{"title":"基于基因表达的诊断方法用于难诊断肿瘤的分子癌分类。","authors":"Catherine A Schnabel, Mark G Erlander","doi":"10.1517/17530059.2012.704363","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Standardized methods for accurate tumor classification are of critical importance for cancer diagnosis and treatment, particularly in diagnostically-challenging cases where site-directed therapies are an option. Molecular diagnostics for tumor classification, subclassification and site of origin determination based on advances in gene expression profiling have translated into clinical practice as complementary approaches to clinicopathological evaluations.</p><p><strong>Areas covered: </strong>In this review, the foundational science of gene expression-based cancer classification, technical and clinical considerations for clinical translation, and an overview of molecular signatures of tumor classification that are available for clinical use will be discussed. Proposed approaches will also be described for further integration of molecular tests for cancer classification into the diagnostic paradigm using a tissue-based strategy as a key component to direct evaluation.</p><p><strong>Expert opinion: </strong>Increasing evidence of improved patient outcomes with the application of site and molecularly-targeted cancer therapy through use of molecular tools highlights the growing potential for these gene expression-based diagnostics to positively impact patient management. Looking forward, the availability of adequate tissue will be a significant issue and limiting factor as cancer diagnosis progresses; when the tumor specimen is limited, use of molecular classification may be a reasonable early step in the evaluation, particularly if the tumor is poorly-differentiated and has atypical features.</p>","PeriodicalId":72996,"journal":{"name":"Expert opinion on medical diagnostics","volume":"6 5","pages":"407-19"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1517/17530059.2012.704363","citationCount":"7","resultStr":"{\"title\":\"Gene expression-based diagnostics for molecular cancer classification of difficult to diagnose tumors.\",\"authors\":\"Catherine A Schnabel, Mark G Erlander\",\"doi\":\"10.1517/17530059.2012.704363\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Standardized methods for accurate tumor classification are of critical importance for cancer diagnosis and treatment, particularly in diagnostically-challenging cases where site-directed therapies are an option. Molecular diagnostics for tumor classification, subclassification and site of origin determination based on advances in gene expression profiling have translated into clinical practice as complementary approaches to clinicopathological evaluations.</p><p><strong>Areas covered: </strong>In this review, the foundational science of gene expression-based cancer classification, technical and clinical considerations for clinical translation, and an overview of molecular signatures of tumor classification that are available for clinical use will be discussed. Proposed approaches will also be described for further integration of molecular tests for cancer classification into the diagnostic paradigm using a tissue-based strategy as a key component to direct evaluation.</p><p><strong>Expert opinion: </strong>Increasing evidence of improved patient outcomes with the application of site and molecularly-targeted cancer therapy through use of molecular tools highlights the growing potential for these gene expression-based diagnostics to positively impact patient management. Looking forward, the availability of adequate tissue will be a significant issue and limiting factor as cancer diagnosis progresses; when the tumor specimen is limited, use of molecular classification may be a reasonable early step in the evaluation, particularly if the tumor is poorly-differentiated and has atypical features.</p>\",\"PeriodicalId\":72996,\"journal\":{\"name\":\"Expert opinion on medical diagnostics\",\"volume\":\"6 5\",\"pages\":\"407-19\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1517/17530059.2012.704363\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert opinion on medical diagnostics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1517/17530059.2012.704363\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2012/7/10 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert opinion on medical diagnostics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1517/17530059.2012.704363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2012/7/10 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Gene expression-based diagnostics for molecular cancer classification of difficult to diagnose tumors.
Introduction: Standardized methods for accurate tumor classification are of critical importance for cancer diagnosis and treatment, particularly in diagnostically-challenging cases where site-directed therapies are an option. Molecular diagnostics for tumor classification, subclassification and site of origin determination based on advances in gene expression profiling have translated into clinical practice as complementary approaches to clinicopathological evaluations.
Areas covered: In this review, the foundational science of gene expression-based cancer classification, technical and clinical considerations for clinical translation, and an overview of molecular signatures of tumor classification that are available for clinical use will be discussed. Proposed approaches will also be described for further integration of molecular tests for cancer classification into the diagnostic paradigm using a tissue-based strategy as a key component to direct evaluation.
Expert opinion: Increasing evidence of improved patient outcomes with the application of site and molecularly-targeted cancer therapy through use of molecular tools highlights the growing potential for these gene expression-based diagnostics to positively impact patient management. Looking forward, the availability of adequate tissue will be a significant issue and limiting factor as cancer diagnosis progresses; when the tumor specimen is limited, use of molecular classification may be a reasonable early step in the evaluation, particularly if the tumor is poorly-differentiated and has atypical features.