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Plasma metabolites as possible biomarkers for diagnosis of breast cancer
Metabolomic approaches have been used to identify new diagnostic biomarkers for various types of cancers, including breast cancer. In this study, we aimed to identify potential biomarkers of breast cancer using plasma metabolic profiling. Furthermore, we analyzed whether these biomarkers had relatio...
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Published in: | PloS one 2019-12, Vol.14 (12), p.e0225129-e0225129 |
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description | Metabolomic approaches have been used to identify new diagnostic biomarkers for various types of cancers, including breast cancer. In this study, we aimed to identify potential biomarkers of breast cancer using plasma metabolic profiling. Furthermore, we analyzed whether these biomarkers had relationships with clinicopathological characteristics of breast cancer. Our study used two liquid chromatography-mass spectrometry sets: a discovery set (40 breast cancer patients and 30 healthy controls) and a validation set (30 breast cancer patients and 16 healthy controls). All breast cancer patients were randomly selected from among stage I-III patients who underwent surgery between 2011 and 2016. First, metabolites distinguishing cancer patients from healthy controls were identified in the discovery set. Then, consistent and reproducible metabolites were evaluated in terms of their utility as possible biomarkers of breast cancer. Receiver operating characteristic (ROC) analysis was applied to the discovery set, and ROC cut-off values for the identified metabolites derived therein were applied to the validation set to determine their diagnostic performance. Ultimately, four candidate biomarkers (L-octanoylcarnitine, 5-oxoproline, hypoxanthine, and docosahexaenoic acid) were identified. L-octanoylcarnitine showed the best diagnostic performance, with a 100.0% positive predictive value. Also, L-octanoylcarnitine levels differed according to tumor size and hormone receptor expression. The plasma metabolites identified in this study show potential as biomarkers allowing early diagnosis of breast cancer. However, the diagnostic performance of the metabolites needs to be confirmed in further studies with larger sample sizes. |
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In this study, we aimed to identify potential biomarkers of breast cancer using plasma metabolic profiling. Furthermore, we analyzed whether these biomarkers had relationships with clinicopathological characteristics of breast cancer. Our study used two liquid chromatography-mass spectrometry sets: a discovery set (40 breast cancer patients and 30 healthy controls) and a validation set (30 breast cancer patients and 16 healthy controls). All breast cancer patients were randomly selected from among stage I-III patients who underwent surgery between 2011 and 2016. First, metabolites distinguishing cancer patients from healthy controls were identified in the discovery set. Then, consistent and reproducible metabolites were evaluated in terms of their utility as possible biomarkers of breast cancer. Receiver operating characteristic (ROC) analysis was applied to the discovery set, and ROC cut-off values for the identified metabolites derived therein were applied to the validation set to determine their diagnostic performance. Ultimately, four candidate biomarkers (L-octanoylcarnitine, 5-oxoproline, hypoxanthine, and docosahexaenoic acid) were identified. L-octanoylcarnitine showed the best diagnostic performance, with a 100.0% positive predictive value. Also, L-octanoylcarnitine levels differed according to tumor size and hormone receptor expression. The plasma metabolites identified in this study show potential as biomarkers allowing early diagnosis of breast cancer. However, the diagnostic performance of the metabolites needs to be confirmed in further studies with larger sample sizes.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0225129</identifier><identifier>PMID: 31794572</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Apoptosis ; Biological markers ; Biology and Life Sciences ; Biomarkers ; Biomarkers, Tumor - blood ; Breast cancer ; Breast Neoplasms - blood ; Breast Neoplasms - diagnosis ; Cancer diagnosis ; Cancer patients ; Cancer research ; Carnitine - analogs & derivatives ; Carnitine - blood ; Case-Control Studies ; Cell growth ; Chromatography ; Chromatography, Liquid ; Criminal investigation ; Diagnosis ; Diagnostic systems ; Disease ; Docosahexaenoic acid ; Docosahexaenoic Acids - blood ; EDTA ; Fatty acids ; Female ; Hormones ; Hospitals ; Humans ; Hypoxanthine ; Hypoxanthine - blood ; Liquid chromatography ; Mammography ; Mass Spectrometry ; Mass spectroscopy ; Medical diagnosis ; Medical prognosis ; Medical schools ; Medical screening ; Medicine ; Medicine and Health Sciences ; Metabolism ; Metabolites ; Metabolomics ; Middle Aged ; NMR ; Nuclear magnetic resonance ; Omega 3 fatty acids ; Phase transitions ; Profiling ; Prostate cancer ; Purines ; Pyrrolidonecarboxylic Acid - blood ; Quantitative analysis ; Research and analysis methods ; Scientific imaging ; Spectroscopy ; Surgery ; Tumors ; Ultrasonic imaging ; Unsaturated fatty acids</subject><ispartof>PloS one, 2019-12, Vol.14 (12), p.e0225129-e0225129</ispartof><rights>COPYRIGHT 2019 Public Library of Science</rights><rights>2019 Park 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. