Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis
Toxic industrial chemicals induce liver injury, which is difficult to diagnose without invasive procedures. Identifying indicators of end organ injury can complement exposure-based assays and improve predictive power. A multiplexed approach was used to experimentally evaluate a panel of 67 genes pre...
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creator | Ippolito,Danielle L AbdulHameed,Mohamed D Tawa,Gregory J Baer,Christine E Permenter,Matthew G McDyre,Bonna C Dennis,William E Boyle,Molly H Hobbs,Cheryl A Streicker,Michael A Snowden,Bobbi S Lewis,John A Wallqvist,Anders Stallings,Jonathan D |
description | Toxic industrial chemicals induce liver injury, which is difficult to diagnose without invasive procedures. Identifying indicators of end organ injury can complement exposure-based assays and improve predictive power. A multiplexed approach was used to experimentally evaluate a panel of 67 genes predicted to be associated with the fibrosis pathology by computationally mining Drug Matrix, a publicly available repository of gene microarray data. Five-day oral gavage studies in male Sprague Dawley rats dosed with varying concentrations of 3 fibrogenic compounds (allyl alcohol, carbon tetrachloride, and 4,40-methylenedianiline) and 2 nonfibrogenic compounds (bromobenzene and dexamethasone) were conducted. Fibrosis was definitively diagnosed by histopathology. The 67-plex gene panel accurately diagnosed fibrosis in both microarray and multiplexed-gene expression assays. Necrosis and inflammatory infiltration were comorbid with fibrosis. ANOVA with contrasts identified that 51 of the 67 predicted genes were significantly associated with the fibrosis phenotype,with 24 of these specific to fibrosis alone. The protein product of the gene most strongly correlated with the fibrosis phenotype PCOLCE (Procollagen C-Endopeptidase Enhancer) was dose-dependently elevated in plasma from animals administered fibrogenic chemicals (P.05). Semiquantitative global mass spectrometry analysis of the plasma identified an additional 5 protein products of the gene panel which increased after fibrogenic toxicant administration: fibronectin, ceruloplasmin, vitronectin, insulin-like growth factor binding protein, and a2-macroglobulin. These results support the data mining approach for identifying gene and/or protein panels for assessing liver injury and may suggest bridging biomarkers for molecular mediators linked to histopathology.
Toxicological Sciences , 149, 1, 01 Jan 0001, 01 Jan 0001, |
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Toxicological Sciences , 149, 1, 01 Jan 0001, 01 Jan 0001,</description><language>eng</language><subject>biomarkers ; BIOMEDICAL INFORMATION SYSTEMS ; computation science ; data mining ; DrugMatrix ; fibrosis ; gene expression ; gene microarray data ; Histopathology ; LIVER DISEASES ; MASS SPECTROMETRY ; multiplexed-gene expression assays ; rats ; TOXIC AGENTS ; toxic liver injury ; transcriptomics</subject><creationdate>2016</creationdate><rights>Approved For Public Release</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,780,885,27567,27568</link.rule.ids><linktorsrc>$$Uhttps://apps.dtic.mil/sti/citations/AD1003890$$EView_record_in_DTIC$$FView_record_in_$$GDTIC$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Ippolito,Danielle L</creatorcontrib><creatorcontrib>AbdulHameed,Mohamed D</creatorcontrib><creatorcontrib>Tawa,Gregory J</creatorcontrib><creatorcontrib>Baer,Christine E</creatorcontrib><creatorcontrib>Permenter,Matthew G</creatorcontrib><creatorcontrib>McDyre,Bonna C</creatorcontrib><creatorcontrib>Dennis,William E</creatorcontrib><creatorcontrib>Boyle,Molly H</creatorcontrib><creatorcontrib>Hobbs,Cheryl A</creatorcontrib><creatorcontrib>Streicker,Michael A</creatorcontrib><creatorcontrib>Snowden,Bobbi S</creatorcontrib><creatorcontrib>Lewis,John A</creatorcontrib><creatorcontrib>Wallqvist,Anders</creatorcontrib><creatorcontrib>Stallings,Jonathan D</creatorcontrib><creatorcontrib>Army Center for Environmental Health Research Fort Detrick United States</creatorcontrib><title>Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis</title><description>Toxic