A Decade of GWAS Results in Lung Cancer

Genetic correlation and causal associations between circulating C-reactive protein levels and lung cancer risk

PURPOSE

We aimed to characterize genetic correlations and causal associations between circulating C-reactive protein (CRP) levels and the risk of lung cancer (LC).

METHODS

Leveraging summary statistics from genome-wide association studies of circulating CRP levels among 575,531 individuals of European ancestry, and LC risk among 29,266 cases and 56,450 controls, we investigated genetic associations of circulating CRP levels with the risk of overall lung cancer and its histological subtypes, by using linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analyses.

RESULTS

Significant positive genetic correlations between circulating CRP levels and the risk of LC and its histological subtypes were identified from LDSC regression, with correlation coefficients ranging from 0.12 to 0.26, and all false discovery adjusted p < 0.05. Univariable MR demonstrated a nominal association between CRP levels and an increased risk of lung squamous cell carcinoma (SCC) (inverse variance-weighted OR = 1.15, 95% CI 1.01-1.30). However, this association disappeared when multivariable MR included cigarettes per day and/or body mass index. By using our recently developed constrained maximum likelihood-based MR method, we identified significant associations of CRP levels with the risk of overall LC (OR 1.06, 95% CI 1.03-1.09), SCC (OR 1.06, 95% CI 1.02-1.09), and small cell lung cancer (SCLC, OR 1.09, 95% CI 1.03-1.15). Moreover, most univariable and multivariable MR analyses also revealed consistent CRP-SCLC associations.

CONCLUSION

There may be a genetic and causal association between circulating CRP levels and the risk of SCLC, which is in line with previous population-based observational studies.

Identification of pathogenic germline variants in a large Chinese lung cancer cohort by clinical sequencing

Genetic factors play significant roles in the tumorigenicity of lung cancer; however, there is lack of systematic and large-scale characterization of pathogenic germline variants for lung cancer. In this study, germline variants in 146 preselected cancer-susceptibility genes were detected in 17 904 Chinese lung cancer patients by clinical next-generation sequencing. Among 17 904 patients, 1738 patients (9.7%) carried 1840 pathogenic/likely pathogenic (P/LP) variants from 87 cancer-susceptibility genes. SBDS (SBDS ribosome maturation factor) (1.37%), TSHR (thyroid stimulating hormone receptor) (1.20%), BLM (BLM RecQ like helicase) (0.62%), BRCA2 (BRCA2 DNA repair associated) (0.62%), and ATM (ATM serine/threonine kinase) (0.45%) were the top five genes with the highest overall prevalence. The top mutated pathways were all involved in DNA damage repair (DDR). Case-control analysis showed SBDS c.184A>T(p.K62*), TSHR c.1574T>C(p.F525S), BRIP1 (BRCA1 interacting helicase 1) c.1018C>T(p.L340F), and MUTYH (mutY DNA glycosylase) c.55C>T(p.R19*) were significantly associated with increased lung cancer risk (q value < 0.05). P/LP variants in certain genes were associated with early onset of lung cancer. Our study indicates that Chinese lung cancer patients have a higher prevalence of P/LP variants than previously reported. P/LP variants are distributed in multiple pathways and dominated by DNA damage repair-associated pathways. The association between identified P/LP variants and lung cancer risk requires further studies for verification.

Poor statistical power in population-based association study of gene interaction

BACKGROUND

Statistical epistasis, or "gene-gene interaction" in genetic association studies, means the nonadditive effects between the polymorphic sites on two different genes affecting the same phenotype. In the genetic association analysis of complex traits, nevertheless, the researchers haven't found enough clues of statistical epistasis so far.

METHODS

We developed a statistical model where the statistical epistasis was presented as an extra linkage disequilibrium between the polymorphic sites of different risk genes. The power of statistical test for identifying the gene-gene interaction was calculated and then compared in different hypothesis scenarios.

RESULTS

Our results show the statistical power increases with the increasing of interaction coefficient, relative risk, and linkage disequilibrium with genetic markers. However, the power of interaction discovery is much lower than that of regular single-site association test. When rigorous criteria were employed in statistical tests, the identification of gene-gene interaction became a very difficult task. Since the criterion of significance was given to be p-value ≤ 5.0 × 10-8, the same as that of many genome-wide association studies, there is little chance to identify the gene-gene interaction in all kind of circumstances.

CONCLUSIONS

The lack of epistasis tends to be an inevitable result caused by the statistical principles of methods in the genetic association studies and therefore is the inherent characteristic of the research itself.

Interaction between Continuous Pack-Years Smoked and Polygenic Risk Score on Lung Cancer Risk: Prospective Results from the Framingham Heart Study

BACKGROUND

Lung cancer risk attributable to smoking is dose dependent, yet few studies examining a polygenic risk score (PRS) by smoking interaction have included comprehensive lifetime pack-years smoked.

METHODS

We analyzed data from participants of European ancestry in the Framingham Heart Study Original (n = 454) and Offspring (n = 2,470) cohorts enrolled in 1954 and 1971, respectively, and followed through 2018. We built a PRS for lung cancer using participant genotyping data and genome-wide association study summary statistics from a recent study in the OncoArray Consortium. We used Cox proportional hazards regression models to assess risk and the interaction between pack-years smoked and genetic risk for lung cancer adjusting for European ancestry, age, sex, and education.

RESULTS

We observed a significant submultiplicative interaction between pack-years and PRS on lung cancer risk (P = 0.09). Thus, the relative risk associated with each additional 10 pack-years smoked decreased with increasing genetic risk (HR = 1.56 at one SD below mean PRS, HR = 1.48 at mean PRS, and HR = 1.40 at one SD above mean PRS). Similarly, lung cancer risk per SD increase in the PRS was highest among those who had never smoked (HR = 1.55) and decreased with heavier smoking (HR = 1.32 at 30 pack-years).

CONCLUSIONS

These results suggest the presence of a submultiplicative interaction between pack-years and genetics on lung cancer risk, consistent with recent findings. Both smoking and genetics were significantly associated with lung cancer risk.

IMPACT

These results underscore the contributions of genetics and smoking on lung cancer risk and highlight the negative impact of continued smoking regardless of genetic risk.

Comprehensive functional interrogation of susceptibility loci in GWASs identified KIAA0391 as a novel oncogenic driver via regulating pyroptosis in NSCLC

Approximately 51 non-small-cell lung cancer (NSCLC) risk loci have been identified by genome-wide association studies (GWASs). We conducted a high throughput RNA-interference (RNAi) screening to identify the candidate causal genes in NSCLC risk loci. KIAA0391 at 14q13.1 had the highest score and could promote proliferation and metastasis of NSCLC in vitro and in vivo. We next prioritized rs3783313 as a causal variant at 14q13.1, by integrating a large-scale population study consisting of 27,120 lung cancer cases and 27,355 controls, functional annotation, and expression quantitative trait locus (eQTL) analysis. Then we found that rs3783313 could facilitate a promoter-enhancer interaction to upregulate KIAA0391 expression by affecting the affinity of transcription factor NFYA. Mechanistically, KIAA0391 knockdown dramatically influenced pyroptosis-related pathways and increased the expression of CASP1. And KIAA0391 transcriptionally repressed CASP1 by binding to SMAD2 and induced an anti-pyroptosis phenotype, promoting tumorigenesis of NSCLC, which provides new insights and potential target for NSCLC.

