Novel Transcriptional and DNA Methylation Abnormalities of SORT1 Gene in Non-Small Cell Lung Cancer.

Sortilin is an important regulator with potential tumour-suppressor function by limiting EGFR signalling. In this study, we undertook a comprehensive expression analysis of sortilin transcript variants and the DNA methylation status of their corresponding promoters in human non-small cell carcinomas (NSCLCs). RNA/DNA was extracted from 81 NSCLC samples and paired normal tissue. mRNA expression was measured by qPCR and DNA methylation determined by pyrosequencing. BigDye-terminator sequencing was used to confirm exon-8 alternative splicing. Results demonstrated that both SORT1A and SORT1B variants were downregulated in lung tumours. The SORT1A/SORT1B expression ratio was higher in tumours compared to normal tissue. SORT1B promoter hypermethylation was detected in lung tumours compared to normal lung (median difference 14%, Mann-Whitney test p = 10-6). Interestingly, SORT1B is hypermethylated in white blood cells, but a small and very consistent drop in methylation (6%, p = 10-15) was observed in the lung cancer cases compared to control subjects. We demonstrate that the SORT1B exon-8 splice variation, reported in sequence databases, is also a feature of SORT1A. The significantly altered quantitative and qualitative characteristics of sortilin mRNA in NSCLC indicate a significant involvement in tumour pathogenesis and may have significant impact for its utility as a predictive marker in lung cancer management.

Impact of single round of low dose CT lung cancer screening on cause of mortality in different socio-economic groups: a post-hoc analysis of long-term follow-up of the UKLS trial.

Background: Lower socioeconomic status, as measured by the Index of Multiple Deprivation (IMD), is associated with higher rates of smoking-related disease mortality, and with poor uptake of cancer screening. Here we explore whether socioeconomic status impacts the effectiveness of a single round of low-dose-CT screening, or impacts other causes of death, in the UKLS LDCT screening trial. Methods: IMD quintiles were defined according to UK-wide data, with the deprived group defined as the lower two quintiles (Q1-2) and the less deprived as Q3-5. Follow-up data was obtained for lung cancer diagnosis (median follow-up 9.1 years) and cause of death (median follow-up 9.9 years). Outcomes were compared based on IMD group and trial arm (CT or control). Findings: More deprived quintiles were less likely to respond to the questionnaire, but this population was more likely to be selected for screening by the LLP risk model. Lower IMD quintiles benefitted from low-dose-CT screening in terms of lung cancer survival (HR 1.89, 95% CI 1.16-3.08) to the same extent as upper quintiles (HR 1.87, 95% CI 1.07-3.26). However, there was a bigger impact on deaths due to COPD and emphysema in more deprived quintiles. Interpretation: Whilst LDCT screening benefit for lung cancer was similar, significant impact on the rates of death from other smoking-related diseases, notably COPD and emphysema, was seen primarily in lower socioeconomic groups. Future research is required to confirm how lung cancer screening benefits other disease outcomes. Funding: NIHR Health Technology Assessment Programme; NIHR Policy Research programme; Roy Castle Lung Cancer Foundation.

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.

Prevalent occupational exposures and risk of lung cancer among women: Results from the application of the Canadian Job-Exposure Matrix (CANJEM) to a combined set of ten case-control studies.