industrial chemicals induce liver injury, which is difficult to diagnose without invasive procedures. Identifying indicators of end organ injury can complement exposure-based assays and improve predictive power. A multiplexed approach was used to experimentally evaluate a panel of 67 genes predicted to be associated with the fibrosis pathology by computationally mining Drug Matrix, a publicly available repository of gene microarray data. Five-day oral gavage studies in male Sprague Dawley rats dosed with varying concentrations of 3 fibrogenic compounds (allyl alcohol, carbon tetrachloride, and 4,40-methylenedianiline) and 2 nonfibrogenic compounds (bromobenzene and dexamethasone) were conducted. Fibrosis was definitively diagnosed by histopathology. The 67-plex gene panel accurately diagnosed fibrosis in both microarray and multiplexed-gene expression assays. Necrosis and inflammatory infiltration were comorbid with fibrosis. ANOVA with contrasts identified that 51 of the 67 predicted genes were significantly associated with the fibrosis phenotype,with 24 of these specific to fibrosis alone. The protein product of the gene most strongly correlated with the fibrosis phenotype PCOLCE (Procollagen C-Endopeptidase Enhancer) was dose-dependently elevated in plasma from animals administered fibrogenic chemicals (P.05). Semiquantitative global mass spectrometry analysis of the plasma identified an additional 5 protein products of the gene panel which increased after fibrogenic toxicant administration: fibronectin, ceruloplasmin, vitronectin, insulin-like growth factor binding protein, and a2-macroglobulin. These results support the data mining approach for identifying gene and/or protein panels for assessing liver injury and may suggest bridging biomarkers for molecular mediators linked to histopathology.
Toxicological Sciences , 149, 1, 01 Jan 0001, 01 Jan 0001,</description><subject>biomarkers</subject><subject>BIOMEDICAL INFORMATION SYSTEMS</subject><subject>computation science</subject><subject>data mining</subject><subject>DrugMatrix</subject><subject>fibrosis</subject><subject>gene expression</subject><subject>gene microarray data</subject><subject>Histopathology</subject><subject>LIVER DISEASES</subject><subject>MASS SPECTROMETRY</subject><subject>multiplexed-gene expression assays</subject><subject>rats</subject><subject>TOXIC AGENTS</subject><subject>toxic liver injury</subject><subject>transcriptomics</subject><fulltext>true</fulltext><rsrctype>report</rsrctype><creationdate>2016</creationdate><recordtype>report</recordtype><sourceid>1RU</sourceid><recordid>eNqFyTEKwkAQBdBtLES9gcVcQFhJo2XQxBSCFgHLsCYT8yHshJ1B4u1t7K1e8ZbuduHIVMxTYlVIpHsw4xSVclVpEYw7esAGqqAmU7BBRnl9CJFqmdHSFW9OVOKZRKFrt-jDqLz5uXLbsqhP1a4ztI0aIluTn_feZ4ejz_70FzaTM_U</recordid><startdate>20160509</startdate><enddate>20160509</enddate><creator>Ippolito,Danielle L</creator><creator>AbdulHameed,Mohamed D</creator><creator>Tawa,Gregory J</creator><creator>Baer,Christine E</creator><creator>Permenter,Matthew G</creator><creator>McDyre,Bonna C</creator><creator>Dennis,William E</creator><creator>Boyle,Molly H</creator><creator>Hobbs,Cheryl A</creator><creator>Streicker,Michael A</creator><creator>Snowden,Bobbi S</creator><creator>Lewis,John A</creator><creator>Wallqvist,Anders</creator><creator>Stallings,Jonathan D</creator><scope>1RU</scope><scope>BHM</scope></search><sort><creationdate>20160509</creationdate><title>Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis</title><author>Ippolito,Danielle L ; AbdulHameed,Mohamed D ; Tawa,Gregory J ; Baer,Christine E ; Permenter,Matthew G ; McDyre,Bonna C ; Dennis,William E ; Boyle,Molly H ; Hobbs,Cheryl A ; Streicker,Michael A ; Snowden,Bobbi S ; Lewis,John A ; Wallqvist,Anders ; Stallings,Jonathan D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-dtic_stinet_AD10038903</frbrgroupid><rsrctype>reports</rsrctype><prefilter>reports</prefilter><language>eng</language><creationdate>2016</creationdate><topic>biomarkers</topic><topic>BIOMEDICAL INFORMATION SYSTEMS</topic><topic>computation science</topic><topic>data mining</topic><topic>DrugMatrix</topic><topic>fibrosis</topic><topic>gene expression</topic><topic>gene microarray