title: Application of a high throughput method of biomarker discovery to improvement of the EarlyCDT(®)-Lung Test.
abstract: BACKGROUND
  The National Lung Screening Trial showed that CT screening for lung cancer led to a 20% reduction in mortality. However, CT screening has a number of disadvantages including low specificity. A validated autoantibody assay is available commercially (EarlyCDT®-Lung) to aid in the early detection of lung cancer and risk stratification in patients with pulmonary nodules detected by CT. Recent advances in high throughput (HTP) cloning and expression methods have been developed into a discovery pipeline to identify biomarkers that detect autoantibodies. The aim of this study was to demonstrate the successful clinical application of this strategy to add to the EarlyCDT-Lung panel in order to improve its sensitivity and specificity (and hence positive predictive value, (PPV)).
  
  
  RESULTS
  Serum from two matched independent cohorts of lung cancer patients were used (n = 100 and n = 165). Sixty nine proteins were initially screened on an abridged HTP version of the autoantibody ELISA using protein prepared on small scale by a HTP expression and purification screen. Promising leads were produced in shake flask culture and tested on the full assay. These results were analyzed in combination with those from the EarlyCDT-Lung panel in order to provide a set of re-optimized cut-offs. Five proteins that still displayed cancer/normal differentiation were tested for reproducibility and validation on a second batch of protein and a separate patient cohort. Addition of these proteins resulted in an improvement in the sensitivity and specificity of the test from 38% and 86% to 49% and 93% respectively (PPV improvement from 1 in 16 to 1 in 7).
  
  
  CONCLUSIONS
  This is a practical example of the value of investing resources to develop a HTP technology. Such technology may lead to improvement in the clinical utility of the EarlyCDT--Lung test, and so further aid the early detection of lung cancer.
authors.affiliation: Oncimmune Ltd, Nottingham City Hospital, Nottingham, United Kingdom. Isabel.Macdonald@nottingham.ac.uk
authors.forename: Isabel K
authors.initials: IK
authors.lastname: Macdonald
authors.forename: Andrea
authors.initials: A
authors.lastname: Murray
authors.forename: Graham F
authors.initials: GF
authors.lastname: Healey
authors.forename: Celine B
authors.initials: CB
authors.lastname: Parsy-Kowalska
authors.forename: Jared
authors.initials: J
authors.lastname: Allen
authors.forename: Jane
authors.initials: J
authors.lastname: McElveen
authors.forename: Chris
authors.initials: C
authors.lastname: Robertson
authors.forename: Herbert F
authors.initials: HF
authors.lastname: Sewell
authors.forename: Caroline J
authors.initials: CJ
authors.lastname: Chapman
authors.forename: John F R
authors.initials: JF
authors.lastname: Robertson
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000378:metabolism*; D003001:Cloning, Molecular; D015331:Cohort Studies; D004797:Enzyme-Linked Immunosorbent Assay / Q000379:methods; D005260:Female; D006801:Humans; D008171:Lung Diseases / Q000175:diagnosis* / Q000378:metabolism; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D015272:Pulmonary Medicine / Q000379:methods*; D012129:Respiratory Function Tests; D012306:Risk; D036542:Tomography, Spiral Computed / Q000379:methods
chemical_list: D015415:Biomarkers