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2019 Park et al 2019 Park et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-6baf3c1ff3b12ce1ce8095a0f4b95bfb93be02c9d490f67177ff4f8333e877413</citedby><cites>FETCH-LOGICAL-c692t-6baf3c1ff3b12ce1ce8095a0f4b95bfb93be02c9d490f67177ff4f8333e877413</cites><orcidid>0000-0003-0860-3239</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2320974969/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2320974969?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31794572$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Mudiam, Mohana Krishna Reddy</contributor><creatorcontrib>Park, Jiwon</creatorcontrib><creatorcontrib>Shin, Yumi</creatorcontrib><creatorcontrib>Kim, Tae Hyun</creatorcontrib><creatorcontrib>Kim, Dong-Hyun</creatorcontrib><creatorcontrib>Lee, Anbok</creatorcontrib><title>Plasma metabolites as possible biomarkers for diagnosis of breast cancer</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Metabolomic approaches have been used to identify new diagnostic biomarkers for various types of cancers, including breast cancer. In this study, we aimed to identify potential biomarkers of breast cancer using plasma metabolic profiling. Furthermore, we analyzed whether these biomarkers had relationships with clinicopathological characteristics of breast cancer. Our study used two liquid chromatography-mass spectrometry sets: a discovery set (40 breast cancer patients and 30 healthy controls) and a validation set (30 breast cancer patients and 16 healthy controls). All breast cancer patients were randomly selected from among stage I-III patients who underwent surgery between 2011 and 2016. First, metabolites distinguishing cancer patients from healthy controls were identified in the discovery set. Then, consistent and reproducible metabolites were evaluated in terms of their utility as possible biomarkers of breast cancer. 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However, the diagnostic performance of the metabolites needs to be confirmed in further studies with larger sample sizes.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Apoptosis</subject><subject>Biological markers</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers</subject><subject>Biomarkers, Tumor - blood</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - blood</subject><subject>Breast Neoplasms - diagnosis</subject><subject>Cancer diagnosis</subject><subject>Cancer patients</subject><subject>Cancer research</subject><subject>Carnitine - analogs & derivatives</subject><subject>Carnitine - blood</subject><subject>Case-Control Studies</subject><subject>Cell growth</subject><subject>Chromatography</subject><subject>Chromatography, Liquid</subject><subject>Criminal investigation</subject><subject>Diagnosis</subject><subject>Diagnostic systems</subject><subject>Disease</subject><subject>Docosahexaenoic acid</subject><subject>Docosahexaenoic Acids - blood</subject><subject>EDTA</subject><subject>Fatty acids</subject><subject>Female</subject><subject>Hormones</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Hypoxanthine</subject><subject>Hypoxanthine - blood</subject><subject>Liquid chromatography</subject><subject>Mammography</subject><subject>Mass Spectrometry</subject><subject>Mass spectroscopy</subject><subject>Medical diagnosis</subject><subject>Medical prognosis</subject><subject>Medical schools</subject><subject>Medical screening</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Metabolomics</subject><subject>Middle Aged</subject><subject>NMR</subject><subject>Nuclear magnetic resonance</subject><subject>Omega 3 fatty acids</subject><subject>Phase transitions</subject><subject>Profiling</subject><subject>Prostate cancer</subject><subject>Purines</subject><subject>Pyrrolidonecarboxylic Acid - blood</subject><subject>Quantitative analysis</subject><subject>Research and analysis methods</subject><subject>Scientific imaging</subject><subject>Spectroscopy</subject><subject>Surgery</subject><subject>Tumors</subject><subject>Ultrasonic imaging</subject><subject>Unsaturated fatty acids</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl1rFDEUhgex2Fr9B6IDgtiLXfM1mcmNUIrahULFr9uQZE92s2Ym22RG9N-b7U7LjvRCcpFw8pz35Jy8RfECozmmNX63CUPslJ9vQwdzREiFiXhUnGBByYwTRB8fnI-LpyltEKpow_mT4pjiWrCqJifF5WevUqvKFnqlg3c9pFKlchtSctpDqV1oVfwJMZU2xHLp1KoLyaUy2FJHUKkvjeoMxGfFkVU-wfNxPy2-f_zw7eJydnX9aXFxfjUzXJB-xrWy1GBrqcbEADbQIFEpZJkWlbZaUA2IGLFkAlle47q2ltmGUgpNXTNMT4tXe92tD0mOQ0iSUIJEzQQXmVjsiWVQG7mNLjfwRwbl5G0gxJVUsXfGgzQKgxEYKcExazhtKoENJxiY5QZZnbXej9UG3cLSQNdH5Sei05vOreUq_JK8EYhQngXejgIx3AyQetm6ZMB71UEYbt-Nc5usYRl9_Q_6cHcjtVK5AdfZkOuanag856hmlDFKMjV_gMprCa0z2THW5fgk4WySkJkefvcrNaQkF1-__D97_WPKvjlg16B8v07BD70LXZqCbA-amL0Xwd4PGSO5M_zdNOTO8HI0fE57efhB90l3Dqd_AaNF-ls</recordid><startdate>20191203</startdate><enddate>20191203</enddate><creator>Park, Jiwon</creator><creator>Shin, Yumi</creator><creator>Kim, Tae