Supervised learning reveals circulating biomarker levels diagnostic of hepatocellular carcinoma in a clinically relevant model of non-alcoholic steatohepatitis; An OAD to NASH
Although cirrhosis is a key risk factor for the development of hepatocellular carcinoma (HCC), mounting evidence indicates that in a subset of patients presenting with non-alcoholic steatohepatitis (NASH) HCC manifests in the absence of cirrhosis. Given the sheer size of the ongoing non-alcoholic fa...
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| Veröffentlicht in: | PloS one 2018-06, Vol.13 (6), p.e0198937-e0198937 |
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| creator | Hwang, Anne Shi, Christopher Zhu, Edward Naaz, Farha Zhou, Ping Rasheed, Zainab Liu, Michelle Jung, Lindsey S Duan, Bin Li, Jingsong Jiang, Kai Paka, Latha Gadhiya, Satishkumar V Dana, Dibyendu Ali, Quaisar Yamin, Michael A Goldberg, Itzhak D Narayan, Prakash |
| description | Although cirrhosis is a key risk factor for the development of hepatocellular carcinoma (HCC), mounting evidence indicates that in a subset of patients presenting with non-alcoholic steatohepatitis (NASH) HCC manifests in the absence of cirrhosis. Given the sheer size of the ongoing non-alcoholic fatty liver disease (NAFLD) epidemic and the dismal prognosis associated with late-stage primary liver cancer there is an urgent need for HCC surveillance in the NASH population. Using serum levels of HCC biomarkers as vectors and biopsy-proven HCC or no HCC as outputs / binary classifier, a supervised learning campaign was undertaken to develop a minimally invasive technique for making a diagnosis of HCC in a clinically relevant model of NASH. Adult mice randomized to control diet or a fast food diet (FFD) were followed for up to 14 mo and serum level of a panel of HCC-relevant biomarkers was compared with liver biopsies at 3 and 14 mo. Both NAFLD Activity Score (NAS) and hepatic hydroxyproline content were elevated at 3 and 14 mo on FFD. Picrosirius red staining of liver sections revealed a filigree pattern of fibrillar collagen deposition with no cirrhosis at 14 mo on FFD. Nevertheless, 46% of animals bore one or more tumors on their livers confirmed as HCC in hematoxylin-eosin-stained liver sections. In this training set, receiver operating characteristic (ROC) curves analysis for serum levels of the HCC biomarkers osteopontin (OPN), alpha-fetoprotein (AFP) and Dickkopf-1 (DKK1) returned concordance-statistic/area under ROC curve of ≥ 0.89. Serum levels of OPN (threshold, 218 ng/mL; sensitivity, 82%; specificity, 86%), AFP (136 ng/mL; 91%; 97%) and DKK1 (2.4 ng/mL; 82%; 81%) diagnostic for HCC were confirmed in a test set comprising mice on control diet or FFD and mice subjected to hepatic ischemia-reperfusion injury. These data suggest that levels of circulating OPN, AFP and DKK1 can be used to make a diagnosis of HCC in a clinically relevant model of NASH. |
| doi_str_mv | 10.1371/journal.pone.0198937 |
| format | Article |
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Given the sheer size of the ongoing non-alcoholic fatty liver disease (NAFLD) epidemic and the dismal prognosis associated with late-stage primary liver cancer there is an urgent need for HCC surveillance in the NASH population. Using serum levels of HCC biomarkers as vectors and biopsy-proven HCC or no HCC as outputs / binary classifier, a supervised learning campaign was undertaken to develop a minimally invasive technique for making a diagnosis of HCC in a clinically relevant model of NASH. Adult mice randomized to control diet or a fast food diet (FFD) were followed for up to 14 mo and serum level of a panel of HCC-relevant biomarkers was compared with liver biopsies at 3 and 14 mo. Both NAFLD Activity Score (NAS) and hepatic hydroxyproline content were elevated at 3 and 14 mo on FFD. Picrosirius red staining of liver sections revealed a filigree pattern of fibrillar collagen deposition with no cirrhosis at 14 mo on FFD. Nevertheless, 46% of animals bore one or more tumors on their livers confirmed as HCC in hematoxylin-eosin-stained liver sections. In this training set, receiver operating characteristic (ROC) curves analysis for serum levels of the HCC biomarkers osteopontin (OPN), alpha-fetoprotein (AFP) and Dickkopf-1 (DKK1) returned concordance-statistic/area under ROC curve of ≥ 0.89. Serum levels of OPN (threshold, 218 ng/mL; sensitivity, 82%; specificity, 86%), AFP (136 ng/mL; 91%; 97%) and DKK1 (2.4 ng/mL; 82%; 81%) diagnostic for HCC were confirmed in a test set comprising mice on control diet or FFD and mice subjected to hepatic ischemia-reperfusion injury. These data suggest that levels of circulating OPN, AFP and DKK1 can be used to make a diagnosis of HCC in a clinically relevant model of NASH.