BACKGROUND: Worldwide, lung cancer is the second leading cause of cancer death in women. The present study explored associations between occupational exposures that are prevalent among women, and lung cancer. METHODS: Data from 10 case-control studies of lung cancer from Europe, Canada, and New Zealand conducted between 1988 and 2008 were combined. Lifetime occupational history and information on nonoccupational factors including smoking were available for 3040 incident lung cancer cases and 4187 controls. We linked each reported job to the Canadian Job-Exposure Matrix (CANJEM), which provided estimates of probability, intensity, and frequency of exposure to each selected agent in each job. For this analysis, we selected 15 agents (cleaning agents, biocides, cotton dust, synthetic fibers, formaldehyde, cooking fumes, organic solvents, cellulose, polycyclic aromatic hydrocarbons from petroleum, ammonia, metallic dust, alkanes C18+, iron compounds, isopropanol, and calcium carbonate) that had lifetime exposure prevalence of at least 5% in the combined study population. For each agent, we estimated lung cancer risk in each study center for ever-exposure, by duration of exposure, and by cumulative exposure, using separate logistic regression models adjusted for smoking and other covariates. We then estimated the meta-odds ratios using random-effects meta-analysis. RESULTS AND CONCLUSIONS: None of the agents assessed showed consistent and compelling associations with lung cancer among women. The following agents showed elevated odds ratio in some analyses: metallic dust, iron compounds, isopropanol, and organic solvents. Future research into occupational lung cancer risk factors among women should prioritize these agents.

Lung Cancer Risks Associated with Occupational Exposure to Pairs of Five Lung Carcinogens: Results from a Pooled Analysis of Case-Control Studies (SYNERGY).

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.

Respirable crystalline silica and lung cancer in community-based studies: impact of job-exposure matrix specifications on exposure-response relationships.

OBJECTIVES: The quantitative job-exposure matrix SYN-JEM consists of various dimensions: job-specific estimates, region-specific estimates, and prior expert ratings of jobs by the semi-quantitative DOM-JEM. We analyzed the effect of different JEM dimensions on the exposure-response relationships between occupational silica exposure and lung cancer risk to investigate how these variations influence estimates of exposure by a quantitative JEM and associated health endpoints. METHODS: Using SYN-JEM, and alternative SYN-JEM specifications with varying dimensions included, cumulative silica exposure estimates were assigned to 16 901 lung cancer cases and 20 965 controls pooled from 14 international community-based case-control studies. Exposure-response relationships based on SYN-JEM and alternative SYN-JEM specifications were analyzed using regression analyses (by quartiles and log-transformed continuous silica exposure) and generalized additive models (GAM), adjusted for age, sex, study, cigarette pack-years, time since quitting smoking, and ever employment in occupations with established lung cancer risk. RESULTS: SYN-JEM and alternative specifications generated overall elevated and similar lung cancer odds ratios ranging from 1.13 (1st quartile) to 1.50 (4th quartile). In the categorical and log-linear analyses SYN-JEM with all dimensions included yielded the best model fit, and exclusion of job-specific estimates from SYN-JEM yielded the poorest model fit. Additionally, GAM showed the poorest model fit when excluding job-specific estimates. CONCLUSION: The established exposure-response relationship between occupational silica exposure and lung cancer was marginally influenced by varying the dimensions of SYN-JEM. Optimized modelling of exposure-response relationships will be obtained when incorporating all relevant dimensions, namely prior rating, job, time, and region. Quantitative job-specific estimates appeared to be the most prominent dimension for this general population JEM.

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

BACKGROUND: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. METHODS: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. RESULTS: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. CONCLUSIONS: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. IMPACT: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

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

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

Occupational Benzene Exposure and Lung Cancer Risk: A Pooled Analysis of 14 Case-Control Studies.

Rationale: Benzene has been classified as carcinogenic to humans, but there is limited evidence linking benzene exposure to lung cancer. Objectives: We aimed to examine the relationship between occupational benzene exposure and lung cancer. Methods: Subjects from 14 case-control studies across Europe and Canada were pooled. We used a quantitative job-exposure matrix to estimate benzene exposure. Logistic regression models assessed lung cancer risk across different exposure indices. We adjusted for smoking and five main occupational lung carcinogens and stratified analyses by smoking status and lung cancer subtypes. Measurements and Main Results: Analyses included 28,048 subjects (12,329 cases, 15,719 control subjects). Lung cancer odds ratios ranged from 1.12 (95% confidence interval, 1.03-1.22) to 1.32 (95% confidence interval, 1.18-1.48) (Ptrend = 0.002) for groups with the lowest and highest cumulative occupational exposures, respectively, compared with unexposed subjects. We observed an increasing trend of lung cancer with longer duration of exposure (Ptrend < 0.001) and a decreasing trend with longer time since last exposure (Ptrend = 0.02). These effects were seen for all lung cancer subtypes, regardless of smoking status, and were not influenced by specific occupational groups, exposures, or studies. Conclusions: We found consistent and robust associations between different dimensions of occupational benzene exposure and lung cancer after adjusting for smoking and main occupational lung carcinogens. These associations were observed across different subgroups, including nonsmokers. Our findings support the hypothesis that occupational benzene exposure increases the risk of developing lung cancer. Consequently, there is a need to revisit published epidemiological and molecular data on the pulmonary carcinogenicity of benzene.

