Integrated analysis of the faecal metagenome and serum metabolome reveals the role of gut microbiome-associated metabolites in the detection of colorectal cancer and adenoma
ObjectiveTo profile gut microbiome-associated metabolites in serum and investigate whether these metabolites could distinguish individuals with colorectal cancer (CRC) or adenoma from normal healthy individuals.DesignIntegrated analysis of untargeted serum metabolomics by liquid chromatography-mass...
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| Veröffentlicht in: | Gut 2022-07, Vol.71 (7), p.1315-1325 |
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| creator | Chen, Feng Dai, Xudong Zhou, Chang-Chun Li, Ke-xin Zhang, Yu-juan Lou, Xiao-Ying Zhu, Yuan-Min Sun, Yan-Lai Peng, Bao-Xiang Cui, Wei |
| description | ObjectiveTo profile gut microbiome-associated metabolites in serum and investigate whether these metabolites could distinguish individuals with colorectal cancer (CRC) or adenoma from normal healthy individuals.DesignIntegrated analysis of untargeted serum metabolomics by liquid chromatography-mass spectrometry and metagenome sequencing of paired faecal samples was applied to identify gut microbiome-associated metabolites with significantly altered abundance in patients with CRC and adenoma. The ability of these metabolites to discriminate between CRC and colorectal adenoma was tested by targeted metabolomic analysis. A model based on gut microbiome-associated metabolites was established and evaluated in an independent validation cohort.ResultsIn total, 885 serum metabolites were significantly altered in both CRC and adenoma, including eight gut microbiome-associated serum metabolites (GMSM panel) that were reproducibly detected by both targeted and untargeted metabolomics analysis and accurately discriminated CRC and adenoma from normal samples. A GMSM panel-based model to predict CRC and colorectal adenoma yielded an area under the curve (AUC) of 0.98 (95% CI 0.94 to 1.00) in the modelling cohort and an AUC of 0.92 (83.5% sensitivity, 84.9% specificity) in the validation cohort. The GMSM model was significantly superior to the clinical marker carcinoembryonic antigen among samples within the validation cohort (AUC 0.92 vs 0.72) and also showed promising diagnostic accuracy for adenomas (AUC=0.84) and early-stage CRC (AUC=0.93).ConclusionGut microbiome reprogramming in patients with CRC is associated with alterations of the serum metabolome, and GMSMs have potential applications for CRC and adenoma detection. |
| doi_str_mv | 10.1136/gutjnl-2020-323476 |
| format | Article |
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The ability of these metabolites to discriminate between CRC and colorectal adenoma was tested by targeted metabolomic analysis. A model based on gut microbiome-associated metabolites was established and evaluated in an independent validation cohort.ResultsIn total, 885 serum metabolites were significantly altered in both CRC and adenoma, including eight gut microbiome-associated serum metabolites (GMSM panel) that were reproducibly detected by both targeted and untargeted metabolomics analysis and accurately discriminated CRC and adenoma from normal samples. A GMSM panel-based model to predict CRC and colorectal adenoma yielded an area under the curve (AUC) of 0.98 (95% CI 0.94 to 1.00) in the modelling cohort and an AUC of 0.92 (83.5% sensitivity, 84.9% specificity) in the validation cohort. The GMSM model was significantly superior to the clinical marker carcinoembryonic antigen among samples within the validation cohort (AUC 0.92 vs 0.72) and also showed promising diagnostic accuracy for adenomas (AUC=0.84) and early-stage CRC (AUC=0.93).ConclusionGut microbiome reprogramming in patients with CRC is associated with alterations of the serum metabolome, and GMSMs have potential applications for CRC and adenoma detection.