Integrative splicing-quantitative-trait-locus analysis reveals risk loci for non-small-cell lung cancer.

Splicing quantitative trait loci (sQTLs) have been demonstrated to contribute to disease etiology by affecting alternative splicing. However, the role of sQTLs in the development of non-small-cell lung cancer (NSCLC) remains unknown. Thus, we performed a genome-wide sQTL study to identify genetic variants that affect alternative splicing in lung tissues from 116 individuals of Chinese ancestry, which resulted in the identification of 1,385 sQTL-harboring genes (sGenes) containing 378,210 significant variant-intron pairs. A comprehensive characterization of these sQTLs showed that they were enriched in actively transcribed regions, genetic regulatory elements, and splicing-factor-binding sites. Moreover, sQTLs were largely distinct from expression quantitative trait loci (eQTLs) and showed significant enrichment in potential risk loci of NSCLC. We also integrated sQTLs into NSCLC GWAS datasets (13,327 affected individuals and 13,328 control individuals) by using splice-transcriptome-wide association study (spTWAS) and identified alternative splicing events in 19 genes that were significantly associated with NSCLC risk. By using functional annotation and experiments, we confirmed an sQTL variant, rs35861926, that reduced the risk of lung adenocarcinoma (rs35861926-T, OR = 0.88, 95% confidence interval [CI]: 0.82-0.93, p = 1.87 × 10-5) by promoting FARP1 exon 20 skipping to downregulate the expression level of the long transcript FARP1-011. Transcript FARP1-011 promoted the migration and proliferation of lung adenocarcinoma cells. Overall, our study provided informative lung sQTL resources and insights into the molecular mechanisms linking sQTL variants to NSCLC risk.

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls.

BACKGROUND: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. METHODS: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. RESULTS: Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified. CONCLUSIONS: Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. PLAIN LANGUAGE SUMMARY: The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.

Integrative analyses of N6-methyladenosine-associated single-nucleotide polymorphisms (m6A-SNPs) identify tumor suppressor gene AK9 in lung cancer.

N6 -methyladenosine (m6 A) modification has been identified as one of the most important epigenetic regulation mechanisms in the development of human cancers. However, the association between m6 A-associated single-nucleotide polymorphisms (m6 A-SNPs) and lung cancer risk remains largely unknown. Here, we identified m6 A-SNPs and examined the association of these m6 A-SNPs with lung cancer risk in 13,793 lung cancer cases and 14,027 controls. In silico functional annotation was used to identify causal m6 A-SNPs and target genes. Furthermore, methylated RNA immunoprecipitation and quantitative real-time polymerase chain reaction (MeRIP-qPCR) assay was performed to assess the m6 A modification level of different genotypes of the causal SNP. In vitro assays were performed to validate the potential role of the target gene in lung cancer. A total of 8794 m6 A-SNPs were detected, among which 397 SNPs in nine susceptibility loci were associated with lung cancer risk, including six novel loci. Bioinformatics analyses indicated that rs1321328 in 6q21 was located around the m6 A modification site of AK9 and significantly reduced AK9 expression (ß = -0.15, p = 2.78 × 10-8 ). Moreover, AK9 was significantly downregulated in lung cancer tissues than that in adjacent normal tissues of samples from the Cancer Genome Atlas and Nanjing Lung Cancer Cohort. MeRIP-qPCR assay suggested that C allele of rs1321328 could significantly decrease the m6 A modification level of AK9 compared with G allele. In vitro assays verified the tumor-suppressing role of AK9 in lung cancer. These findings shed light on the pathogenic mechanism of lung cancer susceptibility loci linked with m6 A modification.

Cancer-testis non-coding RNA LEF1-AS1 regulates the nuclear translocation of PDCD5 and suppresses its interaction with p53 signaling: a novel target for immunotherapy in esophageal squamous cell carcinoma.

Despite the improvement of current classical treatment, the prognosis of esophageal squamous cell carcinoma (ESCC) remains poor. Immunotherapy, as a new treatment method, has revolutionized the therapy of various cancer types and created more attractive for ESCC. Cancer-testis genes (CTGs), because of its characteristic expression and immunomodulation property, are considered as the ideal targets for tumor immunotherapy. However, the ESCC-specific CTGs, especially long non-coding RNA (lncRNA), has not been elucidated. In the present study, a systematic strategy was adopted to screen ESCC-specific cancer-testis lncRNA (CT-lncRNA). Collectively, 447 genes were recognized as ESCC-specific CT-lncRNAs, in particularly LEF1-AS1 showed the most aberrantly expression and clinically associated with poor outcome. Functional assays revealed that H3K27 acetylation in LEF1-AS1 promoter might give rise to the activation of LEF1-AS1 during ESCC tumorigenesis. The activated LEF1-AS1 was predominantly localized in the cytoplasm implicated in regulation of apoptosis and proliferation capacities of ESCC cells in vitro and in vivo. Further mechanistic studies unveiled that LEF1-AS1 participated in ESCC by interacting with RNA binding protein PDCD5 through weakened its nuclear translocation binding to TP53, leading to p53 degradation and disruption the transcription of downstream genes. Taken together, our findings suggest that LEF1-AS1 acts as a CT-lncRNA and might be an ideal immunotherapeutic target for clinical intervention for ESCC.

