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

Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement

BACKGROUND

Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic data. However, the accuracy of clinico-genomic prediction of diseases may vary significantly across ancestry groups due to their unequal representation in clinical genomic datasets.

METHODS

We introduced a deep transfer learning approach to improve the performance of clinico-genomic prediction models for data-disadvantaged ancestry groups. We conducted machine learning experiments on multi-ancestral genomic datasets of lung cancer, prostate cancer, and Alzheimer's disease, as well as on synthetic datasets with built-in data inequality and distribution shifts across ancestry groups.

RESULTS

Deep transfer learning significantly improved disease prediction accuracy for data-disadvantaged populations in our multi-ancestral machine learning experiments. In contrast, transfer learning based on linear frameworks did not achieve comparable improvements for these data-disadvantaged populations.

CONCLUSIONS

This study shows that deep transfer learning can enhance fairness in multi-ancestral machine learning by improving prediction accuracy for data-disadvantaged populations without compromising prediction accuracy for other populations, thus providing a Pareto improvement towards equitable clinico-genomic prediction of diseases.

The effects of ANRIL polymorphisms on colorectal cancer, tumor stage, and tumor grade among Iranian population

BACKGROUND

Colorectal cancer (CRC) is a type of neoplasm, developing in the colon or rectum. The exact etiology of CRC is not well known, but the role of genetic, epigenetic, and environmental factors are established in its pathogenesis. Therefore, the aim of this research was to explore the effects of ANRIL polymorphisms on the CRC and its clinical findings.

METHODS AND RESULTS

The peripheral blood specimens were collected from 142 CRC patients and 225 controls referred to Milad Hospital, Tehran, Iran. PCR- RFLP method was used to analyze ANRIL rs1333040, rs10757274 rs4977574, and rs1333048 polymorphisms. The ANRIL rs1333040 polymorphism was related to a higher risk of CRC in the co-dominant, dominant, and log-additive models. ANRIL rs10757274, rs4977574, and rs1333048 polymorphisms showed no effect on CRC susceptibility. The CGAA and TGGA haplotypes of ANRIL rs1333040/ rs10757274/ rs4977574/rs1333048 polymorphisms were associated with the higher and the lower risk of CRC respectively. The rs1333040 polymorphism was associated with higher TNM stages (III and IV). The frequency of ANRIL rs10757274 polymorphism was lower in CRC patients over 50 years of age only in the dominant model. In addition, the rs10757274 was associated with well differentiation in CRC patients.

CONCLUSION

The ANRIL rs1333040 polymorphism was associated with a higher risk of CRC and higher TNM stages. ANRIL rs10757274 polymorphism was associated with the well-differentiated tumor in CRC.

Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies.

METHODS

This study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein-protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications.

RESULTS

We identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72-0.87), 0.39 (95% CI 0.28-0.55), 0.91 (95% CI 0.72-0.87), and 0.85 (95% CI 0.79-0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08-1.19), NTM (OR, 1.12; 95% CI 1.09-1.16), PMM2 (OR, 1.35; 95% CI 1.18-1.53), RNASET2 (OR, 1.15; 95% CI 1.08-1.21), and TFPI (OR, 4.58; 95% CI 3.02-6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets.

CONCLUSIONS

Our proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.

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.

The causal relationship between severe mental illness and risk of lung carcinoma

Observational studies have suggested a link between severe mental illness (SMI) and risk of lung carcinoma (LC); however, causality has not been established. In this study, we conducted a two-sample, two-step Mendelian randomization (MR) investigation to uncover the etiological influence of SMI on LC risk and quantify the mediating effects of known modifiable risk factors. We obtained summary-level datasets for schizophrenia, major depressive disorder (MDD), and bipolar disorder (BD) from the Psychiatric Genomics Consortium (PGC). Data on single nucleotide polymorphisms (SNPs) associated with lung carcinoma (LC) were sourced from a recent large meta-analysis by McKay et al. We employed two-sample MR and two-step MR utilizing the inverse variance weighted method for causal estimation. Sensitivity tests were conducted to validate causal relationships. In two-sample MR, we identified schizophrenia as a risk factor for LC (OR = 1.06, 95% CI 1.02-1.11, P = 3.48E-03), while MDD (OR = 1.18, 95% CI 0.98-1.42, P = .07) and BD (OR = 1.07, 95% CI 0.99-1.15, P = .09) showed no significant association with LC. In the two-step MR, smoking accounted for 24.66% of the schizophrenia-LC risk association, and alcohol consumption explained 7.59% of the effect. Schizophrenia is a risk factor for lung carcinoma, and smoking and alcohol consumption are the mediating factors in this causal relationship. LC screening should be emphasized in individuals with schizophrenia, particularly in those who smoke and consume alcohol regularly.

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.

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

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

A Genome-Wide Association Study of Small Cell Lung Cancer

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Large-scale whole exome sequencing studies identify two genes,CTSL and APOE, associated with lung cancer

Common genetic variants associated with lung cancer have been well studied in the past decade. However, only 12.3% heritability has been explained by these variants. In this study, we investigate the contribution of rare variants (RVs) (minor allele frequency <0.01) to lung cancer through two large whole exome sequencing case-control studies. We first performed gene-based association tests using a novel Bayes Factor statistic in the International Lung Cancer Consortium, the discovery study (European, 1042 cases vs. 881 controls). The top genes identified are further assessed in the UK Biobank (European, 630 cases vs. 172 864 controls), the replication study. After controlling for the false discovery rate, we found two genes, CTSL and APOE, significantly associated with lung cancer in both studies. Single variant tests in UK Biobank identified 4 RVs (3 missense variants) in CTSL and 2 RVs (1 missense variant) in APOE stongly associated with lung cancer (OR between 2.0 and 139.0). The role of these genetic variants in the regulation of CTSL or APOE expression remains unclear. If such a role is established, this could have important therapeutic implications for lung cancer patients.

The Long Non-Coding RNA ANRIL in Cancers

ANRIL (Antisense Noncoding RNA in the INK4 Locus), a long non-coding RNA encoded in the human chromosome 9p21 region, is a critical factor for regulating gene expression by interacting with multiple proteins and miRNAs. It has been found to play important roles in various cellular processes, including cell cycle control and proliferation. Dysregulation of ANRIL has been associated with several diseases like cancers and cardiovascular diseases, for instance. Understanding the oncogenic role of ANRIL and its potential as a diagnostic and prognostic biomarker in cancer is crucial. This review provides insights into the regulatory mechanisms and oncogenic significance of the 9p21 locus and ANRIL in cancer.

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.

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

Associations between diet and incidence risk of lung cancer: A Mendelian randomization study

Background

Observational studies have revealed associations between diet and lung cancer. However, it is unclear whether the association is disturbed by confounding factors. We used a two-sample Mendelian randomization (MR) method to characterize the associations between diet and the lung cancer risk (including 3 subtypes: lung adenocarcinoma (LA), squamous cell lung carcinoma (SqCLC), and small cell lung cancer (SCLC)).

