SNPs in cytochrome P450 genes decide on the fate of individuals with genetic predisposition to Parkinson's disease.

Parkinson's disease (PD) is one of the most frequent neurological diseases affecting millions of people worldwide. While the majority of PD cases are of unknown origin (idiopathic), about 5%-10% are familial and linked to mutations in different known genes. However, there are also people with a genetic predisposition to PD who do not develop the disease. To elucidate factors leading to the manifestation of PD we compared the occurrence of single nucleotide polymorphisms (SNPs) in various cytochrome P450 (P450) genes in people with a genetic predisposition and suffering from PD (GPD) to that of people, who are genetically predisposed, but show no symptoms of the disease (GUN). We used the PPMI (Parkinson's Progression Markers Initiative) database and the gene sequences of all 57 P450s as well as their three redox partners. Corresponding odds ratios (OR) and confidence intervals (CI) were calculated to assess the incidence of the various SNPs in the two groups of individuals and consequently their relation to PD. We identified for the first time SNPs that are significantly (up to 10fold!) over- or under-represented in GPD patients compared to GUN. SNPs with OR > 5 were found in 10 P450s being involved in eicosanoid, vitamin A and D metabolism as well as cholesterol degradation pointing to an important role of endogenous factors for the manifestation of PD clinical symptoms. Moreover, 12 P450s belonging to all P450 substrate classes as well as POR have SNPs that are significantly under-represented (OR < 0.2) in GPD compared to GUN, indicating a protective role of those SNPs and the corresponding P450s regarding disease advancement. To the best of our knowledge our data for the first time demonstrate an association between known PD predisposition genes and SNPs in other genes, shown here for different P450 genes and for their redox partner POR, which promote the manifestation of the disease in familial PD. Our results thus shed light onto the pathogenesis of PD, especially the switch from GUN to GPD and might further help to advance novel strategies for preventing the development or progression of the disease.

A CYPome-wide study reveals new potential players in the pathogenesis of Parkinson's disease.

Genetic and environmental factors lead to the manifestation of Parkinson's disease (PD) but related mechanisms are only rudimentarily understood. Cytochromes P450 (P450s) are involved in the biotransformation of toxic compounds and in many physiological processes and thus predestinated to be involved in PD. However, so far only SNPs (single nucleotide polymorphisms) in CYP2D6 and CYP2E1 have been associated with the susceptibility of PD. Our aim was to evaluate the role of all 57 human P450s and their redox partners for the etiology and pathophysiology of PD and to identify novel potential players which may lead to the identification of new biomarkers and to a causative treatment of PD. The PPMI (Parkinson's Progression Markers Initiative) database was used to extract the gene sequences of all 57 P450s and their three redox partners to analyze the association of SNPs with the occurrence of PD. Applying statistical analyses of the data, corresponding odds ratios (OR) and confidence intervals (CI) were calculated. We identified SNPs significantly over-represented in patients with a genetic predisposition for PD (GPD patients) or in idiopathic PD (IPD patients) compared to HC (healthy controls). Xenobiotic-metabolizing P450s show a significant accumulation of SNPs in PD patients compared with HC supporting the role of toxic compounds in the pathogenesis of PD. Moreover, SNPs with high OR values (>5) in P450s catalyzing the degradation of cholesterol (CYP46A1, CY7B1, CYP39A1) indicate a prominent role of cholesterol metabolism in the brain for PD risk. Finally, P450s participating in the metabolism of eicosanoids show a strong over-representation of SNPs in PD patients underlining the effect of inflammation on the pathogenesis of PD. Also, the redox partners of P450 show SNPs with OR > 5 in PD patients. Taken together, we demonstrate that SNPs in 26 out of 57 P450s are at least 5-fold over-represented in PD patients suggesting these P450s as new potential players in the pathogenesis of PD. For the first time exceptionally high OR values (up to 12.9) were found. This will lead to deeper insight into the origin and development of PD and may be applied to develop novel strategies for a causative treatment of this disease.

High-Performance Hybrid-Global-Deflated-Local Optimization with Applications to Active Learning.