Hyun</creator><creator>Kim, Dong-Hyun</creator><creator>Lee, Anbok</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-0860-3239</orcidid></search><sort><creationdate>20191203</creationdate><title>Plasma metabolites as possible biomarkers for diagnosis of breast cancer</title><author>Park, Jiwon ; Shin, Yumi ; Kim, Tae Hyun ; Kim, Dong-Hyun ; Lee, Anbok</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-6baf3c1ff3b12ce1ce8095a0f4b95bfb93be02c9d490f67177ff4f8333e877413</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Apoptosis</topic><topic>Biological markers</topic><topic>Biology and Life Sciences</topic><topic>Biomarkers</topic><topic>Biomarkers, Tumor - blood</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - blood</topic><topic>Breast Neoplasms - diagnosis</topic><topic>Cancer diagnosis</topic><topic>Cancer patients</topic><topic>Cancer research</topic><topic>Carnitine - analogs & derivatives</topic><topic>Carnitine - blood</topic><topic>Case-Control Studies</topic><topic>Cell growth</topic><topic>Chromatography</topic><topic>Chromatography, Liquid</topic><topic>Criminal investigation</topic><topic>Diagnosis</topic><topic>Diagnostic systems</topic><topic>Disease</topic><topic>Docosahexaenoic acid</topic><topic>Docosahexaenoic Acids - blood</topic><topic>EDTA</topic><topic>Fatty acids</topic><topic>Female</topic><topic>Hormones</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Hypoxanthine</topic><topic>Hypoxanthine - blood</topic><topic>Liquid chromatography</topic><topic>Mammography</topic><topic>Mass Spectrometry</topic><topic>Mass spectroscopy</topic><topic>Medical diagnosis</topic><topic>Medical prognosis</topic><topic>Medical schools</topic><topic>Medical screening</topic><topic>Medicine</topic><topic>Medicine and Health Sciences</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Metabolomics</topic><topic>Middle Aged</topic><topic>NMR</topic><topic>Nuclear magnetic resonance</topic><topic>Omega 3 fatty acids</topic><topic>Phase transitions</topic><topic>Profiling</topic><topic>Prostate cancer</topic><topic>Purines</topic><topic>Pyrrolidonecarboxylic Acid - 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In this study, we aimed to identify potential biomarkers of breast cancer using plasma metabolic profiling. Furthermore, we analyzed whether these biomarkers had relationships with clinicopathological characteristics of breast cancer. Our study used two liquid chromatography-mass spectrometry sets: a discovery set (40 breast cancer patients and 30 healthy controls) and a validation set (30 breast cancer patients and 16 healthy controls). All breast cancer patients were randomly selected from among stage I-III patients who underwent surgery between 2011 and 2016. First, metabolites distinguishing cancer patients from healthy controls were identified in the discovery set. Then, consistent and reproducible metabolites were evaluated in terms of their utility as possible biomarkers of breast cancer. Receiver operating characteristic (ROC) analysis was applied to the discovery set, and ROC cut-off values for the identified metabolites derived therein were applied to the validation set to determine their diagnostic performance. Ultimately, four candidate biomarkers (L-octanoylcarnitine, 5-oxoproline, hypoxanthine, and docosahexaenoic acid) were identified. L-octanoylcarnitine showed the best diagnostic performance, with a 100.0% positive predictive value. Also, L-octanoylcarnitine levels differed according to tumor size and hormone receptor expression. The plasma metabolites identified in this study show potential as biomarkers allowing early diagnosis of breast cancer. However, the diagnostic performance of the metabolites needs to be confirmed in further studies with larger sample sizes.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>31794572</pmid><doi>10.1371/journal.pone.0225129</doi><tpages>e0225129</tpages><orcidid>https://orcid.org/0000-0003-0860-3239</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Aged Aged, 80 and over Apoptosis Biological markers Biology and Life Sciences Biomarkers Biomarkers, Tumor - blood Breast cancer Breast Neoplasms - blood Breast Neoplasms - diagnosis Cancer diagnosis Cancer patients Cancer research Carnitine - analogs & derivatives Carnitine - blood Case-Control Studies Cell growth Chromatography Chromatography, Liquid Criminal investigation Diagnosis Diagnostic systems Disease Docosahexaenoic acid Docosahexaenoic Acids - blood EDTA Fatty acids Female Hormones Hospitals Humans Hypoxanthine Hypoxanthine - blood Liquid chromatography Mammography Mass Spectrometry Mass spectroscopy Medical diagnosis Medical prognosis Medical schools Medical screening Medicine Medicine and Health Sciences Metabolism Metabolites Metabolomics Middle Aged NMR Nuclear magnetic resonance Omega 3 fatty acids Phase transitions Profiling Prostate cancer Purines Pyrrolidonecarboxylic Acid - blood Quantitative analysis Research and analysis methods Scientific imaging Spectroscopy Surgery Tumors Ultrasonic imaging Unsaturated fatty acids |
title | Plasma metabolites as possible biomarkers for diagnosis of breast cancer |
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