A cross-tissue transcriptome-wide association study identifies novel susceptibility genes for lung cancer in Chinese populations.

Although dozens of susceptibility loci have been identified for lung cancer in genome-wide association studies (GWASs), the susceptibility genes and underlying mechanisms remain unclear. In this study, we conducted a cross-tissue transcriptome-wide association study (TWAS) with UTMOST based on summary statistics from 13 327 lung cancer cases and 13 328 controls and the genetic-expression matrix over 44 human tissues in the Genotype-Tissue Expression (GTEx) project. After further evaluating the associations in each tissue, we revealed 6 susceptibility genes in known loci and identified 12 novel ones. Among those, five novel genes, including DCAF16 (Pcross-tissue = 2.57 × 10-5, PLung = 2.89 × 10-5), CBL (Pcross-tissue = 5.08 × 10-7, PLung = 1.82 × 10-4), ATR (Pcross-tissue = 1.45 × 10-5, PLung = 9.68 × 10-5), GYPE (Pcross-tissue = 1.45 × 10-5, PLung = 2.17 × 10-3) and PARD3 (Pcross-tissue = 5.79 × 10-6, PLung = 4.05 × 10-3), were significantly associated with the risk of lung cancer in both cross-tissue and lung tissue models. Further colocalization analysis indicated that rs7667864 (C > A) and rs2298650 (G > T) drove the GWAS association signals at 4p15.31-32 (OR = 1.09, 95%CI: 1.04-1.12, PGWAS = 5.54 × 10-5) and 11q23.3 (OR = 1.08, 95%CI: 1.04-1.13, PGWAS = 5.55 × 10-5), as well as the expression of DCAF16 (ßGTEx = 0.24, PGTEx = 9.81 × 10-15; ßNJLCC = 0.29, PNJLCC = 3.84 × 10-8) and CBL (ßGTEx = -0.17, PGTEx = 2.82 × 10-8; ßNJLCC = -0.32, PNJLCC = 2.61 × 10-7) in lung tissue. Functional annotations and phenotype assays supported the carcinogenic effect of these novel susceptibility genes in lung carcinogenesis.

Development, validation, and evaluation of a risk assessment tool for personalized screening of gastric cancer in Chinese populations.

BACKGROUND: Effective risk prediction models are lacking for personalized endoscopic screening of gastric cancer (GC). We aimed to develop, validate, and evaluate a questionnaire-based GC risk assessment tool for risk prediction and stratification in the Chinese population. METHODS: In this three-stage multicenter study, we first selected eligible variables by Cox regression models and constructed a GC risk score (GCRS) based on regression coefficients in 416,343 subjects (aged 40-75 years) from the China Kadoorie Biobank (CKB, development cohort). In the same age range, we validated the GCRS effectiveness in 13,982 subjects from another independent Changzhou cohort (validation cohort) as well as in 5348 subjects from an endoscopy screening program in Yangzhou. Finally, we categorized participants into low (bottom 20%), intermediate (20-80%), and high risk (top 20%) groups by the GCRS distribution in the development cohort. RESULTS: The GCRS using 11 questionnaire-based variables demonstrated a Harrell's C-index of 0.754 (95% CI, 0.745-0.762) and 0.736 (95% CI, 0.710-0.761) in the two cohorts, respectively. In the validation cohort, the 10-year risk was 0.34%, 1.05%, and 4.32% for individuals with a low (≤ 13.6), intermediate (13.7~30.6), and high (≥ 30.7) GCRS, respectively. In the endoscopic screening program, the detection rate of GC varied from 0.00% in low-GCRS individuals, 0.27% with intermediate GCRS, to 2.59% with high GCRS. A proportion of 81.6% of all GC cases was identified from the high-GCRS group, which represented 28.9% of all the screened participants. CONCLUSIONS: The GCRS can be an effective risk assessment tool for tailored endoscopic screening of GC in China. Risk Evaluation for Stomach Cancer by Yourself (RESCUE), an online tool was developed to aid the use of GCRS.

A two-stage genome-wide association study identified four potential early-onset nonsmall cell lung cancer risk loci based on 26,652 participants in Chinese population.