TNFRSF19 within the 13q12.12 Risk Locus Functions as a Lung Cancer Suppressor by Binding Wnt3a to Inhibit Wnt/β-Catenin Signaling

Cancer risk loci provide special clues for uncovering pathogenesis of cancers. The TNFRSF19 gene located within the 13q12.12 lung cancer risk locus encodes TNF receptor superfamily member 19 (TNFRSF19) protein and has been proved to be a key target gene of a lung tissue-specific tumor suppressive enhancer, but its functional role in lung cancer pathogenesis remains to be elucidated. Here we showed that the TNFRSF19 gene could protect human bronchial epithelial Beas-2B cells from pulmonary carcinogen nicotine-derived nitrosamine ketone (NNK)-induced malignant transformation. Knockout of the TNFRSF19 significantly increased NNK-induced colony formation rate on soft agar. Moreover, TNFRSF19 expression was significantly reduced in lung cancer tissues and cell lines. Restoration of TNFRSF19 expression in A549 lung cancer cell line dramatically suppressed the tumor formation in xenograft mouse model. Interestingly, the TNFRSF19 protein that is an orphan membrane receptor could compete with LRP6 to bind Wnt3a, thereby inhibiting the Wnt/β-catenin signaling pathway that is required for NNK-induced malignant transformation as indicated by protein pulldown, site mutation, and fluorescence energy resonance transfer experiments. Knockout of the TNFRSF19 enhanced LRP6-Wnt3a interaction, promoting β-catenin nucleus translocation and the downstream target gene expression, and thus sensitized the cells to NNK carcinogen. In conclusion, our study demonstrated that the TNFRSF19 inhibited lung cancer carcinogenesis by competing with LRP6 to combine with Wnt3a to inhibit the Wnt/β-catenin signaling pathway.

IMPLICATIONS

These findings revealed a novel anti-lung cancer mechanism, highlighting the special significance of TNFRSF19 gene within the 13q12.12 risk locus in lung cancer pathogenesis.

Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies

BACKGROUND

Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer.

METHODS

We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer.

RESULTS

Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior.

CONCLUSIONS

We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies.

IMPACT

Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly 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 (β = -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.

An immunogenetic basis for lung cancer risk

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the human leukocyte antigen (HLA)-II loci is associated with reduced lung cancer risk in smokers. Fine-mapping implicated amino acid heterozygosity in the HLA-II peptide binding groove in reduced lung cancer risk, and single-cell analyses showed that smoking drives enrichment of proinflammatory lung macrophages and HLA-II+ epithelial cells. In lung cancer, widespread loss of HLA-II heterozygosity (LOH) favored loss of alleles with larger neopeptide repertoires. Thus, our findings nominate genetic variation in immunosurveillance as a critical risk factor for lung cancer.

Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification

BACKGROUND

Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored.

METHODS

Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold.

RESULTS

Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12-3.50, P-value = 4.13 × 10-15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99-2.49, P-value = 5.70 × 10-46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72-0.74).

CONCLUSIONS

Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.

Lung cancer in patients who have never smoked - an emerging disease

Lung cancer is the most common cause of cancer-related deaths globally. Although smoking-related lung cancers continue to account for the majority of diagnoses, smoking rates have been decreasing for several decades. Lung cancer in individuals who have never smoked (LCINS) is estimated to be the fifth most common cause of cancer-related deaths worldwide in 2023, preferentially occurring in women and Asian populations. As smoking rates continue to decline, understanding the aetiology and features of this disease, which necessitate unique diagnostic and treatment paradigms, will be imperative. New data have provided important insights into the molecular and genomic characteristics of LCINS, which are distinct from those of smoking-associated lung cancers and directly affect treatment decisions and outcomes. Herein, we review the emerging data regarding the aetiology and features of LCINS, particularly the genetic and environmental underpinnings of this disease as well as their implications for treatment. In addition, we outline the unique diagnostic and therapeutic paradigms of LCINS and discuss future directions in identifying individuals at high risk of this disease for potential screening efforts.

The association between METS-IR, an indirect index for insulin resistance, and lung cancer risk

BACKGROUND

Insulin resistance has been reported to increase the risk of breast, prostate and colorectal cancer. However, the role of insulin resistance and its interaction with genetic risk in the development of lung cancer remains controversial. Therefore, we aimed to explore the association between a novel metabolic score for insulin resistance (METS-IR) and lung cancer risk.

METHODS

A total of 395 304 participants without previous cancer at baseline were included. The Cox proportional hazards regression model was performed to investigate the association between METS-IR and lung cancer risk. In addition, a Mendelian randomization analysis was also performed to explore the causal relationship. The joint effects and additive interactions between METS-IR and polygenetic risk score (PRS) of lung cancer were also investigated.

RESULTS

During a median follow-up of 11.03 years (Inter-quartile range (IQR): 10.30-11.73), a total of 3161 incident lung cancer cases were diagnosed in 395 304 participants. There was a significant association between METS-IR and lung cancer risk, with an HR of 1.28 (95% CI: 1.17-1.41). Based on the Mendelian randomization analysis, however, no causal associations were observed. We observed a joint effect but no interaction between METS-IR and genetic risk. The lung cancer incidence was estimated to be 100.42 (95% CI: 91.45-109.38) per 100 000 person-year for participants with a high METS-IR and PRS, while only 42.76 (95% CI: 36.94-48.59) with low METS-IR and PRS.

CONCLUSIONS

High METS-IR was significantly associated with an increased risk of lung cancer. Keeping a low level of METS-IR might help reduce the long-term incident risk of lung cancer.

A genetic variant in gene NDUFAF4 confers the risk of non-small cell lung cancer by perturbing hsa-miR-215 binding

Hsa-microRNA-215 (hsa-miR-215) plays multiple roles in carcinogenesis through regulating its target genes. Genetic variants in hsa-miR-215 target sites thus may affect hsa-miR-215-mRNA interactions, result in altered expression of target genes and even influence cancer susceptibility. This study aimed to investigate the associations of genetic variants which located in the binding sites of hsa-miR-215 with non-small cell lung cancer (NSCLC) susceptibility in the Chinese population and reveal the potential regulatory mechanism of functional variants in NSCLC development. The candidate genetic variants were predicted and screened through bioinformatics analysis based on the degree of complementarity of hsa-miR-215 sequences. The potential effects of genetic variants on the binding ability of hsa-miR-215 and target genes were also predicted. A case-control study with 932 NSCLC patients and 1036 healthy controls was conducted to evaluate the association of candidate genetic variants with NSCLC susceptibility, and an independent case-control study with 552 NSCLC cases and 571 controls were used to further validate the promising associations. Dual luciferase reporter gene assay was applied to explore the regulation of the genetic variants on transcription activity of target gene. Cell phenotyping experiments in vitro and RNA sequencing (RNA-seq) were then carried out to preliminarily explore the potential regulatory mechanisms of the target genes in NSCLC. A total of five candidate genetic variants located in the binding sites of hsa-miR-215 were screened. The two-stage case-control study showed that a variant rs1854268 A > T, which located in the 3' untranslated (3'UTR) region of NDUFAF4 gene, was associated with decreased risk of NSCLC (additive model, odds ratio [OR] = 0.83, 95% confidence interval [CI]: 0.75-0.92, p < 0.001). Functional annotation displayed that rs1854268 A > T might downregulate the expression of NDUFAF4 by enhancing the binding affinity of hsa-miR-215-5p to NDUFAF4 mRNA. Additionally, transient knockdown of the NDUFAF4 could inhibit lung cancer cell migration and promote lung cancer cell apoptosis. Further RNA-seq analysis revealed that the knockdown of NDUFAF4 may affect NSCLC development by downregulating the nuclear factor kappa B (NF-κB) and phosphoinositide 3 kinase-AKT (PI3K-AKT) signaling pathways. Moreover, the overexpression of CCND1 could partially attenuate the effects of NDUFAF4 knock down on lung cancer cell migration and apoptosis, indicating that CCND1 may be involved in the tumor-promoting effects of NDUFAF4 as a downstream molecule of NDUFAF4 gene. In conclusion, the genetic variant rs1854268 (A > T) on NDUFAF4 confers NSCLC susceptibility by altering the binding affinity of hsa-miR-215-5p, thus regulating the expression of NDUFAF4 and subsequently influencing downstream tumor molecules and pathways such as CCND1, NF kappa B, and PI3K-AKT signaling pathways.