Materials and methods

Data on 20 diets were screened from the UK Biobank. Lung cancer data came from a large meta-analysis of 85,716 individuals. The inverse-variance weighted method was used as the main analysis. Sensitivity analysis was also used to explain the different multiplicity patterns of the final model.

Results

Our results showed significant evidence that 3 diets were associated with lung cancer [odds ratio (OR): 0.271, 95% confidence interval (CI): 0.150–0.488, p = 1.46 × 10−4, dried fruit; OR: 3.010, 95% CI: 1.608–5.632, p = 5.70 × 10−4, beer] and SqCLC (OR: 0.135, 95% CI: 0.062–0.293, p = 2.33 × 10−5, dried fruit; OR: 0.485, 95% CI: 0.328–0.717, p = 2.9 × 10−4, cheese). There were also suggestive correlations between 5 dietary intakes and lung cancer (OR: 0.441, 95% CI: 0.250–0.778, p = 0.008, cereal; OR: 2.267, 95% CI: 1.126–4.564, p = 0.022, beef), LA (OR: 0.494, 95% CI: 0.285–0.858, p = 0.012, dried fruit; OR: 3.536, 95% CI: 1.546–8.085, p = 0.003, beer) and SCLC (OR: 0.006, 95% CI: 0.000–0.222, p = 0.039, non-oily fish; OR: 0.239, 95% CI: 0.086–0.664, p = 0.006, dried fruit). No other association between diet and lung cancer was observed.

Conclusion

Our study preliminary found that cheese, dried fruit, and beer intake were significantly associated with the risk of lung cancer or its subtypes, while cereal, beef, and non-oily fish intake were suggestively associated with the risk of lung cancer or its subtypes. Well-designed prospective studies are still needed to confirm our findings in the future.

Learning from the nexus of autoimmunity and cancer

The immune system plays critical roles in both autoimmunity and cancer, diseases at opposite ends of the immune spectrum. Autoimmunity arises from loss of T cell tolerance against self, while in cancer, poor immunity against transformed self fails to control tumor growth. Blockade of pathways that preserve self-tolerance is being leveraged to unleash immunity against many tumors; however, widespread success is hindered by the autoimmune-like toxicities that arise in treated patients. Knowledge gained from the treatment of autoimmunity can be leveraged to treat these toxicities in patients. Further, the understanding of how T cell dysfunction arises in cancer can be leveraged to induce a similar state in autoreactive T cells. Here, we review what is known about the T cell response in autoimmunity and cancer and highlight ways in which we can learn from the nexus of these two diseases to improve the application, efficacy, and management of immunotherapies.

The role of smoking and alcohol in mediating the effect of gastroesophageal reflux disease on lung cancer: A Mendelian randomization study

Observational studies have suggested a positive association between gastroesophageal reflux disease and lung cancer, but due to the existence of confounders, it remains undetermined whether gastroesophageal reflux disease (GERD) has a causal association with lung cancer. Therefore, Mendelian randomization (MR) analyses were applied to investigate the relationship between the two conditions. Two-sample Mendelian randomization analysis was utilized with summary genetic data from the European Bioinformatics Institute (602,604 individuals) and International Lung Cancer Consortium, which provides information on lung cancer and its histological subgroups. Furthermore, we used two-step Mendelian randomization and multivariable Mendelian randomization to estimate whether smoking initiation (311,629 cases and 321,173 controls) and alcohol intake frequency (n = 462,346) mediate any effect of gastroesophageal reflux disease on lung cancer risk. The Mendelian randomization analyses indicated that gastroesophageal reflux disease was associated with and significantly increased the risk of lung cancer (OR_IVW = 1.35, 95% CI = 1.18-1.54; p = 1.36 × 10^-5). Smoking initiation and alcohol intake frequency mediated 35% and 3% of the total effect of gastroesophageal reflux disease on lung cancer, respectively. The combined effect of these two factors accounted for 60% of the total effect. In conclusion, gastroesophageal reflux disease is associated with an increased risk of lung cancer, and interventions to reduce smoking and alcohol intake may reduce the incidence of lung cancer.

SCLC: Epidemiology, Risk Factors, Genetic Susceptibility, Molecular Pathology, Screening, and Early Detection

We review research regarding the epidemiology, risk factors, genetic susceptibility, molecular pathology, and early detection of SCLC, a deadly tumor that accounts for 14% of lung cancers. We first summarize the changing incidences of SCLC globally and in the United States among males and females. We then review the established risk factor (i.e., tobacco smoking) and suspected nonsmoking-related risk factors for SCLC, and emphasize the importance of continued effort in tobacco control worldwide. Review of genetic susceptibility and molecular pathology suggests different molecular pathways in SCLC development compared with other types of lung cancer. Last, we comment on the limited utility of low-dose computed tomography screening in SCLC and on several promising blood-based molecular biomarkers as potential tools in SCLC early detection.

No Association Between Polygenic Risk Scores for Cancer and Development of Radiation Therapy Toxicity

PURPOSE

Our aim was to test whether updated polygenic risk scores (PRS) for susceptibility to cancer affect risk of radiation therapy toxicity.

METHODS AND MATERIALS

Analyses included 9,717 patients with breast (n=3,078), prostate (n=5,748) or lung (n=891) cancer from Radiogenomics and REQUITE Consortia cohorts. Patients underwent potentially curative radiation therapy and were assessed prospectively for toxicity. Germline genotyping involved genome-wide single nucleotide polymorphism (SNP) arrays with nontyped SNPs imputed. PRS for each cancer were generated by summing literature-identified cancer susceptibility risk alleles: 352 breast, 136 prostate, and 24 lung. Weighted PRS were generated using log odds ratio (ORs) for cancer susceptibility. Standardized total average toxicity (STAT) scores at 2 and 5 years (breast, prostate) or 6 to 12 months (lung) quantified toxicity. Primary analysis tested late STAT, secondary analyses investigated acute STAT, and individual endpoints and SNPs using multivariable regression.

RESULTS

Increasing PRS did not increase risk of late toxicity in patients with breast (OR, 1.000; 95% confidence interval [CI], 0.997-1.002), prostate (OR, 0.99; 95% CI, 0.98-1.00; weighted PRS OR, 0.93; 95% CI, 0.83-1.03), or lung (OR, 0.93; 95% CI, 0.87-1.00; weighted PRS OR, 0.68; 95% CI, 0.45-1.03) cancer. Similar results were seen for acute toxicity. Secondary analyses identified rs138944387 associated with breast pain (OR, 3.05; 95% CI, 1.86-5.01; P = 1.09 × 10-5) and rs17513613 with breast edema (OR, 0.94; 95% CI, 0.92-0.97; P = 1.08 × 10-5).

CONCLUSIONS

Patients with increased polygenic predisposition to breast, prostate, or lung cancer can safely undergo radiation therapy with no anticipated excess toxicity risk. Some individual SNPs increase the likelihood of a specific toxicity endpoint, warranting validation in independent cohorts and functional studies to elucidate biologic mechanisms.