Early-onset lung cancer is rare with an increasing incidence rate. Although several genetic variants have been identified for it with candidate gene approaches, no genome-wide association study (GWAS) has been reported. In this study, a two-stage strategy was adopted: firstly we performed a GWAS to identify variants associated with early-onset nonsmall-cell lung cancer (NSCLC) risk using 2556 cases (age ≤ 50 years) and 13,327 controls by logistic regression model. To further discriminate younger cases from older ones, we took a case-case analysis for the promising variants with above early-onset cases and 10,769 cases (age > 50 years) by Cox regression model. After combining these results, we identified four early-onset NSCLC susceptibility loci at 5p15.33 (rs2853677, odds ratio [OR] = 1.48, 95% confidence interval [CI]: 1.36-1.60, Pcase-control = 3.58 × 10-21 ; hazard ratio [HR] = 1.10, 95% CI: 1.04-1.16, Pcase-case = 6.77 × 10-4 ), 5p15.1 (rs2055817, OR = 1.24, 95% CI: 1.15-1.35, Pcase-control = 1.39 × 10-7 ; HR = 1.08, 95% CI: 1.02-1.14, Pcase-case = 6.90 × 10-3 ), 6q24.2 (rs9403497, OR = 1.24, 95% CI: 1.15-1.35, Pcase-control = 1.61 × 10-7 ; HR = 1.11, 95% CI: 1.05-1.17, Pcase-case = 3.60 × 10-4 ) and 12q14.3 (rs4762093, OR = 1.31, 95% CI: 1.18-1.45, Pcase-control = 1.90 × 10-7 ; HR = 1.10, 95% CI: 1.03-1.18, Pcase-case = 7.49 × 10-3 ). Except for 5p15.33, other loci were found to be associated with NSCLC risk for the first time. All of them had stronger effects in younger patients than in older ones. These results provide a promising overview for early-onset NSCLC genetics.

Development and validation of a blood biomarker score for predicting mortality risk in the general population.

BACKGROUND: Blood biomarkers for multiple pathways, such as inflammatory response, lipid metabolism, and hormonal regulation, have been suggested to influence the risk of mortality. However, few studies have systematically evaluated the combined predictive ability of blood biomarkers for mortality risk. METHODS: We included 267,239 participants from the UK Biobank who had measurements of 28 blood biomarkers and were free of cardiovascular disease (CVD) and cancer at baseline (2006-2010). We developed sex-specific blood biomarker scores for predicting all-cause mortality risk in a training set of 247,503 participants from England and Wales, and validated the results in 19,736 participants from Scotland. Cox and LASSO regression analyses were performed to identify independent predictors for men and women separately. Discrimination and calibration were evaluated by C-index and calibration plots, respectively. We also assessed mediating effects of the biomarkers on the association between traditional risk factors (current smoking, obesity, physical inactivity, hypertension, diabetes) and mortality. RESULTS: A total of 13 independent predictive biomarkers for men and 17 for women were identified and included in the score development. Compared to the lowest tertile of the score, the highest tertile showed a hazard ratio of 5.36 (95% confidence interval [CI] 5.04-5.71) in men and 4.23 (95% CI 3.87-4.62) in women for all-cause mortality. In the validation set, the score yielded a C-index of 0.73 (95% CI 0.72-0.75) in men and 0.70 (95% CI 0.68-0.73) in women for all-cause mortality; it was also predictive of CVD (C-index of 0.76 in men and 0.79 in women) and cancer (C-index of 0.70 in men and 0.67 in women) mortality. Moreover, the association between traditional risk factors and all-cause mortality was largely mediated by cystatin C, C-reactive protein, 25-hydroxyvitamin D, and hemoglobin A1c. CONCLUSIONS: We established sex-specific blood biomarker scores for predicting all-cause and cause-specific mortality in the general population, which hold the potential to identify high-risk individuals and improve targeted prevention of premature death.

Single-cell profiling of human CD127+ innate lymphoid cells reveals diverse immune phenotypes in hepatocellular carcinoma.