Ethnic differences of genetic risk and smoking in lung cancer: two prospective cohort studies

BACKGROUND

The role of genetic background underlying the disparity of relative risk of smoking and lung cancer between European populations and East Asians remains unclear.

METHODS

To assess the role of ethnic differences in genetic factors associated with smoking-related risk of lung cancer, we first constructed ethnic-specific polygenic risk scores (PRSs) to quantify individual genetic risk of lung cancer in Chinese and European populations. Then, we compared genetic risk and smoking as well as their interactions on lung cancer between two cohorts, including the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). We also evaluated the absolute risk reduction over a 5-year period.

RESULTS

Differences in compositions and association effects were observed between the Chinese-specific PRSs and European-specific PRSs, especially for smoking-related loci. The PRSs were consistently associated with lung cancer risk, but stronger associations were observed in smokers of the UKB [hazard ratio (HR) 1.26 vs 1.15, P  =  0.028]. A significant interaction between genetic risk and smoking on lung cancer was observed in the UKB (RERI, 11.39 (95% CI, 7.01-17.94)], but not in the CKB. Obvious higher absolute risk was observed in nonsmokers of the CKB, and a greater absolute risk reduction was found in the UKB (10.95 vs 7.12 per 1000 person-years, P <0.001) by comparing heavy smokers with nonsmokers, especially for those at high genetic risk.

CONCLUSIONS

Ethnic differences in genetic factors and the high incidence of lung cancer in nonsmokers of East Asian ethnicity were involved in the disparity of smoking-related risk of lung cancer.

Differences in set-based tests for sparse alternatives when testing sets of outcomes compared to sets of explanatory factors in genetic association studies

Set-based association tests are widely popular in genetic association settings for their ability to aggregate weak signals and reduce multiple testing burdens. In particular, a class of set-based tests including the Higher Criticism, Berk-Jones, and other statistics have recently been popularized for reaching a so-called detection boundary when signals are rare and weak. Such tests have been applied in two subtly different settings: (a) associating a genetic variant set with a single phenotype and (b) associating a single genetic variant with a phenotype set. A significant issue in practice is the choice of test, especially when deciding between innovated and generalized type methods for detection boundary tests. Conflicting guidance is present in the literature. This work describes how correlation structures generate marked differences in relative operating characteristics for settings (a) and (b). The implications for study design are significant. We also develop novel power bounds that facilitate the aforementioned calculations and allow for analysis of individual testing settings. In more concrete terms, our investigation is motivated by translational expression quantitative trait loci (eQTL) studies in lung cancer. These studies involve both testing for groups of variants associated with a single gene expression (multiple explanatory factors) and testing whether a single variant is associated with a group of gene expressions (multiple outcomes). Results are supported by a collection of simulation studies and illustrated through lung cancer eQTL examples.

KCNQ potassium channels modulate Wnt activity in gastro-oesophageal adenocarcinomas

Voltage-sensitive potassium channels play an important role in controlling membrane potential and ionic homeostasis in the gut and have been implicated in gastrointestinal (GI) cancers. Through large-scale analysis of 897 patients with gastro-oesophageal adenocarcinomas (GOAs) coupled with in vitro models, we find KCNQ family genes are mutated in ∼30% of patients, and play therapeutically targetable roles in GOA cancer growth. KCNQ1 and KCNQ3 mediate the WNT pathway and MYC to increase proliferation through resultant effects on cadherin junctions. This also highlights novel roles of KCNQ3 in non-excitable tissues. We also discover that activity of KCNQ3 sensitises cancer cells to existing potassium channel inhibitors and that inhibition of KCNQ activity reduces proliferation of GOA cancer cells. These findings reveal a novel and exploitable role of potassium channels in the advancement of human cancer, and highlight that supplemental treatments for GOAs may exist through KCNQ inhibitors.

Integrative approaches based on genomic techniques in the functional studies on enhancers

With the development of sequencing technology and the dramatic drop in sequencing cost, the functions of noncoding genes are being characterized in a wide variety of fields (e.g. biomedicine). Enhancers are noncoding DNA elements with vital transcription regulation functions. Tens of thousands of enhancers have been identified in the human genome; however, the location, function, target genes and regulatory mechanisms of most enhancers have not been elucidated thus far. As high-throughput sequencing techniques have leapt forwards, omics approaches have been extensively employed in enhancer research. Multidimensional genomic data integration enables the full exploration of the data and provides novel perspectives for screening, identification and characterization of the function and regulatory mechanisms of unknown enhancers. However, multidimensional genomic data are still difficult to integrate genome wide due to complex varieties, massive amounts, high rarity, etc. To facilitate the appropriate methods for studying enhancers with high efficacy, we delineate the principles, data processing modes and progress of various omics approaches to study enhancers and summarize the applications of traditional machine learning and deep learning in multi-omics integration in the enhancer field. In addition, the challenges encountered during the integration of multiple omics data are addressed. Overall, this review provides a comprehensive foundation for enhancer analysis.

Cancer-prone Phenotypes and Gene Expression Heterogeneity at Single-cell Resolution in Cigarette-smoking Lungs

Single-cell RNA sequencing (scRNA-seq) technologies have been broadly utilized to reveal molecular mechanisms of respiratory pathology and physiology at single-cell resolution. Here, we established single-cell meta-analysis (scMeta-analysis) by integrating data from eight public datasets, including 104 lung scRNA-seq samples with clinicopathologic information and designated a cigarette-smoking lung atlas. The atlas revealed early carcinogenesis events and defined the alterations of single-cell transcriptomics, cell population, and fundamental properties of biological pathways induced by smoking. In addition, we developed two novel scMeta-analysis methods: VARIED (Visualized Algorithms of Relationships In Expressional Diversity) and AGED (Aging-related Gene Expressional Differences). VARIED analysis revealed expressional diversity associated with smoking carcinogenesis. AGED analysis revealed differences in gene expression related to both aging and smoking status. The scMeta-analysis paves the way to utilize publicly-available scRNA-seq data and provide new insights into the effects of smoking and into cellular diversity in human lungs, at single-cell resolution.

SIGNIFICANCE

The atlas revealed early carcinogenesis events and defined the alterations of single-cell transcriptomics, cell population, and fundamental properties of biological pathways induced by smoking.

Assessing a Polygenic Risk Score for Lung Cancer Susceptibility in Non-Hispanic White and Black Populations

BACKGROUND

Polygenic risk scores (PRS) have become an increasingly popular approach to evaluate cancer susceptibility, but have not adequately represented Black populations in model development.

METHODS

We used a previously published lung cancer PRS on the basis of 80 SNPs associated with lung cancer risk in the OncoArray cohort and validated in UK Biobank. The PRS was evaluated for association with lung cancer risk adjusting for age, sex, total pack-years, family history of lung cancer, history of chronic obstructive pulmonary disease, and the top five principal components for genetic ancestry.