Investigating Causal Associations of Circulating Micronutrients Concentrations with the Risk of Lung Cancer: A Mendelian Randomization Study

Previous observational studies have suggested that the effect of diet-derived circulating micronutrient concentrations on lung cancer (LC) risk is controversial. We conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between circulating micronutrient concentrations and the overall risk of LC and three LC subtypes (namely lung adenocarcinoma (LA), squamous cell lung cancer (SqCLC), and small cell lung cancer (SCLC)). The instrumental variables (IVs) of 11 micronutrients (beta-carotene, calcium, copper, folate, lycopene, magnesium, phosphorus, retinol, selenium, zinc, and vitamin B6) were screened from the published genome-wide association studies (GWAS). Summary statistics related to LC and its subtypes came from the largest meta-analysis, including 29,266 cases and 56,450 controls. Inverse-variance weighted (IVW) method is used as the main MR analysis, and the sensitivity analysis is carried out to ensure the MR assumptions. This MR study found suggestive evidence that genetically predicted 6 circulating micronutrient concentrations was correlated with the risk of overall LC (odds ratio (OR): 1.394, 95% confidence interval (CI): 1.041–1.868, p = 0.026, phosphorus), LA (OR: 0.794, 95% CI: 0.634–0.995, p = 0.045, beta-carotene; OR: 0.687, 95%CI: 0.494–0.957, p = 0.026, calcium), SqCLC (OR: 0.354, 95% CI: 0.145–0.865, p = 0.023, retinol), and SCLC (OR: 1.267, 95% CI: 1.040–1.543, p = 0.019, copper; OR: 0.801, 95% CI: 0.679–0.944, p = 0.008, zinc). We found no evidence that other micronutrients are associated with the risk of overall LC or its subtypes. Our study suggested that the increase in circulating beta-carotene, calcium, retinol, and zinc concentration may reduce the risk of LC; the increase in circulating copper and phosphorus concentration may be related to the increased risk of LC. In the future, larger replication samples of LC genetic data and larger micronutrient-related GWAS will be needed to verify our findings.

Coronary artery disease and cancer: a significant resemblance

Cancer and coronary artery disease (CAD) are two of the most common causes of death, and they frequently coexist, especially as the world's population ages. CAD can develop prior to or following cancer diagnosis, as well as a side effect of cancer treatment. CAD develops as complex interactions of lifestyle and hereditary variables, just like the development of the most complex and non-communicable diseases. Cancer is caused by both external/acquired factors (tobacco, food, physical activity, alcohol consumption, epigenetic alterations) and internal/inherited factors (genetic mutations, hormones, and immunological diseases). The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (Cas9) system has recently emerged as a strong tool for gene therapy for both cancer as well as CAD treatment due to its great accuracy and efficiency. A deeper understanding of the complex link between CAD and cancer should lead to better prevention, faster detection, and safer treatment strategies.

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.

MicrobiomeGWAS: A Tool for Identifying Host Genetic Variants Associated with Microbiome Composition

The microbiome is the collection of all microbial genes and can be investigated by sequencing highly variable regions of 16S ribosomal RNA (rRNA) genes. Evidence suggests that environmental factors and host genetics may interact to impact human microbiome composition. Identifying host genetic variants associated with human microbiome composition not only provides clues for characterizing microbiome variation but also helps to elucidate biological mechanisms of genetic associations, prioritize genetic variants, and improve genetic risk prediction. Since a microbiota functions as a community, it is best characterized by β diversity; that is, a pairwise distance matrix. We develop a statistical framework and a computationally efficient software package, microbiomeGWAS, for identifying host genetic variants associated with microbiome β diversity with or without interacting with an environmental factor. We show that the score statistics have positive skewness and kurtosis due to the dependent nature of the pairwise data, which makes p-value approximations based on asymptotic distributions unacceptably liberal. By correcting for skewness and kurtosis, we develop accurate p-value approximations, whose accuracy was verified by extensive simulations. We exemplify our methods by analyzing a set of 147 genotyped subjects with 16S rRNA microbiome profiles from non-malignant lung tissues. Correcting for skewness and kurtosis eliminated the dramatic deviation in the quantile–quantile plots. We provided preliminary evidence that six established lung cancer risk SNPs were collectively associated with microbiome composition for both unweighted (p = 0.0032) and weighted (p = 0.011) UniFrac distance matrices. In summary, our methods will facilitate analyzing large-scale genome-wide association studies of the human microbiome.

Functional studies of lung cancer GWAS beyond association

Fourteen years after the first genome-wide association study (GWAS) of lung cancer was published, approximately forty-five genomic loci have now been significantly associated with lung cancer risk. While functional characterization was performed for several of these loci, a comprehensive summary of current molecular understanding of lung cancer risk has been lacking. Further, many novel computational and experimental tools now became available to accelerate the functional assessment of disease-associated variants, moving beyond locus-by-locus approaches. In this review, we first highlight the heterogeneity of lung cancer GWAS findings across histological subtypes, ancestries, and smoking status, which poses unique challenges to follow-up studies. We then summarize the published lung cancer post-GWAS studies for each risk-associated locus to assess the current understanding of biological mechanisms beyond the initial statistical association. We further summarize strategies for GWAS functional follow-up studies considering cutting-edge functional genomics tools and providing a catalog of available resources relevant to lung cancer. Overall, we aim to highlight the importance of integrating computational and experimental approaches to draw biological insights from the lung cancer GWAS results beyond association.

Assessing the causal role of epigenetic clocks in the development of multiple cancers: a Mendelian randomization study

Background

Epigenetic clocks have been associated with cancer risk in several observational studies. Nevertheless, it is unclear whether they play a causal role in cancer risk or if they act as a non-causal biomarker.

Methods

We conducted a two-sample Mendelian randomization (MR) study to examine the genetically predicted effects of epigenetic age acceleration as measured by HannumAge (nine single-nucleotide polymorphisms (SNPs)), Horvath Intrinsic Age (24 SNPs), PhenoAge (11 SNPs), and GrimAge (4 SNPs) on multiple cancers (i.e. breast, prostate, colorectal, ovarian and lung cancer). We obtained genome-wide association data for biological ageing from a meta-analysis (N = 34,710), and for cancer from the UK Biobank (N cases = 2671-13,879; N controls = 173,493-372,016), FinnGen (N cases = 719-8401; N controls = 74,685-174,006) and several international cancer genetic consortia (N cases = 11,348-122,977; N controls = 15,861-105,974). Main analyses were performed using multiplicative random effects inverse variance weighted (IVW) MR. Individual study estimates were pooled using fixed effect meta-analysis. Sensitivity analyses included MR-Egger, weighted median, weighted mode and Causal Analysis using Summary Effect Estimates (CAUSE) methods, which are robust to some of the assumptions of the IVW approach.