BACKGROUND AND AIMS: Innate lymphoid cells (ILCs) are tissue-resident lymphocytes that play critical roles in cytokine-mediated regulation of homeostasis and inflammation. However, relationships between their immune phenotypic characteristics and HCC remain largely unexplored. APPROACH AND RESULTS: We performed single-cell RNA sequencing analysis on sorted hepatic ILC cells from human patients with HCC and validated using flow cytometry, multiplex immunofluorescence staining, and functional experiments. Moreover, we applied selection strategies to enrich ILC populations in HCC samples to investigate the effects of B cells on the immune reaction of inducible T cell costimulator (ICOS)+ ILC2 cells. Dysregulation of ILCs was manifested by the changes in cell numbers or subset proportions in HCC. Seven subsets of 3433 ILCs were identified with unique properties, of which ICOS+ ILC2a were preferentially enriched in HCC and correlated with poor prognosis. Mechanistically, we report that B cells, particularly resting naïve B cells, have a previously unrecognized function that is involved in inflammatory differentiation of ILC2 cells. B cell-derived ICOSL signaling was responsible for exacerbating inflammation through the increased production of IL-13 in ICOS+ ILC2a cells. Heat shock protein 70 (HSP70) genes Heat Shock Protein Family A Member 1A (HSPA1A) and Heat Shock Protein Family A Member 1B (HSPA1B) were highly expressed in ILC2s in late-stage HCC, and targeting to ICOS and its downstream effector HSP70 in ILC2s suppressed tumor growth and remodeled the immunosuppressive tumor microenvironment. CONCLUSIONS: This in-depth understanding sheds light on B cell-driven innate type 2 inflammation and provides a potential strategy for HCC immunotherapy.

Genomic Characterization Revealed PM2.5-Associated Mutational Signatures in Lung Cancer Including Activation of APOBEC3B.

Fine particulate matter (PM2.5) exposure causes DNA mutations and abnormal gene expression leading to lung cancer, but the detailed mechanisms remain unknown. Here, analysis of genomic and transcriptomic changes upon a PM2.5 exposure-induced human bronchial epithelial cell-based malignant transformed cell model in vitro showed that PM2.5 exposure led to APOBEC mutational signatures and transcriptional activation of APOBEC3B along with other potential oncogenes. Moreover, by analyzing mutational profiles of 1117 non-small cell lung cancers (NSCLCs) from patients across four different geographic regions, we observed a significantly higher prevalence of APOBEC mutational signatures in non-smoking NSCLCs than smoking in the Chinese cohorts, but this difference was not observed in TCGA or Singapore cohorts. We further validated this association by showing that the PM2.5 exposure-induced transcriptional pattern was significantly enriched in Chinese NSCLC patients compared with other geographic regions. Finally, our results showed that PM2.5 exposure activated the DNA damage repair pathway. Overall, here we report a previously uncharacterized association between PM2.5 and APOBEC activation, revealing a potential molecular mechanism of PM2.5 exposure and lung cancer.

Association of the interaction between mosaic chromosomal alterations and polygenic risk score with the risk of lung cancer: an array-based case-control association and prospective cohort study.

BACKGROUND: Mosaic chromosomal alterations (mCAs) detected from blood-derived DNA are large structural alterations of clonal haematopoietic origin and are associated with various diseases, such as haematological malignancies, infections, and solid cancers. We aimed to investigate whether mCAs contribute to the risk of lung cancer and modify the effect of polygenic risk score (PRS) on lung cancer risk prediction. METHODS: The blood-derived DNA of patients with lung cancer and cancer-free controls with Chinese ancestry from the Nanjing Lung Cancer Cohort (NJLCC) study were genotyped with a Global Screening Array, and mCAs were detected with the Mosaic Chromosomal Alterations (MoChA) pipeline. mCA call sets of individuals with European ancestry were obtained from the prospective cohort UK Biobank (UKB) study, including documented incident lung cancer. All patients with lung cancer from the NJLCC study (aged 15 years or older at diagnosis) were histopathologically confirmed as new lung cancer cases by at least two pathologists and were free of chemotherapy or radiotherapy before diagnosis. Participants with incident lung cancer (aged 37-73 years at assessment) diagnosed after recruitment to the UKB were identified through linkage to national cancer registries. Logistic regression and Cox proportional hazard models were applied to evaluate associations between mCAs and risk of lung cancer in the NJLCC (logistic regression) and UKB (Cox proportional hazard model) studies. FINDINGS: The NJLCC study included 10 248 individuals (6445 [62·89%] men and 3803 [37·11%] women; median age 60·0 years [IQR 53·0-66·0]) with lung cancer and 9298 individuals (5871 [63·14%] men and 3427 [36·86%] women; median age 60·0 years [52·0-65·0]) without lung cancer recruited from three sub-regions (north, central, and south) across China between April 15, 2003, and Aug 18, 2017. The UKB included 450 821 individuals recruited from 22 centres across the UK between March 13, 2006, and Nov 1, 2010, including 2088 individuals with lung cancer (1075 [51·48%] men and 1013 [48·52%] women; median age 63·0 years [IQR 59·0-66·0]), and 448 733 participants were free of lung cancer (204 713 [45·62%] men and 244 020 [54·38%] women; median age 58·0 years [IQR 50·0-63·0]). Compared with non-carriers of mosaic losses, carriers had a significantly increased risk of lung cancer in the NJLCC (odds ratio [OR] 1·81, 95% CI 1·43-2·28; p=6·69 × 10-7) and UKB (hazard ratio [HR] 1·40, 95% CI 1·00-1·95; p=0·048) studies. This increased risk was even higher in patients with expanded cell fractions of mCAs (ie, cell fractions ≥10% vs cell fractions <10%) in the NJLCC (OR 1·61 [95% CI 1·26-2·08] vs 1·03 [0·83-1·26]; p for heterogeneity test=6·41 × 10-3). A significant multiplicative interaction was observed between PRS and mosaic losses on the risk of lung cancer in both the NJLCC (interaction p value=0·030) and UKB (p=0·043). Compared with non-carriers of mosaic loss abnormalities with low genetic risk, participants with expanded mosaic losses (cell fractions ≥10%) and high genetic risk had around a six-times increased risk of lung cancer in the NJLCC study (OR 6·40 [95% CI 3·22-12·69]), and an almost four-times increased risk of lung cancer (HR 3·75 [95% CI 1·86-7·55]) in the UKB study. The additive interaction also contributed a 3·67 (95% CI 0·49-6·85) relative excess risk of developing lung cancer in the NJLCC study, and a 2·15 (0·12-4·19) relative excess risk in the UKB study. INTERPRETATION: mCAs act as a new endogenous indicator for the risk of lung cancer and might be jointly used with PRS to optimise personalised risk stratification for lung cancer. FUNDING: National Natural Science Foundation of China, Outstanding Youth Foundation of Jiangsu Province, Natural Science Foundation of Jiangsu Province, and Postdoctoral Science Foundation of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Untargeted plasma metabolomics for risk prediction of hepatocellular carcinoma: A prospective study in two Chinese cohorts.