data</topic><topic>Histopathology</topic><topic>LIVER DISEASES</topic><topic>MASS SPECTROMETRY</topic><topic>multiplexed-gene expression assays</topic><topic>rats</topic><topic>TOXIC AGENTS</topic><topic>toxic liver injury</topic><topic>transcriptomics</topic><toplevel>online_resources</toplevel><creatorcontrib>Ippolito,Danielle L</creatorcontrib><creatorcontrib>AbdulHameed,Mohamed D</creatorcontrib><creatorcontrib>Tawa,Gregory J</creatorcontrib><creatorcontrib>Baer,Christine E</creatorcontrib><creatorcontrib>Permenter,Matthew G</creatorcontrib><creatorcontrib>McDyre,Bonna C</creatorcontrib><creatorcontrib>Dennis,William E</creatorcontrib><creatorcontrib>Boyle,Molly H</creatorcontrib><creatorcontrib>Hobbs,Cheryl A</creatorcontrib><creatorcontrib>Streicker,Michael A</creatorcontrib><creatorcontrib>Snowden,Bobbi S</creatorcontrib><creatorcontrib>Lewis,John A</creatorcontrib><creatorcontrib>Wallqvist,Anders</creatorcontrib><creatorcontrib>Stallings,Jonathan D</creatorcontrib><creatorcontrib>Army Center for Environmental Health Research Fort Detrick United States</creatorcontrib><collection>DTIC Technical Reports</collection><collection>DTIC STINET</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ippolito,Danielle L</au><au>AbdulHameed,Mohamed D</au><au>Tawa,Gregory J</au><au>Baer,Christine E</au><au>Permenter,Matthew G</au><au>McDyre,Bonna C</au><au>Dennis,William E</au><au>Boyle,Molly H</au><au>Hobbs,Cheryl A</au><au>Streicker,Michael A</au><au>Snowden,Bobbi S</au><au>Lewis,John A</au><au>Wallqvist,Anders</au><au>Stallings,Jonathan D</au><aucorp>Army Center for Environmental Health Research Fort Detrick United States</aucorp><format>book</format><genre>unknown</genre><ristype>RPRT</ristype><btitle>Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis</btitle><date>2016-05-09</date><risdate>2016</risdate><abstract>Toxic industrial chemicals induce liver injury, which is difficult to diagnose without invasive procedures. Identifying indicators of end organ injury can complement exposure-based assays and improve predictive power. A multiplexed approach was used to experimentally evaluate a panel of 67 genes predicted to be associated with the fibrosis pathology by computationally mining Drug Matrix, a publicly available repository of gene microarray data. Five-day oral gavage studies in male Sprague Dawley rats dosed with varying concentrations of 3 fibrogenic compounds (allyl alcohol, carbon tetrachloride, and 4,40-methylenedianiline) and 2 nonfibrogenic compounds (bromobenzene and dexamethasone) were conducted. Fibrosis was definitively diagnosed by histopathology. The 67-plex gene panel accurately diagnosed fibrosis in both microarray and multiplexed-gene expression assays. Necrosis and inflammatory infiltration were comorbid with fibrosis. ANOVA with contrasts identified that 51 of the 67 predicted genes were significantly associated with the fibrosis phenotype,with 24 of these specific to fibrosis alone. The protein product of the gene most strongly correlated with the fibrosis phenotype PCOLCE (Procollagen C-Endopeptidase Enhancer) was dose-dependently elevated in plasma from animals administered fibrogenic chemicals (P.05). Semiquantitative global mass spectrometry analysis of the plasma identified an additional 5 protein products of the gene panel which increased after fibrogenic toxicant administration: fibronectin, ceruloplasmin, vitronectin, insulin-like growth factor binding protein, and a2-macroglobulin. These results support the data mining approach for identifying gene and/or protein panels for assessing liver injury and may suggest bridging biomarkers for molecular mediators linked to histopathology.
Toxicological Sciences , 149, 1, 01 Jan 0001, 01 Jan 0001,</abstract><oa>free_for_read</oa></addata></record> |
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subjects | biomarkers BIOMEDICAL INFORMATION SYSTEMS computation science data mining DrugMatrix fibrosis gene expression gene microarray data Histopathology LIVER DISEASES MASS SPECTROMETRY multiplexed-gene expression assays rats TOXIC AGENTS toxic liver injury transcriptomics |
title | Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis |
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