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Metabolomics Workbench ST000396 - GNPS - Lung Cancer Plasma Discovery

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NIAID Data Ecosystem2026-03-11 收录
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https://www.omicsdi.org/dataset/gnps/MSV000084032
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Recently, major efforts have been directed toward early detection of lung cancer through low-dose computed tomography (LDCT) scanning. Data from the National Lung Screening Trial (NLST) suggest that yearly screening with thoracic LDCT scanning for high-risk current and former smokers reduces lung cancer mortality by 20% and total mortality by 7%. However, issues including indeterminate nodules detected by LDCT and radiation exposure impact the practicality of LDCT-based screening on a national and global basis. A blood-based biomarker or multiplexed marker panel that could complement LDCT would represent a major advance in implementing lung cancer screening. Efforts to develop blood-based biomarkers for lung cancer early detection using a variety of methodologies are currently ongoing. Proteomic studies have led to the identification of several candidate markers including pro-surfactantproteinB(pro-SFTPB), a target of a lineage-survival oncogene in lung cancer, NKX2-1.Validation studies using blood samples collected at the time of LDCT screening for lung cancer substantiated the performance of pro-SFTPB. Multivariable logistic regression models were used to evaluate the predictive ability of pro-SFTPB. The area under the curve (AUC) values of the full model with and without pro-SFTPB were 0.741 (95% CI, 0.696 to 0.783) and 0.669 (95%CI, 0.620 to 0.717), respectively (difference in AUC, P_.001). Single markers are unlikely to have sufficient performance for implementation in a screening setting, hence the need to explore several discovery platforms to identify markers that provide complementary performance. Metabolomics represents a global unbiased approach to the profiling of small molecules and has been established as a platform for biomarker discovery for a variety of human biofluids and tissues. Here we used an untargeted liquid chromatography/mass spectrometry (MS) metabolomics approach to identify metabolites that distinguish human sera collected before the diagnosis of lung cancer from matched control sera in a prospective cohort of highrisk patients from the Beta-Carotene and Retinol Efficacy Trial (CARET).
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2019-07-01
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