Characterization of metabolic perturbation prior to hepatocellular carcinoma (HCC) may deepen the understanding of causal pathways and identify novel biomarkers for early prevention. We conducted two 1:1 matched nested case-control studies (108 and 55 pairs) to examine the association of plasma metabolome (profiled using LC-MS) with the risk of HCC based on two prospective cohorts in China. Differential metabolites were identified by paired t tests and orthogonal partial least-squares discriminant analysis (OPLS-DA). Weighted gene coexpression network analysis (WGCNA) was performed to classify metabolites into modules for identifying biological pathways involved in hepatocarcinogenesis. We assessed the risk predictivity of metabolites using multivariable logistic regression models. Among 612 named metabolites, 44 differential metabolites were identified between cases and controls, including 12 androgenic/progestin steroid hormones, 8 bile acids, 10 amino acids, 6 phospholipids, and 8 others. These metabolites were associated with HCC in the multivariable logistic regression analyses, with odds ratios ranging from 0.19 (95% confidence interval [CI]: 0.11-0.35) to 5.09 (95% CI: 2.73-9.50). WGCNA including 612 metabolites showed 8 significant modules related to HCC risk, including those representing metabolic pathways of androgen and progestin, primary and secondary bile acids, and amino acids. A combination of 18 metabolites of independent effects showed the potential to predict HCC risk, with an AUC of 0.87 (95% CI: 0.82-0.92) and 0.86 (95% CI: 0.80-0.93) in the training and validation sets, respectively. In conclusion, we identified a panel of plasma metabolites that could be implicated in hepatocellular carcinogenesis and have the potential to predict HCC risk.

Circulating C-reactive protein increases lung cancer risk: Results from a prospective cohort of UK Biobank.

Chronic inflammation has been associated with the development of lung cancer. In this study, we examined the association between C-reactive protein (CRP) and lung cancer in a prospective cohort study and used Mendelian randomization (MR) to clarify the causality. We included 420 977 participants from the UK Biobank (UKB) in the analyses; 1892 thereof were diagnosed with lung cancer during the follow-up. Hazards ratios (HRs) of CRP concentrations were estimated by Cox proportional hazard models and two approaches of MR analysis were performed. Besides, we added CRP concentrations to epidemiological model of lung cancer to evaluate its prediagnostic role through time-dependent receiver operating characteristic curve analysis. Elevated CRP levels were associated with a 22% increased lung cancer risk per 1 SD increase (HR = 1.22, 95% confidence interval [CI] = 1.18-1.26). Positive associations were observed in small cell lung cancer (HR = 1.21, 95% CI = 1.10-1.33), lung adenocarcinoma (HR = 1.17, 95% CI = 1.11-1.23) and lung squamous cell carcinoma (HR = 1.22, 95% CI = 1.14-1.31). No genetical association of circulating CRP levels and lung cancer risk was observed in MR analysis. When added to a risk model of lung cancer, CRP improved the performance of model as long as 8 years among current smokers (basic model: C-statistic = 0.78 [95% CI = 0.75-0.80]; CRP model: C-statistic = 0.79 [95% CI = 0.76-0.81]; Pnonadjusted  = .003, Padjusted  = .014). Our results did not support the causal association of circulating CRP with lung cancer risk. However, circulating CRP could be a prediagnostic marker of lung cancer as long as 8 years in advance for current smokers.

