Abstract Background We investigated whether markers, genes or terms of the Human Phenotype Ontology associated with genetic or rare diseases (GARDs) that affect airway or lung function are associated with lung cancer. Methods Genes of interest were extracted from GARD (Genetic and Rare Diseases Information Center), OMIM (Online Mendelian Inheritance in Man®), ORPHANET and Monarch Initiative. Individual SNP, gene level and gene-set analyses were performed for 52,207 SNPs, 1677 genes or for 620 terms of the Human Phenotype Ontology. The analysis included 14,068 lung cancer cases and 12,390 cancer-free control subjects of European descent from the International Lung Cancer Consortium ILCCO. Results The marker rs56113850 (OR=0.893, 95%CI: 0.862-0.924) was associated with lung cancer (p=1.2x10-10). This marker is located in CYP2A6 as well as in an enhancer region of LTBP4, which is associated with cutis laxa. A suggestive significant association was observed for two markers associated with the DMD gene, which is linked to Duchenne muscular dystrophy. The gene sets "Abnormal circulating adrenocorticotropin concentration" and "Central nervous system neoplasm" were found to be significantly enriched with GARD genes, and can therefore be considered to be associated with lung cancer. Conclusions Genes associated with genetic and rare lung diseases do not generally appear to carry risk factors for lung cancer. However, genes associated with the hypothalamic-pituitary-adrenal axis show some, but rather weak or complex, associations with lung cancer. Tests at the gene level provide extremely inhomogeneous results, even when applied to the same data.

Most solid tumors harbor somatic mutations attributed to off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B). However, how APOBEC3A/B enzymes affect tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, multi-omics profiling of 309 lung cancers from smokers identifies two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations; HAS for A3A-like mutagenesis and TP53 mutations. Compared to LAS, HAS have older age at onset and high proportions of newly generated progenitor-like cells likely due to the combined tobacco smoking- and APOBEC3A-associated DNA damage and apoptosis. Consistently, HAS exhibit high expression of pulmonary healing signaling pathway, stemness markers, distal cell-of-origin, more neoantigens, slower clonal expansion, but no smoking-associated genomic/epigenomic changes. With validation in 184 lung tumor samples, these findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development.

Understanding lung cancer evolution can identify tools for intercepting its growth. In a landscape analysis of 1024 lung adenocarcinomas (LUAD) with deep whole-genome sequencing integrated with multiomic data, we identified 542 LUAD that displayed diverse clonal architecture. In this group, we observed an interplay between mobile elements, endogenous and exogenous mutational processes, distinct driver genes, and epidemiological features. Our results revealed divergent evolutionary trajectories based on tobacco smoking exposure, ancestry, and sex. LUAD from smokers showed an abundance of tobacco-related C:G>A:T driver mutations in KRAS plus short subclonal diversification. LUAD in never smokers showed early occurrence of copy number alterations and EGFR mutations associated with SBS5 and SBS40a mutational signatures. Tumors harboring EGFR mutations exhibited long latency, particularly in females of European-ancestry (EU_N). In EU_N, EGFR mutations preceded the occurrence of other driver genes, including TP53 and RBM10. Tumors from Asian never smokers showed a short clonal evolution and presented with heterogeneous repetitive patterns for the inferred mutational order. Importantly, we found that the mutational signature ID2 is a marker of a previously unrecognized mechanism for LUAD evolution. Tumors with ID2 showed short latency and high L1 retrotransposon activity linked to L1 promoter demethylation. These tumors exhibited an aggressive phenotype, characterized by increased genomic instability, elevated hypoxia scores, low burden of neoantigens, propensity to develop metastasis, and poor overall survival. Reactivated L1 retrotransposition-induced mutagenesis can contribute to the origin of the mutational signature ID2, including through the regulation of the transcriptional factor ZNF695, a member of the KZFP family. The complex nature of LUAD evolution creates both challenges and opportunities for screening and treatment plans.

