An immune response enriched 72-gene prognostic profile for early-stage non-small-cell lung cancer.

Overview

abstract

PURPOSE: 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. EXPERIMENTAL DESIGN: 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.