Results

Meta-analysed IVW MR findings suggested that higher GrimAge acceleration increased the risk of colorectal cancer (OR = 1.12 per year increase in GrimAge acceleration, 95% CI 1.04-1.20, p = 0.002). The direction of the genetically predicted effects was consistent across main and sensitivity MR analyses. Among subtypes, the genetically predicted effect of GrimAge acceleration was greater for colon cancer (IVW OR = 1.15, 95% CI 1.09-1.21, p = 0.006), than rectal cancer (IVW OR = 1.05, 95% CI 0.97-1.13, p = 0.24). Results were less consistent for associations between other epigenetic clocks and cancers.

Conclusions

GrimAge acceleration may increase the risk of colorectal cancer. Findings for other clocks and cancers were inconsistent. Further work is required to investigate the potential mechanisms underlying the results.

Funding

FMB was supported by a Wellcome Trust PhD studentship in Molecular, Genetic and Lifecourse Epidemiology (224982/Z/22/Z which is part of grant 218495/Z/19/Z). KKT was supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and by the Hellenic Republic's Operational Programme 'Competitiveness, Entrepreneurship & Innovation' (OΠΣ 5047228). PH was supported by Cancer Research UK (C18281/A29019). RMM was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). RMM is a National Institute for Health Research Senior Investigator (NIHR202411). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. GDS and CLR were supported by the Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5, respectively) and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). REM was supported by an Alzheimer's Society project grant (AS-PG-19b-010) and NIH grant (U01 AG-18-018, PI: Steve Horvath). RCR is a de Pass Vice Chancellor's Research Fellow at the University of Bristol.

Gene-gene interaction of AhRwith and within the Wntcascade affects susceptibility to lung cancer

BACKGROUND

Aberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility.

AIM

To assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent.

METHODS

Odds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups.

RESULTS

No genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR  = 1.20; 95% CI 1.13-1.27; p  = 5.6 × 10-10) and never smokers (e.g., maker rs1133683 Axin2; OR  = 1.27; 95% CI 1.19-1.35; p  = 1.0 × 10-12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants.

CONCLUSIONS

The role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers.

Investigating the effect of sexual behaviour on oropharyngeal cancer risk: a methodological assessment of Mendelian randomization

BACKGROUND

Human papilloma virus infection is known to influence oropharyngeal cancer (OPC) risk, likely via sexual transmission. However, sexual behaviour has been correlated with other risk factors including smoking and alcohol, meaning independent effects are difficult to establish. We aimed to evaluate the causal effect of sexual behaviour on the risk of OPC using Mendelian randomization (MR).

METHODS

Genetic variants robustly associated with age at first sex (AFS) and the number of sexual partners (NSP) were used to perform both univariable and multivariable MR analyses with summary data on 2641 OPC cases and 6585 controls, obtained from the largest available genome-wide association studies (GWAS). Given the potential for genetic pleiotropy, we performed a number of sensitivity analyses: (i) MR methods to account for horizontal pleiotropy, (ii) MR of sexual behaviours on positive (cervical cancer and seropositivity for Chlamydia trachomatis) and negative control outcomes (lung and oral cancer), (iii) Causal Analysis Using Summary Effect estimates (CAUSE), to account for correlated and uncorrelated horizontal pleiotropic effects, (iv) multivariable MR analysis to account for the effects of smoking, alcohol, risk tolerance and educational attainment.

RESULTS

In univariable MR, we found evidence supportive of an effect of both later AFS (IVW OR = 0.4, 95%CI (0.3, 0.7), per standard deviation (SD), p = < 0.001) and increasing NSP (IVW OR = 2.2, 95%CI (1.3, 3.8) per SD, p = < 0.001) on OPC risk. These effects were largely robust to sensitivity analyses accounting for horizontal pleiotropy. However, negative control analysis suggested potential violation of the core MR assumptions and subsequent CAUSE analysis implicated pleiotropy of the genetic instruments used to proxy sexual behaviours. Finally, there was some attenuation of the univariable MR results in the multivariable models (AFS IVW OR = 0.7, 95%CI (0.4, 1.2), p = 0.21; NSP IVW OR = 0.9, 95%CI (0.5 1.7), p = 0.76).

CONCLUSIONS

Despite using genetic variants strongly related sexual behaviour traits in large-scale GWAS, we found evidence for correlated pleiotropy. This emphasizes a need for multivariable approaches and the triangulation of evidence when performing MR of complex behavioural traits.

The effect of CHRNA3 rs1051730 C>T and ABCB1 rs3842 A>G polymorphisms on non-small cell lung cancer and nicotine dependence in Iranian population

Aims

Lung cancer is still the leading cause of cancer mortality in all over the world. Nicotine and its derivatives are the most well-known carcinogens that participate in both etiology and progression of lung cancer. The objective of the current study was to investigate whether single nucleotide polymorphisms (SNPs) rs1051730C > T in CHRNA3 and rs3842A > G in ABCB1, two genes contributing in the mechanism of disposition and metabolism of nicotine and its derivatives, could modify the risk of developing lung cancer, as well as nicotine dependence in Iranian.

Main methods

The genotyping analysis for these two SNPs was conducted in a case-control study of 108 lung cancer cases and 120 healthy controls using ARMS-PCR and Tetra-primer ARMS-PCR techniques. The correlation between studied SNPs and lung cancer was assessed by the regression analysis.

Key findings

We observed a significant association between lung cancer and rs1051730C > T by using four genetic models: allele (OR:1.83; 95% CI:1.24-2.6; p = 0.002), dominant (OR: 2.19; 95% CI:1.27-3.78; p = 0.005), recessive (OR: 2.25; 95% CI: 1.02-4.95; p = 0.043) and additive (TT vs CC: OR:3.25; 95% CI:1.38-7.60; p = 0.007, CT vs CC: OR:1.96; 95% CI:1.10-3.48; p = 0.021). Furthermore, a significant association between this variant and nicotine dependence (OR: 2.27; 95% CI: 1.52-3.39; p = 0.00005) was reported. However, no association was found for rs3842A > G.

Significance

The results suggested that the CHRNA3 rs1051730C > T via a smoking-dependent manner could modify susceptibility to lung cancer among Iranian population.

The shared genetic architecture between epidemiological and behavioral traits with lung cancer

The complex polygenic nature of lung cancer is not fully characterized. Our study seeks to identify novel phenotypes associated with lung cancer using cross-trait linkage disequilibrium score regression (LDSR). We measured pairwise genetic correlation (rg) and SNP heritability (h2) between 347 traits and lung cancer risk using genome-wide association study summary statistics from the UKBB and OncoArray consortium. Further, we conducted analysis after removing genomic regions previously associated with smoking behaviors to mitigate potential confounding effects. We found significant negative genetic correlations between lung cancer risk and dietary behaviors, fitness metrics, educational attainment, and other psychosocial traits. Alcohol taken with meals (rg = - 0.41, h2 = 0.10, p = 1.33 × 10-16), increased fluid intelligence scores (rg = - 0.25, h2 = 0.22, p = 4.54 × 10-8), and the age at which full time education was completed (rg = - 0.45, h2 = 0.11, p = 1.24 × 10-20) demonstrated negative genetic correlation with lung cancer susceptibility. The body mass index was positively correlated with lung cancer risk (rg = 0.20, h2 = 0.25, p = 2.61 × 10-9). This analysis reveals shared genetic architecture between several traits and lung cancer predisposition. Future work should test for causal relationships and investigate common underlying genetic mechanisms across these genetically correlated traits.

