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Biomarker Validation for Aging: Lessons from mtDNA Heteroplasmy Analyses in Early Cancer Detection
The anticipated biological and clinical utility of biomarkers has attracted significant interest recently. Aging and early cancer detection represent areas active in the search for predictive and prognostic biomarkers. While applications differ, overlapping biological features, analytical technologi...
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Published in: | Biomarker insights 2009-11, Vol.4, p.165-179 |
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description | The anticipated biological and clinical utility of biomarkers has attracted significant interest recently. Aging and early cancer detection represent areas active in the search for predictive and prognostic biomarkers. While applications differ, overlapping biological features, analytical technologies and specific biomarker analytes bear comparison. Mitochondrial DNA (mtDNA) as a biomarker in both biological models has been evaluated. However, it remains unclear whether mtDNA changes in aging and cancer represent biological relationships that are causal, incidental, or a combination of both. This article focuses on evaluation of mtDNA-based biomarkers, emerging strategies for quantitating mtDNA admixtures, and how current understanding of mtDNA in aging and cancer evolves with introduction of new technologies. Whether for cancer or aging, lessons from mtDNA based biomarker evaluations are several. Biological systems are inherently dynamic and heterogeneous. Detection limits for mtDNA sequencing technologies differ among methods for low-level DNA sequence admixtures in healthy and diseased states. Performance metrics of analytical mtDNA technology should be validated prior to application in heterogeneous biologically-based systems. Critical in evaluating biomarker performance is the ability to distinguish measurement system variance from inherent biological variance, because it is within the latter that background healthy variability as well as high-value, disease-specific information reside. |
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Aging and early cancer detection represent areas active in the search for predictive and prognostic biomarkers. While applications differ, overlapping biological features, analytical technologies and specific biomarker analytes bear comparison. Mitochondrial DNA (mtDNA) as a biomarker in both biological models has been evaluated. However, it remains unclear whether mtDNA changes in aging and cancer represent biological relationships that are causal, incidental, or a combination of both. This article focuses on evaluation of mtDNA-based biomarkers, emerging strategies for quantitating mtDNA admixtures, and how current understanding of mtDNA in aging and cancer evolves with introduction of new technologies. Whether for cancer or aging, lessons from mtDNA based biomarker evaluations are several. Biological systems are inherently dynamic and heterogeneous. Detection limits for mtDNA sequencing technologies differ among methods for low-level DNA sequence admixtures in healthy and diseased states. Performance metrics of analytical mtDNA technology should be validated prior to application in heterogeneous biologically-based systems. Critical in evaluating biomarker performance is the ability to distinguish measurement system variance from inherent biological variance, because it is within the latter that background healthy variability as well as high-value, disease-specific information reside.</description><identifier>EISSN: 1177-2719</identifier><identifier>PMID: 20029650</identifier><language>eng</language><publisher>United States: Sage Publications Ltd</publisher><subject>Aging ; biomarkers ; Cancer ; heteroplasmy ; Mitochondrial DNA ; Nucleotide sequence ; Review</subject><ispartof>Biomarker insights, 2009-11, Vol.4, p.165-179</ispartof><rights>Copyright Libertas Academica Ltd 2009</rights><rights>2009 by the authors 2009</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796862/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1037776387?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25731,36989,36990,44566,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20029650$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Barker, Peter E</creatorcontrib><creatorcontrib>Murthy, Mahadev</creatorcontrib><title>Biomarker Validation for Aging: Lessons from mtDNA Heteroplasmy Analyses in Early Cancer Detection</title><title>Biomarker insights</title><addtitle>Biomark Insights</addtitle><description>The anticipated biological and clinical utility of biomarkers has attracted significant interest recently. Aging and early cancer detection represent areas active in the search for predictive and prognostic biomarkers. While applications differ, overlapping biological features, analytical technologies and specific biomarker analytes bear comparison. Mitochondrial DNA (mtDNA) as a biomarker in both biological models has been evaluated. However, it remains unclear whether mtDNA changes in aging and cancer represent biological relationships that are causal, incidental, or a combination of both. This article focuses on evaluation of mtDNA-based biomarkers, emerging strategies for quantitating