With over 80, 000 new cases of non-Hodgkin's lymphoma (NHL) diagnosed annually, modifiable risk factors remain unclear. Circadian disruption, linked to cancers like breast and prostate, affects immune cells (e.g., natural killer cells and T-helper cells) by altering their trafficking and proliferation. Some studies (PMID: 30566672, 27611440) suggest long sleep may increase overall NHL risk, including a Mendelian randomization (MR) study (PMID: 32895918). However, no research has examined the causal relationship between sleep traits, including long sleep, and NHL risk, by subtypes. We hypothesize that sleep traits are causally associated with NHL subtypes in European populations, testing this using MR with data from the International Lymphoma Epidemiology Consortium (InterLymph). We conducted two-sample MR using genome-wide association studies (GWAS) summary data for sleep traits and NHL subtypes. Only independent, genome-wide significant (p < 5×10-8) Single Nucleotide Polymorphisms (SNPs) were selected as valid instruments, sourced from the UK Biobank. Sleep traits included chronotype (153 SNPs), insomnia (48 SNPs), sleep duration (78 SNPs), excessive daytime sleepiness (37 SNPs), short sleep (27 SNPs), and long sleep (8 SNPs). NHL subtype data were from InterLymph: follicular lymphoma (6, 508 cases / 64, 183 controls), mantle cell lymphoma (1, 169 cases / 61, 603 controls), Waldenstrom macroglobulinemia/lymphoplasmacytic lymphoma (WM/LPL: 1, 697 cases / 59, 333 controls), and chronic lymphocytic leukemia (8, 522 cases / 67, 653 controls). The primary analysis used inverse-variance weighted (IVW) random-effects, with MR-Egger for pleiotropy adjustment. Using the IVW method, we did not identify any statistically significant causal association between sleep traits and the risk of NHL subtypes, but did yield several intriguing trends. Long sleep (sleep duration >= 9 h per night) showed a marginally increased NHL risk [Odds ratio (OR) range: 1.51 - 247.9] across each subtype. Short sleep (sleep duration < 7 h per night) showed a similar trend [OR range: 1.25 - 1.81], except for WM/LPL, where we noticed a negative trend. The confidence limit for long sleep was imprecise due to the small number of variants. We did not notice any significant directional horizontal pleiotropy or weak instrument bias. We found no conclusive evidence of a relationship between sleep traits and four NHL subtypes. However, we see suggestive trends of long and short sleep associated with higher risk of some NHL subtypes. These findings align with the previous studies, which showed long sleep was associated with higher risk of NHL overall. Future directions include expanding our analysis to additional NHL subtypes, generating polygenic risk scores, and conducting stratified analyses. Pankhil Shah, Brittany Crawford, Anwar Merchant, Brenda Birmann, Angelica Macauda, Michelle A. Hildebrandt, Aaron Norman, Neil E. Caporaso, Meredith Yeager, Michael Dean, Immaculata De Vivo, Lynn Goldin, Nicola J. Camp, Rosalie Griffin, Delphine Casabonne, Federico Canzian, Pelin Unal, Elad Ziv, Catherine R. Marinac, Alexandra Nieters, Stephen J. Chanock, Mitchell J. Machiela, Michael Conry, Charlie Zhong, Hanla A. Park, Simon Cheah, Jonathan N. Hofmann, Elizabeth E. Brown, Celine Vachon, Susan Slager, Sonja Berndt, Sophia S. Wang, Vijai Joseph, James McKay, Henrik Hjalgrim, Lara Sucheston-Campbell, Karl Smith-Byrne, Alyssa Clay-Gilmour. Association between sleep traits and risk of non-Hodgkin's lymphoma subtypes: a mendelian randomization study in the International Lymphoma Epidemiology (InterLymph) Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7415.

Despite lung cancer affecting all races and ethnicities, disparities are observed in incidence and mortality rates among different ethnic groups in the United States. Non-Hispanic African Americans had a high incidence rate of lung cancer at 55.8 per 100 000 people, as well as the highest death rate at 37.2 per 100 000 people from 2016 to 2020. While previous genome-wide association studies (GWAS) have identified over 45 susceptibility risk loci that influence lung cancer development, few GWAS have investigated the etiology of lung cancer in African Americans. To address this gap in knowledge, we conducted GWAS of lung cancer focused on studying African Americans, comprising 2267 lung cancer cases and 4264 controls. We identified three loci associated with lung cancer, one with lung adenocarcinoma, and four with lung squamous cell carcinoma in this population at the genomic-wide significance level. Among them, three novel loci were identified near VWF at 12p13.31 for overall lung cancer and GACAT3 at 2p24.3 and LMAN1L at 15q24.1 for lung squamous cell carcinoma. In addition, we confirmed previously reported risk loci with known or new lead variants near CHRNA5 at 15q25.1 and CYP2A6 at 19q13.2 associated with lung cancer and TRIP13 at 5p15.33 and ERC1 at 12p13.33 associated with lung squamous cell carcinoma. Further multi-step functional analyses shed light on biological mechanisms underlying these associations of lung cancer in this population. Our study highlights the importance of ancestry-specific studies for the potential alleviation of lung cancer burden in African Americans.

