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.

Pre-operative plasma cell-free circulating tumor DNA and serum protein tumor markers as predictors of lung adenocarcinoma recurrence.

Background: Lung cancer patients have a risk of recurrence even after curatively intended surgery. Cell-free circulating tumor DNA (ctDNA) and circulating tumor marker measurements are easily accessible through peripheral blood and could potentially identify patients with worse prognosis. The aim of this study was to examine ctDNA in pre-operative plasma and the role of tumor markers in pre-operative serum for their predictive potential on risk of tumor recurrence. Methods: Mutation analysis by 26-gene targeted sequencing was performed on 157 lung adenocarcinomas (ACs) from patients surgically treated at the Lund University Hospital 2005-2014. Of these, 58 tumors from patients in stages I-IIIA (34 stage I, 14 stage II and 10 stage III) with mutation(s) in EGFR, BRAF or KRAS were included. ctDNA from corresponding plasma (median 1.5 ml, range 1-1.6) was analyzed for one tumor-specific mutation in either of these three oncogenes using ultrasensitive IBSAFE droplet digital PCR (ddPCR). The tumor markers cancer antigen 125 (CA 125) and carbohydrate antigen 19-9 (CA 19-9) were analyzed in corresponding serum with electrochemiluminiscence immunoassay. Results: 6/7 patients with ctDNA and 19/51 without detected ctDNA were diagnosed with recurrence (log-rank test p = .001). 8/10 patients with positive serum tumor markers and 17/47 without tumor markers were diagnosed with recurrence (log-rank test, p = .0002). Fifteen patients had positive ctDNA and/or tumor markers, 12 of these had recurrence (log-rank test, p < .0001). Conclusion: A combination of tumor markers and ctDNA single mutation detection in low-volume pre-operative blood samples is a promising prognostic test. Prediction of recurrent disease in surgically treated early stage lung cancer can likely be further improved by using larger volumes of blood.

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.

Landscape of somatic allelic imbalances and copy number alterations in human lung carcinoma.

Lung cancer is the worldwide leading cause of death from cancer and has been shown to be a heterogeneous disease at the genomic level. To delineate the genomic landscape of copy number alterations, amplifications, loss-of-heterozygosity (LOH), tumor ploidy and copy-neutral allelic imbalance in lung cancer, microarray-based genomic profiles from 2,141 tumors and cell lines including adenocarcinomas (AC, n = 1,206), squamous cell carcinomas (SqCC, n = 467), large cell carcinomas (n = 37) and small cell lung carcinomas (SCLC, n = 88) were assembled from different repositories. Copy number alteration differences between lung cancer histologies were confirmed in 285 unrelated tumors analyzed by BAC array comparative genomic hybridization. Tumor ploidy patterns were validated by DNA flow cytometry analysis of 129 unrelated cases. Eighty-nine recurrent copy number alterations (55 gains, 34 losses) were identified harboring genes with gene expression putatively driven by gene dosage through integration with gene expression data for 496 cases. Thirteen and 26 of identified regions discriminated AC/SqCC and AC/SqCC/SCLC, respectively, while 48 regions harbored recurrent (n > 15) high-level amplifications comprising established and putative oncogenes, differing in frequency and coamplification patterns between histologies. Lung cancer histologies displayed differences in patterns/frequency of copy number alterations, genomic architecture, LOH, copy-neutral allelic imbalance and tumor ploidy, with AC generally displaying less copy number alterations and allelic imbalance. Moreover, a strong association was demonstrated between different types of copy number alterations and allelic imbalances with tumor aneuploidy. In summary, these analyses provide a comprehensive overview of the landscape of genomic alterations in lung cancer, highlighting differences but also similarities between subgroups of the disease.

Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms.

Despite major advancements in lung cancer treatment, long-term survival is still rare, and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune evasion mechanisms. Here we performed in-depth mass spectrometry (MS)-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition MS-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples.

Clinical Utility of Targeted Sequencing in Lung Cancer: Experience From an Autonomous Swedish Health Care Center.

OBJECTIVES: Mutation analysis by massive parallel sequencing (MPS) is routinely performed in the clinical management of lung cancer in Sweden. We describe the clinical and mutational profiles of lung cancer patients subjected to the first 1.5 years of treatment predictive MPS testing in an autonomous regional health care region. METHODS: Tumors from all patients with lung cancer who had an MPS test from January 2015 to June 2016 in the Skåne health care region in Sweden (1.3 million citizens) were included. Six hundred eleven tumors from 599 patients were profiled using targeted sequencing with a 26-gene exon-focused panel. Data on disease patterns and characteristics of the patients subjected to testing were assembled, and correlations between mutational profiles and clinical features were analyzed. RESULTS: MPS with the 26-gene panel revealed alterations in 92% of the 611 lung tumors, with the most frequent mutations detected in the nontargetable genes TP53 (62%) and KRAS (37%). Neither KRAS nor TP53 mutations were associated with disease pattern, chemotherapy response, progression-free survival, or overall survival in advanced-stage disease treated with platinum-based doublet chemotherapy as a first-line treatment. Among targetable genes, EGFR driver mutations were detected in 10% of the tumors, and BRAF p.V600 variants in 2.3%. For the 71 never smokers (12%), targetable alterations (EGFR mutations, BRAF p.V600, MET exon 14 skipping, or ALK/ROS1 rearrangement) were detected in 59% of the tumors. CONCLUSION: Although the increasing importance of MPS as a predictor of response to targeted therapies is indisputable, its role in prognostics or as a predictor of clinical course in nontargetable advanced stage lung cancer requires further investigation.

