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

Recent genome-wide association studies (GWASs) have identified common genetic variants at 5p15.33, 6p21-6p22 and 15q25.1 associated with lung cancer risk. Several other genetic regions including variants of CHEK2 (22q12), TP53BP1 (15q15) and RAD52 (12p13) have been demonstrated to influence lung cancer risk in candidate- or pathway-based analyses. To identify novel risk variants for lung cancer, we performed a meta-analysis of 16 GWASs, totaling 14 900 cases and 29 485 controls of European descent. Our data provided increased support for previously identified risk loci at 5p15 (P = 7.2 × 10(-16)), 6p21 (P = 2.3 × 10(-14)) and 15q25 (P = 2.2 × 10(-63)). Furthermore, we demonstrated histology-specific effects for 5p15, 6p21 and 12p13 loci but not for the 15q25 region. Subgroup analysis also identified a novel disease locus for squamous cell carcinoma at 9p21 (CDKN2A/p16(INK4A)/p14(ARF)/CDKN2B/p15(INK4B)/ANRIL; rs1333040, P = 3.0 × 10(-7)) which was replicated in a series of 5415 Han Chinese (P = 0.03; combined analysis, P = 2.3 × 10(-8)). This large analysis provides additional evidence for the role of inherited genetic susceptibility to lung cancer and insight into biological differences in the development of the different histological types of lung cancer.

Predictive accuracy of the Liverpool Lung Project risk model for stratifying patients for computed tomography screening for lung cancer: a case-control and cohort validation study

BACKGROUND

External validation of existing lung cancer risk prediction models is limited. Using such models in clinical practice to guide the referral of patients for computed tomography (CT) screening for lung cancer depends on external validation and evidence of predicted clinical benefit.

OBJECTIVE

To evaluate the discrimination of the Liverpool Lung Project (LLP) risk model and demonstrate its predicted benefit for stratifying patients for CT screening by using data from 3 independent studies from Europe and North America.

DESIGN

Case-control and prospective cohort study.

SETTING

Europe and North America.

PATIENTS

Participants in the European Early Lung Cancer (EUELC) and Harvard case-control studies and the LLP population-based prospective cohort (LLPC) study.

MEASUREMENTS

5-year absolute risks for lung cancer predicted by the LLP model.

RESULTS

The LLP risk model had good discrimination in both the Harvard (area under the receiver-operating characteristic curve [AUC], 0.76 [95% CI, 0.75 to 0.78]) and the LLPC (AUC, 0.82 [CI, 0.80 to 0.85]) studies and modest discrimination in the EUELC (AUC, 0.67 [CI, 0.64 to 0.69]) study. The decision utility analysis, which incorporates the harms and benefit of using a risk model to make clinical decisions, indicates that the LLP risk model performed better than smoking duration or family history alone in stratifying high-risk patients for lung cancer CT screening.

LIMITATIONS

The model cannot assess whether including other risk factors, such as lung function or genetic markers, would improve accuracy. Lack of information on asbestos exposure in the LLPC limited the ability to validate the complete LLP risk model.

CONCLUSION

Validation of the LLP risk model in 3 independent external data sets demonstrated good discrimination and evidence of predicted benefits for stratifying patients for lung cancer CT screening. Further studies are needed to prospectively evaluate model performance and evaluate the optimal population risk thresholds for initiating lung cancer screening.

SHOX2 DNA methylation is a biomarker for the diagnosis of lung cancer based on bronchial aspirates

BACKGROUND

This study aimed to show that SHOX2 DNA methylation is a tumor marker in patients with suspected lung cancer by using bronchial fluid aspirated during bronchoscopy. Such a biomarker would be clinically valuable, especially when, following the first bronchoscopy, a final diagnosis cannot be established by histology or cytology. A test with a low false positive rate can reduce the need for further invasive and costly procedures and ensure early treatment.

METHODS

Marker discovery was carried out by differential methylation hybridization (DMH) and real-time PCR. The real-time PCR based HeavyMethyl technology was used for quantitative analysis of DNA methylation of SHOX2 using bronchial aspirates from two clinical centres in a case-control study. Fresh-frozen and Saccomanno-fixed samples were used to show the tumor marker performance in different sample types of clinical relevance.