Disease-related blood-based differential methylation in cystic fibrosis and its representation in lung cancer revealed a regulatory locus in PKP3 in lung epithelial cells

Cystic fibrosis (CF) is a monogenic disease, characterized by massive chronic lung inflammation. The observed variability in clinical phenotypes in monozygotic CF twins is likely associated with the extent of inflammation. This study sought to investigate inflammation-related aberrant DNA methylation in CF twins and to determine to what extent acquired methylation changes may be associated with lung cancer.

Blood-based genome-wide DNA methylation analysis was performed to compare the DNA methylomes of monozygotic twins, from the European CF Twin and Sibling Study with various degrees of disease severity. Putatively inflammation-related and differentially methylated positions were selected from a large lung cancer case-control study and investigated in blood by targeted bisulphite next-generation-sequencing. An inflammation-related locus located in the Plakophilin-3 (PKP3) gene was functionally analysed regarding promoter and enhancer activity in presence and absence of methylation using luciferase reporter assays.

We confirmed in a unique cohort that monozygotic twins, even if clinically discordant, have only minor differences in global DNA methylation patterns and blood cell composition. Further, we determined the most differentially methylated positions, a high proportion of which are blood cell-type-specific, whereas others may be acquired and thus have potential relevance in the context of inflammation as lung cancer risk factors. We identified a sequence in the gene body of PKP3 which is hypermethylated in blood from CF twins with severe phenotype and highly variably methylated in lung cancer patients and controls, independent of known clinical parameters, and showed that this region exhibits methylation-dependent promoter activity in lung epithelial cells.

How to Better Understand the Influence of Host Genetics on Developing an Effective Immune Response to Thoracic Cancers

Thoracic cancers pose a significant global health burden. Immune checkpoint blockade therapies have improved treatment outcomes, but durable responses remain limited. Understanding how the host immune system interacts with a developing tumor is essential for the rational development of improved treatments for thoracic malignancies. Recent technical advances have improved our understanding of the mutational burden of cancer cells and changes in cancer-specific gene expression, providing a detailed understanding of the complex biology underpinning tumor-host interactions. While there has been much focus on the genetic alterations associated with cancer cells and how they may impact treatment outcomes, how host genetics affects cancer development is also critical and will greatly determine treatment response. Genome-wide association studies (GWAS) have identified genetic variants associated with cancer predisposition. This approach has successfully identified host genetic risk factors associated with common thoracic cancers like lung cancer, but is less effective for rare cancers like malignant mesothelioma. To assess how host genetics impacts rare thoracic cancers, we used the Collaborative Cross (CC); a powerful murine genetic resource designed to maximize genetic diversity and rapidly identify genes associated with any biological trait. We are using the CC in conjunction with our asbestos-induced MexTAg mouse model, to identify host genes associated with mesothelioma development. Once genes that moderate tumor development and progression are known, human homologues can be identified and human datasets interrogated to validate their association with disease outcome. Furthermore, our CC-MexTAg animal model enables in-depth study of the tumor microenvironment, allowing the correlation of immune cell infiltration and gene expression signatures with disease development. This strategy provides a detailed picture of the underlying biological pathways associated with mesothelioma susceptibility and progression; knowledge that is crucial for the rational development of new diagnostic and therapeutic strategies. Here we discuss the influence of host genetics on developing an effective immune response to thoracic cancers. We highlight current knowledge gaps, and with a focus on mesothelioma, describe the development and application of the CC-MexTAg to overcome limitations and illustrate how the knowledge gained from this unique study will inform the rational design of future treatments of mesothelioma.

Lung Cancer Stem Cells-Origin, Diagnostic Techniques and Perspective for Therapies

Lung cancer remains one of the most aggressive solid tumors with an overall poor prognosis. Molecular studies carried out on lung tumors during treatment have shown the phenomenon of clonal evolution, thereby promoting the occurrence of a temporal heterogeneity of the tumor. Therefore, the biology of lung cancer is interesting. Cancer stem cells (CSCs) are involved in tumor initiation and metastasis. Aging is still the most important risk factor for lung cancer development. Spontaneously occurring mutations accumulate in normal stem cells or/and progenitor cells by human life resulting in the formation of CSCs. Deepening knowledge of these complex processes and improving early recognition and markers of predictive value are of utmost importance. In this paper, we discuss the CSC hypothesis with an emphasis on age-related changes that initiate carcinogenesis. We analyze the current literature in the field, describe our own experience in CSC investigation and discuss the technical challenges with special emphasis on liquid biopsy.

RAD52 variants influence NSCLC risk in the Chinese population in a high altitude area

BACKGROUND

Non-small cell lung cancer (NSCLC) accounts for approximately 80% of diagnosed lung cancer patients. RAD52 has been reported to be associated with the development of squamous cell lung carcinoma. In this study, we assessed the relationships of RAD52 genetic polymorphisms and NSCLC risk among the Chinese population at high altitude.

METHODS

Eight single nucleotide polymorphisms (SNPs) of RAD52 were genotyped in the Agena MassARRAY platform among 506 NSCLC patients and 510 healthy controls. We examined the association of RAD52 polymorphisms with NSCLC risk using odds ratios (ORs) and 95% confidence intervals (CIs) via multiple genetic models.

RESULTS

The rs10774474 A allele was related to a decreased risk of NSCLC in a high altitude population of China (OR = 0.82, 95% CI = 0.69-0.98, p = 0.032), whereas mutant alleles of rs1051672, rs7310449, rs1051669, rs6413436, rs4766377 and rs10849605 significantly increased NSCLC risk. Haplotype analysis showed that four haplotypes of RAD52 polymorphisms conferred an enhanced susceptibility to NSCLC (A_rs1051672G_rs7310449T_rs1051669A_rs6413436: OR = 1.29, p = 0.021; G_rs1051672A_rs7310449C_rs1051669G_rs6413436: OR = 1.21, p = 0.027; G_rs4766377C_rs12822733T_rs10774474C_rs10849605: OR = 1.26, p = 0.032; A_rs4766377C_rs12822733A_rs10774474T_rs10849605: OR = 1.21, p = 0.032).

CONCLUSIONS

Our findings suggested the remarkable association of RAD52 polymorphisms with NSCLC risk among the Chinese population in a high altitude area. The reviews of this paper are available via the supplemental material section.

