title: Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer.
abstract: BACKGROUND
  Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease.
  
  
  RESULTS
  We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥ 10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES) that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC.
  
  
  CONCLUSIONS
  This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels. Separate verification of classifier performance provides evidence against over-fitting and is encouraging for the next development phase, independent validation. This careful study provides a solid foundation to develop tests sorely needed to identify early stage lung cancer.
authors.affiliation: SomaLogic, Boulder, Colorado, United States of America. rostroff@somalogic.com
authors.forename: Rachel M
authors.initials: RM
authors.lastname: Ostroff
authors.forename: William L
authors.initials: WL
authors.lastname: Bigbee
authors.forename: Wilbur
authors.initials: W
authors.lastname: Franklin
authors.forename: Larry
authors.initials: L
authors.lastname: Gold
authors.forename: Mike
authors.initials: M
authors.lastname: Mehan
authors.forename: York E
authors.initials: YE
authors.lastname: Miller
authors.forename: Harvey I
authors.initials: HI
authors.lastname: Pass
authors.forename: William N
authors.initials: WN
authors.lastname: Rom
authors.forename: Jill M
authors.initials: JM
authors.lastname: Siegfried
authors.forename: Alex
authors.initials: A
authors.lastname: Stewart
authors.forename: Jeffrey J
authors.initials: JJ
authors.lastname: Walker
authors.forename: Joel L
authors.initials: JL
authors.lastname: Weissfeld
authors.forename: Stephen
authors.initials: S
authors.lastname: Williams
authors.forename: Dom
authors.initials: D
authors.lastname: Zichi
authors.forename: Edward N
authors.initials: EN
authors.lastname: Brody
mesh_terms: D000465:Algorithms; D001323:Autoantibodies / Q000737:chemistry; D015415:Biomarkers / Q000378:metabolism*; D014408:Biomarkers, Tumor / Q000378:metabolism*; D002289:Carcinoma, Non-Small-Cell Lung / Q000378:metabolism*; D016022:Case-Control Studies; D015331:Cohort Studies; D055088:Early Detection of Cancer / Q000379:methods*; D006801:Humans; D008175:Lung Neoplasms / Q000378:metabolism*; D013058:Mass Spectrometry / Q000379:methods; D015233:Models, Statistical; D040901:Proteomics / Q000379:methods*; D012680:Sensitivity and Specificity; D012907:Smoking / Q000009:adverse effects
chemical_list: D001323:Autoantibodies; D015415:Biomarkers; D014408:Biomarkers, Tumor