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

Genome Wide Association Studies in Small-Cell Lung Cancer. A Systematic Review

Small cell lung cancer (SCLC) is one of the deadliest forms of lung cancer, but few information exists regarding the role of genetics, particularly on Genome Wide Association Studies (GWAS). The aim of the study is to explore the evidence available obtained through GWAS studies for SCLC using a systematic review. We performed a literature search in the main databases until July 31st, 2023. We included all human based studies on GWAS for lung cancer which presented results for SCLC. Only studies with participants diagnosed of SCLC with anatomopathological confirmation were included. Fourteen studies were identified; 8 studies showed a relationship between ASCL1 overexpression and SCLC, which may regulate CHRNA5/A3/B4 cluster, producing a consequent nAChR overexpression. Nine papers, including 8 of the previous, found a positive association between SNPs located in chromosome 15 and SCLC. The most important cluster of genes found is CHRNA5/A3/B4 but the mechanism for the role of these genes is unclear. Kyoto Encyclopaedia of Genes and Genome (KEGG) shows that these receptors were found to be overexpressed where nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N'-Nitrosonornicotine (NNN) acts, involving different routes in SCLC carcinogenesis.

An integrative analysis reveals the prognostic value and potential functions of MTMR2 in hepatocellular carcinoma

Abnormal expression of myotubularin-related protein 2 (MTMR2) has been identified in certain types of cancer, leading to varying effects on tumor genesis and progression. However, the various biological significances of MTMR2 in hepatocellular carcinoma (HCC) have not been systematically and comprehensively studied. The aim of this study was to explore the role of MTMR2 in HCC. We obtained the raw data from Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Afterward, we analyzed the data using R and cBioPortal. We investigated the connection between MTMR2 and its expression, prognosis, clinical significance, methylation, genetic alterations, tumor microenvironment (TME), tumor mutation burden (TMB), and drug reactivity in HCC patients. MTMR2 expression levels in HCC cells were validated through western blotting and RT-qPCR. MTMR2 exhibits high levels of expression across a wide range of cancer types, including HCC. MTMR2 is diagnostically valuable in detecting HCC, with its up-regulated expression often being indicative of poor prognosis among HCC patients. The in vitro experiments confirmed elevated MTMR2 expression in HepG2, HUH-7, and MHCC-97H cells. Univariate and multivariate Cox analysis demonstrated that MTMR2 was an independent prognostic factor in HCC patients. The cg20195272 site has the highest degree of methylation in MTMR2, and it is positively correlated with MTMR2 expression. Patients with high levels of methylation at the cg20195272 site show poor prognosis. Analysis of the TME indicates that high expression of MTMR2 is associated with elevated ESTIMATE score and that MTMR2 expression correlates positively with infiltration by resting memory CD4 T cells, activated dendritic cells, as well as several immune checkpoints. There is a negative correlation between MTMR2 expression and TMB, and drug sensitivity analyses have shown that higher MTMR2 expression is associated with lower IC50 values. This study indicates that increased expression of MTMR2 may play a crucial role in the occurrence, progression, diagnosis, prognostic prediction and drug therapy of HCC.

A Genome-Wide Association Study of Small Cell Lung Cancer

INTRODUCTION

Small cell lung cancer (SCLC) comprises 10-15% of all lung cancer cases and is the most aggressive histological type. Survival is poor and the molecular landscape of this disease is extraordinarily complex. The objective of this paper was to perform a Genome-Wide Association Study (GWAS) of this disease using a case-control study specifically designed for small cell lung cancer (SCLC).

METHODS

Incident cases were consecutively recruited from 8 hospitals from different regions of Spain. Controls were recruited from the same hospitals using a frequency sampling based on age and sex distribution of cases. Biological samples were obtained along with detailed information on cases and controls lifestyle, including tobacco and radon exposure.

RESULTS

We included 271 SCLC cases and 557 controls. We found evidence (p-values<10-5) of an association in the complete dataset for several loci, while MAP4 showed a significant association in the gene-based analysis. Pathway analysis suggested that ATR, ATRIP, MCM4, MCM5, ORC4, RPA3 and CDC25A genes have a role on the onset of SCLC.

CONCLUSION

This study provides biological evidence for pathways related to SCLC, offering novel loci for further research.