RESULTS

Among the 80 PRS SNPs included in the score, 14 were significantly associated with lung cancer risk (P < 0.05) in INHALE White participants, while there were no significant SNPs among INHALE Black participants. After adjusting for covariates, the PRS was significantly associated with risk in Whites (continuous score P = 0.007), but not in Blacks (continuous score P = 0.88). The PRS remained a statistically significant predictor of lung cancer risk in Whites ineligible for lung cancer screening under current U.S. Preventive Services Task Force guidelines (P = 0.02).

CONCLUSIONS

Using a previously validated PRS, we did find some predictive ability for lung cancer in INHALE White participants beyond traditional risk factors. However, this effect was not observed in Black participants, indicating the need to develop and validate ancestry-specific lung cancer risk models.

IMPACT

While a previously published lung cancer PRS was able to stratify White participants into different levels of risk, the model was not predictive in Blacks. Our findings highlight the need to develop and validate ancestry-specific lung cancer risk models.

Machine Learning Study of SNPs in Noncoding Regions to Predict Non-small Cell Lung Cancer Susceptibility

Non-small cell lung cancer (NSCLC) is the most common pathological subtype of lung cancer. Both environmental and genetic factors have been reported to impact the lung cancer susceptibility. We conducted a genome-wide association study (GWAS) of 287 NSCLC patients and 467 healthy controls in a Chinese population using the Illumina Genome-Wide Asian Screening Array Chip on 712,095 SNPs (single nucleotide polymorphisms). Using logistic regression modeling, GWAS identified 17 new noncoding region SNP loci associated with the NSCLC risk, and the top three (rs80040741, rs9568547, rs6010259) were under a stringent p-value (<3.02e-6). Notably, rs80040741 and rs6010259 were annotated from the intron regions of MUC3A and MLC1, respectively. Together with another five SNPs previously reported in Chinese NSCLC patients and another four covariates (e.g., smoking status, age, low dose CT screening, sex), a predictive model by machine learning methods can separate the NSCLC from healthy controls with an accuracy of 86%. This is the first time to apply machine learning method in predicting the NSCLC susceptibility using both genetic and clinical characteristics. Our findings will provide a promising method in NSCLC early diagnosis and improve our understanding of applying machine learning methods in precision medicine.

Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants

BACKGROUND

Plasma proteins are potential biomarkers for complex diseases. We aimed to identify plasma protein biomarkers for lung cancer.

METHODS

We investigated genetically predicted plasma levels of 1130 proteins in association with lung cancer risk among 29,266 cases and 56,450 controls of European descent. For proteins significantly associated with lung cancer risk, we evaluated associations of genetically predicted expression of their coding genes with the risk of lung cancer.

RESULTS

Nine proteins were identified with genetically predicted plasma levels significantly associated with overall lung cancer risk at a false discovery rate (FDR) of <0.05. Proteins C2, MICA, AIF1, and CTSH were associated with increased lung cancer risk, while proteins SFTPB, HLA-DQA2, MICB, NRP1, and GMFG were associated with decreased lung cancer risk. Stratified analyses by histological types revealed the cross-subtype consistency of these nine associations and identified an additional protein, ICAM5, significantly associated with lung adenocarcinoma risk (FDR < 0.05). Coding genes of NRP1 and ICAM5 proteins are located at two loci that have never been reported by previous GWAS. Genetically predicted blood levels of genes C2, AIF1, and CTSH were associated with lung cancer risk, in directions consistent with those shown in protein-level analyses.

CONCLUSION

Identification of novel plasma protein biomarkers provided new insights into the biology of lung cancer.

Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.

Mechanisms underlying the effects, and clinical applications, of oral microbiota in lung cancer: current challenges and prospects

The oral cavity contains a site-specific microbiota that interacts with host cells to regulate many physiological processes in the human body. Emerging evidence has suggested that changes in the oral microbiota can increase the risk of lung cancer (LC), and the oral microbiota is also altered in patients with LC. Human and animal studies have shown that oral microecological disorders and/or specific oral bacteria may play an active role in the occurrence and development of LC through direct and/or indirect mechanisms. These studies support the potential of oral microbiota in the clinical treatment of LC. Oral microbiota may therefore be used in the prevention and treatment of LC and to improve the side effects of anticancer therapy by regulating the balance of the oral microbiome. Specific oral microbiota in LC may also be used as screening or predictive biomarkers. This review summarizes the main findings in research on oral microbiome-related LC and discusses current challenges and future research directions.

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.

Ethnicity-specific association between TERT rs2736100 (A > C) polymorphism and lung cancer risk: a comprehensive meta-analysis

The rs2736100 (A > C) polymorphism of the second intron of Telomerase reverse transcriptase (TERT) has been confirmed to be closely associated with the risk of Lung cancer (LC), but there is still no unified conclusion on the results of its association with LC. This study included Genome-wide association studies (GWAS) and case-control studies reported so far on this association between TERT rs2736100 polymorphism and LC to clarify such a correlation with LC and the differences in it between different ethnicities and different types of LC. Relevant literatures published before May 7, 2022 on 'TERT rs2736100 polymorphism and LC susceptibility' in PubMed, EMbase, CENTRAL, MEDLINE databases were searched through the Internet, and data were extracted. Statistical analysis of data was performed in Revman5.3 software, including drawing forest diagrams, drawing funnel diagrams and so on. Sensitivity and publication bias analysis were performed in Stata 12.0 software. The C allele of TERT rs2736100 was associated with the risk of LC (Overall population: [OR] = 1.21, 95%CI [1.17, 1.25]; Caucasians: [OR] = 1.11, 95%CI [1.06, 1.17]; Asians: [OR] = 1.26, 95%CI [1.21, 1.30]), and Asians had a higher risk of LC than Caucasians (C vs. A: Caucasians: [OR] = 1.11 /Asians: [OR]) = 1.26). The other gene models also showed similar results. The results of stratified analysis of LC patients showed that the C allele was associated with the risk of Non-small-cell lung carcinoma (NSCLC) and Lung adenocarcinoma (LUAD), and the risk of NSCLC and LUAD in Asians was higher than that in Caucasians. The C allele was associated with the risk of Lung squamous cell carcinoma (LUSC) and Small cell lung carcinoma(SCLC) in Asians but not in Caucasians. NSCLC patients ([OR] = 1.27) had a stronger correlation than SCLC patients ([OR] = 1.03), and LUAD patients ([OR] = 1.32) had a stronger correlation than LUSC patients ([OR] = 1.09).In addition, the C allele of TERT rs2736100 was associated with the risk of LC, NSCLC and LUAD in both smoking groups and non-smoking groups, and the risk of LC in non-smokers of different ethnic groups was higher than that in smokers. In the Asians, non-smoking women were more at risk of developing LUAD. The C allele of TERT rs2736100 is a risk factor for LC, NSCLC, and LUAD in different ethnic groups, and the Asian population is at a more common risk. The C allele is a risk factor for LUSC and SCLC in Asians but not in Caucasians. And smoking is not the most critical factor that causes variation in TERT rs2736100 to increase the risk of most LC (NSCLC, LUAD). Therefore, LC is a multi-etiological disease caused by a combination of genetic, environmental and lifestyle factors.

Noncoding SNP at rs1663689 represses ADGRG6 via interchromosomal interaction and reduces lung cancer progression

A previous genome-wide association study (GWAS) revealed an association of the noncoding SNP rs1663689 with susceptibility to lung cancer in the Chinese population. However, the underlying mechanism is unknown. In this study, using allele-specific 4C-seq in heterozygous lung cancer cells combined with epigenetic information from CRISPR/Cas9-edited cell lines, we show that the rs1663689 C/C variant represses the expression of ADGRG6, a gene located on a separate chromosome, through an interchromosomal interaction of the rs1663689 bearing region with the ADGRG6 promoter. This reduces downstream cAMP-PKA signaling and subsequently tumor growth both in vitro and in xenograft models. Using patient-derived organoids, we show that rs1663689 T/T-but not C/C-bearing lung tumors are sensitive to the PKA inhibitor H89, potentially informing therapeutic strategies. Our study identifies a genetic variant-mediated interchromosomal interaction underlying ADGRG6 regulation and suggests that targeting the cAMP-PKA signaling pathway may be beneficial in lung cancer patients bearing the homozygous risk genotype at rs1663689.