RESULTS

Valid measurements were obtained from a total of 523 patient samples (242 controls, 281 cases). DNA methylation of SHOX2 allowed to distinguish between malignant and benign lung disease, i.e. abscesses, infections, obstructive lung diseases, sarcoidosis, scleroderma, stenoses, at high specificity (68% sensitivity [95% CI 62-73%], 95% specificity [95% CI 91-97%]).

CONCLUSIONS

Hypermethylation of SHOX2 in bronchial aspirates appears to be a clinically useful tumor marker for identifying subjects with lung carcinoma, especially if histological and cytological findings after bronchoscopy are ambiguous.

Previous lung diseases and lung cancer risk: a pooled analysis from the International Lung Cancer Consortium

To clarify the role of previous lung diseases (chronic bronchitis, emphysema, pneumonia, and tuberculosis) in the development of lung cancer, the authors conducted a pooled analysis of studies in the International Lung Cancer Consortium. Seventeen studies including 24,607 cases and 81,829 controls (noncases), mainly conducted in Europe and North America, were included (1984-2011). Using self-reported data on previous diagnoses of lung diseases, the authors derived study-specific effect estimates by means of logistic regression models or Cox proportional hazards models adjusted for age, sex, and cumulative tobacco smoking. Estimates were pooled using random-effects models. Analyses stratified by smoking status and histology were also conducted. A history of emphysema conferred a 2.44-fold increased risk of lung cancer (95% confidence interval (CI): 1.64, 3.62 (16 studies)). A history of chronic bronchitis conferred a relative risk of 1.47 (95% CI: 1.29, 1.68 (13 studies)). Tuberculosis (relative risk = 1.48, 95% CI: 1.17, 1.87 (16 studies)) and pneumonia (relative risk = 1.57, 95% CI: 1.22, 2.01 (12 studies)) were also associated with lung cancer risk. Among never smokers, elevated risks were observed for emphysema, pneumonia, and tuberculosis. These results suggest that previous lung diseases influence lung cancer risk independently of tobacco use and that these diseases are important for assessing individual risk.

Increased risk of lung cancer in individuals with a family history of the disease: a pooled analysis from the International Lung Cancer Consortium

BACKGROUND AND METHODS

Familial aggregation of lung cancer exists after accounting for cigarette smoking. However, the extent to which family history affects risk by smoking status, histology, relative type and ethnicity is not well described. This pooled analysis included 24 case-control studies in the International Lung Cancer Consortium. Each study collected age of onset/interview, gender, race/ethnicity, cigarette smoking, histology and first-degree family history of lung cancer. Data from 24,380 lung cancer cases and 23,305 healthy controls were analysed. Unconditional logistic regression models and generalised estimating equations were used to estimate odds ratios and 95% confidence intervals.

RESULTS

Individuals with a first-degree relative with lung cancer had a 1.51-fold increase in the risk of lung cancer, after adjustment for smoking and other potential confounders (95% CI: 1.39, 1.63). The association was strongest for those with a family history in a sibling, after adjustment (odds ratios (OR) = 1.82, 95% CI: 1.62, 2.05). No modifying effect by histologic type was found. Never smokers showed a lower association with positive familial history of lung cancer (OR = 1.25, 95% CI: 1.03, 1.52), slightly stronger for those with an affected sibling (OR = 1.44, 95% CI: 1.07, 1.93), after adjustment.

CONCLUSIONS

The occurrence of lung cancer among never smokers and similar magnitudes of the effect of family history on lung cancer risk across histological types suggests familial aggregation of lung cancer is independent of those risks associated with cigarette smoking. While the role of genetic variation in the aetiology of lung cancer remains to be fully characterised, family history assessment is immediately available and those with a positive history represent a higher risk group.