Mathematical optimization lies at the core of many science and industry applications. One important issue with many current optimization strategies is a well-known trade-off between the number of function evaluations and the probability to find the global, or at least sufficiently high-quality local optima. In machine learning (ML), and by extension in active learning - for instance for autonomous experimentation - mathematical optimization is often used to find the underlying uncertain surrogate model from which subsequent decisions are made and therefore ML relies on high-quality optima to obtain the most accurate models. Active learning often has the added complexity of missing offline training data; therefore, the training has to be conducted during the data collection which can stall the acquisition if standard methods are used. In this work, we highlight recent efforts to create a high-performance hybrid optimization algorithm (HGDL), combining derivative-free global optimization strategies with local, derivative-based optimization, ultimately yielding an ordered list of unique local optima. Redundancies are avoided by deflating the objective function around earlier encountered optima. HGDL is designed to take full advantage of parallelism by having the most computationally expensive process, the local first and second-order-derivative-based optimizations, run in parallel on separate compute nodes in separate processes. In addition, the algorithm runs asynchronously; as soon as the first solution is found, it can be used while the algorithm continues to find more solutions. We apply the proposed optimization and training strategy to Gaussian-Process-driven stochastic function approximation and active learning.

Long non-coding RNA dysregulation is a frequent event in non-small cell lung carcinoma pathogenesis.

BACKGROUND: Long non-coding RNAs compose an important level of epigenetic regulation in normal physiology and disease. Despite the plethora of publications of lncRNAs in human cancer, the landscape is still unclear. METHODS: Microarray analysis in 44 NSCLC paired specimens was followed by qPCR-based validation in 29 (technical) and 38 (independent) tissue pairs. Cross-validation of the selected targets was achieved in 850 NSCLC tumours from TCGA datasets. RESULTS: Twelve targets were successfully validated by qPCR (upregulated: FEZF1-AS1, LINC01214, LINC00673, PCAT6, NUTM2A-AS1, LINC01929; downregulated: PCAT19, FENDRR, SVIL-AS1, LANCL1-AS1, ADAMTS9-AS2 and LINC00968). All of them were successfully cross validated in the TCGA datasets. Abnormal DNA methylation was observed in the promoters of FENDRR, FEZF1-AS1 and SVIL-AS1. FEZF1-AS1 and LINC01929 were associated with survival in the TCGA set. CONCLUSIONS: Our study provides through multiple levels of internal and external validation, a comprehensive list of dysregulated lncRNAs in NSCLC. We therefore envisage this dataset to serve as an important source for the lung cancer research community assisting future investigations on the involvement of lncRNAs in the pathogenesis of the disease and providing novel biomarkers for diagnosis, prognosis and therapeutic stratification.

Development and validation of a multivariable risk prediction model for head and neck cancer using the UK Biobank.

Head and neck cancer (HNC) is the eighth most common cancer in the UK, with over 12,000 new cases every year. The incidence of HNC is predicted to increase by 33% by 2035. Risk modelling produces personalised risk estimates for specific diseases, which can be used to inform education, screening programmes and recruitment to clinical trials. The present study describes the development and validation of the first risk prediction model for absolute risk of HNC, using a nested case­control study within the UK Biobank dataset. The UK Biobank recruited 502,647 individuals aged 40­69 years from around the UK. In total, 859 cases of HNC were identified, with 253 incident cases (individuals who developed HNC in the 7 years following recruitment to the UK Biobank study). Logistic regression was used to develop the model, then the model performance was validated using a cohort from the North West of England. Overall, increasing age, male sex, positive history of smoking and alcohol consumption and higher levels of material deprivation were significantly associated with a higher risk of HNC. Consuming at least five portions of fruit and vegetables per day, exercising at least once per week and higher BMI offered a protective effect against HNC. The C­statistic was 0.69 [95% confidence interval (CI), 0.66­0.71] and the model displayed good calibration. Upon external validation, the C­statistic was 0.64 (95% CI, 0.60­0.68) with reasonable calibration. The model developed and validated in the present study allows calculation of a personalised risk estimate for HNC. This could be used to guide clinicians when counselling individuals on risk behaviour, and there is potential for such models to inform recruitment to screening trials.

Early poststroke seizures following thrombolysis and/or thrombectomy for acute stroke: Clinical and stroke characteristics.

