Brian C-S Liu, Daniel A Dijohnson, Dennis J O'Rourke
{"title":"Antibody profiling with protein antigen microarrays in early stage cancer.","authors":"Brian C-S Liu, Daniel A Dijohnson, Dennis J O'Rourke","doi":"10.1517/17530059.2012.672969","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Proteins not present in normal cells, that is, cancer cells, may elicit a host immune response that leads to the generation of antibodies that might react with these tumor-associated proteins. In recent years, a growing number of reports have showed that autoantibody profiling may provide an alternative approach for the detection of cancer. However, most studies of antigen-autoantibody reactivity have relied on recombinant proteins. Recombinant proteins lack the proper post-translational modifications present in native proteins. Because of this limitation, native or natural protein antigen microarrays are gaining popularity for profiling antibody responses.</p><p><strong>Areas covered: </strong>i) To illustrate some examples of autoantibodies as signatures for early stage cancer; ii) to briefly outline the various protein antigen microarray platforms; iii) to illustrate the use of native or natural protein microarrays in the discovery of potential biomarkers and iv) to discuss the advantages of native protein antigen microarrays over other approaches.</p><p><strong>Expert opinion: </strong>The nature of protein microarray platforms is conducive to multiplexing, which amplifies the potential for uncovering effective biomarkers for many significant diseases. However, the major challenge will be in integrating microarray platforms into multiplexed clinical diagnostic tools, as the main drawback is the reproducibility and coefficient of variation of the results from array to array, and the transportability of the array platform to a more automatable platform.</p>","PeriodicalId":72996,"journal":{"name":"Expert opinion on medical diagnostics","volume":"6 3","pages":"187-96"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1517/17530059.2012.672969","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert opinion on medical diagnostics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1517/17530059.2012.672969","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2012/3/22 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Introduction: Proteins not present in normal cells, that is, cancer cells, may elicit a host immune response that leads to the generation of antibodies that might react with these tumor-associated proteins. In recent years, a growing number of reports have showed that autoantibody profiling may provide an alternative approach for the detection of cancer. However, most studies of antigen-autoantibody reactivity have relied on recombinant proteins. Recombinant proteins lack the proper post-translational modifications present in native proteins. Because of this limitation, native or natural protein antigen microarrays are gaining popularity for profiling antibody responses.
Areas covered: i) To illustrate some examples of autoantibodies as signatures for early stage cancer; ii) to briefly outline the various protein antigen microarray platforms; iii) to illustrate the use of native or natural protein microarrays in the discovery of potential biomarkers and iv) to discuss the advantages of native protein antigen microarrays over other approaches.
Expert opinion: The nature of protein microarray platforms is conducive to multiplexing, which amplifies the potential for uncovering effective biomarkers for many significant diseases. However, the major challenge will be in integrating microarray platforms into multiplexed clinical diagnostic tools, as the main drawback is the reproducibility and coefficient of variation of the results from array to array, and the transportability of the array platform to a more automatable platform.