The International Association for the Study of Lung Cancer Early Lung Imaging Confederation Open-Source Deep Learning and Quantitative Measurement Initiative.

INTRODUCTION: With global adoption of computed tomography (CT) lung cancer screening, there is increasing interest to use artificial intelligence (AI) deep learning methods to improve the clinical management process. To enable AI research using an open-source, cloud-based, globally distributed, screening CT imaging data set and computational environment that are compliant with the most stringent international privacy regulations that also protect the intellectual properties of researchers, the International Association for the Study of Lung Cancer sponsored development of the Early Lung Imaging Confederation (ELIC) resource in 2018. The objective of this report is to describe the updated capabilities of ELIC and illustrate how this resource can be used for clinically relevant AI research. METHODS: In this second phase of the initiative, metadata and screening CT scans from two time points were collected from 100 screening participants in seven countries. An automated deep learning AI lung segmentation algorithm, automated quantitative emphysema metrics, and a quantitative lung nodule volume measurement algorithm were run on these scans. RESULTS: A total of 1394 CTs were collected from 697 participants. The LAV950 quantitative emphysema metric was found to be potentially useful in distinguishing lung cancer from benign cases using a combined slice thickness more than or equal to 2.5 mm. Lung nodule volume change measurements had better sensitivity and specificity for classifying malignant from benign lung nodules when applied to solid lung nodules from high-quality CT scans. CONCLUSIONS: These initial experiments revealed that ELIC can support deep learning AI and quantitative imaging analyses on diverse and globally distributed cloud-based data sets.

CYP2A6 Activity and Cigarette Consumption Interact in Smoking-Related Lung Cancer Susceptibility.

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.

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.

Association between duration of smoking abstinence before non-small-cell lung cancer diagnosis and survival: a retrospective, pooled analysis of cohort studies.

BACKGROUND: The association between duration of smoking abstinence before non-small-cell lung cancer (NSCLC) diagnosis and subsequent survival can influence public health messaging delivered in lung-cancer screening. We aimed to assess whether the duration of smoking abstinence before diagnosis of NSCLC is associated with improved survival. METHODS: In this retrospective, pooled analysis of cohort studies, we used 26 cohorts participating in Clinical Outcomes Studies of the International Lung Cancer Consortium (COS-ILCCO) at 23 hospitals. 16 (62%) were from North America, six (23%) were from Europe, three (12%) were from Asia, and one (4%) was from South America. Patients enrolled were diagnosed between June 1, 1983, and Dec 31, 2019. Eligible patients had smoking data before NSCLC diagnosis, epidemiological data at diagnosis (obtained largely from patient questionnaires), and clinical information (retrieved from medical records). Kaplan-Meier curves and multivariable Cox models (ie, adjusted hazard ratios [aHRs]) were generated with individual, harmonised patient data from the consortium database. We estimated overall survival for all causes, measured in years from diagnosis date until the date of the last follow-up or death due to any cause and NSCLC-specific survival. FINDINGS: Of 42 087 patients with NSCLC in the COS-ILCCO database, 21 893 (52·0%) of whom were male and 20 194 (48·0%) of whom were female, we excluded 4474 (10·6%) with missing data. Compared with current smokers (15 036 [40·0%] of 37 613), patients with 1-3 years of smoking abstinence before NSCLC diagnosis (2890 [7·7%]) had an overall survival aHR of 0·92 (95% CI 0·87-0·97), patients with 3-5 years of smoking abstinence (1114 [3·0%]) had an overall survival aHR of 0·90 (0·83-0·97), and patients with more than 5 years of smoking abstinence (10 841 [28·8%]) had an overall survival aHR of 0·90 (0·87-0·93). Improved NSCLC-specific survival was observed in 4301 (44%) of 9727 patients who had quit cigarette smoking and was significant at abstinence durations of more than 5 years (aHR 0·87, 95% CI 0·81-0·93). Results were consistent across age, sex, histology, and disease-stage distributions. INTERPRETATION: In this large, pooled analysis of cohort studies across Asia, Europe, North America, and South America, overall survival was improved in patients with NSCLC whose duration of smoking abstinence before diagnosis was as short as 1 year. These findings suggest that quitting smoking can improve overall survival, even if NSCLC is diagnosed at a later lung-cancer screening visit. These findings also support the implementation of public health smoking cessation strategies at any time. FUNDING: The Alan B Brown Chair, The Posluns Family Fund, The Lusi Wong Fund, and the Princess Margaret Cancer Foundation.