Mapping Multi-factor-mediated Chromatin Interactions to Assess Dysregulation of Lung Cancer-related Genes

Studies on the lung cancer genome are indispensable for developing a cure for lung cancer. Whole-genome resequencing, genome-wide association studies, and transcriptome sequencing have greatly improved our understanding of the cancer genome. However, dysregulation of long-range chromatin interactions in lung cancer remains poorly described. To better understand the three-dimensional (3D) genomic interaction features of the lung cancer genome, we used the A549 cell line as a model system and generated high-resolution chromatin interactions associated with RNA polymerase II (RNAPII), CCCTC-binding factor (CTCF), enhancer of zeste homolog 2 (EZH2), and histone 3 lysine 27 trimethylation (H3K27me3) using long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). Analysis showed that EZH2/H3K27me3-mediated interactions further repressed target genes, either through loops or domains, and their distributions along the genome were distinct from and complementary to those associated with RNAPII. Cancer-related genes were highly enriched with chromatin interactions, and chromatin interactions specific to the A549 cell line were associated with oncogenes and tumor suppressor genes, such as additional repressive interactions on FOXO4 and promoter-promoter interactions between NF1 and RNF135. Knockout of an anchor associated with chromatin interactions reversed the dysregulation of cancer-related genes, suggesting that chromatin interactions are essential for proper expression of lung cancer-related genes. These findings demonstrate the 3D landscape and gene regulatory relationships of the lung cancer genome.

Germline variants of the genes involved in NF-kB activation are associated with the risk of COPD and lung cancer development

Chronic obstructive pulmonary disease (COPD) and lung cancer (LC) are closely related diseases associated with smoking history and dysregulated immune response. However, not all smokers develop the disease, indicating that genetic susceptibility could be important. Therefore, the aim of this study was to search for the potential overlapping genetic biomarkers, with a focus on single nucleotide polymorphisms (SNPs) located in the regulatory regions of immune-related genes. Additionally, the aim was to see if an identified SNP has potentially an effect on proinflamma-tory cytokine concentration in the serum of COPD patients. We extracted summary data of variants in 1511 immune-related genes from COPD and LC genome-wide association studies (GWAS) from the UK Biobank. The LC data had 203 cases, patients diagnosed with LC, and 360 938 controls, while COPD data had 1 897 cases and 359 297 controls. Assuming 1 association/gene, SNPs with a p-value < 3.3 × 10^-5 were considered statistically significantly associated with the disease. We identified seven SNPs located in different genes (BAG6, BTNL2, TNF, HCP5, MICB, NCR3, ABCF1, TCF7L1) to be associated with the COPD risk and two with the LC risk (HLA-C, HLA-B), with statistical significance. We also identified two SNPs located in the IL2RA gene associated with LC (rs2386841; p = 1.86 × 10^-4) and COPD (rs11256442; p = 9.79 × 10^-3) but with lower significance. Functional studies conducted on COPD patients showed that RNA expression of IL2RA, IFNγ and related proinflammatory cytokines in blood serum did not correlate with a specific genotype. Although results presented in this study do not fully support our hypothesis, it is worth to mention that the identified genes/SNPs that were associated with either COPD or LC risk, all were involved in the activation of the NF-κB transcription factor which is closely related to the regulation of the inflammatory response, a condition associated with both pathologies.

Debiased lasso for generalized linear models with a diverging number of covariates

Modeling and drawing inference on the joint associations between single-nucleotide polymorphisms and a disease has sparked interest in genome-wide associations studies. In the motivating Boston Lung Cancer Survival Cohort (BLCSC) data, the presence of a large number of single nucleotide polymorphisms of interest, though smaller than the sample size, challenges inference on their joint associations with the disease outcome. In similar settings, we find that neither the debiased lasso approach (van de Geer et al., 2014), which assumes sparsity on the inverse information matrix, nor the standard maximum likelihood method can yield confidence intervals with satisfactory coverage probabilities for generalized linear models. Under this "large n, diverging p" scenario, we propose an alternative debiased lasso approach by directly inverting the Hessian matrix without imposing the matrix sparsity assumption, which further reduces bias compared to the original debiased lasso and ensures valid confidence intervals with nominal coverage probabilities. We establish the asymptotic distributions of any linear combinations of the parameter estimates, which lays the theoretical ground for drawing inference. Simulations show that the proposed refined debiased estimating method performs well in removing bias and yields honest confidence interval coverage. We use the proposed method to analyze the aforementioned BLCSC data, a large-scale hospital-based epidemiology cohort study investigating the joint effects of genetic variants on lung cancer risks.

Identification and validation of novel lung adenocarcinoma subtypes and construction of prognostic models: based on cuprotosis-related genes

Cuprotosis is a novel and unique form of cell death that is of great value in a variety of cancers. However, the prognostic role of cuprotosis-related genes (CRGs) in lung cancer remains undetermined. We compared the expression profile of CRGs in lung adenocarcinoma (LUAD) patients, revealing the genetic alterations and inter-gene correlations of CRGs. Based on 13 CRGs, LUAD patients could be well differentiated into two molecular subgroups, and the differentially expressed genes (DEGs) in these molecular subtypes were identified. Furthermore, 10 cuprotosis pattern-related DEGs with a significant prognostic value were obtained for constructing a prognostic model. Through validation in an external validation set, the prognostic model based on the CRGs-risk score showed the robust and effective predictive ability and served as an independent prognostic indicator for LUAD patients. Therefore, combining the CRGs-risk score with multiple factors such as clinicopathological characteristics, a quantitative nomogram was developed to predict the survival and prognosis of LUAD patients, improving the clinical application value of the CRGs-risk score. In the low CRGs-risk score group, the related immune cell infiltration was increased and the immune function was activated in LUAD patients. This study may add to the knowledge of CRGs in LUAD, partly contribute to evaluating the prognosis of LUAD patients, and provide direction for the development of targeted therapy and immunotherapy.

Epigenetic age and lung cancer risk in the CLUE II prospective cohort study

BACKGROUND

Epigenetic age, a robust marker of biological aging, has been associated with obesity, low-grade inflammation and metabolic diseases. However, few studies have examined associations between different epigenetic age measures and risk of lung cancer, despite great interest in finding biomarkers to assist in risk stratification for lung cancer screening.

METHODS

A nested case-control study of lung cancer from the CLUE II cohort study was conducted using incidence density sampling with 1:1 matching of controls to lung cancer cases (n = 208 matched pairs). Prediagnostic blood samples were collected in 1989 (CLUE II study baseline) and stored at -70°C. DNA was extracted from buffy coat and DNA methylation levels were measured using Illumina MethylationEPIC BeadChip Arrays. Three epigenetic age acceleration (i.e., biological age is greater than chronological age) measurements (Horvath, Hannum and PhenoAge) were examined in relation to lung cancer risk using conditional logistic regression.

RESULTS

We did not observe associations between the three epigenetic age acceleration measurements and risk of lung cancer overall; however, inverse associations for the two Hannum age acceleration measures (intrinsic and extrinsic) were observed in men and among younger participants, but not in women or older participants. We did not observe effect modification by time from blood draw to diagnosis.