Genome-Wide Analysis of Sex Disparities in the Genetic Architecture of Lung and Colorectal Cancers

Almost all complex disorders have manifested epidemiological and clinical sex disparities which might partially arise from sex-specific genetic mechanisms. Addressing such differences can be important from a precision medicine perspective which aims to make medical interventions more personalized and effective. We investigated sex-specific genetic associations with colorectal (CRCa) and lung (LCa) cancers using genome-wide single-nucleotide polymorphisms (SNPs) data from three independent datasets. The genome-wide association analyses revealed that 33 SNPs were associated with CRCa/LCa at P < 5.0 × 10⁻⁶ neither males or females. Of these, 26 SNPs had sex-specific effects as their effect sizes were statistically different between the two sexes at a Bonferroni-adjusted significance level of 0.0015. None had proxy SNPs within their ±1 Mb regions and the closest genes to 32 SNPs were not previously associated with the corresponding cancers. The pathway enrichment analyses demonstrated the associations of 35 pathways with CRCa or LCa which were mostly implicated in immune system responses, cell cycle, and chromosome stability. The significant pathways were mostly enriched in either males or females. Our findings provided novel insights into the potential sex-specific genetic heterogeneity of CRCa and LCa at SNP and pathway levels.

Description of a Lung Cancer Hotspot: Disparities in Lung Cancer Histology, Incidence, and Survival in Kentucky and Appalachian Kentucky

INTRODUCTION

Kentucky is recognized as the state with the highest lung cancer burden for more than 2 decades, but how lung cancer differs in Kentucky relative to other US populations is not fully understood.

PATIENTS AND METHODS

We examined lung cancer reported to the Surveillance, Epidemiology, and End Results (SEER) Program by Kentucky and the other SEER regions for patients diagnosed between 2012 and 2016. Our analyses included histologic types, incidence rates, stage at diagnosis, and survival in Kentucky and Appalachian Kentucky relative to other SEER regions.

RESULTS

We found that both squamous cell carcinomas and small-cell lung cancers represent larger proportions of lung cancer diagnoses in Kentucky and Appalachian Kentucky than they do in the SEER registries. Furthermore, age-adjusted cancer incidence rates were higher in Kentucky for every subtype of lung cancer examined. Most notably, for Appalachian women the rate of small-cell carcinomas was 3.5-fold higher, and for Appalachian men the rate of squamous cell carcinoma was 3.1-fold higher, than the SEER rates. In Kentucky, lung cancers were diagnosed at later stages and lung cancer survival was lower for adenocarcinoma and neuroendocrine carcinomas than in SEER registries. Squamous cell carcinomas and small-cell carcinomas were most lethal in Appalachian Kentucky.

CONCLUSION

Together, these data highlight the considerable disparities among lung cancer cases in the United States and demonstrate the continuing high burden and poor survival of lung cancer in Kentucky and Appalachian Kentucky. Strategies to identify and rectify causes of these disparities are discussed.

Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1β pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

Long non-coding RNA ANRIL polymorphisms in papillary thyroid cancer and its severity

Background: Long non-coding RNAs are likely to have a role in the pathogenesis of many diseases, including cancer. We hypothesised an effect of certain ANRIL single nucleotide polymorphisms (SNPs) in papillary thyroid cancer. Methods: Genomic ANRIL SNPs in rs11333048, rs4977574, rs1333040 and rs10757274 were determined in 134 papillary thyroid cancer patients and 155 age- and sex-matched controls. Results: None of the ANRIL SNPs were individually linked to papillary thyroid cancer. However, the AAAC haplotype (A from rs11333048, A from rs4977574, A from rs1333040 and C from rs10757274, respectively) showed a protective effect from papillary thyroid cancer whilst the CAAC and CAGT haplotypes were associated with cancer. The rs1333048 CC variant was more frequent in patients with larger tumour size (≥1 cm) in a recessive model (OR 3.4 [95%CI, 1.1-11], P = 0.035). The rs4977574 AC variant was associated with smaller tumour size in an over-dominant model (OR 0.4 [95%CI, 0.2-1.0], P = 0.041). SNPs in rs10757274 (AA: p = 0.045) and rs1333040 (CC: p = 0.019) are linked to a lower likelihood of III-IV cancer stages in dominant or codominant models. Conclusions: Certain haplotypes of ANRIL SNPs are associated with papillary thyroid cancer. ANRIL rs1333048 and rs4977574 variants were associated with larger and smaller tumour sizes, respectively. rs10757274 and rs1333040 variants might lead to lower III-IV cancer stages. These SNPs may be important in the diagnosis of this form of thyroid cancer.

Current lung cancer screening guidelines may miss high-risk population: a real-world study

BACKGROUND

Despite much research published on lung cancer screening, China has had no large-scale study on the missed diagnosis of lung cancer in a health examination population. We therefore did a real-world study using the current lung cancer screening guidelines to a health examination population in China to determine the proportion of lung cancer cases that have been missed.

METHODS

A real-world cohort study of screening, with the use of low-dose computed tomography, was conducted among people who took yearly health checkup in health management center of West China Hospital between 2006 and 2017. We respectively used current guidelines including lung cancer screening guidelines of the U.S. Preventive Services Task Force (USPSTF) and expert consensus on low dose spiral CT lung cancer screening in China.

RESULTS

In a total of 15,996 participants with health examination who completed the baseline screening, 6779 (42.4%) subjects had at least one positive finding, and 142 (2.1%) cases of lung cancer were screened positive. The false positive rate was 97.9%. Of 142 lung cancer cases detected in our study, only 9.2% met the lung cancer screening guidelines proposed by the USPSTF, and 24.4% met that of China. The rates of missed diagnosis were as high as 90.8 and 75.6% respectively. In addition, we did an in-depth analysis by gender. We found that among male patients with lung cancer, the proportion of smokers was 75%, and the proportion of young people under 50 was 23.2%. Among female patients with lung cancer, the proportion of smokers was only 5.8%, and the proportion of young people under 50 was up to 33.3%.

CONCLUSIONS

The rate of missed diagnosis was as high as 90.8% applying the current lung cancer screening guidelines to the health examination population in China. Further study to determine screening guidelines for targeted populations, is warranted.

Proteomic Signatures of Lifestyle Risk Factors for Cardiovascular Disease: A Cross-Sectional Analysis of the Plasma Proteome in the Framingham Heart Study

Background Proteomic biomarkers related to cardiovascular disease risk factors may offer insights into the pathogenesis of cardiovascular disease. We investigated whether modifiable lifestyle risk factors for cardiovascular disease are associated with distinctive proteomic signatures. Methods and Results We analyzed 1305 circulating plasma proteomic biomarkers (assayed using the SomaLogic platform) in 897 FHS (Framingham Heart Study) Generation 3 participants (mean age 46±8 years; 56% women; discovery sample) and 1121 FOS (Framingham Offspring Study) participants (mean age 52 years; 54% women; validation sample). Participants were free of hypertension, diabetes mellitus, and clinical cardiovascular disease. We used linear mixed effects models (adjusting for age, sex, body mass index, and family structure) to relate levels of each inverse-log transformed protein to 3 lifestyle factors (ie, smoking, alcohol consumption, and physical activity). A Bonferroni-adjusted P value indicated statistical significance (based on number of proteins and traits tested, P<4.2×10-6 in the discovery sample; P<6.85×10-4 in the validation sample). We observed statistically significant associations of 60 proteins with smoking (37/40 top proteins validated in FOS), 30 proteins with alcohol consumption (23/30 proteins validated), and 5 proteins with physical activity (2/3 proteins associated with the physical activity index validated). We assessed the associations of protein concentrations with previously identified genetic variants (protein quantitative trait loci) linked to lifestyle-related disease traits in the genome-wide-association study catalogue. The protein quantitative trait loci were associated with coronary artery disease, inflammation, and age-related mortality. Conclusions Our cross-sectional study from a community-based sample elucidated distinctive sets of proteins associated with 3 key lifestyle factors.