Functional characterization and clinical significance of super-enhancers in lung adenocarcinoma.

Super-enhancers (SEs) are important transcriptional regulators in tumorigenesis; however, the functional characterization and clinical significance of SEs in lung adenocarcinoma (LUAD) remain unclear. By using H3K27ac ChIP-seq data of two LUAD cell lines and eight lung tissues, we detected 1045 cancer-specific and 5032 normal-specific SEs. Compared to normal-specific SEs, cancer-specific SEs have different regulatory mechanisms where associated target genes were enriched in critical tumor-related pathways and tended to be regulated by transcription factors of Fos Proto-Oncogene, AP-1 Transcription Factor Subunit and Jun Proto-Oncogene, AP-1 Transcription Factor Subunit families. By using expression data of 513 LUAD and 57 adjacent samples from The Cancer Genome Atlas and 80 tumor-normal paired LUAD samples from the Nanjing Lung Cancer Cohort study, we performed differential expression analysis of target genes for SEs and defined 243 crucial SEs. Unsupervised clustering of crucial SEs revealed two subtypes with different levels of genomic aberrations (i.e., mutation and copy number alteration) and clinical outcomes (progression-free interval: p = 0.030; disease-free interval: p = 0.047). In addition, patients with adverse clinical outcomes were more sensitive to three small molecule inhibitors (bortezomib, doxorubicin, and etoposide), and their targets (PSMB5 and TOP2A) also have elevated expression levels among these patients. Taken together, our findings provided a comprehensive characterization of SEs in LUAD and emphasized their clinical significance in LUAD therapy.

Air Pollution, Genetic Factors, and the Risk of Lung Cancer: A Prospective Study in the UK Biobank.

Rationale: Both genetic and environmental factors contribute to lung cancer, but the degree to which air pollution modifies the impact of genetic susceptibility on lung cancer remains unknown. Objectives: To investigate whether air pollution and genetic factors jointly contribute to incident lung cancer. Methods: We analyzed data from 455,974 participants (53% women) without previous cancer at baseline in the UK Biobank. The concentrations of particulate matter (PM) (PM ⩽2.5 µm in aerodynamic diameter [PM2.5], coarse PM between 2.5 µm and 10 µm in aerodynamic diameter [PMcoarse], and PM ⩽10 µm in aerodynamic diameter [PM10]), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were estimated by using land-use regression models, and the association between air pollutants and incident lung cancer was investigated by using a Cox proportional hazard model. Furthermore, we constructed a polygenic risk score and evaluated whether air pollutants modified the effect of genetic susceptibility on the development of lung cancer. Measurements and Main Results: The results showed significant associations between the risk of lung cancer and PM2.5 (hazard ratio [HR], 1.63; 95% confidence interval [CI], 1.33-2.01; per 5 µg/m3), PM10 (HR, 1.53; 95% CI, 1.20-1.96; per 10 µg/m3), NO2 (HR, 1.10; 95% CI, 1.05-1.15; per 10 µg/m3), and NOx (HR, 1.13; 95% CI, 1.07-1.18; per 20 µg/m3). There were additive interactions between air pollutants and the genetic risk. Compared with participants with low genetic risk and low air pollution exposure, those with high air pollution exposure and high genetic risk had the highest risk of lung cancer (PM2.5: HR, 1.71; 95% CI, 1.45-2.02; PM10: HR, 1.77; 95% CI, 1.50-2.10; NO2: HR, 1.77; 95% CI, 1.42-2.22; NOx: HR, 1.67; 95% CI, 1.43-1.95). Conclusions: Long-term exposure to air pollution may increase the risk of lung cancer, especially in those with high genetic risk.

Investigation of the relationships between sleep behaviors and risk of healthspan termination: a prospective cohort study based on 323,373 UK-Biobank participants.

