A gene expression-based single sample predictor of lung adenocarcinoma molecular subtype and prognosis.

Disease recurrence in surgically treated lung adenocarcinoma (AC) remains high. New approaches for risk stratification beyond tumor stage are needed. Gene expression-based AC subtypes such as the Cancer Genome Atlas Network (TCGA) terminal-respiratory unit (TRU), proximal-inflammatory (PI) and proximal-proliferative (PP) subtypes have been associated with prognosis, but show methodological limitations for robust clinical use. We aimed to derive a platform independent single sample predictor (SSP) for molecular subtype assignment and risk stratification that could function in a clinical setting. Two-class (TRU/nonTRU=SSP2) and three-class (TRU/PP/PI=SSP3) SSPs using the AIMS algorithm were trained in 1655 ACs (n = 9659 genes) from public repositories vs TCGA centroid subtypes. Validation and survival analysis were performed in 977 patients using overall survival (OS) and distant metastasis-free survival (DMFS) as endpoints. In the validation cohort, SSP2 and SSP3 showed accuracies of 0.85 and 0.81, respectively. SSPs captured relevant biology previously associated with the TCGA subtypes and were associated with prognosis. In survival analysis, OS and DMFS for cases discordantly classified between TCGA and SSP2 favored the SSP2 classification. In resected Stage I patients, SSP2 identified TRU-cases with better OS (hazard ratio [HR] = 0.30; 95% confidence interval [CI] = 0.18-0.49) and DMFS (TRU HR = 0.52; 95% CI = 0.33-0.83) independent of age, Stage IA/IB and gender. SSP2 was transformed into a NanoString nCounter assay and tested in 44 Stage I patients using RNA from formalin-fixed tissue, providing prognostic stratification (relapse-free interval, HR = 3.2; 95% CI = 1.2-8.8). In conclusion, gene expression-based SSPs can provide molecular subtype and independent prognostic information in early-stage lung ACs. SSPs may overcome critical limitations in the applicability of gene signatures in lung cancer.

Histological specificity of alterations and expression of KIT and KITLG in non-small cell lung carcinoma.

Characterization of molecules within important oncogenetic pathways may have future implications for development of therapies and biomarkers in lung cancer. One such target is the tyrosine kinase receptor KIT (c-KIT). We evaluated alterations and expression of KIT and its ligand, KITLG (also known as SCF), in 72 clinical lung tumor specimens of different histologies. Gene copy number, mRNA expression levels, and protein expression were assayed using array-based comparative genomic hybridization, real-time quantitative reverse transcription PCR and immunohistochemistry, respectively. For validation, we investigated copy number alterations and mRNA expression in external microarray data sets of 1,600 and 555 primary lung tumors, respectively. Positivity for KIT staining was most common in large cell neuroendocrine carcinoma (LCNEC) which also showed the highest KIT mRNA expression levels whereas expression was lowest in squamous cell carcinoma (SqCC). KIT mRNA expression levels were higher in KIT immunopositive samples, but expression was not affected by KIT copy numbers. Copy number gains of KIT were significantly more frequent in SqCC compared with adenocarcinoma in our own series and in the 1,600-sample data set. Immunopositivity for both KIT and KITLG in the same tumor was rare except in LCNEC. Our results highlight an increased KIT mRNA expression and frequent KIT immunopositivity in LCNEC but point out a poor correlation between KIT copy numbers and expression in SqCC, perhaps reflecting the existence of a protective mechanism against KIT alterations in this subgroup.

Comprehensive analysis of RNA binding motif protein 3 (RBM3) in non-small cell lung cancer.

AIMS: High expression of the RNA-binding motif protein 3 (RBM3) correlates with improved prognosis in several major types of cancer. The aim of the present study was to examine the prognostic value of RBM3 protein and mRNA expression in non-small cell lung cancer (NSCLC). METHODS AND RESULTS: Immunohistochemical expression of RBM3 was evaluated in surgically treated NSCLC from two independent patient populations (n = 213 and n = 306). Staining patterns were correlated with clinicopathological parameters, overall survival (OS), and recurrence-free interval (RFI). Cases with high nuclear RBM3 protein expression had a prolonged 5-year OS in both cohorts when analyzing adenocarcinomas separately (P = .02 and P = .01). RBM3 remained an independent prognostic factor for OS in multivariable analysis of cohort I (HR 0.44, 95% CI 0.21-0.90) and for RFI in cohort II (HR 0.38, 95% CI 0.22-0.74). In squamous cell carcinoma, there was instead an insignificant association to poor prognosis. Also, the expression levels of RBM3 mRNA were investigated in 2087 lung adenocarcinomas and 899 squamous cell carcinomas assembled from 13 and 8 public gene expression microarray datasets, respectively. The RBM3 mRNA levels were not clearly associated with patient outcome in either adenocarcinomas or squamous cell carcinomas. CONCLUSIONS: The results from this study support that high protein expression of RBM3 is linked to improved outcome in lung adenocarcinoma.