</description><identifier>ISSN: 0017-5749</identifier><identifier>EISSN: 1468-3288</identifier><identifier>DOI: 10.1136/gutjnl-2020-323476</identifier><identifier>PMID: 34462336</identifier><language>eng</language><publisher>England: BMJ Publishing Group Ltd and British Society of Gastroenterology</publisher><subject>Adenoma ; Adenoma - diagnosis ; Antigens ; Bacteria ; Biomarkers ; Biomarkers, Tumor ; Carcinoembryonic antigen ; Chromatography ; colorectal adenomas ; Colorectal cancer ; Colorectal carcinoma ; Colorectal Neoplasms - genetics ; Digestive system ; Feces ; Gastrointestinal Microbiome - genetics ; Gut Microbiota ; Humans ; Intestinal microflora ; Laboratories ; Liquid chromatography ; Mass spectrometry ; Mass spectroscopy ; Metabolism ; Metabolites ; Metabolome ; Metabolomics ; Metagenome ; Methods ; Microbiomes ; Microbiota ; Patients ; Population ; Quality control ; Scientific imaging ; Statistical analysis ; Tumors</subject><ispartof>Gut, 2022-07, Vol.71 (7), p.1315-1325</ispartof><rights>Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.</rights><rights>Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.</rights><rights>2022 Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ . 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Published by BMJ. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b507t-38be1fe763c1d10ab9a5d33c512750d108beb19dccd2b137ff3e1a61ea607ac43</citedby><cites>FETCH-LOGICAL-b507t-38be1fe763c1d10ab9a5d33c512750d108beb19dccd2b137ff3e1a61ea607ac43</cites><orcidid>0000-0002-0947-5091 ; 0000-0003-2034-6351</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/PMC9185821/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185821/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34462336$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chen, Feng</creatorcontrib><creatorcontrib>Dai, Xudong</creatorcontrib><creatorcontrib>Zhou, Chang-Chun</creatorcontrib><creatorcontrib>Li, Ke-xin</creatorcontrib><creatorcontrib>Zhang, Yu-juan</creatorcontrib><creatorcontrib>Lou, Xiao-Ying</creatorcontrib><creatorcontrib>Zhu, Yuan-Min</creatorcontrib><creatorcontrib>Sun, Yan-Lai</creatorcontrib><creatorcontrib>Peng, Bao-Xiang</creatorcontrib><creatorcontrib>Cui, Wei</creatorcontrib><title>Integrated analysis of the faecal metagenome and serum metabolome reveals the role of gut microbiome-associated metabolites in the detection of colorectal cancer and adenoma</title><title>Gut</title><addtitle>Gut</addtitle><addtitle>Gut</addtitle><description>ObjectiveTo profile gut microbiome-associated metabolites in serum and investigate whether these metabolites could distinguish individuals with colorectal cancer (CRC) or adenoma from normal healthy individuals.DesignIntegrated analysis of untargeted serum metabolomics by liquid chromatography-mass spectrometry and metagenome sequencing of paired faecal samples was applied to identify gut microbiome-associated metabolites with significantly altered abundance in patients with CRC and adenoma. The ability of these metabolites to discriminate between CRC and colorectal adenoma was tested by targeted metabolomic analysis. A model based on gut microbiome-associated metabolites was established and evaluated in an independent validation cohort.ResultsIn total, 885 serum metabolites were significantly altered in both CRC and adenoma, including eight gut microbiome-associated serum metabolites (GMSM panel) that were reproducibly detected by both targeted and untargeted metabolomics analysis and accurately discriminated CRC and adenoma from normal samples. A GMSM panel-based model to predict CRC and colorectal adenoma yielded an area under the curve (AUC) of 0.98 (95% CI 0.94 to 1.00) in the modelling cohort and an AUC of 0.92 (83.5% sensitivity, 84.9% specificity) in the validation cohort. The GMSM model was significantly superior to the clinical marker carcinoembryonic antigen among samples within the validation cohort (AUC 0.92 vs 0.72) and also showed promising diagnostic accuracy for adenomas (AUC=0.84) and early-stage CRC (AUC=0.93).ConclusionGut microbiome reprogramming in patients with CRC is associated with alterations of the serum metabolome, and GMSMs have potential applications for CRC and adenoma detection.