Identification of a Blood-Based Protein Biomarker Panel for Lung Cancer Detection

Victoria El‐Khoury(Luxembourg Institute of Health), Anna Schritz(Luxembourg Institute of Health), Sang‐Yoon Kim(Luxembourg Institute of Health), Antoine Lesur(Luxembourg Institute of Health), Katriina Sertamo(Luxembourg Institute of Health), François Bernardin(Luxembourg Institute of Health), Konstantinos Pétritis(Translational Genomics Research Institute), Patrick Pirrotte(Translational Genomics Research Institute), Cheryl Selinsky(Translational Genomics Research Institute), Jeffrey R. Whiteaker(Fred Hutch Cancer Center), Haizhen Zhang(Fred Hutch Cancer Center), Jacob J. Kennedy(Fred Hutch Cancer Center), Chenwei Lin(Fred Hutch Cancer Center), Lik Wee Lee(Fred Hutch Cancer Center), Ping Yan(Fred Hutch Cancer Center), Nhan L. Tran(Mayo Clinic in Arizona), Landon J. Inge(St. Joseph's Hospital and Medical Center), Khaled Chalabi(Laboratoire National de Santé), G. Anton Decker, Rolf Bjerkvig(Luxembourg Institute of Health), Amanda G. Paulovich(Fred Hutch Cancer Center), Guy Berchem(Centre Hospitalier de Luxembourg), Yeoun Jin Kim(Luxembourg Institute of Health)
Cancers
June 19, 2020
Cited by 29Open Access
Full Text

Abstract

Lung cancer is the deadliest cancer worldwide, mainly due to its advanced stage at the time of diagnosis. A non-invasive method for its early detection remains mandatory to improve patients' survival. Plasma levels of 351 proteins were quantified by Liquid Chromatography-Parallel Reaction Monitoring (LC-PRM)-based mass spectrometry in 128 lung cancer patients and 93 healthy donors. Bootstrap sampling and least absolute shrinkage and selection operator (LASSO) penalization were used to find the best protein combination for outcome prediction. The PanelomiX platform was used to select the optimal biomarker thresholds. The panel was validated in 48 patients and 49 healthy volunteers. A 6-protein panel clearly distinguished lung cancer from healthy individuals. The panel displayed excellent performance: area under the receiver operating characteristic curve (AUC) = 0.999, positive predictive value (PPV) = 0.992, negative predictive value (NPV) = 0.989, specificity = 0.989 and sensitivity = 0.992. The panel detected lung cancer independently of the disease stage. The 6-protein panel and other sub-combinations displayed excellent results in the validation dataset. In conclusion, we identified a blood-based 6-protein panel as a diagnostic tool in lung cancer. Used as a routine test for high- and average-risk individuals, it may complement currently adopted techniques in lung cancer screening.


Related Papers

No related papers found

Powered by citation graph analysis