Kristjan Välk

Rare variants of large effect in BRCA2 and CHEK2 affect risk of lung cancer

We conducted imputation to the 1000 Genomes Project of four genome-wide association studies of lung cancer in populations of European ancestry (11,348 cases and 15,861 controls) and genotyped an additional 10,246 cases and 38,295 controls for follow-up. We identified large-effect genome-wide associations for squamous lung cancer with the rare variants BRCA2 p.Lys3326X (rs11571833, odds ratio (OR) = 2.47, P = 4.74 × 10−20) and CHEK2 p.Ile157Thr (rs17879961, OR = 0.38, P = 1.27 × 10−13). We also showed an association between common variation at 3q28 (TP63, rs13314271, OR = 1.13, P = 7.22 × 10−10) and lung adenocarcinoma that had been previously reported only in Asians. These findings provide further evidence for inherited genetic susceptibility to lung cancer and its biological basis. Additionally, our analysis demonstrates that imputation can identify rare disease-causing variants with substantive effects on cancer risk from preexisting genome-wide association study data.

Influence of common genetic variation on lung cancer risk: meta-analysis of 14 900 cases and 29 485 controls

Recent genome-wide association studies (GWASs) have identified common genetic variants at 5p15.33, 6p21–6p22 and 15q25.1 associated with lung cancer risk. Several other genetic regions including variants of CHEK2 (22q12), TP53BP1 (15q15) and RAD52 (12p13) have been demonstrated to influence lung cancer risk in candidate- or pathway-based analyses. To identify novel risk variants for lung cancer, we performed a meta-analysis of 16 GWASs, totaling 14 900 cases and 29 485 controls of European descent. Our data provided increased support for previously identified risk loci at 5p15 (P = 7.2 × 10−16), 6p21 (P = 2.3 × 10−14) and 15q25 (P = 2.2 × 10−63). Furthermore, we demonstrated histology-specific effects for 5p15, 6p21 and 12p13 loci but not for the 15q25 region. Subgroup analysis also identified a novel disease locus for squamous cell carcinoma at 9p21 (CDKN2A/p16INK4A/p14ARF/CDKN2B/p15INK4B/ANRIL; rs1333040, P = 3.0 × 10−7) which was replicated in a series of 5415 Han Chinese (P = 0.03; combined analysis, P = 2.3 × 10−8). This large analysis provides additional evidence for the role of inherited genetic susceptibility to lung cancer and insight into biological differences in the development of the different histological types of lung cancer.

Identification of miR-374a as a prognostic marker for survival in patients with early-stage nonsmall cell lung cancer†

Lung cancer is one of the deadliest types of cancer proven by the poor survival and high relapse rates after surgery. Recently discovered microRNAs (miRNAs), small noncoding RNA molecules, play a crucial role in modulating gene expression networks and are directly involved in the progression of a number of human cancers. In this study, we analyzed the expression profile of 858 miRNAs in 38 Estonian nonsmall cell lung cancer (NSCLC) samples (Stage I and II) and 27 adjacent nontumorous tissue samples using Illumina miRNA arrays. We found that 39 miRNAs were up‐regulated and 33 down‐regulated significantly in tumors compared with normal lung tissue. We observed aberrant expression of several well‐characterized tumorigenesis‐related miRNAs, as well as a number of miRNAs whose function is currently unknown. We show that low expression of miR‐374a in early‐stage NSCLC is associated with poor patient survival. The combinatorial effect of the up‐ and down‐regulated miRNAs is predicted to most significantly affect pathways associated with cell migration, differentiation and growth, and several signaling pathways that contribute to tumorigenesis. In conclusion, our results demonstrate that expression of miR‐374a at early stages of NSCLC progression can serve as a prognostic marker for patient risk stratification and may be a promising therapeutic target for the treatment of lung cancer.

Gene Expression Profiles of Non-Small Cell Lung Cancer: Survival Prediction and New Biomarkers

Objectives: Despite the well-defined histological types of non-small cell lung cancer (NSCLC), a given stage is often associated with wide-ranging survival rates and treatment outcomes. This disparity has led to an increased demand for the discovery and identification of new informative biomarkers. Methods: In the current study, we screened 81 NSCLC samples using Illumina® whole-genome gene expression microarrays in an effort to identify differentially expressed genes and new NSCLC biomarkers. Results: We identified novel genes whose expression was upregulated in NSCLC, including SPAG5, POLH, KIF23, and RAD54L, which are associated with mitotic spindle formation, DNA repair, chromosome segregation, and dsDNA break repair, respectively. We also identified several novel genes whose expression was downregulated in NSCLC, including SGCG, NLRC4, MMRN1, and SFTPD, which are involved in extracellular matrix formation, apoptosis, blood vessel leakage, and inflammation, respectively. We found a significant correlation between RNA degradation and survival in adenocarcinoma cases. Conclusions: Even though the follow-up time was too limited to draw final conclusions, we were able to show better prediction p values in a group selection based on molecular profiles compared to histology. The current study also uncovered new candidate biomarker genes that are likely to be involved in diverse processes associated with NSCLC development.