In this retrospective study, we explored the clinical and stroke characteristics of patients treated with thrombolysis and/or mechanical thrombectomy for an acute stroke and experiencing early poststroke seizures within 7 days of the cerebrovascular accident. Patients with prior epilepsy, primary intracerebral hemorrhage or transient ischemic attacks, or taking antiepileptic drugs were excluded. We retrospectively identified 32 patients admitted between 2010 and 2016 (mean age 75 years; range: 49-90; 14 females and 18 males). A cortical stroke was found in more than 70% of patients. Most epileptic seizures were focal aware (46.7%) or generalized convulsive (43.3%). The median time between stroke onset and seizure occurrence was 2 days; in 75.9% of the cases, seizures occurred within the first 3 days. This retrospective case series is the largest published so far providing details on clinical features of patients with early poststroke seizures following different reperfusion therapies, not only restricted to intravenous (i.v.) thrombolysis. Early poststroke seizures following reperfusion therapies are associated with cortical stroke involvement, are usually focal without impairment of awareness or generalized convulsive, and occur mostly within the first 3 days. Further studies are needed to clarify whether the low prevalence of focal impaired awareness seizures (and nonconvulsive seizures/status) is real or reflects the failure to recognize and correctly diagnose this seizure type in the acute poststroke period (risk of underascertainment due to the lack of systematic video-electroencephalogram (EEG) recording in patients with stroke and difficulties in recognizing these seizures). This article is part of the Special Issue "Seizures & Stroke".

Highly aggressive undifferentiated small round blue cell tumor of foot with unique SMARCA1, KAT6A and NAV3 mutations.

Malignancies characterized histologically by high-grade monotonous small round blue cells (SRBCs) belong to a heterogeneous group of neoplasms often referred to as Ewing family of tumors. The most common molecular confirmation of these neoplasms is by fusions between EWSR1 gene on chromosome 22 and the ETS family of transcription factors, including FLI1 gene (11q24) and the ERG (21q22), that are implicated in the development of different tissues as well as cancer progression. In this article, we present a case of highly aggressive extraskeletal SRBC tumor involving the foot of a 24-year-old male with sole molecular findings of mutations in KAT6A, NAV3 and SMARCA1 genes with high expression of soft tissue markers (COL1A1, COL1A2, COL3A1) and MYC mRNA. To our knowledge, this unique mutational pattern has not previously been described in SRBCs.

Evaluation of a health service adopting proactive approach to reduce high risk of lung cancer: The Liverpool Healthy Lung Programme.

OBJECTIVES: This Liverpool Healthy Lung Programme is a response to high rates of lung cancer and respiratory diseases locally and aims to diagnose lung cancer at an earlier stage by proactive approach to those at high risk of lung cancer. The objective of this study is to evaluate the programme in terms of its likely effect on mortality from lung cancer and its delivery to deprived populations. METHODS: Persons aged 58-75 years, with a history of smoking or a diagnosis of chronic obstructive pulmonary disease (COPD)2 according to general practice records were invited for lung health check in a community health hub setting. A detailed risk assessment and spirometry were performed in eligible patients. Those with a 5% or greater five-year risk of lung cancer were referred for a low dose CT3 scan. RESULTS: A total of 4 566 subjects attended the appointment for risk assessment and 3 591 (79%) consented to data sharing. More than 80% of the patients were in the most deprived quintile of the index of multiple deprivation. Of those attending, 63% underwent spirometry and 43% were recommended for a CT scan. A total of 25 cancers were diagnosed, of which 16 (64%) were stage I. Comparison with the national stage distribution implied that the programme was reducing lung cancer mortality by 22%. CONCLUSIONS: Community based proactive approaches to early diagnosis of lung cancer in health deprived regions are likely to be effective in early detection of lung cancer.

DPP-4 Inhibitor Dose Selection According to Manufacturer Specifications: A Contemporary Experience From UK General Practice.

Recently, 2 dipeptidyl peptidase-4 (DPP-4) inhibitors, sitagliptin and saxagliptin, adjusted dosing specification from creatinine clearance to glomerular filtration rate, more typically reported in routine laboratory tests. This cross-sectional study examines all DPP-4 inhibitor initiations that require dose adjustment and the dose selection using data from UK general practice. Results indicate that 34% of patients taking a nonlinagliptin DPP-4 inhibitor were given a higher dose and 11% a lower dose than specified in the Summary of Product Characteristics. This reinforces the deviation from Summary of Product Characteristics prescription of DPP-4 inhibitors identified in earlier studies despite improvement in compatibility with routine reporting.

Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development.

The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10-11 in overall lung cancer and OR=0.41, p value=9.71x10-11 in non-small cell lung cancer), SYNE1:RNF43 (OR=0.73, p value=1.01x10-12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10-11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis in lung tissues provided information supporting the functional role of the identified epistasis in lung tumorigenesis. Gene set enrichment analysis revealed potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play an important role in lung tumorigenesis and epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.

Probability of cancer in lung nodules using sequential volumetric screening up to 12 months: the UKLS trial.