Detecting EGFR alterations in clinical specimens-pitfalls and necessities.

We investigated the epidermal growth factor receptor (EGFR) status in early stage lung cancer in Southern Sweden, a population for which there are no previous reports on the EGFR mutation frequency. Three hundred fifty small cell lung cancers, adenocarcinomas (AC), squamous cell carcinomas (SqCC), and large cell carcinomas were analyzed using a combination of techniques for the analysis of protein expression, gene copy numbers, and mutations. Immunohistochemical (IHC) staining with antibodies for the EGFR mutations L858R and del E746-A750 revealed intratumoral heterogeneity and several discrepant cases when compared to mutation-specific polymerase chain reaction (PCR)-based analysis. The frequencies of these two mutations, when considering IHC staining with mutation-specific antibodies in a cohort of 298 cases and subsequent confirmation by PCR, were 10 % in AC and <2 % in SqCC. Furthermore, screening by sequencing of EGFR in a cohort of 52 lung AC and squamous carcinomas demonstrated a more diverse mutation spectrum, not covered by the mutation-specific antibodies. High expression of total EGFR protein was correlated to high gene copy numbers but did not reflect the mutational status of the tumors. We believe that the mutation spectra in a Southern Swedish population is too diverse to be covered by the mutation-specific antibodies, and we also raise some other issues regarding the use of the mutation-specific antibodies, for example concerning heterogeneous expression of the mutated protein, optimal antibody dilution, and discrepancies between staining results and PCR.

Relation between smoking history and gene expression profiles in lung adenocarcinomas.

BACKGROUND: Lung cancer is the worldwide leading cause of death from cancer. Tobacco usage is the major pathogenic factor, but all lung cancers are not attributable to smoking. Specifically, lung cancer in never-smokers has been suggested to represent a distinct disease entity compared to lung cancer arising in smokers due to differences in etiology, natural history and response to specific treatment regimes. However, the genetic aberrations that differ between smokers and never-smokers' lung carcinomas remain to a large extent unclear. METHODS: Unsupervised gene expression analysis of 39 primary lung adenocarcinomas was performed using Illumina HT-12 microarrays. Results from unsupervised analysis were validated in six external adenocarcinoma data sets (n=687), and six data sets comprising normal airway epithelial or normal lung tissue specimens (n=467). Supervised gene expression analysis between smokers and never-smokers were performed in seven adenocarcinoma data sets, and results validated in the six normal data sets. RESULTS: Initial unsupervised analysis of 39 adenocarcinomas identified two subgroups of which one harbored all never-smokers. A generated gene expression signature could subsequently identify never-smokers with 79-100% sensitivity in external adenocarcinoma data sets and with 76-88% sensitivity in the normal materials. A notable fraction of current/former smokers were grouped with never-smokers. Intriguingly, supervised analysis of never-smokers versus smokers in seven adenocarcinoma data sets generated similar results. Overlap in classification between the two approaches was high, indicating that both approaches identify a common set of samples from current/former smokers as potential never-smokers. The gene signature from unsupervised analysis included several genes implicated in lung tumorigenesis, immune-response associated pathways, genes previously associated with smoking, as well as marker genes for alveolar type II pneumocytes, while the best classifier from supervised analysis comprised genes strongly associated with proliferation, but also genes previously associated with smoking. CONCLUSIONS: Based on gene expression profiling, we demonstrate that never-smokers can be identified with high sensitivity in both tumor material and normal airway epithelial specimens. Our results indicate that tumors arising in never-smokers, together with a subset of tumors from smokers, represent a distinct entity of lung adenocarcinomas. Taken together, these analyses provide further insight into the transcriptional patterns occurring in lung adenocarcinoma stratified by smoking history.