CONCLUSION

Findings from this study do not support a positive association between three different biological age acceleration measures and risk of lung cancer. Additional studies are needed to address whether epigenetic age is associated with lung cancer in never smokers.

Association of outdoor air pollution, lifestyle, genetic factors with the risk of lung cancer: A prospective cohort study

OBJECTIVES

The effect of air pollution exposure on incident lung cancer remains uncertain, and the modifying role of lifestyle and genetic susceptibility in association between air pollution and lung cancer is ambiguous.

METHODS

A total of 367,623 participants from UK biobank cohort were enrolled in the analysis. The concentrations of particle matter (PM_2.5, PM₁₀), nitrogen dioxide (NO₂), and nitrogen oxides (NO_x), were evaluated by land-use regression model. Cox proportional hazard model was applied to assess the associations between air pollution and incident lung cancer. A lifestyle risk score and a polygenic risk score were established to investigate whether lifestyle and heritable risk could modify the effect of air pollution on lung cancer risk.

RESULTS

Per interquartile range (IQR) increment in annual concentrations of PM_2.5 (HR = 1.22, 95% CI, 1.15∼1.30), NO₂ (HR = 1.19, 95% CI, 1.10∼1.27), and NO_x (HR = 1.14, 95% CI, 1.09∼1.20) were associated with increased risk of lung cancer. We observed an additive interaction between air pollution including PM_2.5 and NO_x and lifestyle or genetic risk. Individuals with high air pollution exposure, poor lifestyle and high genetic risk had the highest risk of incident lung cancer.

CONCLUSION

Long-term exposures to air pollution is associated with increased risk of lung cancer, and this effect was modified by lifestyle or genetic risk. Integrated interventions for environmental pollution by government and adherence to healthy lifestyle by individuals are advocated for lung cancer prevention.

Why does the X chromosome lag behind autosomes in GWAS findings?

The X-chromosome is among the largest human chromosomes. It differs from autosomes by a number of important features including hemizygosity in males, an almost complete inactivation of one copy in females, and unique patterns of recombination. We used data from the Catalog of Published Genome Wide Association Studies to compare densities of the GWAS-detected SNPs on the X-chromosome and autosomes. The density of GWAS-detected SNPs on the X-chromosome is 6-fold lower compared to the density of the GWAS-detected SNPs on autosomes. Differences between the X-chromosome and autosomes cannot be explained by differences in the overall SNP density, lower X-chromosome coverage by genotyping platforms or low call rate of X-chromosomal SNPs. Similar differences in the density of GWAS-detected SNPs were found in female-only GWASs (e.g. ovarian cancer GWASs). We hypothesized that the lower density of GWAS-detected SNPs on the X-chromosome compared to autosomes is not a result of a methodological bias, e.g. differences in coverage or call rates, but has a real underlying biological reason-a lower density of functional SNPs on the X-chromosome versus autosomes. This hypothesis is supported by the observation that (i) the overall SNP density of X-chromosome is lower compared to the SNP density on autosomes and that (ii) the density of genic SNPs on the X-chromosome is lower compared to autosomes while densities of intergenic SNPs are similar.

In Utero and Childhood/Adolescence Exposure to Tobacco Smoke, Genetic Risk, and Lung Cancer Incidence and Mortality in Adulthood

Rationale: The individual effects of early-life tobacco smoke exposure and its interactions with genetic factors on lung cancer in adulthood remain unclear. Objectives: To investigate the associations of early-life tobacco exposures as well as their interactions with polygenic risk scores (PRSs) with lung cancer incidence and mortality. Methods: A total of 432,831 participants from the UK Biobank study were included. We estimated the associations of in utero exposure to tobacco smoke, the age of smoking initiation and their interactions with PRSs with lung cancer incidence and mortality in adulthood using Cox proportional hazard models. Measurements and Main Results: Lung cancer incidence (hazard ratio [HR]: 1.59, 95% confidence interval [CI], 1.44-1.76) increased among participants with in utero tobacco exposure. Multivariable-adjusted HRs (with 95% CIs) of lung cancer incidence for smoking initiation in adulthood, adolescence, and childhood (versus never-smokers) were 6.10 (5.25-7.09), 9.56 (8.31-11.00), and 15.15 (12.90-17.79) (P_trend < 0.001). Similar findings were observed in lung cancer mortality. Participants with high PRSs and in utero tobacco exposure (versus low PRSs participants without in utero exposure) had an HR of 2.35 for lung cancer incidence (95% CI, 1.97-2.80, P_interaction = 0.089) and 2.43 for mortality (95% CI, 2.05-2.88, P_interaction = 0.032). High PRSs with smoking initiation in childhood (versus never-smokers with low PRSs) had HRs of 18.71 for incidence (95% CI, 14.21-24.63, P_interaction = 0.004) and 19.74 for mortality (95% CI, 14.98-26.01, P_interaction = 0.033). Conclusions: In utero and childhood/adolescence exposure to tobacco smoke and its interaction with genetic factors may substantially increase the risks of lung cancer incidence and mortality in adulthood.

Dual inhibition of EGFR‑VEGF: An effective approach to the treatment of advanced non‑small cell lung cancer with EGFR mutation (Review)

On a global scale, the incidence and mortality rates of lung cancer are gradually increasing year by year. A number of bad habits and environmental factors are associated with lung cancer, including smoking, second‑hand smoke exposure, occupational exposure, respiratory diseases and genetics. At present, low‑dose spiral computed tomography is routinely the first choice in the diagnosis of lung cancer. However, pathological examination is still the gold standard for the diagnosis of lung cancer. Based on the classification and stage of the cancer, treatment options such as surgery, radiotherapy, chemotherapy, targeted therapy and immunotherapy are available. The activation of the EGFR pathway can promote the survival and proliferation of tumor cells, and the VEGF pathway can promote the formation of blood vessels, thereby promoting tumor growth. In non‑small cell lung cancer (NSCLC) with EGFR mutation, EGFR activation can promote tumor growth by promoting VEGF upregulation through a hypoxia‑independent mechanism. The upregulation of VEGF can make tumor cells resistant to EGFR inhibitors. In addition, the expression of the VEGF signal is also affected by other factors. Therefore, the use of a single EGFR inhibitor cannot completely inhibit the expression of the VEGF signal. In order to overcome this problem, the combination of VEGF inhibitors and EGFR inhibitors has become the method of choice. Dual inhibition can not only overcome the resistance of tumor cells to EGFR inhibitors, but also significantly increase the progression‑free survival time of patients with NSCLC. The present review discusses the associations between the EGFR and VEGF pathways, and the characteristics of dual inhibition of the EGFR‑VEGF pathway.