OBJECTIVES: To examine the associations between four sleep behaviors and the risk of healthspan termination. METHODS: This study included 323,373 participants, free of terminated healthspan at baseline, from the UK-Biobank (UKB). We applied multivariable-adjusted Cox regression models to estimate the risk of terminated healthspan based on four sleep behaviors (insomnia/sleeplessness, napping, daytime sleepiness, and difficulty getting up from bed), which were self-reported and measured on Likert scales from "usually" to "never/rarely" experiences. In this study, healthspan was defined based on eight events that are strongly associated with longevity (congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, diabetes, cancer, and death). RESULTS: Participants who reported the following unhealthy sleep behaviors had a significantly higher risk of terminated healthspan: "usually experience sleeplessness/insomnia" (HR = 1.05, 95% CI: 1.03-1.07; P < 0.001); "usually nap" (HR = 1.22, 95% CI: 1.18-1.26; P < 0.01); "excessive daytime sleepiness" (HR = 1.25, 95% CI: 1.19-1.32; P < 0.001); and "difficult getting up from bed" (HR = 1.08, 95% CI: 1.05-1.10; P < 0.001). The corresponding population attributable risk percentage (PAR%) indicated that about 7% of healthspan termination in this cohort would have been eliminated if all participants had healthy sleep behaviors. CONCLUSION: Participants who reported "usually experience sleeplessness/insomnia," "usually nap," "excessive daytime sleepiness," and "difficult getting up from bed" had increased risk of shortened healthspan. Therefore, adherence to healthy sleep behavior is significant for the extension of healthspan.

Genome-wide gene-smoking interaction study identified novel susceptibility loci for non-small cell lung cancer in Chinese populations.

Gene-smoking interactions play important roles in the development of non-small cell lung cancer (NSCLC). To identify single-nucleotide polymorphisms (SNPs) that modify the association of smoking behavior with NSCLC risk, we conducted a genome-wide gene-smoking interaction study in Chinese populations. The genome-wide interaction analysis between SNPs and smoking status (ever- versus never-smokers) was carried out using genome-wide association studies of NSCLC, which included 13 327 cases and 13 328 controls. Stratified analysis by histological subtypes was also conducted. We used a genome-wide significance threshold of 5 × 10-8 for identifying significant gene-smoking interactions and 1 × 10-6 for identifying suggestive results. Functional annotation was performed to identify potential functional SNPs and target genes. We identified three novel loci with significant or suggestive gene-smoking interaction. For NSCLC, the interaction between rs2746087 (20q11.23) and smoking status reached genome-wide significance threshold [odds ratio (OR) = 0.63, 95% confidence interval (CI): 0.54-0.74, P = 3.31 × 10-8], and the interaction between rs11912498 (22q12.1) and smoking status reached suggestive significance threshold (OR = 0.72, 95% CI: 0.63-0.82, P = 8.10 × 10-7). Stratified analysis by histological subtypes identified suggestive interactions between rs459724 (5q11.2) and smoking status (OR = 0.61, 95% CI: 0.51-0.73, P = 7.55 × 10-8) in the risk of lung squamous cell carcinoma. Functional annotation indicated that both classic and novel biological processes, including nicotine addiction and airway clearance, may modulate the susceptibility to NSCLC. These novel loci provide new insights into the biological mechanisms underlying NSCLC risk. Independent replication in large-scale studies is needed and experimental studies are warranted to functionally validate these associations.

RNAIndel: discovering somatic coding indels from tumor RNA-Seq data.

MOTIVATION: Reliable identification of expressed somatic insertions/deletions (indels) is an unmet need due to artifacts generated in PCR-based RNA-Seq library preparation and the lack of normal RNA-Seq data, presenting analytical challenges for discovery of somatic indels in tumor transcriptome. RESULTS: We present RNAIndel, a tool for predicting somatic, germline and artifact indels from tumor RNA-Seq data. RNAIndel leverages features derived from indel sequence context and biological effect in a machine-learning framework. Except for tumor samples with microsatellite instability, RNAIndel robustly predicts 88-100% of somatic indels in five diverse test datasets of pediatric and adult cancers, even recovering subclonal (VAF range 0.01-0.15) driver indels missed by targeted deep-sequencing, outperforming the current best-practice for RNA-Seq variant calling which had 57% sensitivity but with 14 times more false positives. AVAILABILITY AND IMPLEMENTATION: RNAIndel is freely available at https://github.com/stjude/RNAIndel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Meta-analysis of genome-wide association studies and functional assays decipher susceptibility genes for gastric cancer in Chinese populations.