DNA methylation biomarkers offer improved diagnostic efficiency in lung cancer

The exceptional high mortality of lung cancer can be instigated to a high degree by late diagnosis. Despite the plethora of studies on potential molecular biomarkers for lung cancer diagnosis, very few have reached clinical implementation. In this study, we developed a panel of DNA methylation biomarkers and validated their diagnostic efficiency in bronchial washings from a large retrospective cohort. Candidate targets from previous high-throughput approaches were examined by pyrosequencing in an independent set of 48 lung tumor/normal paired. Ten promoters were selected and quantitative methylation-specific PCR (qMSP) assays were developed and used to screen 655 bronchial washings from the Liverpool Lung Project (LLP) subjects divided into training (194 cases and 214 controls) and validation (139 cases and 109 controls) sets. Three statistical models were used to select the optimal panel of markers and to evaluate the performance of the discriminatory algorithms. The final logit regression model incorporated hypermethylation at p16, TERT, WT1, and RASSF1. The performance of this 4-gene methylation signature in the validation set showed 82% sensitivity and 91% specificity. In comparison, cytology alone in this set provided 43% sensitivity at 100% specificity. The diagnostic efficiency of the panel did not show any biases with age, gender, smoking, and the presence of a nonlung neoplasm. However, sensitivity was predictably higher in central (squamous and small cell) than peripheral (adenocarcinomas) tumors, as well as in stage 2 or greater tumors. These findings clearly show the impact of DNA methylation-based assays in the diagnosis of cytologically occult lung neoplasms. A prospective trial is currently imminent in the LLP study to provide data on the enhancement of diagnostic accuracy in a clinical setting, including by additional markers.

Identification and validation of an anthracycline/cyclophosphamide-based chemotherapy response assay in breast cancer

Background

There is no method routinely used to predict response to anthracycline and cyclophosphamide–based chemotherapy in the clinic; therefore patients often receive treatment for breast cancer with no benefit. Loss of the Fanconi anemia/BRCA (FA/BRCA) DNA damage response (DDR) pathway occurs in approximately 25% of breast cancer patients through several mechanisms and results in sensitization to DNA-damaging agents. The aim of this study was to develop an assay to detect DDR-deficient tumors associated with loss of the FA/BRCA pathway, for the purpose of treatment selection.

Methods

DNA microarray data from 21 FA patients and 11 control subjects were analyzed to identify genetic processes associated with a deficiency in DDR. Unsupervised hierarchical clustering was then performed using 60 BRCA1/2 mutant and 47 sporadic tumor samples, and a molecular subgroup was identified that was defined by the molecular processes represented within FA patients. A 44-gene microarray-based assay (the DDR deficiency assay) was developed to prospectively identify this subgroup from formalin-fixed, paraffin-embedded samples. All statistical tests were two-sided.

Results

In a publicly available independent cohort of 203 patients, the assay predicted complete pathologic response vs residual disease after neoadjuvant DNA-damaging chemotherapy (5-fluorouracil, anthracycline, and cyclophosphamide) with an odds ratio of 3.96 (95% confidence interval [Cl] =1.67 to 9.41; P = .002). In a new independent cohort of 191 breast cancer patients treated with adjuvant 5-fluorouracil, epirubicin, and cyclophosphamide, a positive assay result predicted 5-year relapse-free survival with a hazard ratio of 0.37 (95% Cl = 0.15 to 0.88; P = .03) compared with the assay negative population.

Conclusions

A formalin-fixed, paraffin-embedded tissue-based assay has been developed and independently validated as a predictor of response and prognosis after anthracycline/cyclophosphamide–based chemotherapy in the neoadjuvant and adjuvant settings. These findings warrant further validation in a prospective clinical study.

Asthma and lung cancer risk: a systematic investigation by the International Lung Cancer Consortium

Asthma has been hypothesized to be associated with lung cancer (LC) risk. We conducted a pooled analysis of 16 studies in the International Lung Cancer Consortium (ILCCO) to quantitatively assess this association and compared the results with 36 previously published studies. In total, information from 585 444 individuals was used. Study-specific measures were combined using random effects models. A meta-regression and subgroup meta-analyses were performed to identify sources of heterogeneity. The overall LC relative risk (RR) associated with asthma was 1.28 [95% confidence intervals (CIs) = 1.16-1.41] but with large heterogeneity (I(2) = 73%, P < 0.001) between studies. Among ILCCO studies, an increased risk was found for squamous cell (RR = 1.69, 95%, CI = 1.26-2.26) and for small-cell carcinoma (RR = 1.71, 95% CI = 0.99-2.95) but was weaker for adenocarcinoma (RR = 1.09, 95% CI = 0.88-1.36). The increased LC risk was strongest in the 2 years after asthma diagnosis (RR = 2.13, 95% CI = 1.09-4.17) but subjects diagnosed with asthma over 10 years prior had no or little increased LC risk (RR = 1.10, 95% CI = 0.94-1.30). Because the increased incidence of LC was chiefly observed in small cell and squamous cell lung carcinomas, primarily within 2 years of asthma diagnosis and because the association was weak among never smokers, we conclude that the association may not reflect a causal effect of asthma on the risk of LC.

