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Early detection is critical to improve the overall survival of lung cancer. Endogenous volatile organic compounds (VOCs) can be derived from many different metabolic pathways. On the other hand, cancer cells have different metabolism patterns compared with normal cells. Thus, detecting VOCs in exhaled breath using highly sensitive mass spectrometry would be a promising approach for lung cancer detection.
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Endogenous volatile organic compounds (VOCs) can be derived from many different metabolic pathways. VOCs can be transported to the alveoli through the blood circulation and expelled by exhalation. Changes in VOCs production, clearance, and alterations in lung air-blood exchange functions can lead to aberrant VOCs profiles in the exhaled breath. Testing exhaled breath has the advantages of being completely non-invasive and easy to collect, and has been considered as a perfect approach for disease diagnoses and therapeutic monitoring. Many clinical studies have found that VOCs in exhaled breath are closely related to disease status. Specific VOCs alterations have been identified in many tumors, especially lung cancer.
In this study, we use a highly sensitive mass spectrometry to detect exhaled VOCs of lung cancer patients and healthy people. A lung cancer diagnosis model based on mass spectrometry data and support vector machine will be initially established and validated.
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2,236 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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