissues with excellent accuracy in four Gene Expression Omnibus (GEO) cohorts. We also found a positive correlation between the risk score of the gene signature and inherited germline mutations in PDAC predisposition genes. A glycolysis and lipid metabolism-based gene nomogram and corresponding calibration curves showed significant performance for survival prediction in the TCGA-PDAC dataset. The high-risk designation was closely connected with oncological signatures and multiple aggressiveness-related pathways, as determined by gene set enrichment analysis (GSEA). In summary, our study developed a three-gene signature and established a prognostic nomogram that objectively predicted overall survival in PDAC. The findings could provide a reference for the prediction of overall survival and could aid in individualized management for PDAC patients. |
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Extensive enhancement of glycolysis and reprogramming of lipid metabolism are both associated with the development and progression of PDAC. Previous studies have suggested that various gene signatures could convey prognostic information about PDAC. However, the use of these signatures has some limitations, perhaps because of a lack of knowledge regarding the genetic and energy supply backgrounds of PDAC. Therefore, we conducted multi-mRNA analysis based on metabolic reprogramming to identify novel signatures for accurate prognosis prediction in PDAC patients. In this study, a three-gene signature comprising MET, ENO3 and CD36 was established to predict the overall survival of PDAC patients. The three-gene signature could divide patients into high- and low-risk groups by disparities in overall survival verified by log-rank test in two independent validation cohorts and could differentiate tumors from normal tissues with excellent accuracy in four Gene Expression Omnibus (GEO) cohorts. We also found a positive correlation between the risk score of the gene signature and inherited germline mutations in PDAC predisposition genes. A glycolysis and lipid metabolism-based gene nomogram and corresponding calibration curves showed significant performance for survival prediction in the TCGA-PDAC dataset. The high-risk designation was closely connected with oncological signatures and multiple aggressiveness-related pathways, as determined by gene set enrichment analysis (GSEA). In summary, our study developed a three-gene signature and established a prognostic nomogram that objectively predicted overall survival in PDAC. The findings could provide a reference for the prediction of overall survival and could aid in individualized management for PDAC patients.</description><identifier>ISSN: 1945-4589</identifier><identifier>EISSN: 1945-4589</identifier><identifier>DOI: 10.18632/aging.104134</identifier><identifier>PMID: 33226369</identifier><language>eng</language><publisher>United States: Impact Journals</publisher><subject>Biomarkers, Tumor - genetics ; Carcinoma, Pancreatic Ductal - genetics ; Carcinoma, Pancreatic Ductal - metabolism ; Carcinoma, Pancreatic Ductal - mortality ; Carcinoma, Pancreatic Ductal - therapy ; Cellular Reprogramming ; Databases, Genetic ; Decision Support Techniques ; Energy Metabolism - genetics ; Female ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Germ-Line Mutation ; Humans ; Male ; Nomograms ; Pancreatic Neoplasms - genetics ; Pancreatic Neoplasms - metabolism ; Pancreatic Neoplasms - mortality ; Pancreatic Neoplasms - therapy ; Predictive Value of Tests ; Prognosis ; Reproducibility of Results ; Research Paper ; Risk Assessment ; Risk Factors ; Signal Transduction ; Transcriptome</subject><ispartof>Aging (Albany, NY.), 2020-11, Vol.12 (23), p.24228-24241</ispartof><rights>Copyright: © 2020 Tan et al.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c453t-85699b999faeb172cba36c23fce6b53d13afc264c1dcc1a4345dab54079ee373</citedby><cites>FETCH-LOGICAL-c453t-85699b999faeb172cba36c23fce6b53d13afc264c1dcc1a4345dab54079ee373</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/PMC7762467/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762467/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,882,27905,27906,53772,53774</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33226369$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tan, Zhen</creatorcontrib><creatorcontrib>Lei, Yubin</creatorcontrib><creatorcontrib>Xu, Jin</creatorcontrib><creatorcontrib>Shi, Si</creatorcontrib><creatorcontrib>Hua, Jie</creatorcontrib><creatorcontrib>Zhang, Bo</creatorcontrib><creatorcontrib>Meng, Qingcai</creatorcontrib><creatorcontrib>Liu, Jiang</creatorcontrib><creatorcontrib>Zhang, Yiyin</creatorcontrib><creatorcontrib>Wei, Miaoyan</creatorcontrib><creatorcontrib>Yu, Xianjun</creatorcontrib><creatorcontrib>Liang, Chen</creatorcontrib><title>The value of a metabolic reprogramming-related gene signature for pancreatic adenocarcinoma prognosis prediction</title><title>Aging (Albany, NY.)