Gene Signatures Stratify Computed Tomography Screening Detected Lung Cancer in High-Risk Populations

Abstract

BackgroundAlthough screening programmes of smokers have detected resectable early lung cancers more frequently than expected, their efficacy in reducing mortality remains debatable. To elucidate the biological features of computed tomography (CT) screening detected lung cancer, we examined the mRNA signatures on tumours according to the year of detection, stage and survival. MethodsGene expression profiles were analysed on 28 patients (INT–IEO training cohort) and 24 patients of Multicentre Italian Lung Detection (MILD validation cohort). The gene signatures generated from the training set were validated on the MILD set and a public deposited DNA microarray data set (GSE11969). Expression of selected genes and proteins was validated by real-time RT-PCR and immunohistochemistry. Enriched core pathway and pathway networks were explored by GeneSpring GX10. FindingsA 239-gene signature was identified according to the year of tumour detection in the training INT–IEO set and correlated with the patients' outcomes. These signatures divided the MILD patients into two distinct survival groups independently of tumour stage, size, histopathological type and screening year. The signatures can also predict survival in the clinically detected cancers (GSE11969). Pathway analyses revealed tumours detected in later years enrichment of the PI3K/PTEN/AKT pathway, with up-regulation of PDPK1, ITGB1 and down-regulation of FOXO1A. Analysis of normal lung tissue from INT–IEO cohort produced signatures distinguishing patients with early from late detected tumours. InterpretationThe distinct pattern of “indolent” and “aggressive” tumour exists in CT-screening detected lung cancer according to the gene expression profiles. The early development of an aggressive phenotype may account for the lack of mortality reduction by screening observed in some cohorts.