LLPi: Liverpool Lung Project Risk Prediction Model for Lung Cancer Incidence

Identification of high-risk individuals will facilitate early diagnosis, reduce overall costs, and also improve the current poor survival from lung cancer. The Liverpool Lung Project prospective cohort of 8,760 participants ages 45 to 79 years, recruited between 1998 and 2008, was followed annually through the hospital episode statistics until January 31, 2013. Cox proportional hazards models were used to identify risk predictors of lung cancer incidence. C-statistic was used to assess the discriminatory accuracy of the models. Models were internally validated using the bootstrap method. During mean follow-up of 8.7 years, 237 participants developed lung cancer. Age [hazard ratio (HR), 1.04; 95% confidence interval (CI), 1.02-1.06], male gender (HR, 1.48; 95% CI, 1.10-1.98), smoking duration (HR, 1.04; 95% CI, 1.03-1.05), chronic obstructive pulmonary disease (HR, 2.43; 95% CI, 1.79-3.30), prior diagnosis of malignant tumor (HR, 2.84; 95% CI, 2.08-3.89), and early onset of family history of lung cancer (HR, 1.68; 95% CI, 1.04-2.72) were associated with the incidence of lung cancer. The LLPi risk model had a good calibration (goodness-of-fit χ(2) 7.58, P = 0.371). The apparent C-statistic was 0.852 (95% CI, 0.831-0.873) and the optimism-corrected bootstrap resampling C-statistic was 0.849 (95% CI, 0.829-0.873). The LLPi risk model may assist in identifying individuals at high risk of developing lung cancer in population-based screening programs.

Performance evaluation of the DNA methylation biomarker SHOX2 for the aid in diagnosis of lung cancer based on the analysis of bronchial aspirates

In the identification of subjects with lung cancer, increased DNA methylation of the SHOX2 gene locus in bronchial aspirates has previously been proven to be a clinically valuable biomarker. This is particularly true in cases where the cytological and histological results following bronchoscopy are undetermined. This previous case control study was conducted using research assay components and a complex work flow. To facilitate the use in a diagnostic setting, a CE marked in vitro diagnostic test kit to quantify SHOX2 DNA methylation in bronchial aspirates was developed and characterized. The presented assay for measuring SHOX2 DNA methylation in bronchial aspirates is based on two major steps: generation of bisulfite converted template DNA from patient samples followed by subsequent determination of SHOX2 biomarker methylation by real-time PCR. Individual kits for DNA preparation, real-time PCR analysis and work flow control were developed. This study describes the analytical performance (reproducibility, accuracy, interfering substances, cross-reactivity) of the in vitro diagnostic (IVD) test kit 'Epi proLung BL Reflex Assay'. In addition, the intended use of the test was validated in a clinical performance evaluation (case control) study comprised of 250 patients (125 cases, 125 controls). The results describe the test as a robust and reliable diagnostic tool for identifying patients with lung cancer using Saccomanno-fixed bronchial lavage specimens (AUC [95% confidence intervals] = 0.94 [0.91-0.98], sensitivity 78% [69-86]/specificity 96% [90-99]). This test may be used as a diagnostic adjunct to existing clinical and pathological investigations in lung cancer.

Comparison of discriminatory power and accuracy of three lung cancer risk models

Background:

Three lung cancer (LC) models have recently been constructed to predict an individual's absolute risk of LC within a defined period. Given their potential application in prevention strategies, a comparison of their accuracy in an independent population is important.

Methods:

We used data for 3197 patients with LC and 1703 cancer-free controls recruited to an ongoing case–control study at the Harvard School of Public Health and Massachusetts General Hospital. We estimated the 5-year LC risk for each risk model and compared the discriminatory power, accuracy, and clinical utility of these models.