Roles of ARF tumour suppressor protein in lung cancer: time to hit the nail on the head!

Owing to its poor prognosis, the World Health Organization (WHO) lists lung cancer on top of the list when it comes to growing mortality rates and incidence. Usually, there are two types of lung cancer, small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC), which also includes adenocarcinoma, squamous cell carcinoma and large cell carcinomas. ARF, also known in humans as p14ARF and in the mouse as p19ARF, is a nucleolar protein and a member of INK4, a family of cyclin-independent kinase inhibitors (CKI). These genes are clustered on chromosome number 9p21 within the locus of CDKN2A. NSCLC has reported the role of p14ARF as a potential target. p14ARF has a basic mechanism to inhibit mouse double minute 2 protein that exhibits inhibitory action on p53, a phosphoprotein tumour suppressor, thus playing a role in various tumour-related activities such as growth inhibition, DNA damage, autophagy, apoptosis, cell cycle arrest and others. Extensive cancer research is ongoing and updated reports regarding the role of ARF in lung cancer are available. This article summarizes the available lung cancer ARF data, its molecular mechanisms and its associated signalling pathways. Attempts have been made to show how p14ARF functions in different types of lung cancer providing a thought to look upon ARF as a new target for treating the debilitating condition of lung cancer.

Association of PARP1-specific polymorphisms and haplotypes with non-small cell lung cancer subtypes

OBJECTIVE

The carcinogenesis role of PARP1 in lung cancer is still not clear. Analysis at allelic levels cannot fully explain the function of PARP1 on lung cancer. Our study aims to further explore the relation between PARP1 haplotypes and lung cancer.

MATERIALS AND METHODS

DNA and RNA were extracted from non-small cell lung cancer (NSCLC) tumor and adjacent normal fresh frozen tissue. Five PARP1-SNPs were genotyped and PARP1-specific SNPs were imputed using IMPUTE and SHAPEIT software. The SNPs were subjected to allelic, haplotype and SNP-SNP interaction analyses. Correlation between SNPs and mRNA/protein expressions were performed.

RESULTS

SNP imputation inferred the ungenotyped SNPs and increased the power for association analysis. Tumor tissue samples are more likely to carry rs1805414 (OR = 1.85; 95% CI: 1.12-3.06; P-value: 0.017) and rs1805404 (OR = 2.74; 95%CI 1.19-6.32; P-value: 0.015) compared to normal tissues. Our study is the first study to show that haplotypes comprising of 5 SNPs on PARP1 (rs1136410, rs3219073, rs1805414, rs1805404, rs1805415) is able to differentiate the NSCLC tumor from normal tissues. Interaction between rs3219073, rs1805415, and rs1805414 were significantly associated with the NSCLC tumor with OR ranging from 3.61-6.75; 95%CI from 1.82 to 19.9; P-value<0.001.

CONCLUSION

PARP1 haplotypes may serve as a better predictor in lung cancer development and prognosis compared to single alleles.

Potential Genes Associated with the Survival of Lung Adenocarcinoma Were Identified by Methylation

Background

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. The purpose of this study is to search for genes related to the prognosis of LUAD through methylation based on a linear mixed model (LMM).

Methods

Gene expression, methylation, and survival data of LUAD patients were downloaded from the TCGA database. Based on the LMM model, the GEMMA algorithm was used to screen the predictive genes related to LUAD survival. The Cox model was used to further screen the predicted genes, and then, protein-protein interaction (PPI) network was constructed. Through the software plugin Cytoscape MCODE 3.8.0, the most closely related genes in the PPI network module were selected for in-depth biological function analysis to further explore the interaction and correlation between genes.

Results

We screened out 97 predictive genes from 18,834 genes and eliminated one gene associated with lung squamous cell carcinoma from previous studies, leaving 96 genes. The MCODE and the Kaplan-Meier curve analysis were used to finally identify two genes ASB16 and NEDD4 that are related to the prognosis of LUAD.

Conclusions

The newly identified two genes associated with the prognosis of LUAD may provide a basis for the treatment of patients.

Genome-Wide Meta-Analyses of FTND and TTFC Phenotypes

INTRODUCTION

FTND (Fagerstrӧm test for nicotine dependence) and TTFC (time to smoke first cigarette in the morning) are common measures of nicotine dependence (ND). However, genome-wide meta-analysis for these phenotypes has not been reported.

METHODS

Genome-wide meta-analyses for FTND (N = 19,431) and TTFC (N = 18,567) phenotypes were conducted for adult smokers of European ancestry from 14 independent cohorts.

RESULTS

We found that SORBS2 on 4q35 (p = 4.05 × 10-8), BG182718 on 11q22 (p = 1.02 × 10-8), and AA333164 on 14q21 (p = 4.11 × 10-9) were associated with TTFC phenotype. We attempted replication of leading candidates with independent samples (FTND, N = 7010 and TTFC, N = 10 061), however, due to limited power of the replication samples, the replication of these new loci did not reach significance. In gene-based analyses, COPB2 was found associated with FTND phenotype, and TFCP2L1, RELN, and INO80C were associated with TTFC phenotype. In pathway and network analyses, we found that the interconnected interactions among the endocytosis, regulation of actin cytoskeleton, axon guidance, MAPK signaling, and chemokine signaling pathways were involved in ND.

CONCLUSIONS

Our analyses identified several promising candidates for both FTND and TTFC phenotypes, and further verification of these candidates was necessary. Candidates supported by both FTND and TTFC (CHRNA4, THSD7B, RBFOX1, and ZNF804A) were associated with addiction to alcohol, cocaine, and heroin, and were associated with autism and schizophrenia. We also identified novel pathways involved in cigarette smoking. The pathway interactions highlighted the importance of receptor recycling and internalization in ND.

IMPLICATIONS

Understanding the genetic architecture of cigarette smoking and ND is critical to develop effective prevention and treatment. Our study identified novel candidates and biological pathways involved in FTND and TTFC phenotypes, and this will facilitate further investigation of these candidates and pathways.

