Sanaya Bamji-Stocke1, Victor van Berkel2,3, Donald M Miller3, Hermann B Frieboes4,5. 1. Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY, 40208, USA. 2. Department of Cardiovascular and Thoracic Surgery, University of Louisville, Louisville, KY, USA. 3. James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA. 4. Department of Bioengineering, University of Louisville, Lutz Hall 419, Louisville, KY, 40208, USA. hbfrie01@louisville.edu. 5. James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA. hbfrie01@louisville.edu.
Abstract
INTRODUCTION: Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort. OBJECTIVES: This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes. METHOD: We compare the metabolite profiling of cancer patients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancer patients and smokers/risk-factor individuals. RESULT: Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis. CONCLUSION: We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.
INTRODUCTION:Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort. OBJECTIVES: This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes. METHOD: We compare the metabolite profiling of cancerpatients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancerpatients and smokers/risk-factor individuals. RESULT: Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis. CONCLUSION: We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.
Entities:
Keywords:
Cancer metabolomics; cancer diagnosis; cancer treatment; lung cancer; metabolism biomarkers
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