</title><addtitle>Aging (Albany NY)</addtitle><description>Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. Extensive enhancement of glycolysis and reprogramming of lipid metabolism are both associated with the development and progression of PDAC. Previous studies have suggested that various gene signatures could convey prognostic information about PDAC. However, the use of these signatures has some limitations, perhaps because of a lack of knowledge regarding the genetic and energy supply backgrounds of PDAC. Therefore, we conducted multi-mRNA analysis based on metabolic reprogramming to identify novel signatures for accurate prognosis prediction in PDAC patients. In this study, a three-gene signature comprising MET, ENO3 and CD36 was established to predict the overall survival of PDAC patients. The three-gene signature could divide patients into high- and low-risk groups by disparities in overall survival verified by log-rank test in two independent validation cohorts and could differentiate tumors from normal tissues with excellent accuracy in four Gene Expression Omnibus (GEO) cohorts. We also found a positive correlation between the risk score of the gene signature and inherited germline mutations in PDAC predisposition genes. A glycolysis and lipid metabolism-based gene nomogram and corresponding calibration curves showed significant performance for survival prediction in the TCGA-PDAC dataset. The high-risk designation was closely connected with oncological signatures and multiple aggressiveness-related pathways, as determined by gene set enrichment analysis (GSEA). In summary, our study developed a three-gene signature and established a prognostic nomogram that objectively predicted overall survival in PDAC. The findings could provide a reference for the prediction of overall survival and could aid in individualized management for PDAC patients.</description><subject>Biomarkers, Tumor - genetics</subject><subject>Carcinoma, Pancreatic Ductal - genetics</subject><subject>Carcinoma, Pancreatic Ductal - metabolism</subject><subject>Carcinoma, Pancreatic Ductal - mortality</subject><subject>Carcinoma, Pancreatic Ductal - therapy</subject><subject>Cellular Reprogramming</subject><subject>Databases, Genetic</subject><subject>Decision Support Techniques</subject><subject>Energy Metabolism - genetics</subject><subject>Female</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Germ-Line Mutation</subject><subject>Humans</subject><subject>Male</subject><subject>Nomograms</subject><subject>Pancreatic Neoplasms - genetics</subject><subject>Pancreatic Neoplasms - metabolism</subject><subject>Pancreatic Neoplasms - mortality</subject><subject>Pancreatic Neoplasms - therapy</subject><subject>Predictive Value of Tests</subject><subject>Prognosis</subject><subject>Reproducibility of Results</subject><subject>Research Paper</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>Signal Transduction</subject><subject>Transcriptome</subject><issn>1945-4589</issn><issn>1945-4589</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVkctLxDAQh4Morq-jV8nRS7VpHt1cBBFfIHjZe5im0xppk5q0C_73Vndd9DQD8803Az9Czll-xZaKF9fQOt9esVwwLvbIEdNCZkIu9f6ffkGOU3rPcyWlUIdkwXlRKK70ERlWb0jX0E1IQ0OB9jhCFTpnacQhhjZC38_-LGIHI9a0RY80udbDOEWkTYh0AG8jwjjvQI0-WIjW-dAD_Rb4kFyaO6ydHV3wp-SggS7h2baekNXD_eruKXt5fXy-u33JrJB8zJZSaV1prRvAipWFrYArW_DGoqokrxmHxhZKWFZby0BwIWuopMhLjchLfkJuNtphqnqsLfoxQmeG6HqInyaAM_8n3r2ZNqxNWapCqG_B5VYQw8eEaTS9Sxa7DjyGKZkZ4ipXS6VnNNugNoaUIja7Myw3PyGZn5DMJqSZv_j7247-TYV_AVjYkp0</recordid><startdate>20201120</startdate><enddate>20201120</enddate><creator>Tan, Zhen</creator><creator>Lei, Yubin</creator><creator>Xu, Jin</creator><creator>Shi, Si</creator><creator>Hua, Jie</creator><creator>Zhang, Bo</creator><creator>Meng, Qingcai</creator><creator>Liu, Jiang</creator><creator>Zhang, Yiyin</creator><creator>Wei, Miaoyan</creator><creator>Yu, Xianjun</creator><creator>Liang, Chen</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>20201120</creationdate><title>The value of a metabolic reprogramming-related gene signature for pancreatic adenocarcinoma prognosis prediction</title><author>Tan, Zhen ; Lei, Yubin ; Xu, Jin ; Shi, Si ; Hua, Jie ; Zhang, Bo ; Meng, Qingcai ; Liu, Jiang ; Zhang, Yiyin ; Wei, Miaoyan ; Yu, Xianjun ; Liang, Chen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c453t-85699b999faeb172cba36c23fce6b53d13afc264c1dcc1a4345dab54079ee373</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Biomarkers, Tumor - genetics</topic><topic>Carcinoma, Pancreatic Ductal - genetics</topic><topic>Carcinoma, Pancreatic Ductal - metabolism</topic><topic>Carcinoma, Pancreatic Ductal - mortality</topic><topic>Carcinoma, Pancreatic Ductal - therapy</topic><topic>Cellular Reprogramming</topic><topic>Databases, Genetic</topic><topic>Decision Support Techniques</topic><topic>Energy Metabolism - genetics</topic><topic>Female</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Germ-Line Mutation</topic><topic>Humans</topic><topic>Male</topic><topic>Nomograms</topic><topic>Pancreatic Neoplasms - genetics</topic><topic>Pancreatic Neoplasms - metabolism</topic><topic>Pancreatic Neoplasms - mortality</topic><topic>Pancreatic Neoplasms - therapy</topic><topic>Predictive Value of Tests</topic><topic>Prognosis</topic><topic>Reproducibility of Results</topic><topic>Research Paper</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>Signal Transduction</topic><topic>Transcriptome</topic><toplevel>online_resources</toplevel><creatorcontrib>Tan, Zhen</creatorcontrib><creatorcontrib>Lei, Yubin</creatorcontrib><creatorcontrib>Xu, Jin</creatorcontrib><creatorcontrib>Shi, Si</creatorcontrib><creatorcontrib>Hua, Jie</creatorcontrib><creatorcontrib>Zhang, Bo</creatorcontrib><creatorcontrib>Meng, Qingcai</creatorcontrib><creatorcontrib>Liu, Jiang</creatorcontrib><creatorcontrib>Zhang, Yiyin</creatorcontrib><creatorcontrib>Wei, Miaoyan</creatorcontrib><creatorcontrib>Yu, Xianjun</creatorcontrib><creatorcontrib>Liang, Chen</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>Tan, Zhen</au><au>Lei, Yubin</au><au>Xu, Jin</au><au>Shi, Si</au><au>Hua, Jie</au><au>Zhang, Bo</au><au>Meng, Qingcai</au><au>Liu, Jiang</au><au>Zhang, Yiyin</au><au>Wei, Miaoyan</au><au>Yu, Xianjun</au><au>Liang, Chen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The value of a metabolic reprogramming-related gene signature for pancreatic adenocarcinoma prognosis prediction</atitle><jtitle>Aging (Albany, NY.)</jtitle><addtitle>Aging (Albany NY)</addtitle><date>2020-11-20</date><risdate>2020</risdate><volume>12</volume><issue>23</issue><spage>24228</spage><epage>24241</epage><pages>24228-24241</pages><issn>1945-4589</issn><eissn>1945-4589</eissn><abstract>Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. Extensive enhancement of glycolysis and reprogramming of lipid metabolism are both associated with the development and progression of PDAC. Previous studies have suggested that various gene signatures could convey prognostic information about PDAC. However, the use of these signatures has some limitations, perhaps because of a lack of knowledge regarding the genetic and energy supply backgrounds of PDAC. Therefore, we conducted multi-mRNA analysis based on metabolic reprogramming to identify novel signatures for accurate prognosis prediction in PDAC patients. In this study, a three-gene signature comprising MET, ENO3 and CD36 was established to predict the overall survival of PDAC patients. The three-gene signature could divide patients into high- and low-risk groups by disparities in overall survival verified by log-rank test in two independent validation cohorts and could differentiate tumors from normal tissues with excellent accuracy in four Gene Expression Omnibus (GEO) cohorts. We also found a positive correlation between the risk score of the gene signature and inherited germline mutations in PDAC predisposition genes. A glycolysis and lipid metabolism-based gene nomogram and corresponding calibration curves showed significant performance for survival prediction in the TCGA-PDAC dataset. The high-risk designation was closely connected with oncological signatures and multiple aggressiveness-related pathways, as determined by gene set enrichment analysis (GSEA). In summary, our study developed a three-gene signature and established a prognostic nomogram that objectively predicted overall survival in PDAC. The findings could provide a reference for the prediction of overall survival and could aid in individualized management for PDAC patients.</abstract><cop>United States</cop><pub>Impact Journals</pub><pmid>33226369</pmid><doi>10.18632/aging.104134</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Biomarkers, Tumor - genetics Carcinoma, Pancreatic Ductal - genetics Carcinoma, Pancreatic Ductal - metabolism Carcinoma, Pancreatic Ductal - mortality Carcinoma, Pancreatic Ductal - therapy Cellular Reprogramming Databases, Genetic Decision Support Techniques Energy Metabolism - genetics Female Gene Expression Profiling Gene Expression Regulation, Neoplastic Germ-Line Mutation Humans Male Nomograms Pancreatic Neoplasms - genetics Pancreatic Neoplasms - metabolism Pancreatic Neoplasms - mortality Pancreatic Neoplasms - therapy Predictive Value of Tests Prognosis Reproducibility of Results Research Paper Risk Assessment Risk Factors Signal Transduction Transcriptome |
title | The value of a metabolic reprogramming-related gene signature for pancreatic adenocarcinoma prognosis prediction |
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