</description><subject>Adenoma</subject><subject>Adenoma - diagnosis</subject><subject>Antigens</subject><subject>Bacteria</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor</subject><subject>Carcinoembryonic antigen</subject><subject>Chromatography</subject><subject>colorectal adenomas</subject><subject>Colorectal cancer</subject><subject>Colorectal carcinoma</subject><subject>Colorectal Neoplasms - genetics</subject><subject>Digestive system</subject><subject>Feces</subject><subject>Gastrointestinal Microbiome - genetics</subject><subject>Gut Microbiota</subject><subject>Humans</subject><subject>Intestinal microflora</subject><subject>Laboratories</subject><subject>Liquid chromatography</subject><subject>Mass spectrometry</subject><subject>Mass spectroscopy</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Metabolome</subject><subject>Metabolomics</subject><subject>Metagenome</subject><subject>Methods</subject><subject>Microbiomes</subject><subject>Microbiota</subject><subject>Patients</subject><subject>Population</subject><subject>Quality control</subject><subject>Scientific imaging</subject><subject>Statistical analysis</subject><subject>Tumors</subject><issn>0017-5749</issn><issn>1468-3288</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>9YT</sourceid><sourceid>ACMMV</sourceid><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqNkstu1TAQhiMEoofCC7BAkdiwSfElsZ0NEqq4VKrEBtbWxJmc-iixi-1U6kP1HXGSw-GyQKysmfn-f8b2FMVLSi4o5eLtfk4HN1aMMFJxxmspHhU7WguVI6UeFztCqKwaWbdnxbMYD4QQpVr6tDjjdS0Y52JXPFy5hPsACfsSHIz30cbSD2W6wXIANDCWEybYo_MTZqIvI4Z5WpOdH5dkwDuEMa6S4Edc5Hm0crIm-M5mpIIYvbFrk6PQJoyldauox4QmWe8WpcmmIYe5sQFnMKxNoV8GgOfFkyG3whfH87z49vHD18vP1fWXT1eX76-rriEyVVx1SAeUghvaUwJdC03PuWkokw3JmVzvaNsb07OOcjkMHCkIiiCIBFPz8-Ld5ns7dxP2Bl0KMOrbYCcI99qD1X9WnL3Re3-nW6oaxWg2eHM0CP77jDHpyUaD4wgO_Rw1a4RslZScZPT1X-jBzyF_RaaErFXTMsUzxTYqv2mMAYfTMJToZRv0tg162Qa9bUMWvfr9GifJz-_PQLUB3XT4P8OLX_xpzH8IfgAwzNRt</recordid><startdate>20220701</startdate><enddate>20220701</enddate><creator>Chen, Feng</creator><creator>Dai, Xudong</creator><creator>Zhou, Chang-Chun</creator><creator>Li, Ke-xin</creator><creator>Zhang, Yu-juan</creator><creator>Lou, Xiao-Ying</creator><creator>Zhu, Yuan-Min</creator><creator>Sun, Yan-Lai</creator><creator>Peng, Bao-Xiang</creator><creator>Cui, Wei</creator><general>BMJ Publishing Group Ltd and British Society of Gastroenterology</general><general>BMJ Publishing Group LTD</general><general>BMJ Publishing Group</general><scope>9YT</scope><scope>ACMMV</scope><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>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8AF</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</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/0000-0002-0947-5091</orcidid><orcidid>https://orcid.org/0000-0003-2034-6351</orcidid></search><sort><creationdate>20220701</creationdate><title>Integrated analysis of the faecal metagenome and serum metabolome reveals the role of gut microbiome-associated metabolites in the detection of colorectal cancer and adenoma</title><author>Chen, Feng ; Dai, Xudong ; Zhou, Chang-Chun ; Li, Ke-xin ; Zhang, Yu-juan ; Lou, Xiao-Ying ; Zhu, Yuan-Min ; Sun, Yan-Lai ; Peng, Bao-Xiang ; Cui, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b507t-38be1fe763c1d10ab9a5d33c512750d108beb19dccd2b137ff3e1a61ea607ac43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adenoma</topic><topic>Adenoma - diagnosis</topic><topic>Antigens</topic><topic>Bacteria</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor</topic><topic>Carcinoembryonic antigen</topic><topic>Chromatography</topic><topic>colorectal adenomas</topic><topic>Colorectal cancer</topic><topic>Colorectal carcinoma</topic><topic>Colorectal Neoplasms - genetics</topic><topic>Digestive system</topic><topic>Feces</topic><topic>Gastrointestinal Microbiome - genetics</topic><topic>Gut Microbiota</topic><topic>Humans</topic><topic>Intestinal microflora</topic><topic>Laboratories</topic><topic>Liquid chromatography</topic><topic>Mass spectrometry</topic><topic>Mass spectroscopy</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Metabolome</topic><topic>Metabolomics</topic><topic>Metagenome</topic><topic>Methods</topic><topic>Microbiomes</topic><topic>Microbiota</topic><topic>Patients</topic><topic>Population</topic><topic>Quality control</topic><topic>Scientific imaging</topic><topic>Statistical