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0198937</identifier><identifier>PMID: 29944670</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Animals ; Biocompatibility ; Biological markers ; Biology and Life Sciences ; Biomarkers ; Biomarkers, Tumor - blood ; Biomedical materials ; Biopsy ; Carcinoma, Hepatocellular - blood ; Carcinoma, Hepatocellular - diagnosis ; Carcinoma, Hepatocellular - pathology ; Cirrhosis ; Collagen ; Diagnosis ; Diagnostic systems ; Diet ; Disease Models, Animal ; Dkk1 protein ; Epidemics ; Fast food ; Fatty liver ; Gastroenterology ; Health aspects ; Hepatocellular carcinoma ; Humans ; Hydroxyproline ; Identification and classification ; Ischemia ; Liver ; Liver - pathology ; Liver cancer ; Liver cirrhosis ; Liver diseases ; Liver Neoplasms - blood ; Liver Neoplasms - diagnosis ; Liver Neoplasms - pathology ; Male ; Medical diagnosis ; Medical prognosis ; Medical research ; Medicine and Health Sciences ; Mice ; Mice, Inbred C57BL ; Non-alcoholic Fatty Liver Disease - blood ; Non-alcoholic Fatty Liver Disease - diagnosis ; Non-alcoholic Fatty Liver Disease - pathology ; Osteopontin ; Reperfusion ; Research and Analysis Methods ; Risk factors ; Rodents ; Serum levels ; Supervised learning ; Supervised Machine Learning ; Surveillance ; Tidal bores ; Tumors ; α-Fetoprotein</subject><ispartof>PloS one, 2018-06, Vol.13 (6), p.e0198937-e0198937</ispartof><rights>COPYRIGHT 2018 Public Library of Science</rights><rights>2018 Hwang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Given the sheer size of the ongoing non-alcoholic fatty liver disease (NAFLD) epidemic and the dismal prognosis associated with late-stage primary liver cancer there is an urgent need for HCC surveillance in the NASH population. Using serum levels of HCC biomarkers as vectors and biopsy-proven HCC or no HCC as outputs / binary classifier, a supervised learning campaign was undertaken to develop a minimally invasive technique for making a diagnosis of HCC in a clinically relevant model of NASH. Adult mice randomized to control diet or a fast food diet (FFD) were followed for up to 14 mo and serum level of a panel of HCC-relevant biomarkers was compared with liver biopsies at 3 and 14 mo. Both NAFLD Activity Score (NAS) and hepatic hydroxyproline content were elevated at 3 and 14 mo on FFD. Picrosirius red staining of liver sections revealed a filigree pattern of fibrillar collagen deposition with no cirrhosis at 14 mo on FFD. Nevertheless, 46% of animals bore one or more tumors on their livers confirmed as HCC in hematoxylin-eosin-stained liver sections. In this training set, receiver operating characteristic (ROC) curves analysis for serum levels of the HCC biomarkers osteopontin (OPN), alpha-fetoprotein (AFP) and Dickkopf-1 (DKK1) returned concordance-statistic/area under ROC curve of ≥ 0.89. Serum levels of OPN (threshold, 218 ng/mL; sensitivity, 82%; specificity, 86%), AFP (136 ng/mL; 91%; 97%) and DKK1 (2.4 ng/mL; 82%; 81%) diagnostic for HCC were confirmed in a test set comprising mice on control diet or FFD and mice subjected to hepatic ischemia-reperfusion injury. 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factors</subject><subject>Rodents</subject><subject>Serum levels</subject><subject>Supervised learning</subject><subject>Supervised Machine Learning</subject><subject>Surveillance</subject><subject>Tidal 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Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</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>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hwang, Anne</au><au>Shi, Christopher</au><au>Zhu, Edward</au><au>Naaz, Farha</au><au>Zhou, Ping</au><au>Rasheed, Zainab</au><au>Liu, Michelle</au><au>Jung, Lindsey S</au><au>Duan, Bin</au><au>Li, Jingsong</au><au>Jiang, Kai</au><au>Paka, Latha</au><au>Gadhiya, Satishkumar V</au><au>Dana, Dibyendu</au><au>Ali, Quaisar</au><au>Yamin, Michael A</au><au>Goldberg, Itzhak D</au><au>Narayan, Prakash</au><au>Narayan, Mahesh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Supervised learning reveals circulating biomarker levels diagnostic of hepatocellular carcinoma in a clinically relevant model of non-alcoholic steatohepatitis; An OAD to