Candidate pathway analysis of surfactant proteins identifies CTSH and SFTA2 that influences lung cancer risk.

Pulmonary surfactant is a lipoprotein synthesized and secreted by alveolar type II cells in lung. We evaluated the associations between 200,139 single nucleotide polymorphisms (SNPs) of 40 surfactant-related genes and lung cancer risk using genotyped data from two independent lung cancer genome-wide association studies. Discovery data included 18,082 cases and 13,780 controls of European ancestry. Replication data included 1,914 cases and 3,065 controls of European descent. Using multivariate logistic regression, we found novel SNPs in surfactant-related genes CTSH [rs34577742 C > T, odds ratio (OR) = 0.90, 95% confidence interval (CI) = 0.89-0.93, P = 7.64 × 10-9] and SFTA2 (rs3095153 G > A, OR = 1.16, 95% CI = 1.10-1.21, P = 1.27 × 10-9) associated with overall lung cancer in the discovery data and validated in an independent replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.80-0.96, P = 5.76 × 10-3) and SFTA2 (rs3095153 G > A, OR = 1.14, 95% CI = 1.01-1.28, P = 3.25 × 10-2). Among ever smokers, we found SNPs in CTSH (rs34577742 C > T, OR = 0.89, 95% CI = 0.85-0.92, P = 1.94 × 10-7) and SFTA2 (rs3095152 G > A, OR = 1.20, 95% CI = 1.14-1.27, P = 4.25 × 10-11) associated with overall lung cancer in the discovery data and validated in the replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.79-0.97, P = 1.64 × 10-2) and SFTA2 (rs3095152 G > A, OR = 1.15, 95% CI = 1.01-1.30, P = 3.81 × 10-2). Subsequent transcriptome-wide association study using expression weights from a lung expression quantitative trait loci study revealed genes most strongly associated with lung cancer are CTSH (PTWAS = 2.44 × 10-4) and SFTA2 (PTWAS = 2.32 × 10-6).

Plasma protein biomarkers for early prediction of lung cancer.