BACKGROUND:Lung adenocarcinoma (LUAD) in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve LUAD risk prediction. METHODS:PRSs were developed using genome-wide association study summary statistics from East Asian (8,002 cases; 20,782 controls) and European (2,058 cases; 5,575 controls) populations. Single-ancestry models included PRS-25, PRS-CT, and LDpred2; multi-ancestry models included LDpred2+PRS-EUR128, PRS-CSx, and CT-SLEB. Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium (FLCCA) and externally validated in the Nanjing Lung Cancer Cohort (NJLCC). We assessed predictive accuracy via AUC, with 10-year and (age 30-80) absolute risks estimates. RESULTS:The best multi-ancestry PRS, using East Asian and European data via CT-SLEB (clumping and thresholding, super learning, empirical Bayes), outperformed the best East Asian-only PRS (LDpred2; AUC = 0.629, 95% CI:0.618,0.641), achieving an AUC of 0.640 (95% CI : 0.629,0.653) and odds ratio of 1.71 (95% CI : 1.61,1.82) per SD increase. NJLCC Validation confirmed robust performance (AUC =0.649, 95% CI: 0.623, 0.676). The top 20% PRS group had a 3.92-fold higher LUAD risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year LUAD risk at age 50 (0.42%) by age 41, nine years earlier. CONCLUSIONS:Multi-ancestry PRS approaches enhance LUAD risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

CLL and its precursor, monoclonal B-cell lymphocytosis (MBL), are associated with immune deficits. In MBL, the higher percentages of normal B cells (NBC) provide a unique opportunity to study B-cell defects. We compared transcriptomes of NBC from healthy donors (HD) and people with high-count MBL (hcMBL) with mutated (M-MBL) and unmutated (U-MBL) IGHV, and with low-count MBL (lcMBL). We also explored B-cell subset distribution and BCR repertoires. PBMC were collected from 21 hcMBL (12 M-MBL, 9 U-MBL), 7 lcMBL (1 M-MBL, the rest unknown), and 13 HD. 111 sorted B-cell samples were obtained: 21 hcMBL clones (CD20LowCD5+Igκ+/Igλ+), 36 NBC-hcMBL (30 CD20+CD5⁻; 6 CD20+CD5⁺), 12 NBC-lcMBL (CD20+CD5⁻), and 42 NBC-HD (25 CD20+CD5⁻; 17 CD20+CD5⁺). RNA was sequenced using SMART-Seqv4 on HiSeq. Differentially expressed genes (DEG) were analyzed with DESeq2 (Padj<0.05, |FC|≥1.5). Transcriptome variation was assessed by PCA and enriched pathways by IPA. Flow cytometry validated DEG in 6 hcMBL and 8 HD. B-cell subset distribution was analyzed in 14 hcMBL (10 M-MBL, 4 U-MBL) and 9 HD using FACSymphony. BCR repertoire analysis was performed on NBCs of 4 HD, 7 hcMBL (4 M-MBL, 3 U-MBL), and 1 M-lcMBL patient, using the ImmunoRead platform and a custom pipeline built upon the Immcantation framework. Leukemic IGHV-D-J reads were removed. PCA clearly separated NBC-HD, NBC-lcMBL, NBC-hcMBL, and hcMBL clones, forming a gradient with NBC-HD and hcMBL clones at opposite extremes, and NBC-lcMBL samples occupying an intermediate position between NBC-HD and NBC-hcMBL. Within hcMBL, CD5⁺NBC and NBC-U-MBL clustered closer to hcMBL clones. Comparing CD5⁻NBC-M-hcMBL to NBC-HD revealed 8,380 DEG, with most pathways, including B-cell activation (20/21, 95%), inhibited. Mismatch and base-excision repair (MMR, BER), typically found in follicular B-cell responses, were activated. CD5⁻NBC-U-hcMBL vs. NBC-HD exhibited 12,793 DEG and widespread upregulation of activation pathways (23/26, 88%). Comparing CD5-NBC-U-hcMBL and NBC-M-hcMBL revealed fewer DEG (1,316), consistent with the groups being hcMBL, although the former showed activated pathways (cytokine storm, NET, S-phase and cyclophilin signaling, and RIPK1-mediated necrosis), typical for heightened inflammation and extrafollicular responses. Phenotypically, NBC-hcMBL had reduced naïve B cells, and increased memory, ABC and DN B cells compared to NBC-HD (P<0.05). NBC-M-hcMBL exhibited increased DN1 cells (P=0.046), considered switched memory precursors, and expanded switched memory B cells (P=0.008), whereas NBC-U-hcMBL displayed increased unswitched memory B cells (P=0.018). NBC-U-MBL also exhibited higher DN2/3 cells which are precursors to antibody-secreting cells compared to NBC-HD (P=0.003) and NBC-M-hcMBL (P=0.024). BCR analysis of NBCs revealed significant differences (P<0.05) in clonal space occupancy (CSO) among groups. NBC-HD exhibited a polyclonal repertoire with low clonal dominance; expanded clones (0.5-1% CSO) were rare (1.4%) and hyperexpanded clones (>1% CSO) absent. NBC-U-hcMBL showed increased expanded and hyperexpanded clones (5% each). NBC-M-hcMBL had the most restricted repertoire, with 16.3% hyperexpanded clones and the highest SHM rates, significantly surpassing NBC-U-hcMBL and NBC-HD (P<0.001). The sole M-lcMBL case analyzed had a clearly distinct BCR repertoire, with a high proportion of hyperexpanded clones (45% CSO) and unique V gene usage. Altogether, our results demonstrate a global B-cell defect both in lcMBL and hcMBL, being markedly more pronounced in the latter. Nevertheless, the transcriptomic differences (NBC from lcMBL being much closer to HD), together with the different immunogenetic pressures revealed by BCR analysis point toward separate pathogenic drivers in lcMBL and hcMBL. In hcMBL, the transcriptome defects were demonstrated in CD5⁺ and CD5⁻ NBC subsets and in M- and U- MBL patients. NBC from M-hcMBL appear to follow a follicular B-cell maturation pathway (BER and MMR signatures, switched memory and DN1 B cells, and a more restricted and hypermutated BCR repertoire). Conversely, NBC from U-hcMBL show a gene signature of extensive inflammation compatible with extrafollicular maturation, supported by unswitched memory and DN2/3 B-cell subsets and reduced SHM rates. These findings suggest that different antigenic challenges push hcMBL NBCs into separate developmental paths that correlate with IGHV-mutation status. GB was supported by the Lymphoma Research Foundation.