Etiology of lung cancer: Evidence from epidemiologic studies

Lung cancer is one of the leading causes of cancer incidence and mortality worldwide. While smoking, radon, air pollution, as well as occupational exposure to asbestos, diesel fumes, arsenic, beryllium, cadmium, chromium, nickel, and silica are well-established risk factors, many lung cancer cases cannot be explained by these known risk factors. Over the last two decades the incidence of adenocarcinoma has risen, and it now surpasses squamous cell carcinoma as the most common histologic subtype. This increase warrants new efforts to identify additional risk factors for specific lung cancer subtypes as well as a comprehensive review of current evidence from epidemiologic studies to inform future studies. Given the myriad exposures individuals experience in real-world settings, it is essential to investigate mixture effects from complex exposures and gene-environment interactions in relation to lung cancer and its subtypes.

Genetic variation as a long-distance modulator of RAD21 expression in humans

Somatic mutations and changes in expression of RAD21 are common in many types of cancer. Moreover, sub-optimal levels of RAD21 expression in early development can result in cohesinopathies. Altered RAD21 levels can result directly from mutations in the RAD21 gene. However, whether DNA variants outside of the RAD21 gene could control its expression and thereby contribute to cancer and developmental disease is unknown. In this study, we searched for genomic variants that modify RAD21expression to determine their potential to contribute to development or cancer by RAD21 dysregulation. We searched 42,953,834 genomic variants for a spatial-eQTL association with the transcription of RAD21. We identified 123 significant associations (FDR < 0.05), which are local (cis) or long-distance (trans) regulators of RAD21 expression. The 123 variants co-regulate a further seven genes (AARD, AKAP11, GRID1, KCNIP4, RCN1, TRIOBP, and USP32), enriched for having Sp2 transcription factor binding sites in their promoter regions. The Sp2 transcription factor and six of the seven genes had previously been associated with cancer onset, progression, and metastasis. Our results suggest that genome-wide variation in non-coding regions impacts on RAD21 transcript levels in addition to other genes, which then could impact on oncogenesis and the process of ubiquitination. This identification of distant co-regulation of oncogenes represents a strategy for discovery of novel genetic regions influencing cancer onset and a potential for diagnostics.

Assessing Lung Cancer Absolute Risk Trajectory Based on a Polygenic Risk Model

Lung cancer is the leading cause of cancer-related death globally. An improved risk stratification strategy can increase efficiency of low-dose CT (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. On the basis of 13,119 patients with lung cancer and 10,008 controls with European ancestry in the International Lung Cancer Consortium, we constructed a polygenic risk score (PRS) via 10-fold cross-validation with regularized penalized regression. The performance of risk model integrating PRS, including calibration and ability to discriminate, was assessed using UK Biobank data (N = 335,931). Absolute risk was estimated on the basis of age-specific lung cancer incidence and all-cause mortality as competing risk. To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial (N = 50,772 participants). The lung cancer ORs for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 [95% confidence interval (CI) = 1.92-3.00; P = 1.80 × 10-14] in the validation set (P trend = 5.26 × 10-20). The OR per SD of PRS increase was 1.26 (95% CI = 1.20-1.32; P = 9.69 × 10-23) for overall lung cancer risk in the validation set. When considering absolute risks, individuals at different PRS deciles showed differential trajectories of 5-year and cumulative absolute risk. The age reaching the LDCT screening recommendation threshold can vary by 4 to 8 years, depending on the individual's genetic background, smoking status, and family history. Collectively, these results suggest that individual's genetic background may inform the optimal lung cancer LDCT screening strategy. SIGNIFICANCE: Three large-scale datasets reveal that, after accounting for risk factors, an individual's genetics can affect their lung cancer risk trajectory, thus may inform the optimal timing for LDCT screening.