BACKGROUND: Individual plasma proteins have been identified as minimally invasive biomarkers for lung cancer diagnosis with potential utility in early detection. Plasma proteomes provide insight into contributing biological factors; we investigated their potential for future lung cancer prediction. METHODS: The Olink® Explore-3072 platform quantitated 2941 proteins in 496 Liverpool Lung Project plasma samples, including 131 cases taken 1-10 years prior to diagnosis, 237 controls, and 90 subjects at multiple times. 1112 proteins significantly associated with haemolysis were excluded. Feature selection with bootstrapping identified differentially expressed proteins, subsequently modelled for lung cancer prediction and validated in UK Biobank data. FINDINGS: For samples 1-3 years pre-diagnosis, 240 proteins were significantly different in cases; for 1-5 year samples, 117 of these and 150 further proteins were identified, mapping to significantly different pathways. Four machine learning algorithms gave median AUCs of 0.76-0.90 and 0.73-0.83 for the 1-3 year and 1-5 year proteins respectively. External validation gave AUCs of 0.75 (1-3 year) and 0.69 (1-5 year), with AUC 0.7 up to 12 years prior to diagnosis. The models were independent of age, smoking duration, cancer histology and the presence of COPD. INTERPRETATION: The plasma proteome provides biomarkers which may be used to identify those at greatest risk of lung cancer. The proteins and the pathways are different when lung cancer is more imminent, indicating that both biomarkers of inherent risk and biomarkers associated with presence of early lung cancer may be identified. FUNDING: Janssen Pharmaceuticals Research Collaboration Award; Roy Castle Lung Cancer Foundation.

Circulating proteome for pulmonary nodule malignancy.

BACKGROUND: Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules. METHODS: Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated. RESULTS: We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001). CONCLUSIONS: Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.

Defining the road map to a UK national lung cancer screening programme.

Lung cancer screening with low-dose CT was recommended by the UK National Screening Committee (UKNSC) in September, 2022, on the basis of data from trials showing a reduction in lung cancer mortality. These trials provide sufficient evidence to show clinical efficacy, but further work is needed to prove deliverability in preparation for a national roll-out of the first major targeted screening programme. The UK has been world leading in addressing logistical issues with lung cancer screening through clinical trials, implementation pilots, and the National Health Service (NHS) England Targeted Lung Health Check Programme. In this Policy Review, we describe the consensus reached by a multiprofessional group of experts in lung cancer screening on the key requirements and priorities for effective implementation of a programme. We summarise the output from a round-table meeting of clinicians, behavioural scientists, stakeholder organisations, and representatives from NHS England, the UKNSC, and the four UK nations. This Policy Review will be an important tool in the ongoing expansion and evolution of an already successful programme, and provides a summary of UK expert opinion for consideration by those organising and delivering lung cancer screenings in other countries.

Mosaic Chromosomal Alterations Are Associated With Increased Lung Cancer Risk: Insight From the INTEGRAL-ILCCO Cohort Analysis.

INTRODUCTION: Mosaic chromosomal alterations (mCAs) detected in white blood cells represent a type of clonal hematopoiesis (CH) that is understudied compared with CH-related somatic mutations. A few recent studies indicated their potential link with nonhematological cancers, especially lung cancer. METHODS: In this study, we investigated the association between mCAs and lung cancer using the high-density genotyping data from the OncoArray study of INTEGRAL-ILCCO, the largest single genetic study of lung cancer with 18,221 lung cancer cases and 14,825 cancer-free controls. RESULTS: We identified a comprehensive list of autosomal mCAs, ChrX mCAs, and mosaic ChrY (mChrY) losses from these samples. Autosomal mCAs were detected in 4.3% of subjects, in addition to ChrX mCAs in 3.6% of females and mChrY losses in 9.6% of males. Multivariable logistic regression analysis indicated that the presence of autosomal mCAs in white blood cells was associated with an increased lung cancer risk after adjusting for key confounding factors, including age, sex, smoking status, and race. This association was mainly driven by a specific type of mCAs: copy-neutral loss of heterozygosity on autosomal chromosomes. The association between autosome copy-neutral loss of heterozygosity and increased risk of lung cancer was further confirmed in two major histologic subtypes, lung adenocarcinoma and squamous cell carcinoma. In addition, we observed a significant increase of ChrX mCAs and mChrY losses in smokers compared with nonsmokers and racial differences in certain types of mCA events. CONCLUSIONS: Our study established a link between mCAs in white blood cells and increased risk of lung cancer.

Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program.

The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smoking and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project measured 1078 proteins among participants with a heavy smoking history within four LDCT screening studies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.