analysis</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Feng</creatorcontrib><creatorcontrib>Dai, Xudong</creatorcontrib><creatorcontrib>Zhou, Chang-Chun</creatorcontrib><creatorcontrib>Li, Ke-xin</creatorcontrib><creatorcontrib>Zhang, Yu-juan</creatorcontrib><creatorcontrib>Lou, Xiao-Ying</creatorcontrib><creatorcontrib>Zhu, Yuan-Min</creatorcontrib><creatorcontrib>Sun, Yan-Lai</creatorcontrib><creatorcontrib>Peng, Bao-Xiang</creatorcontrib><creatorcontrib>Cui, Wei</creatorcontrib><collection>BMJ Open Access Journals</collection><collection>BMJ Journals:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</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>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>BMJ Journals</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>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science 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>Gut</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Feng</au><au>Dai, Xudong</au><au>Zhou, Chang-Chun</au><au>Li, Ke-xin</au><au>Zhang, Yu-juan</au><au>Lou, Xiao-Ying</au><au>Zhu, Yuan-Min</au><au>Sun, Yan-Lai</au><au>Peng, Bao-Xiang</au><au>Cui, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrated analysis of the faecal metagenome and serum metabolome reveals the role of gut microbiome-associated metabolites in the detection of colorectal cancer and adenoma</atitle><jtitle>Gut</jtitle><stitle>Gut</stitle><addtitle>Gut</addtitle><date>2022-07-01</date><risdate>2022</risdate><volume>71</volume><issue>7</issue><spage>1315</spage><epage>1325</epage><pages>1315-1325</pages><issn>0017-5749</issn><eissn>1468-3288</eissn><abstract>ObjectiveTo profile gut microbiome-associated metabolites in serum and investigate whether these metabolites could distinguish individuals with colorectal cancer (CRC) or adenoma from normal healthy individuals.DesignIntegrated analysis of untargeted serum metabolomics by liquid chromatography-mass spectrometry and metagenome sequencing of paired faecal samples was applied to identify gut microbiome-associated metabolites with significantly altered abundance in patients with CRC and adenoma. The ability of these metabolites to discriminate between CRC and colorectal adenoma was tested by targeted metabolomic analysis. A model based on gut microbiome-associated metabolites was established and evaluated in an independent validation cohort.ResultsIn total, 885 serum metabolites were significantly altered in both CRC and adenoma, including eight gut microbiome-associated serum metabolites (GMSM panel) that were reproducibly detected by both targeted and untargeted metabolomics analysis and accurately discriminated CRC and adenoma from normal samples. A GMSM panel-based model to predict CRC and colorectal adenoma yielded an area under the curve (AUC) of 0.98 (95% CI 0.94 to 1.00) in the modelling cohort and an AUC of 0.92 (83.5% sensitivity, 84.9% specificity) in the validation cohort. The GMSM model was significantly superior to the clinical marker carcinoembryonic antigen among samples within the validation cohort (AUC 0.92 vs 0.72) and also showed promising diagnostic accuracy for adenomas (AUC=0.84) and early-stage CRC (AUC=0.93).ConclusionGut microbiome reprogramming in patients with CRC is associated with alterations of the serum metabolome, and GMSMs have potential applications for CRC and adenoma detection.</abstract><cop>England</cop><pub>BMJ Publishing Group Ltd and British Society of Gastroenterology</pub><pmid>34462336</pmid><doi>10.1136/gutjnl-2020-323476</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-0947-5091</orcidid><orcidid>https://orcid.org/0000-0003-2034-6351</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adenoma Adenoma - diagnosis Antigens Bacteria Biomarkers Biomarkers, Tumor Carcinoembryonic antigen Chromatography colorectal adenomas Colorectal cancer Colorectal carcinoma Colorectal Neoplasms - genetics Digestive system Feces Gastrointestinal Microbiome - genetics Gut Microbiota Humans Intestinal microflora Laboratories Liquid chromatography Mass spectrometry Mass spectroscopy Metabolism Metabolites Metabolome Metabolomics Metagenome Methods Microbiomes Microbiota Patients Population Quality control Scientific imaging Statistical analysis Tumors |
| title | Integrated analysis of the faecal metagenome and serum metabolome reveals the role of gut microbiome-associated metabolites in the detection of colorectal cancer and adenoma |
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