Physical Activity Does Not Lower the Risk of Lung Cancer

Observational studies have suggested that physical activity might lower the risk of lung cancer in former and current smokers, but not in never-smokers. Using genetic instruments for self-reported and accelerometer-measured physical activity traits implemented through two-sample Mendelian randomization (MR), we sought to strengthen the evidence for causality. We used 18 genome-wide significant (P < 5 × 10-8) single-nucleotide polymorphisms (SNP) for self-reported moderate-to-vigorous physical activity and seven SNP for accelerometer-measured ("average acceleration") physical activity from up to 377,234 UK Biobank participants and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell carcinoma, and 2,664 small-cell carcinoma cases) and 56,450 controls. MR analysis suggested no effect of self-reported physical activity [OR (95% confidence interval (CI)) = 0.67 (0.42-1.05); P = 0.081; Q-value = 0.243] and accelerometer-measured activity [OR (95% CI) = 0.98 (0.93-1.03); P = 0.372; Q-value = 0.562] on lung cancer. There was no evidence for associations of physical activity with histologic types and lung cancer in ever and never smokers. Replication analysis using genetic instruments from a different genome-wide study and sensitivity analysis to address potential pleiotropic effects led to no substantive change in estimates. Collectively, these findings do not support a protective relationship between physical activity and the risk of lung cancer. SIGNIFICANCE: A new genetic study provides little evidence that recommending physical activity would help prevent lung cancer.

DNA Mismatch Repair Gene Variants in Sporadic Solid Cancers

The phenotypic effects of single nucleotide polymorphisms (SNPs) in the development of sporadic solid cancers are still scarce. The aim of this review was to summarise and analyse published data on the associations between SNPs in mismatch repair genes and various cancers. The mismatch repair system plays a unique role in the control of the genetic integrity and it is often inactivated (germline and somatic mutations and hypermethylation) in cancer patients. Here, we focused on germline variants in mismatch repair genes and found the outcomes rather controversial: some SNPs are sometimes ascribed as protective, while other studies reported their pathological effects. Regarding the complexity of cancer as one disease, we attempted to ascertain if particular polymorphisms exert the effect in the same direction in the development and treatment of different malignancies, although it is still not straightforward to conclude whether polymorphisms always play a clear positive role or a negative one. Most recent and robust genome-wide studies suggest that risk of cancer is modulated by variants in mismatch repair genes, for example in colorectal cancer. Our study shows that rs1800734 in MLH1 or rs2303428 in MSH2 may influence the development of different malignancies. The lack of functional studies on many DNA mismatch repair SNPs as well as their interactions are not explored yet. Notably, the concerted action of more variants in one individual may be protective or harmful. Further, complex interactions of DNA mismatch repair variations with both the environment and microenvironment in the cancer pathogenesis will deserve further attention.

Exosomal Long Non-Coding RNAs in Lung Diseases

Within the non-coding genome landscape, long non-coding RNAs (lncRNAs) and their secretion within exosomes are a window that could further explain the regulation, the sustaining, and the spread of lung diseases. We present here a compilation of the current knowledge on lncRNAs commonly found in Chronic Obstructive Pulmonary Disease (COPD), asthma, Idiopathic Pulmonary Fibrosis (IPF), or lung cancers. We built interaction networks describing the mechanisms of action for COPD, asthma, and IPF, as well as private networks for H19, MALAT1, MEG3, FENDRR, CDKN2B-AS1, TUG1, HOTAIR, and GAS5 lncRNAs in lung cancers. We identified five signaling pathways targeted by these eight lncRNAs over the lung diseases mentioned above. These lncRNAs were involved in ten treatment resistances in lung cancers, with HOTAIR being itself described in seven resistances. Besides, five of them were previously described as promising biomarkers for the diagnosis and prognosis of asthma, COPD, and lung cancers. Additionally, we describe the exosomal-based studies on H19, MALAT1, HOTAIR, GAS5, UCA1, lnc-MMP2-2, GAPLINC, TBILA, AGAP2-AS1, and SOX2-OT. This review concludes on the need for additional studies describing the lncRNA mechanisms of action and confirming their potential as biomarkers, as well as their involvement in resistance to treatment, especially in non-cancerous lung diseases.

Transcriptome-wide association study reveals candidate causal genes for lung cancer

We have recently completed the largest GWAS on lung cancer including 29,266 cases and 56,450 controls of European descent. The goal of our study has been to integrate the complete GWAS results with a large-scale expression quantitative trait loci (eQTL) mapping study in human lung tissues (n = 1,038) to identify candidate causal genes for lung cancer. We performed transcriptome-wide association study (TWAS) for lung cancer overall, by histology (adenocarcinoma, squamous cell carcinoma and small cell lung cancer) and smoking subgroups (never- and ever-smokers). We performed replication analysis using lung data from the Genotype-Tissue Expression (GTEx) project. DNA damage assays were performed in human lung fibroblasts for selected TWAS genes. As expected, the main TWAS signal for all histological subtypes and ever-smokers was on chromosome 15q25. The gene most strongly associated with lung cancer at this locus using the TWAS approach was IREB2 (pTWAS = 1.09E-99), where lower predicted expression increased lung cancer risk. A new lung adenocarcinoma susceptibility locus was revealed on 9p13.3 and associated with higher predicted expression of AQP3 (pTWAS = 3.72E-6). Among the 45 previously described lung cancer GWAS loci, we mapped candidate target gene for 17 of them. The association AQP3-adenocarcinoma on 9p13.3 was replicated using GTEx (pTWAS = 6.55E-5). Consistent with the effect of risk alleles on gene expression levels, IREB2 knockdown and AQP3 overproduction promote endogenous DNA damage. These findings indicate genes whose expression in lung tissue directly influences lung cancer risk.

The hazards of smoking and the benefits of cessation: a critical summation of the epidemiological evidence in high-income countries

In high-income countries, the biggest cause of premature death, defined as death before 70 years, is smoking of manufactured cigarettes. Smoking-related disease was responsible for about 41 million deaths in the United States, United Kingdom and Canada, cumulatively, from 1960 to 2020. Every million cigarettes smoked leads to one death in the US and Canada, but slightly more than one death in the UK. The 21^st century hazards reveal that smokers who start smoking early in adult life and do not quit lose a decade of life expectancy versus non-smokers. Cessation, particularly before age 40 years, yields large reductions in mortality risk. Up to two-thirds of deaths among smokers are avoidable at non-smoking death rates, and former smokers have about only a quarter of the excess risk of death compared to current smokers. The gap between scientific and popular understanding of smoking hazards is surprisingly large.

Inherited lung cancer: a review

Lung cancer is the most common cancer worldwide and has high rates of mortality. The major risk factor associated with this disease is tobacco smoke, but approximately 10%-25% of all lung cancer cases occur in patients who have never smoked. Data suggest that lung cancer in never-smokers has a different molecular profile, tumour microenvironment and epidemiology than that in smokers. Several risk factors have been associated with its occurrence, and the possibility of inherited predisposition is becoming clearer. A better understanding of this disease is essential for the future development of personalised screening, diagnosis and treatment approaches, with consequent reduction of mortality. In this review, we discuss historical studies of lung cancer in never-smokers and the currently available evidence of inherited predisposition to this disease.