{"title":"A Review of Exhaled Volatile Organic Compounds as Biomarkers for Thoracic Malignancies","authors":"Gerardo Velez, H. Pass","doi":"10.11648/J.AJBLS.20200806.17","DOIUrl":null,"url":null,"abstract":"Lung cancer, malignant pleural mesothelioma, and esophageal cancer are the most common thoracic malignancies and are responsible for substantial cancer-related morbidity and mortality worldwide. Early cancer identification prompts earlier intervention and can therefore improve patient survival. Traditional diagnostics are costly and invasive, however, creating an urgent need for alternative methods. Over the past 30 years, breath analysis has emerged as a rapid, minimally invasive, and cost-effective approach. Metabolites in exhaled breath, known as volatile organic compounds (VOCs), reflect internal biomolecular processes and their composition has been shown to vary in association with numerous pathological states. This review provides an overview on the use of VOCs in exhaled breath for the early screening and diagnosis of thoracic malignancies. Study design, methodology, and significant results from over sixty studies published since 1990 are specified and summarized. A total of 439 significant VOCs are reported in the literature, mainly consisting of aromatic compounds, aldehydes, alkanes, lipids, ketones, and sulfur-containing compounds. Diagnostic sensitivities and specificities range from 51-100% and 68.8 – 100%, respectively. Cancer-specific VOC profiles and associations of clinical interest (e.g., comorbidities, histology, and staging) are emphasized and discussed. While there is considerable evidence to support the diagnostic utility of VOCs, the lack of standardization and external validation in large independent cohorts remain key barriers to clinical translation. However, efforts to address these limitations are currently underway.","PeriodicalId":7857,"journal":{"name":"American Journal of Biomedical and Life Sciences","volume":"31 1","pages":"231"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Biomedical and Life Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/J.AJBLS.20200806.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Lung cancer, malignant pleural mesothelioma, and esophageal cancer are the most common thoracic malignancies and are responsible for substantial cancer-related morbidity and mortality worldwide. Early cancer identification prompts earlier intervention and can therefore improve patient survival. Traditional diagnostics are costly and invasive, however, creating an urgent need for alternative methods. Over the past 30 years, breath analysis has emerged as a rapid, minimally invasive, and cost-effective approach. Metabolites in exhaled breath, known as volatile organic compounds (VOCs), reflect internal biomolecular processes and their composition has been shown to vary in association with numerous pathological states. This review provides an overview on the use of VOCs in exhaled breath for the early screening and diagnosis of thoracic malignancies. Study design, methodology, and significant results from over sixty studies published since 1990 are specified and summarized. A total of 439 significant VOCs are reported in the literature, mainly consisting of aromatic compounds, aldehydes, alkanes, lipids, ketones, and sulfur-containing compounds. Diagnostic sensitivities and specificities range from 51-100% and 68.8 – 100%, respectively. Cancer-specific VOC profiles and associations of clinical interest (e.g., comorbidities, histology, and staging) are emphasized and discussed. While there is considerable evidence to support the diagnostic utility of VOCs, the lack of standardization and external validation in large independent cohorts remain key barriers to clinical translation. However, efforts to address these limitations are currently underway.