Results:

Overall, the Liverpool Lung Project (LLP) and Spitz models had comparable discriminatory power (0.69), whereas the Bach model had significantly lower power (0.66; P=0.02). Positive predictive values were highest with the Spitz models, whereas negative predictive values were highest with the LLP model. The Spitz and Bach models had lower sensitivity but better specificity than did the LLP model.

Conclusion:

We observed modest differences in discriminatory power among the three LC risk models, but discriminatory powers were moderate at best, highlighting the difficulty in developing effective risk models.

Incorporation of a genetic factor into an epidemiologic model for prediction of individual risk of lung cancer: the Liverpool Lung Project

The Liverpool Lung Project (LLP) has previously developed a risk model for prediction of 5-year absolute risk of lung cancer based on five epidemiologic risk factors. SEZ6L, a Met430IIe polymorphic variant found on 22q12.2 region, has been previously linked with an increased risk of lung cancer in a case-control population. In this article, we quantify the improvement in risk prediction with addition of SEZ6L to the LLP risk model. Data from 388 LLP subjects genotyped for SEZ6L single-nucleotide polymorphism (SNP) were combined with epidemiologic risk factors. Multivariable conditional logistic regression was used to predict 5-year absolute risk of lung cancer with and without this SNP. The improvement in the model associated with the SEZ6L SNP was assessed through pairwise comparison of the area under the receiver operating characteristic curve and the net reclassification improvements (NRI). The extended model showed better calibration compared with the baseline model. There was a statistically significant modest increase in the area under the receiver operating characteristic curve when SEZ6L was added into the baseline model. The NRI also revealed a statistically significant improvement of around 12% for the extended model; this improvement was better for subjects classified into the two intermediate-risk categories by the baseline model (NRI, 27%). Our results suggest that the addition of SEZ6L improved the performance of the LLP risk model, particularly for subjects whose initial absolute risks were unable to discriminate into "low-risk" or "high-risk" group. This work shows an approach to incorporate genetic biomarkers in risk models for predicting an individual's lung cancer risk.

Associations between genes for killer immunoglobulin-like receptors and their ligands in patients with solid tumors

Killer immunoglobulin-like receptor (KIR) and human leukocyte antigen (HLA) genotypes were analyzed from panels of lung (non-small-cell lung cancer [NSCLC] and small-cell lung cancer [SCLC]), colon, and kidney cancer patients and compared with normal control subjects. No significant differences were noted between KIR gene frequencies in patients compared with normal subjects. When combinations of KIR genes and their HLA ligands were considered, there were significant decreases in frequencies of both KIR2DL2 and KIR2DL3 in homozygotes for their ligand HLA-C1, and an increase in the frequency of KIR3DL1 and its ligand HLA-Bw4 in kidney cancer patients compared with controls. Both associations were partly attributable to changes in ligand frequencies alone. NSCLC patients showed a significant increase in the frequency of KIR2DL1 and its ligand HLA-C2 and a corresponding decrease in frequency of KIR2DL3 and its ligand HLA-C1 in homozygotes. In NSCLC, the Ile80 form of HLA-Bw4 was decreased in KIR3DL1+ HLA-Bw4+ patients, whereas in SCLC the Ile80 form was increased and the Thr80 form decreased in KIR3DS1+ HLA-Bw4+ patients. These findings are consistent with increased co-expression of high-affinity inhibitory KIRs and their ligands, potentially resulting in decreased natural killer cell function, and hence with natural killer cells having a protective role in lung and kidney cancer but not colon cancer.