Association of oxidative stress, programmed cell death, GSTM1 gene polymorphisms, smoking and the risk of lung carcinogenesis: A two-step Mendelian randomization study

Aim: We aimed to examine the association of oxidative stress, programmed cell death, smoking, and the GSTM1 gene in the risk of lung carcinogenesis. The two-step Mendelian randomization will reveal evidence supporting the association of the exposure and mediators with the resulting outcome. Methods: In step 1, we estimated the impact of smoking exposure on lung carcinogenesis and programmed cell death. Our study involved a total of 500,000 patients of European ancestry, from whom we obtained genotype imputation information. Specifically, we genotyped two arrays: the UK Biobank Axiom (UKBB) which accounted for 95% of marker content, and the UK BiLIEVE Axiom (UKBL). This allowed us to unmask the association between smoking exposure and the incidence of lung carcinogenesis. In step 2, we further examined the effects of smoking on oxidative stress, programmed cell death, and the incidence of lung carcinogenesis. Results: Different outcomes emerged from the two-step Mendelian randomization. The GSTM1 gene variant was found to be critical in the development of lung carcinogenesis, as its deletion or deficiency can induce the condition. A GWAS study on participant information obtained from the UK Biobank revealed that smoking interferes with the GSTM1 gene, causing programmed cell death in the lungs and ultimately leading to lung carcinogenesis. The relative risk of developing lung carcinogenesis associated with oxidative stress was significantly high among current smokers (a hazard ratio of 17.8, 95% confidence interval of 12.2-26.0) and heavy smokers (a hazard ratio of 16.6 and a 95% confidence interval of 13.6-20.3) compared to individuals who never smoked. The GSTM1 gene polymorphism was found to be 0.006 among participants who have never smoked, <0.001 among ever-smokers, and 0.002 and <0.001 among current and former smokers, respectively. We compared the effect of smoking within two particular time frames, 6 years and 55 years, and found that smoking's impact on the GSTM1 gene was highest among participants who were 55 years old. The genetic risk peaked among individuals aged 50 years and above (PRS of at least 80%). Conclusion: Exposure to smoking is a significant factor in developing lung carcinogenesis, as it is associated with programmed cell death and other mediators involved in the condition. Oxidative stress caused by smoking is also a key mechanism in lung carcinogenesis. The results of the present study highlight the association between oxidative stress, programmed cell death, and the GSTM1 gene in the development of lung carcinogenesis.

Genetic polymorphisms of MRPS30-DT and NINJ2 may influence lung cancer risk

Lung cancer is one of the malignant tumors, and genetic background is a risk factor in lung cancer that cannot be neglected. In this study, we aimed to find out the effect of MRPS30-DT and NINJ2 variants on lung cancer risk. In this study, the seven selected single-nucleotide polymorphisms (SNPs) of MRPS30-DT and NINJ2 were genotyped in 509 lung cancer patients and 501 healthy controls based on the Agena MassARRAY platform. Odds ratios and 95% confidence intervals were calculated by logistic regression analysis to evaluate association between gene polymorphisms and lung cancer risk. False-positive report probability was also used to assess false-positive results. Furthermore, the interaction between SNPs was analyzed by multifactor dimensionality reduction to predict lung cancer risk. We identified the genotype TA of rs16901963 (T < A) in MRPS30-DT as a protective factor against lung cancer, while rs16901963-TT was significantly associated with an increased risk of lung cancer. We also revealed that the effect of MRPS30-DT and NINJ2 variants on the risk of lung cancer was dependent on age, gender, smoking, and drinking status. In conclusion, this study first proved that MRPS30-DT and NINJ2 variants played important roles in affecting the susceptibility to lung cancer.

Association of CYP19A1 rs28757157 polymorphism with lung cancer risk in the Chinese Han population

BACKGROUND

Lung cancer is the leading cause of cancer death globally. Recent studies have revealed that CYP19A1 gene plays a crucial role in cancer initiation and development. The aim of this study was to assess the association of CYP19A1 genetic polymorphisms with the risk of lung cancer in the Chinese Han population.

METHODS

This study randomly recruited 489 lung cancer patients and 467 healthy controls. The genotypes of four single nucleotide polymorphisms (SNPs) of the CYP19A1 gene were identified by the Agena MassARRY technique. Genetic model analysis was used to assess the association between genetic variations and lung cancer risk. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to evaluate the effect of four selected SNPs on lung cancer risk.

RESULTS

CYP19A1 rs28757157 might contribute to an increased risk of lung cancer (p = 0.025, OR = 1.30, 95% CI 1.03-1.64). In stratified analysis, rs28757157 was associated with an increased cancer risk in the population aged under 60 years, females, smokers, and drinkers. Besides, rs3751592 and rs59429575 were also identified as risk biomarkers in the population under 60 years and drinkers. Meanwhile, a relationship between an enhanced risk of squamous cell carcinoma and rs28757157 was found, while the rs3751592 CC genotype was identified as a risk factor for lung adenocarcinoma development.

CONCLUSIONS

This study has identified revealed that the three SNPs (rs28757157, rs3751592, and rs59429575) of CYP19A1 are associated with lung cancer in the Chinese Han population. These findings will provide theoretical support for further functional studies of CYP19A1 in lung cancer.

KIR-HLA gene diversities and susceptibility to lung cancer

Killer-cell immunoglobulin-like receptors (KIR) are essential for acquiring natural killer (NK) cell effector function, which is modulated by a balance between the net input of signals derived from inhibitory and activating receptors through engagement by human leukocyte antigen (HLA) class I ligands. KIR and HLA loci are polygenic and polymorphic and exhibit substantial variation between individuals and populations. We attempted to investigate the contribution of KIR complex and HLA class I ligands to the genetic predisposition to lung cancer in the native population of southern Iran. We genotyped 16 KIR genes for a total of 232 patients with lung cancer and 448 healthy controls (HC), among which 85 patients and 178 HCs were taken into account for evaluating combined KIR-HLA associations. KIR2DL2 and 2DS2 were increased significantly in patients than in controls, individually (OR 1.63, and OR 1.42, respectively) and in combination with HLA-C1 ligands (OR 1.99, and OR 1.93, respectively). KIR3DS1 (OR 0.67) and 2DS1 (OR 0.69) were more likely presented in controls in the absence of their relative ligands. The incidence of CxTx subset was increased in lung cancer patients (OR 1.83), and disease risk strikingly increased by more than fivefold among genotype ID19 carriers (a CxTx genotype that carries 2DL2 in the absence of 2DS2, OR 5.92). We found that genotypes with iKIRs > aKIRs (OR 1.67) were more frequently presented in lung cancer patients. Additionally, patients with lung cancer were more likely to carry the combination of CxTx/2DS2 compared to controls (OR 2.04), and iKIRs > aKIRs genotypes in the presence of 2DL2 (OR 2.05) increased the likelihood of lung cancer development. Here we report new susceptibility factors and the contribution of KIR and HLA-I encoding genes to lung cancer risk, highlighting an array of genetic effects and disease setting which regulates NK cell responsiveness. Our results suggest that inherited KIR genes and HLA-I ligands specifying the educational state of NK cells can modify lung cancer risk.

Non-small cell lung cancer in China

In China, lung cancer is a primary cancer type with high incidence and mortality. Risk factors for lung cancer include tobacco use, family history, radiation exposure, and the presence of chronic lung diseases. Most early-stage non-small cell lung cancer (NSCLC) patients miss the optimal timing for treatment due to the lack of clinical presentations. Population-based nationwide screening programs are of significant help in increasing the early detection and survival rates of NSCLC in China. The understanding of molecular carcinogenesis and the identification of oncogenic drivers dramatically facilitate the development of targeted therapy for NSCLC, thus prolonging survival in patients with positive drivers. In the exploration of immune escape mechanisms, programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitor monotherapy and PD-1/PD-L1 inhibitor plus chemotherapy have become a standard of care for advanced NSCLC in China. In the Chinese Society of Clinical Oncology's guidelines for NSCLC, maintenance immunotherapy is recommended for locally advanced NSCLC after chemoradiotherapy. Adjuvant immunotherapy and neoadjuvant chemoimmunotherapy will be approved for resectable NSCLC. In this review, we summarized recent advances in NSCLC in China in terms of epidemiology, biology, molecular pathology, pathogenesis, screening, diagnosis, targeted therapy, and immunotherapy.

The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores

The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.

Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians

INTRODUCTION

Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).

METHODS

Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.

RESULTS

With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10-13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10-13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10-13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10-4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.

CONCLUSIONS

Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.