Supplementary Table S7 shows the signals from interaction with smoking status for the identified variants in lung cancer.

Abstract Cigarette smoke, containing both nicotine and carcinogens, causes lung cancer. However, not all smokers develop lung cancer, highlighting the importance of the interaction between host susceptibility and environmental exposure in tumorigenesis. Here, we aimed to delineate the interaction between metabolizing ability of tobacco carcinogens and smoking intensity in mediating genetic susceptibility to smoking-related lung tumorigenesis. Single-variant and gene-based associations of 43 tobacco carcinogen–metabolizing genes with lung cancer were analyzed using summary statistics and individual-level genetic data, followed by causal inference of Mendelian randomization, mediation analysis, and structural equation modeling. Cigarette smoke–exposed cell models were used to detect gene expression patterns in relation to specific alleles. Data from the International Lung Cancer Consortium (29,266 cases and 56,450 controls) and UK Biobank (2,155 cases and 376,329 controls) indicated that the genetic variant rs56113850 C>T located in intron 4 of CYP2A6 was significantly associated with decreased lung cancer risk among smokers (OR = 0.88, 95% confidence interval = 0.85–0.91, P = 2.18 × 10−16), which might interact (Pinteraction = 0.028) with and partially be mediated (ORindirect = 0.987) by smoking status. Smoking intensity accounted for 82.3% of the effect of CYP2A6 activity on lung cancer risk but entirely mediated the genetic effect of rs56113850. Mechanistically, the rs56113850 T allele rescued the downregulation of CYP2A6 caused by cigarette smoke exposure, potentially through preferential recruitment of transcription factor helicase-like transcription factor. Together, this study provides additional insights into the interplay between host susceptibility and carcinogen exposure in smoking-related lung tumorigenesis. Significance: The causal pathway connecting CYP2A6 genetic variability and activity, cigarette consumption, and lung cancer susceptibility in smokers highlights the need for behavior modification interventions based on host susceptibility for cancer prevention.

