title: An immune response enriched 72-gene prognostic profile for early-stage non-small-cell lung cancer.
abstract: OBJECTIVE
  Current staging methods are imprecise for predicting prognosis of early-stage non-small-cell lung cancer (NSCLC). We aimed to develop a gene expression profile for stage I and stage II NSCLC, allowing identification of patients with a high risk of disease recurrence within 2 to 3 years after initial diagnosis.
  
  
  METHODS
  We used whole-genome gene expression microarrays to analyze frozen tumor samples from 172 NSCLC patients (pT1-2, N0-1, M0) from five European institutions, who had undergone complete surgical resection. Median follow-up was 89 months (range, 1.2-389) and 64 patients developed a recurrence. A random two thirds of the samples were assigned as the training cohort with the remaining samples set aside for independent validation. Cox proportional hazards models were used to evaluate the association between expression levels of individual genes and patient recurrence-free survival. A nearest mean analysis was used to develop a gene-expression classifier for disease recurrence.
  
  
  RESULTS
  We have developed a 72-gene expression prognostic NSCLC classifier. Based on the classifier score, patients were classified as either high or low risk of disease recurrence. Patients classified as low risk showed a significantly better recurrence-free survival both in the training set (P < 0.001; n = 103) and in the independent validation set (P < 0.01; n = 69). Genes in our prognostic signature were strongly enriched for genes associated with immune response.
  
  
  CONCLUSIONS
  Our 72-gene signature is closely associated with recurrence-free and overall survival in early-stage NSCLC patients and may become a tool for patient selection for adjuvant therapy.
authors.affiliation: Agendia BV.
authors.forename: Paul
authors.initials: P
authors.lastname: Roepman
authors.forename: Jacek
authors.initials: J
authors.lastname: Jassem
authors.forename: Egbert F
authors.initials: EF
authors.lastname: Smit
authors.forename: Thomas
authors.initials: T
authors.lastname: Muley
authors.forename: Jacek
authors.initials: J
authors.lastname: Niklinski
authors.forename: Tony
authors.initials: T
authors.lastname: van de Velde
authors.forename: Anke T
authors.initials: AT
authors.lastname: Witteveen
authors.forename: Witold
authors.initials: W
authors.lastname: Rzyman
authors.forename: Arno
authors.initials: A
authors.lastname: Floore
authors.forename: Sjaak
authors.initials: S
authors.lastname: Burgers
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Giaccone
authors.forename: Michael
authors.initials: M
authors.lastname: Meister
authors.forename: Hendrik
authors.initials: H
authors.lastname: Dienemann
authors.forename: Marcin
authors.initials: M
authors.lastname: Skrzypski
authors.forename: Miroslaw
authors.initials: M
authors.lastname: Kozlowski
authors.forename: Wolter J
authors.initials: WJ
authors.lastname: Mooi
authors.forename: Nico
authors.initials: N
authors.lastname: van Zandwijk
mesh_terms: D002289:Carcinoma, Non-Small-Cell Lung / Q000235:genetics* / Q000473:pathology; D018572:Disease-Free Survival; D020869:Gene Expression Profiling; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000473:pathology; D009367:Neoplasm Staging / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D015996:Survival Rate