NASH</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2018-06-26</date><risdate>2018</risdate><volume>13</volume><issue>6</issue><spage>e0198937</spage><epage>e0198937</epage><pages>e0198937-e0198937</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Although cirrhosis is a key risk factor for the development of hepatocellular carcinoma (HCC), mounting evidence indicates that in a subset of patients presenting with non-alcoholic steatohepatitis (NASH) HCC manifests in the absence of cirrhosis. Given the sheer size of the ongoing non-alcoholic fatty liver disease (NAFLD) epidemic and the dismal prognosis associated with late-stage primary liver cancer there is an urgent need for HCC surveillance in the NASH population. Using serum levels of HCC biomarkers as vectors and biopsy-proven HCC or no HCC as outputs / binary classifier, a supervised learning campaign was undertaken to develop a minimally invasive technique for making a diagnosis of HCC in a clinically relevant model of NASH. Adult mice randomized to control diet or a fast food diet (FFD) were followed for up to 14 mo and serum level of a panel of HCC-relevant biomarkers was compared with liver biopsies at 3 and 14 mo. Both NAFLD Activity Score (NAS) and hepatic hydroxyproline content were elevated at 3 and 14 mo on FFD. Picrosirius red staining of liver sections revealed a filigree pattern of fibrillar collagen deposition with no cirrhosis at 14 mo on FFD. Nevertheless, 46% of animals bore one or more tumors on their livers confirmed as HCC in hematoxylin-eosin-stained liver sections. In this training set, receiver operating characteristic (ROC) curves analysis for serum levels of the HCC biomarkers osteopontin (OPN), alpha-fetoprotein (AFP) and Dickkopf-1 (DKK1) returned concordance-statistic/area under ROC curve of ≥ 0.89. Serum levels of OPN (threshold, 218 ng/mL; sensitivity, 82%; specificity, 86%), AFP (136 ng/mL; 91%; 97%) and DKK1 (2.4 ng/mL; 82%; 81%) diagnostic for HCC were confirmed in a test set comprising mice on control diet or FFD and mice subjected to hepatic ischemia-reperfusion injury. These data suggest that levels of circulating OPN, AFP and DKK1 can be used to make a diagnosis of HCC in a clinically relevant model of NASH.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>29944670</pmid><doi>10.1371/journal.pone.0198937</doi><tpages>e0198937</tpages><orcidid>https://orcid.org/0000-0002-7007-0245</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2018-06, Vol.13 (6), p.e0198937-e0198937 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2059529035 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Animals Biocompatibility Biological markers Biology and Life Sciences Biomarkers Biomarkers, Tumor - blood Biomedical materials Biopsy Carcinoma, Hepatocellular - blood Carcinoma, Hepatocellular - diagnosis Carcinoma, Hepatocellular - pathology Cirrhosis Collagen Diagnosis Diagnostic systems Diet Disease Models, Animal Dkk1 protein Epidemics Fast food Fatty liver Gastroenterology Health aspects Hepatocellular carcinoma Humans Hydroxyproline Identification and classification Ischemia Liver Liver - pathology Liver cancer Liver cirrhosis Liver diseases Liver Neoplasms - blood Liver Neoplasms - diagnosis Liver Neoplasms - pathology Male Medical diagnosis Medical prognosis Medical research Medicine and Health Sciences Mice Mice, Inbred C57BL Non-alcoholic Fatty Liver Disease - blood Non-alcoholic Fatty Liver Disease - diagnosis Non-alcoholic Fatty Liver Disease - pathology Osteopontin Reperfusion Research and Analysis Methods Risk factors Rodents Serum levels Supervised learning Supervised Machine Learning Surveillance Tidal bores Tumors α-Fetoprotein |
| title | Supervised learning reveals circulating biomarker levels diagnostic of hepatocellular carcinoma in a clinically relevant model of non-alcoholic steatohepatitis; An OAD to NASH |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T09%3A52%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Supervised%20learning%20reveals%20circulating%20biomarker%20levels%20diagnostic%20of%20hepatocellular%20carcinoma%20in%20a%20clinically%20relevant%20model%20of%20non-alcoholic%20steatohepatitis;%20An%20OAD%20to%20NASH&rft.jtitle=PloS%20one&rft.au=Hwang,%20Anne&rft.date=2018-06-26&rft.volume=13&rft.issue=6&rft.spage=e0198937&rft.epage=e0198937&rft.pages=e0198937-e0198937&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0198937&rft_dat=%3Cgale_plos_%3EA544467198%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2059529035&rft_id=info:pmid/29944670&rft_galeid=A544467198&rft_doaj_id=oai_doaj_org_article_1518570945cf4c56b70a89b77545c7f9&rfr_iscdi=true |