Supplementary Methods and Figures

Supplementary Table S8 displays the sample size from independent Asian studies.

BACKGROUND:While much research has been done to identify individual workplace lung carcinogens, little is known about joint effects on risk when workers are exposed to multiple agents. OBJECTIVES:We investigated the pairwise joint effects of occupational exposures to asbestos, respirable crystalline silica, metals (i.e., nickel, chromium-VI), and polycyclic aromatic hydrocarbons (PAH) on lung cancer risk, overall and by major histologic subtype, while accounting for cigarette smoking. METHODS:In the international 14-center SYNERGY project, occupational exposures were assigned to 16,901 lung cancer cases and 20,965 control subjects using a quantitative job-exposure matrix (SYN-JEM). Odds ratios (ORs) and 95% confidence intervals (CIs) were computed for ever vs. never exposure using logistic regression models stratified by sex and adjusted for study center, age, and smoking habits. Joint effects among pairs of agents were assessed on multiplicative and additive scales, the latter by calculating the relative excess risk due to interaction (RERI). RESULTS:All pairwise joint effects of lung carcinogens in men were associated with an increased risk of lung cancer. However, asbestos/metals and metals/PAH resulted in less than additive effects; while the chromium-VI/silica pair showed marginally synergistic effect in relation to adenocarcinoma (RERI: 0.24; CI: 0.02, 0.46; p = 0.05). In women, several pairwise joint effects were observed for small cell lung cancer including exposure to PAH/silica (OR = 5.12; CI: 1.77, 8.48), and to asbestos/silica (OR = 4.32; CI: 1.35, 7.29), where exposure to PAH/silica resulted in a synergistic effect (RERI: 3.45; CI: 0.10, 6.8). DISCUSSION:Small or no deviation from additive or multiplicative effects was observed, but co-exposure to the selected lung carcinogens resulted generally in higher risk than exposure to individual agents, highlighting the importance to reduce and control exposure to carcinogens in workplaces and the general environment. https://doi.org/10.1289/EHP13380.

Supplementary Table S1 displays the number of ever- and never-smokers from each of the ten studies.

Supplementary Figure S4 shows the results of eQTL analysis of rs968516 in GTEx.

Supplementary Table S4 shows the imputation quality score of identified variants in different studies.

BACKGROUND Studies of sleep and prostate cancer are almost entirely based on self-report, with limited research using actigraphy. Our goal was to evaluate actigraphy-measured sleep and prostate cancer and to expand on findings from prior studies of self-reported sleep. METHODS We prospectively examined 34 260 men without a history of prostate cancer in the UK Biobank. Sleep characteristics were measured over 7 days using actigraphy. We calculated sleep duration, onset, midpoint, wake-up time, social jetlag (difference in weekend-weekday sleep midpoints), sleep efficiency (percentage of time spent asleep between onset and wake-up time), and wakefulness after sleep onset. Cox proportional hazards models were used to estimate covariate-adjusted hazards ratios (HRs) and 95% confidence intervals (CIs). RESULTS Over 7.6 years, 1152 men were diagnosed with prostate cancer. Sleep duration was not associated with prostate cancer risk. Sleep midpoint earlier than 4:00 am was not associated with prostate cancer risk, though sleep midpoint of 5:00 am or later was suggestively associated with lower prostate cancer risk but had limited precision (earlier than 4:00 am vs 4:00-4:59 am HR = 1.00, 95% CI = 0.87 to 1.16; 5:00 am or later vs 4:00-4:59 am HR = 0.79, 95% CI = 0.57 to 1.10). Social jetlag was not associated with greater prostate cancer risk (1 to <2 hours vs <1 hour HR = 1.06, 95% CI = 0.89 to 1.25; ≥2 hours vs <1 hour HR = 0.90, 95% CI = 0.65 to 1.26). Compared with men who averaged less than 30 minutes of wakefulness after sleep onset per day, men with 60 minutes or more had a higher risk of prostate cancer (HR = 1.20, 95% CI = 1.00 to 1.43). CONCLUSIONS Of the sleep characteristics studied, higher wakefulness after sleep onset-a measure of poor sleep quality-was associated with greater prostate cancer risk. Replication of our findings between wakefulness after sleep onset and prostate cancer are warranted.

Supplementary Table S5 shows the signals for the variants in stratified analysis by smoking behavior

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.

Supplementary Figure S3 displays the Validation of the association effect of rs6757077 at IKZF2 using data from six independent study sites in China.