mtDNA admixtures, and how current understanding of mtDNA in aging and cancer evolves with introduction of new technologies. Whether for cancer or aging, lessons from mtDNA based biomarker evaluations are several. Biological systems are inherently dynamic and heterogeneous. Detection limits for mtDNA sequencing technologies differ among methods for low-level DNA sequence admixtures in healthy and diseased states. Performance metrics of analytical mtDNA technology should be validated prior to application in heterogeneous biologically-based systems. Critical in evaluating biomarker performance is the ability to distinguish measurement system variance from inherent biological variance, because it is within the latter that background healthy variability as well as high-value, disease-specific information reside.</description><subject>Aging</subject><subject>biomarkers</subject><subject>Cancer</subject><subject>heteroplasmy</subject><subject>Mitochondrial DNA</subject><subject>Nucleotide sequence</subject><subject>Review</subject><issn>1177-2719</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNp9kU1Lw0AQhoMgtlb_gix40Etgs-l-eRBiWz-g6EW9hk0yqVuT3bqbCPn3brGKevA0h3l4ZuadvWicJJzHhCdyFB16v8aYMkHwQTQiGBPJKB5HxZW2rXKv4NCzanSlOm0Nqq1D2Uqb1QVagvfWeFQ726K2m99n6BY6cHbTKN8OKDOqGTx4pA1aKNcMaKZMGXTzQJVb21G0X6vGw_GuTqKn68Xj7DZePtzczbJlvCGUdfG0VrWQnBSCAKSVpKQSUFYpKVhNiwpzIoUoKwmCgwKGSyqkSEgNLGGU8ySdRJef3k1ftFCVYDqnmnzjdDhwyK3S-e-O0S_5yr7nhEsmGAmCs53A2bcefJe32pfQNMqA7X3O0ynBU0m2o87_JUPwiRCUSR7Q0z_o2vYuhBYonHLOWSq21MnP3b-X_npU-gFMhY6f</recordid><startdate>20091127</startdate><enddate>20091127</enddate><creator>Barker, Peter E</creator><creator>Murthy, Mahadev</creator><general>Sage Publications Ltd</general><general>Libertas Academica</general><scope>NPM</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AYAGU</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7TM</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20091127</creationdate><title>Biomarker Validation for Aging: Lessons from mtDNA Heteroplasmy Analyses in Early Cancer Detection</title><author>Barker, Peter E ; Murthy, Mahadev</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p256t-4faf8972b82ee3d952d8ecd32b6f5bd072988cd9e87eae60c589812fe61657713</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Aging</topic><topic>biomarkers</topic><topic>Cancer</topic><topic>heteroplasmy</topic><topic>Mitochondrial DNA</topic><topic>Nucleotide sequence</topic><topic>Review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Barker, Peter E</creatorcontrib><creatorcontrib>Murthy, Mahadev</creatorcontrib><collection>PubMed</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Australia & New Zealand Database</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Biological Sciences</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</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>Nucleic Acids Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Biomarker insights</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Barker, Peter E</au><au>Murthy, Mahadev</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Biomarker Validation for Aging: Lessons from mtDNA Heteroplasmy Analyses in Early Cancer Detection</atitle><jtitle>Biomarker insights</jtitle><addtitle>Biomark Insights</addtitle><date>2009-11-27</date><risdate>2009</risdate><volume>4</volume><spage>165</spage><epage>179</epage><pages>165-179</pages><eissn>1177-2719</eissn><abstract>The anticipated biological and clinical utility of biomarkers has attracted significant interest recently. Aging and early cancer detection represent areas active in the search for predictive and prognostic biomarkers. While applications differ, overlapping biological features, analytical technologies and specific biomarker analytes bear comparison. Mitochondrial DNA (mtDNA) as a biomarker in both biological models has been evaluated. However, it remains unclear whether mtDNA changes in aging and cancer represent biological relationships that are causal, incidental, or a combination of both. This article focuses on evaluation of mtDNA-based biomarkers, emerging strategies for quantitating mtDNA admixtures, and how current understanding of mtDNA in aging and cancer evolves with introduction of new technologies. Whether for cancer or aging, lessons from mtDNA based biomarker evaluations are several. Biological systems are inherently dynamic and heterogeneous. Detection limits for mtDNA sequencing technologies differ among methods for low-level DNA sequence admixtures in healthy and diseased states. Performance metrics of analytical mtDNA technology should be validated prior to application in heterogeneous biologically-based systems. Critical in evaluating biomarker performance is the ability to distinguish measurement system variance from inherent biological variance, because it is within the latter that background healthy variability as well as high-value, disease-specific information reside.</abstract><cop>United States</cop><pub>Sage Publications Ltd</pub><pmid>20029650</pmid><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aging biomarkers Cancer heteroplasmy Mitochondrial DNA Nucleotide sequence Review |
title | Biomarker Validation for Aging: Lessons from mtDNA Heteroplasmy Analyses in Early Cancer Detection |
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