The UK Childhood Cancer Study: maternal occupational exposures and childhood leukaemia and lymphoma

Risks of childhood leukaemia and lymphoma were investigated for specific work-related exposures of mothers in the UK Childhood Cancer Study. Interviews with parents of 1881 leukaemia and lymphoma cases (0-14 years) and 3742 controls collected job histories recording exposure to eight specific agents. Exposure was (1) self-reported and (2) reviewed, based mainly on exposure probability and exposure level. Completeness, consistency and sufficiency evaluated data quality. Of all job exposures which were self-reported as exposed, 33% cases and 34% controls remained classified as exposed after review, with the remainder designated as partially exposed or unexposed. No review of underreporting of exposure was made. Data quality was 'good' for 26% of cases and 24% of controls. For self-reported exposure, significant risks of acute lymphoblastic leukaemia (ALL) were observed for solvents and petrol in all time windows. For reviewed exposure, solvents remained significant for ALL during pregnancy and postnatally. Restricting analyses to good-quality information removed all significant results. Refinement of exposure assessment revealed misclassification of self-reported exposures and data quality influenced risk assessment. Maternal exposure to solvents should further be investigated. These findings must invoke caution in the interpretation of risks reliant on self-reported occupational data.

A microRNA-based prediction algorithm for diagnosis of non-small lung cell carcinoma in minimal biopsy material

BACKGROUND

Diagnosis is jeopardised when limited biopsy material is available or histological quality compromised. Here we developed and validated a prediction algorithm based on microRNA (miRNA) expression that can assist clinical diagnosis of lung cancer in minimal biopsy material to improve clinical management.

METHODS

Discovery utilised Taqman Low Density Arrays (754 miRNAs) in 20 non-small cell lung cancer (NSCLC) tumour/normal pairs. In an independent set of 40 NSCLC patients, 28 miRNA targets were validated using qRT-PCR. A prediction algorithm based on eight miRNA targets was validated blindly in a third independent set of 47 NSCLC patients. The panel was also tested in formalin-fixed paraffin-embedded (FFPE) specimens from 20 NSCLC patients. The genomic methylation status of highly deregulated miRNAs was investigated by pyrosequencing.

RESULTS

In the final, frozen validation set the panel had very high sensitivity (97.5%), specificity (96.3%) and ROC-AUC (0.99, P=10(-15)). The panel provided 100% sensitivity and 95% specificity in FFPE tissue (ROC-AUC=0.97 (P=10(-6))). DNA methylation abnormalities contribute little to the deregulation of the miRNAs tested.

CONCLUSION

The developed prediction algorithm is a valuable potential biomarker for assisting lung cancer diagnosis in minimal biopsy material. A prospective validation is required to measure the enhancement of diagnostic accuracy of our current clinical practice.

Early brain trauma and schizophrenia in Nigerian patients

OBJECTIVE

A number of reports have suggested that early brain trauma, especially obstetric complications, may be associated with schizophrenia. This observation seems at variance with the similar rates of schizophrenia reported for advanced and developing countries when viewed against the high rate of perinatal morbidity in developing countries. Using patients with mania as comparison subjects, the authors investigated the association of early brain trauma with schizophrenia in adult life among Nigerian patients.

METHOD

The manic (N = 12) and schizophrenic (N = 26) groups, both diagnosed according to the Research Diagnostic Criteria, were compared in respect to the prevalence of events commonly regarded as definite obstetric complications and the prevalence of childhood brain injury for which hospitalization was required.

RESULTS

A history of early brain trauma was associated with an adult diagnosis of schizophrenia. Schizophrenic patients with a history of early brain trauma were more likely than those without early brain trauma to have shown poor scholastic performance in childhood. They also showed mixed cerebral laterality in adulthood.

CONCLUSIONS

Early brain trauma may be a specific risk factor for the later development of schizophrenia. Patients with such a history may evidence other features of neurodevelopmental deviance.

Incorporating epistasis interaction of genetic susceptibility single nucleotide polymorphisms in a lung cancer risk prediction model