A Bayes factor approach with informative prior for rare genetic variant analysis from next generation sequencing data

The discovery of rare genetic variants through next generation sequencing is a very challenging issue in the field of human genetics. We propose a novel region-based statistical approach based on a Bayes Factor (BF) to assess evidence of association between a set of rare variants (RVs) located on the same genomic region and a disease outcome in the context of case-control design. Marginal likelihoods are computed under the null and alternative hypotheses assuming a binomial distribution for the RV count in the region and a beta or mixture of Dirac and beta prior distribution for the probability of RV. We derive the theoretical null distribution of the BF under our prior setting and show that a Bayesian control of the false Discovery Rate can be obtained for genome-wide inference. Informative priors are introduced using prior evidence of association from a Kolmogorov-Smirnov test statistic. We use our simulation program, sim1000G, to generate RV data similar to the 1000 genomes sequencing project. Our simulation studies showed that the new BF statistic outperforms standard methods (SKAT, SKAT-O, Burden test) in case-control studies with moderate sample sizes and is equivalent to them under large sample size scenarios. Our real data application to a lung cancer case-control study found enrichment for RVs in known and novel cancer genes. It also suggests that using the BF with informative prior improves the overall gene discovery compared to the BF with noninformative prior.

MTMR2 promotes invasion and metastasis of gastric cancer via inactivating IFNγ/STAT1 signaling

Background

The aberrant expression of myotubularin-related protein 2 (MTMR2) has been found in some cancers, but little is known about the roles and clinical relevance. The present study aimed to investigate the roles and clinical relevance of MTMR2 as well as the underlying mechanisms in gastric cancer (GC).

Methods

MTMR2 expression was examined in 295 GC samples by using immunohistochemistry (IHC). The correlation between MTMR2 expression and clinicopathological features and outcomes of the patients was analyzed. The roles of MTMR2 in regulating the invasive and metastatic capabilities of GC cells were observed using gain-and loss-of-function assays both in vitro and in vivo. The pathways involved in MTMR2-regulating invasion and metastasis were selected and identified by using mRNA expression profiling. Functions and underlying mechanisms of MTMR2-mediated invasion and metastasis were further investigated in a series of in vitro studies.

Results

MTMR2 was highly expressed in human GC tissues compared to adjacent normal tissues and its expression levels were significantly correlated with depth of invasion, lymph node metastasis, and TNM stage. Patients with MTMR2^high had significantly shorter lifespan than those with MTMR2^low. Cox regression analysis showed that MTMR2 was an independent prognostic indicator for GC patients. Knockdown of MTMR2 significantly reduced migratory and invasive capabilities in vitro and metastases in vivo in GC cells, while overexpressing MTMR2 achieved the opposite results. MTMR2 knockdown and overexpression markedly inhibited and promoted the epithelial-mesenchymal transition (EMT), respectively. MTMR2 mediated EMT through the IFNγ/STAT1/IRF1 pathway to promote GC invasion and metastasis. Phosphorylation of STAT1 and IRF1 was increased by MTMR2 knockdown and decreased by MTMR2 overexpression accompanying with ZEB1 down-regulation and up-regulation, respectively. Silencing IRF1 upregulated ZEB1, which induced EMT and consequently enhanced invasion and metastasis in GC cells.

Conclusions

Our findings suggest that MTMR2 is an important promoter in GC invasion and metastasis by inactivating IFNγ/STAT1 signaling and may act as a new prognostic indicator and a potential therapeutic target for GC.

Electronic supplementary material

The online version of this article (10.1186/s13046-019-1186-z) contains supplementary material, which is available to authorized users.

Multi-Omics Analysis Reveals a HIF Network and Hub Gene EPAS1 Associated with Lung Adenocarcinoma

Recent technological advancements have permitted high-throughput measurement of the human genome, epigenome, metabolome, transcriptome, and proteome at the population level. We hypothesized that subsets of genes identified from omic studies might have closely related biological functions and thus might interact directly at the network level. Therefore, we conducted an integrative analysis of multi-omic datasets of non-small cell lung cancer (NSCLC) to search for association patterns beyond the genome and transcriptome. A large, complex, and robust gene network containing well-known lung cancer-related genes, including EGFR and TERT, was identified from combined gene lists for lung adenocarcinoma. Members of the hypoxia-inducible factor (HIF) gene family were at the center of this network. Subsequent sequencing of network hub genes within a subset of samples from the Transdisciplinary Research in Cancer of the Lung-International Lung Cancer Consortium (TRICL-ILCCO) consortium revealed a SNP (rs12614710) in EPAS1 associated with NSCLC that reached genome-wide significance (OR = 1.50; 95% CI: 1.31-1.72; p = 7.75 × 10^-9). Using imputed data, we found that this SNP remained significant in the entire TRICL-ILCCO consortium (p = .03). Additional functional studies are warranted to better understand interrelationships among genetic polymorphisms, DNA methylation status, and EPAS1 expression.