Pharmacogenetics of the cytochromes P450: Selected pharmacological and toxicological aspects

With the availability of detailed genomic data on all 57 human cytochrome P450 genes, it is clear that there is substantial variability in gene product activity with functionally significant polymorphisms reported across almost all isoforms. This article is concerned mainly with 13 P450 isoforms of particular relevance to xenobiotic metabolism. After brief review of the extent of polymorphism in each, the relevance of selected P450 isoforms to both adverse drug reaction and disease susceptibility is considered in detail. Bleeding due to warfarin and other coumarin anticoagulants is considered as an example of a type A reaction with idiosyncratic adverse drug reactions affecting the liver and skin as type B. It is clear that CYP2C9 variants contribute significantly to warfarin dose requirement and also risk of bleeding, with a minor contribution from CYP4F2. In the case of idiosyncratic adverse drug reactions, CYP2B6 variants appear relevant to both liver and skin reactions to several drugs with CYP2C9 variants also relevant to phenytoin-related skin rash. The relevance of P450 genotype to disease susceptibility is also considered but detailed genetic studies now suggest that CYP2A6 is the only P450 relevant to risk of lung cancer with alleles associated with low or absent activity clearly protective against disease. Other cytochrome P450 genotypes are generally not predictors for risk of cancer or other complex disease development.

Efficient estimation of indirect effects in case-control studies using a unified likelihood framework

Mediation models are a set of statistical techniques that investigate the mechanisms that produce an observed relationship between an exposure variable and an outcome variable in order to deduce the extent to which the relationship is influenced by intermediate mediator variables. For a case-control study, the most common mediation analysis strategy employs a counterfactual framework that permits estimation of indirect and direct effects on the odds ratio scale for dichotomous outcomes, assuming either binary or continuous mediators. While this framework has become an important tool for mediation analysis, we demonstrate that we can embed this approach in a unified likelihood framework for mediation analysis in case-control studies that leverages more features of the data (in particular, the relationship between exposure and mediator) to improve efficiency of indirect effect estimates. One important feature of our likelihood approach is that it naturally incorporates cases within the exposure-mediator model to improve efficiency. Our approach does not require knowledge of disease prevalence and can model confounders and exposure-mediator interactions, and is straightforward to implement in standard statistical software. We illustrate our approach using both simulated data and real data from a case-control genetic study of lung cancer.

Genetic variants in DDO and PEX5L in peroxisome-related pathways predict non-small cell lung cancer survival

Peroxisomes play a role in lipid metabolism and regulation of reactive oxygen species, but its role in development and progression of non-small cell lung cancer (NSCLC) is not well understood. Here, we investigated the associations between 9708 single-nucleotide polymorphisms (SNPs) in 113 genes in the peroxisome-related pathways and survival of NSCLC patients from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and the Harvard Lung Cancer Susceptibility (HLCS) study. In 1185 NSCLC patients from the PLCO trial, we found that 213 SNPs were significantly associated with NSCLC overall survival (OS) (p ≤ 0.05, Bayesian false discovery probability [BFDP] ≤ 0.80), of which eight SNPs were validated in the HLCS data set. In a multivariate Cox proportional hazards regression model, two independent SNPs (rs9384742 DDO and rs9825224 PEX5L) were significantly associated with NSCLC survival (hazards ratios [HR] of 1.17 with 95% CI [confidence interval] of 1.06-1.28 and 0.86 with 95% CI of 0.77-0.96, respectively). Patients with one or two protective genotypes had a significantly higher OS (HR: 0.787 [95% CI: 0.620-0.998] and 0.691 [95% CI: 0.543-0.879], respectively). Further expression quantitative trait loci analysis using whole blood and lung tissue showed that the minor allele of rs9384742 DDO was significantly associated with decreased messenger RNA (mRNA) expression levels and that DDO expression was also decreased in NSCLC tumor tissue. Additionally, high PEX5L expression levels were significantly associated with lower survival of NSCLC. Our data suggest that variants in these peroxisome-related genes may influence gene regulation and are potential predictors of NSCLC OS, once validated by additional studies.

Identification and robust estimation of swapped direct and indirect effects: Mediation analysis with unmeasured mediator-outcome confounding and intermediate confounding

Counterfactual-model-based mediation analysis can yield substantial insight into the causal mechanism through the assessment of natural direct effects (NDEs) and natural indirect effects (NIEs). However, the assumptions regarding unmeasured mediator-outcome confounding and intermediate mediator-outcome confounding that are required for the determination of NDEs and NIEs present practical challenges. To address this problem, we introduce an instrumental blocker, a novel quasi-instrumental variable, to relax both of these assumptions, and we define a swapped direct effect (SDE) and a swapped indirect effect (SIE) to assess the mediation. We show that the SDE and SIE are identical to the NDE and NIE, respectively, based on a causal interpretation. Moreover, the empirical expressions of the SDE and SIE are derived with and without an intermediate mediator-outcome confounder. Then, a multiply robust estimation method is derived to mitigate the model misspecification problem. We prove that the proposed estimator is consistent, asymptotically normal, and achieves the semiparametric efficiency bound. As an illustration, we apply the proposed method to genomic datasets of lung cancer to investigate the potential role of the epidermal growth factor receptor in the treatment of lung cancer.

Associations of genetic risk, BMI trajectories, and the risk of non-small cell lung cancer: a population-based cohort study

BACKGROUND

Body mass index (BMI) has been found to be associated with a decreased risk of non-small cell lung cancer (NSCLC); however, the effect of BMI trajectories and potential interactions with genetic variants on NSCLC risk remain unknown.

METHODS

Cox proportional hazards regression model was applied to assess the association between BMI trajectory and NSCLC risk in a cohort of 138,110 participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. One-sample Mendelian randomization (MR) analysis was further used to access the causality between BMI trajectories and NSCLC risk. Additionally, polygenic risk score (PRS) and genome-wide interaction analysis (GWIA) were used to evaluate the multiplicative interaction between BMI trajectories and genetic variants in NSCLC risk.

RESULTS

Compared with individuals maintaining a stable normal BMI (n = 47,982, 34.74%), BMI trajectories from normal to overweight (n = 64,498, 46.70%), from normal to obese (n = 21,259, 15.39%), and from overweight to obese (n = 4,371, 3.16%) were associated with a decreased risk of NSCLC (hazard ratio [HR] for trend = 0.78, P < 2×10^-16). An MR study using BMI trajectory associated with genetic variants revealed no significant association between BMI trajectories and NSCLC risk. Further analysis of PRS showed that a higher GWAS-identified PRS (PRS_GWAS) was associated with an increased risk of NSCLC, while the interaction between BMI trajectories and PRS_GWAS with the NSCLC risk was not significant (P_sPRS= 0.863 and P_wPRS= 0.704). In GWIA analysis, four independent susceptibility loci (P < 1×10^-6) were found to be associated with BMI trajectories on NSCLC risk, including rs79297227 (12q14.1, located in SLC16A7, P_interaction = 1.01×10^-7), rs2336652 (3p22.3, near CLASP2, P_interaction = 3.92×10^-7), rs16018 (19p13.2, in CACNA1A, P_interaction = 3.92×10^-7), and rs4726760 (7q34, near BRAF, P_interaction = 9.19×10^-7). Functional annotation demonstrated that these loci may be involved in the development of NSCLC by regulating cell growth, differentiation, and inflammation.

CONCLUSIONS

Our study has shown an association between BMI trajectories, genetic factors, and NSCLC risk. Interestingly, four novel genetic loci were identified to interact with BMI trajectories on NSCLC risk, providing more support for the aetiology research of NSCLC.

TRIAL REGISTRATION

http://www.

CLINICALTRIALS

gov , NCT01696968 .