Incorporation of genetic variants such as single nucleotide polymorphisms (SNPs) into risk prediction models may account for a substantial fraction of attributable disease risk. Genetic data, from 2385 subjects recruited into the Liverpool Lung Project (LLP) between 2000 and 2008, consisting of 20 SNPs independently validated in a candidate-gene discovery study was used. Multifactor dimensionality reduction (MDR) and random forest (RF) were used to explore evidence of epistasis among 20 replicated SNPs. Multivariable logistic regression was used to identify similar risk predictors for lung cancer in the LLP risk model for the epidemiological model and extended model with SNPs. Both models were internally validated using the bootstrap method and model performance was assessed using area under the curve (AUC) and net reclassification improvement (NRI). Using MDR and RF, the overall best classifier of lung cancer status were SNPs rs1799732 (DRD2), rs5744256 (IL-18), rs2306022 (ITGA11) with training accuracy of 0.6592 and a testing accuracy of 0.6572 and a cross-validation consistency of 10/10 with permutation testing P<0.0001. The apparent AUC of the epidemiological model was 0.75 (95% CI 0.73–0.77). When epistatic data were incorporated in the extended model, the AUC increased to 0.81 (95% CI 0.79–0.83) which corresponds to 8% increase in AUC (DeLong's test P=2.2e-¹⁶); 17.5% by NRI. After correction for optimism, the AUC was 0.73 for the epidemiological model and 0.79 for the extended model. Our results showed modest improvement in lung cancer risk prediction when the SNP epistasis factor was added.

Lung cancer screening: identifying the high risk cohort

Low dose computed tomography (LDCT) is a viable screening tool for early lung cancer detection and mortality reduction. In practice, the success of any lung cancer screening programme will depend on successful identification of individuals at high risk in order to maximise the benefit-harm ratio. Risk prediction models incorporating multiple risk factors have been recognised as a method of identifying individuals at high risk of developing lung cancer. Identification of individuals at high risk will facilitate early diagnosis, reduce overall costs and also improve the current poor survival from lung cancer. This review summarises the current methods utilised in identifying high risk cohorts for lung cancer as proposed by the Liverpool Lung Project (LLP) risk model, Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial risk models and the prediction model for lung cancer death using quintiles. In addition, the cost-effectiveness of CT screening and future perspective for selecting high risk individuals is discussed.

Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia

Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10(-7)) and MTMR2 at 11q21 (rs10501831, P = 3.1×10(-6)) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10(-7)) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10(-4) for KCNIP4, represented by rs9799795) and AC (P = 2.16×10(-4) for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range.

The potential for using risk models in future lung cancer screening trials

Computed tomography screening for early diagnosis of lung cancer is one of the more potentially useful strategies, aside from smoking cessation programmes, for reducing mortality and improving the current poor survival from this disease. The long-term success of lung cancer screening will be dependent upon identifying populations at sufficient risk in order to maximise the benefit-to-harm ratio of the intervention. Risk prediction models could potentially play a major role in the selection of high-risk individuals who would benefit most from screening intervention programmes for the early detection of lung cancer. Improvements of developed lung cancer risk prediction models (through incorporation of objective clinical factors and genetic and molecular biomarkers for precise and accurate estimation of risks), demonstration of their clinical usefulness in decision making, and their use in future screening programmes are the focus of current research.

Factors associated with dropout in a lung cancer high‑risk cohort--the Liverpool lung project

In long-term longitudinal cohort studies the dropout of participants occurring as a result of withdrawal or lost to follow-up may have greater impact on the effect estimates, if characteristics of participants who drop out and those still active in the study differ significantly. The study aimed to investigate factors associated with dropout in a 5-year follow-up of individuals at 'high‑risk' of lung cancer. We studied 'high‑risk' group of 1,486 individuals aged 45-79 selected from the Liverpool Lung Prospective (LLP) cohort study using a strategy reflecting only age, smoking duration and history of pulmonary disease. Study subjects were recalled annually from 2005-2009 for follow-up collection of specimens and questionnaire data. The dropout rate over the follow-up time was investigated using the Kaplan‑Meier survival curve and the Cox proportional hazard model. Dropout rate was 31% after an average of 3 annual visits. Female gender hazard ratio (HR) 1.35 (95% CI 1.09-1.66), current smoking 1.26 (1.02-1.57), prior diagnosis of malignant disease 0.54 (0.36-0.79), home visits 0.67 (0.48-0.94) and systolic blood pressure 1.46 (1.10-1.94) were significantly associated with the dropout rate. Nearly 40% of individuals selected into the 'high‑risk' group by the old criteria were low risk with predicted 5-year absolute risk of less than 2.5%. In conclusion, follow-up of individuals is feasible within the LLP, but may be prone to selective withdrawal attributable to patient's state of health and mobility. We recommend future design of 'high‑risk' follow‑up studies to consider home visit as a useful strategy to encourage continued participation.