OBJECTIVE: Although a subset of genetic loci have been associated with gastric cancer (GC) risk, the underlying mechanisms are largely unknown. We aimed to identify new susceptibility genes and elucidate their mechanisms in GC development. DESIGN: We conducted a meta-analysis of four genome-wide association studies (GWASs) encompassing 3771 cases and 5426 controls. After targeted sequencing and functional annotation, we performed in vitro and in vivo experiments to confirm the functions of genetic variants and candidate genes. Moreover, we selected 33 promising variants for two-stage replication in 7035 cases and 8323 controls from other five studies. RESULTS: The meta-analysis of GWASs identified three loci at 1q22, 5p13.1 and 10q23.33 associated with GC risk at p<5×10-8 and replicated seven known loci at p<0.05. At 5p13.1, the risk rs59133000[C] allele enhanced the binding affinity of NF-κB1 (nuclear factor kappa B subunit 1) to the promoter of PRKAA1, resulting in a reduced promoter activity and lower expression. The knockout of PRKAA1 promoted both GC cell proliferation and xenograft tumour growth in nude mice. At 10q23.33, the rs3781266[C] and rs3740365[T] risk alleles in complete linkage disequilibrium disrupted and created, respectively, the binding motifs of POU2F1 and PAX3, resulting in an increased enhancer activity and expression of NOC3L, while the NOC3L knockdown suppressed GC cell growth. Moreover, two new loci at 3q11.2 (OR=1.21, p=4.56×10-9) and 4q28.1 (OR=1.14, p=3.33×10-11) were associated with GC risk. CONCLUSION: We identified 12 loci to be associated with GC risk in Chinese populations and deciphered the mechanisms of PRKAA1 at 5p13.1 and NOC3L at 10q23.33 in gastric tumourigenesis.

Genetic risk, incident gastric cancer, and healthy lifestyle: a meta-analysis of genome-wide association studies and prospective cohort study.

BACKGROUND: Genetic variants and lifestyle factors have been associated with gastric cancer risk, but the extent to which an increased genetic risk can be offset by a healthy lifestyle remains unknown. We aimed to establish a genetic risk model for gastric cancer and assess the benefits of adhering to a healthy lifestyle in individuals with a high genetic risk. METHODS: In this meta-analysis and prospective cohort study, we first did a fixed-effects meta-analysis of the association between genetic variants and gastric cancer in six independent genome-wide association studies (GWAS) with a case-control study design. These GWAS comprised 21 168 Han Chinese individuals, of whom 10 254 had gastric cancer and 10 914 geographically matched controls did not. Using summary statistics from the meta-analysis, we constructed five polygenic risk scores in a range of thresholds (p=5 × 10-4 p=5 × 10-5 p=5 × 10-6 p=5 × 10-7, and p=5 × 10-8) for gastric cancer. We then applied these scores to an independent, prospective, nationwide cohort of 100 220 individuals from the China Kadoorie Biobank (CKB), with more than 10 years of follow-up. The relative and absolute risk of incident gastric cancer associated with healthy lifestyle factors (defined as not smoking, never consuming alcohol, the low consumption of preserved foods, and the frequent intake of fresh fruits and vegetables), was assessed and stratified by genetic risk (low [quintile 1 of the polygenic risk score], intermediate [quintile 2-4 of the polygenic risk score], and high [quintile 5 of the polygenic risk score]). Individuals with a favourable lifestyle were considered as those who adopted all four healthy lifestyle factors, those with an intermediate lifestyle adopted two or three factors, and those with an unfavourable lifestyle adopted none or one factor. FINDINGS: The polygenic risk score derived from 112 single-nucleotide polymorphisms (p<5 × 10-5) showed the strongest association with gastric cancer risk (p=7·56 × 10-10). When this polygenic risk score was applied to the CKB cohort, we found that there was a significant increase in the relative risk of incident gastric cancer across the quintiles of the polygenic risk score (ptrend<0·0001). Compared with individuals who had a low genetic risk, those with an intermediate genetic risk (hazard ratio [HR] 1·54 [95% CI 1·22-1·94], p=2·67 × 10-4) and a high genetic risk (2·08 [1·61-2·69], p<0·0001) had a greater risk of gastric cancer. A similar increase in the relative risk of incident gastric cancer was observed across the lifestyle categories (ptrend<0·0001), with a higher risk of gastric cancer in those with an unfavourable lifestyle than those with a favourable lifestyle (2·03 [1·46-2·83], p<0·0001). Participants with a high genetic risk and a favourable lifestyle had a lower risk of gastric cancer than those with a high genetic risk and an unfavourable lifestyle (0·53 [0·29-0·99], p=0·048), with an absolute risk reduction of 1·12% (95% CI 0·62-1·56). INTERPRETATION: Chinese individuals at an increased risk of incident gastric cancer could be identified by use of our newly developed polygenic risk score. Compared with individuals at a high genetic risk who adopt an unhealthy lifestyle, those who adopt a healthy lifestyle could substantially reduce their risk of incident gastric cancer. FUNDING: National Key R&D Program of China, National Natural Science Foundation of China, 333 High-Level Talents Cultivation Project of Jiangsu Province, and China Postdoctoral Science Foundation.