A Decade of GWAS Results in Lung Cancer

Genome-wide association studies (GWAS) were successful to identify genetic factors robustly associated with lung cancer. This review aims to synthesize the literature in this field and accelerate the translation of GWAS discoveries into results that are closer to clinical applications. A chronologic presentation of published GWAS on lung cancer susceptibility, survival, and response to treatment is presented. The most important results are tabulated to provide a concise overview in one read. GWAS have reported 45 lung cancer susceptibility loci with varying strength of evidence and highlighted suspected causal genes at each locus. Some genetic risk loci have been refined to more homogeneous subgroups of lung cancer patients in terms of histologic subtypes, smoking status, gender, and ethnicity. Overall, these discoveries are an important step for future development of new therapeutic targets and biomarkers to personalize and improve the quality of care for patients. GWAS results are on the edge of offering new tools for targeted screening in high-risk individuals, but more research is needed if GWAS are to pay off the investment. Complementary genomic datasets and functional studies are needed to refine the underlying molecular mechanisms of lung cancer preliminarily revealed by GWAS and reach results that are medically actionable. Cancer Epidemiol Biomarkers Prev; 27(4); 363-79. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Complex genetic control of lung tumorigenesis in resistant mice strains

The SM/J mouse strain is resistant to chemically‐induced lung tumorigenesis despite having a haplotype, in the pulmonary adenoma susceptibility locus (Pas1) locus, that confers tumor susceptibility in other strains. To clarify this inconsistent genotype‐phenotype correlation, we crossed SM/J mice with another resistant strain and conducted genome‐wide linkage analysis in the (C57BL/6J × SM/J)F2 progeny exposed to urethane to induce lung tumors. Overall, >80% of F2 mice of both sexes developed from 1 to 20 lung tumors. Genotyping of 372 F2 mice for 744 informative non‐redundant SNPs dispersed over all autosomal chromosomes revealed four quantitative trait loci (QTLs) affecting lung tumor multiplicity, on chromosomes 3 (near rs13477379), 15 (rs6285067), 17 (rs33373629) and 18 (rs3706601), all with logarithm of the odds (LOD) scores >5. Four QTLs modulated total lung tumor volume, on chromosome 3 (rs13477379), 10 (rs13480702), 15 (rs6285067) and 17 (rs3682923), all with LOD scores >4. No QTL modulating lung tumor multiplicity or total volume was detected in Pas1 on chromosome 6. The present study demonstrates that the SM/J strain carries, at the Pas1 locus, the resistance allele: a finding that will facilitate identification of the Pas1 causal element. More generally, it demonstrates that lung tumorigenesis is under complex polygenic control even in a pedigree with low susceptibility to this neoplasia, suggesting that the genetics of lung tumorigenesis is much more complex than evidenced by the pulmonary adenoma susceptibility and resistance loci that have, so far, been mapped in a small number of crosses between a few inbred strains.

Association between GWAS-identified lung adenocarcinoma susceptibility loci and EGFR mutations in never-smoking Asian women, and comparison with findings from Western populations

To evaluate associations by EGFR mutation status for lung adenocarcinoma risk among never-smoking Asian women, we conducted a meta-analysis of 11 loci previously identified in genome-wide association studies (GWAS). Genotyping in an additional 10,780 never-smoking cases and 10,938 never-smoking controls from Asia confirmed associations with eight known single nucleotide polymorphisms (SNPs). Two new signals were observed at genome-wide significance (P < 5 × 10-8), namely, rs7216064 (17q24.3, BPTF), for overall lung adenocarcinoma risk, and rs3817963 (6p21.3, BTNL2) which is specific to cases with EGFR mutations. In further sub-analyses by EGFR status, rs9387478 (ROS1/DCBLD1) and rs2179920 (HLA-DPB1) showed stronger estimated associations in EGFR-positive compared to EGFR-negative cases. Comparison of the overall associations with published results in Western populations revealed that the majority of these findings were distinct, underscoring the importance of distinct contributing factors for smoking and non-smoking lung cancer. Our results extend the catalogue of regions associated with lung adenocarcinoma in non-smoking Asian women and highlight the importance of how the germline could inform risk for specific tumour mutation patterns, which could have important translational implications.