CA 19-9 and CA 125 as potential predictors of disease recurrence in resectable lung adenocarcinoma.

OBJECTIVES: Among patients who underwent primary surgery for non-small cell lung cancer (NSCLC), recurrent disease is frequent and cannot be accurately predicted solely from TNM stage and histopathological features. The aim of this study was to examine the association of tumor markers in pre-operative serum with recurrent disease. MATERIAL AND METHODS: Blood samples were collected prior to lung cancer surgery from 107 patients with stage I-III lung adenocarcinoma surgically treated at Lund University hospital, Lund, Sweden, between 2005 and 2011. The serum tumor markers Carcinoembryonic antigen (CEA), Neuron-specific enolase (NSE), Cancer antigen 125 (CA 125), Human epididymis protein 4 (HE4) and Carbohydrate antigen (CA 19-9) were analyzed retrospectively and clinical follow-up data were collected from patient charts. Forty (37%) patients were diagnosed with recurrent disease. RESULTS: Sixty-eight (64%) patients had at least one elevated tumor marker prior to surgery. In analysis of disease-free survival (DFS), CA 125 and/or CA 19-9 were significantly associated with recurrent disease adjusted to stage and adjuvant treatment (hazard ratio 2.8, 95% confidence interval 1.4-5.7, p = 0.006). CONCLUSION: High pre-operative serum CA 19-9 and/or CA 125 might indicate an increased incidence of recurrent disease in resectable lung adenocarcinomas.

Identification of transcriptional subgroups in EGFR-mutated and EGFR/KRAS wild-type lung adenocarcinoma reveals gene signatures associated with patient outcome.

PURPOSE: In lung adenocarcinoma, EGFR and KRAS mutations dominate the mutational spectrum and have clear therapeutic implications. We sought to determine whether transcriptional subgroups of clinical relevance exist within EGFR-mutated, KRAS-mutated, or EGFR and KRAS wild-type (EGFRwt/KRASwt) adenocarcinomas. EXPERIMENTAL DESIGN: Gene expression profiles from 1,186 adenocarcinomas, including 215 EGFR-mutated, 84 KRAS-mutated, and 219 EGFRwt/KRASwt tumors, were assembled and divided into four discovery (n = 522) and four validation cohorts (n = 664). Subgroups within the mutation groups were identified by unsupervised consensus clustering, significance analysis of microarrays (SAM) analysis, and centroid classification across discovery cohorts. Genomic alterations in identified mutation subgroups were assessed by integration of genomic profiles for 158 cases with concurrent data. Multicohort expression subgroup predictors were built for each mutation group using the discovery cohorts, and validated in the four validation cohorts. RESULTS: Consensus clustering within the mutation groups identified reproducible transcriptional subgroups in EGFR-mutated and EGFRwt/KRASwt tumors, but not in KRAS-mutated tumors. Subgroups displayed differences in genomic alterations, clinicopathologic characteristics, and overall survival. Multicohort gene signatures derived from the mutation subgroups added independent prognostic information in their respective mutation group, for adenocarcinoma in general and stage I tumors specifically, irrespective of mutation status, when applied to the validation cohorts. Consistent with their worse clinical outcome, high-risk subgroups showed higher expression of proliferation-related genes, higher frequency of copy number alterations/amplifications, and association with a poorly differentiated tumor phenotype. CONCLUSIONS: We identified transcriptional subgroups in EGFR-mutated and EGFRwt/KRASwt adenocarcinomas with significant differences in clinicopathologic characteristics and patient outcome, not limited to a mutation-specific setting.

Genomic and transcriptional alterations in lung adenocarcinoma in relation to EGFR and KRAS mutation status.

INTRODUCTION: In lung adenocarcinoma, the mutational spectrum is dominated by EGFR and KRAS mutations. Improved knowledge about genomic and transcriptional alterations in and between mutation-defined subgroups may identify genes involved in disease development or progression. METHODS: Genomic profiles from 457 adenocarcinomas, including 113 EGFR-mutated, 134 KRAS-mutated and 210 EGFR and KRAS-wild type tumors (EGFRwt/KRASwt), and gene expression profiles from 914 adenocarcinomas, including 309 EGFR-mutated, 192 KRAS-mutated, and 413 EGFRwt/KRASwt tumors, were assembled from different repositories. Genomic and transcriptional differences between the three mutational groups were analyzed by both supervised and unsupervised methods. RESULTS: EGFR-mutated adenocarcinomas displayed a larger number of copy number alterations and recurrent amplifications, a higher fraction of total loss-of-heterozygosity, higher genomic complexity, and a more distinct expression pattern than EGFR-wild type adenocarcinomas. Several of these differences were also consistent when the three mutational groups were stratified by stage, gender and smoking status. Specific copy number alterations were associated with mutation status, predominantly including regions of gain with the highest frequency in EGFR-mutated tumors. Differential regions included both large and small regions of gain on 1p, 5q34-q35.3, 7p, 7q11.21, 12p12.1, 16p, and 21q, and losses on 6q16.3-q21, 8p, and 9p, with 20-40% frequency differences between the mutational groups. Supervised gene expression analyses identified 96 consistently differentially expressed genes between the mutational groups, and together with unsupervised analyses these analyses highlighted the difficulty in broadly resolving the three mutational groups into distinct transcriptional entities. CONCLUSIONS: We provide a comprehensive overview of the genomic and transcriptional landscape in lung adenocarcinoma stratified by EGFR and KRAS mutations. Our analyses suggest that the overall genomic and transcriptional landscape of lung adenocarcinoma is affected, but only to a minor extent, by EGFR and KRAS mutation status.

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.