Methylation Markers of Early-Stage Non-Small Cell Lung Cancer

Background Despite of intense research in early cancer detection, there is a lack of biomarkers for the reliable detection of malignant tumors, including non-small cell lung cancer (NSCLC). DNA methylation changes are common and relatively stable in various types of cancers, and may be used as diagnostic or prognostic biomarkers. Methods We performed DNA methylation profiling of samples from 48 patients with stage I NSCLC and 18 matching cancer-free lung samples using microarrays that cover the promoter regions of more than 14,500 genes. We correlated DNA methylation changes with gene expression levels and performed survival analysis. Results We observed hypermethylation of 496 CpGs in 379 genes and hypomethylation of 373 CpGs in 335 genes in NSCLC. Compared to adenocarcinoma samples, squamous cell carcinoma samples had 263 CpGs in 223 hypermethylated genes and 513 CpGs in 436 hypomethylated genes. 378 of 869 (43.5%) CpG sites discriminating the NSCLC and control samples showed an inverse correlation between CpG site methylation and gene expression levels. As a result of a survival analysis, we found 10 CpGs in 10 genes, in which the methylation level differs in different survival groups. Conclusions We have identified a set of genes with altered methylation in NSCLC and found that a minority of them showed an inverse correlation with gene expression levels. We also found a set of genes that associated with the survival of the patients. These newly-identified marker candidates for the molecular screening of NSCLC will need further analysis in order to determine their clinical utility.

Lung cancer and DNA repair genes: multilevel association analysis from the International Lung Cancer Consortium

Lung cancer (LC) is the leading cause of cancer-related death worldwide and tobacco smoking is the major associated risk factor. DNA repair is an important process, maintaining genome integrity and polymorphisms in DNA repair genes may contribute to susceptibility to LC. To explore the role of DNA repair genes in LC, we conducted a multilevel association study with 1655 single nucleotide polymorphisms (SNPs) in 211 DNA repair genes using 6911 individuals pooled from four genome-wide case-control studies. Single SNP association corroborates previous reports of association with rs3131379, located on the gene MSH5 (P = 3.57 × 10-5) and returns a similar risk estimate. The effect of this SNP is modulated by histological subtype. On the log-additive scale, the odds ratio per allele is 1.04 (0.84-1.30) for adenocarcinomas, 1.52 (1.28-1.80) for squamous cell carcinomas and 1.31 (1.09-1.57) for other histologies (heterogeneity test: P = 9.1 × 10(-)(3)). Gene-based association analysis identifies three repair genes associated with LC (P < 0.01): UBE2N, structural maintenance of chromosomes 1L2 and POLB. Two additional genes (RAD52 and POLN) are borderline significant. Pathway-based association analysis identifies five repair pathways associated with LC (P < 0.01): chromatin structure, DNA polymerases, homologous recombination, genes involved in human diseases with sensitivity to DNA-damaging agents and Rad6 pathway and ubiquitination. This first international pooled analysis of a large dataset unravels the role of specific DNA repair pathways in LC and highlights the importance of accounting for gene and pathway effects when studying LC.

Metagenes Associated with Survival in Non-Small Cell Lung Cancer

NSCLC (non-small cell lung cancer) comprises about 80% of all lung cancer cases worldwide. Surgery is most effective treatment for patients with early-stage disease. However, 30%–55% of these patients develop recurrence within 5 years. Therefore, markers that can be used to accurately classify early-stage NSCLC patients into different prognostic groups may be helpful in selecting patients who should receive specific therapies. A previously published dataset was used to evaluate gene expression profiles of different NSCLC subtypes. A moderated two-sample t-test was used to identify differentially expressed genes between all tumor samples and cancer-free control tissue, between SCC samples and AC/BC samples and between stage I tumor samples and all other tumor samples. Gene expression microarray measurements were validated using qRT-PCR. Bayesian regression analysis and Kaplan-Meier survival analysis were performed to determine metagenes associated with survival. We identified 599 genes which were down-regulated and 402 genes which were up-regulated in NSCLC compared to the normal lung tissue and 112 genes which were up-regulated and 101 genes which were down-regulated in AC/BC compared to the SCC. Further, for stage Ib patients the metagenes potentially associated with survival were identified. Genes that expressed differently between normal lung tissue and cancer showed enrichment in gene ontology terms which were associated with mitosis and proliferation. Bayesian regression and Kaplan-Meier analysis showed that gene-expression patterns and metagene profiles can be applied to predict the probability of different survival outcomes in NSCLC patients.

Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia

Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10(-7)) and MTMR2 at 11q21 (rs10501831, P = 3.1×10(-6)) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10(-7)) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10(-4) for KCNIP4, represented by rs9799795) and AC (P = 2.16×10(-4) for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range.

Gene Expression-Based Approaches in Differentiation of Metastases and Second Primary Tumour.

A 64-year-old male patient was diagnosed with 3 consecutive non-small cell lung carcinomas (NSCLC). In the current study, we applied whole-genome gene expression analysis to control, primary and locally recurrent cancer, and supposed metastasis samples of a single patient. According to our knowledge, there are no published papers describing the gene expression profiles of a single patient’s squamous cell lung cancers. As the histology and differentiation grade of the primary cancer and the supposed metastasis differed minimally, but local recurrence was poorly differentiated, molecular profiling of the samples was carried out in order to confirm or reject the hypothesis of second primary cancer. Principal component analysis of the gene expression data revealed distinction of the local recurrence. Gene ontology analysis showed no molecular characteristics of metastasis in the supposed metastasis. Gene expression analysis is valuable and can be supportive in decision-making of diagnostically complicated cancer cases.

Corrigendum: Rare variants of large effect in BRCA2 and CHEK2 affect risk of lung cancer (Nature Genetics (2014) 46 (736-741))

Nat. Genet. 46, 736–741 (2014); published online 1 June 2014; corrected after print 23 January 2017 In the version of this article initially published, the name of author Florence Le Calvez-Kelm appeared incorrectly as Florence LeCalvez-Kelm. The error has been corrected in the HTML and PDF versionsof the article.