BACKGROUND: Estimation of the clinical probability of malignancy in patients with pulmonary nodules will facilitate early diagnosis, determine optimum patient management strategies and reduce overall costs. METHODS: Data from the UK Lung Cancer Screening trial were analysed. Multivariable logistic regression models were used to identify independent predictors and to develop a parsimonious model to estimate the probability of lung cancer in lung nodules detected at baseline and at 3-month and 12-month repeat screening. RESULTS: Of 1994 participants who underwent CT scan, 1013 participants had a total of 5063 lung nodules and 52 (2.6%) of the participants developed lung cancer during a median follow-up of 4 years. Covariates that predict lung cancer in our model included female gender, asthma, bronchitis, asbestos exposure, history of cancer, early and late onset of family history of lung cancer, smoking duration, FVC, nodule type (pure ground-glass and part-solid) and volume as measured by semiautomated volumetry. The final model incorporating all predictors had excellent discrimination: area under the receiver operating characteristic curve (AUC 0.885, 95% CI 0.880 to 0.889). Internal validation suggested that the model will discriminate well when applied to new data (optimism-corrected AUC 0.882, 95% CI 0.848 to 0.907). The risk model had a good calibration (goodness-of-fit χ[8] 8.13, p=0.42). CONCLUSIONS: Our model may be used in estimating the probability of lung cancer in nodules detected at baseline and at 3 months and 12 months from baseline, allowing more efficient stratification of follow-up in population-based lung cancer screening programmes. TRIAL REGISTRATION NUMBER: 78513845.

Elevated Platelet Count Appears to Be Causally Associated with Increased Risk of Lung Cancer: A Mendelian Randomization Analysis.

BACKGROUND: Platelets are a critical element in coagulation and inflammation, and activated platelets are linked to cancer risk through diverse mechanisms. However, a causal relationship between platelets and risk of lung cancer remains unclear. METHODS: We performed single and combined multiple instrumental variable Mendelian randomization analysis by an inverse-weighted method, in addition to a series of sensitivity analyses. Summary data for associations between SNPs and platelet count are from a recent publication that included 48,666 Caucasian Europeans, and the International Lung Cancer Consortium and Transdisciplinary Research in Cancer of the Lung data consisting of 29,266 cases and 56,450 controls to analyze associations between candidate SNPs and lung cancer risk. RESULTS: Multiple instrumental variable analysis incorporating six SNPs showed a 62% increased risk of overall non-small cell lung cancer [NSCLC; OR, 1.62; 95% confidence interval (CI), 1.15-2.27; P = 0.005] and a 200% increased risk for small-cell lung cancer (OR, 3.00; 95% CI, 1.27-7.06; P = 0.01). Results showed only a trending association with NSCLC histologic subtypes, which may be due to insufficient sample size and/or weak effect size. A series of sensitivity analysis retained these findings. CONCLUSIONS: Our findings suggest a causal relationship between elevated platelet count and increased risk of lung cancer and provide evidence of possible antiplatelet interventions for lung cancer prevention. IMPACT: These findings provide a better understanding of lung cancer etiology and potential evidence for antiplatelet interventions for lung cancer prevention.

Genome-wide interaction study of smoking behavior and non-small cell lung cancer risk in Caucasian population.

Non-small cell lung cancer is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) and smoking status (never- versus ever-smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13336 non-small cell lung cancer cases. Candidate SNPs with P-value <0.001 were further analyzed using a standard case-control interaction analysis including 13970 controls. The significant SNPs with P-value <3.5 × 10-5 (correcting for multiple tests) from the case-control analysis in the discovery stage were further validated using an independent replication dataset comprising 5377 controls and 3054 non-small cell lung cancer cases. We further stratified the analysis by histological subtypes. Two novel SNPs, rs6441286 and rs17723637, were identified for overall lung cancer risk. The interaction odds ratio and meta-analysis P-value for these two SNPs were 1.24 with 6.96 × 10-7 and 1.37 with 3.49 × 10-7, respectively. In addition, interaction of smoking with rs4751674 was identified in squamous cell lung carcinoma with an odds ratio of 0.58 and P-value of 8.12 × 10-7. This study is by far the largest genome-wide SNP-smoking interaction analysis reported for lung cancer. The three identified novel SNPs provide potential candidate biomarkers for lung cancer risk screening and intervention. The results from our study reinforce that gene-smoking interactions play important roles in the etiology of lung cancer and account for part of the missing heritability of this disease.

Utilizing Lung Cancer Risk Prediction Models to Promote Smoking Cessation: Two Randomized Controlled Trials.

PURPOSE: The current project sought to examine whether delivery of lung cancer risk projections (calculated using the Liverpool Lung Project [LLP] risk model) predicted follow-up smoking status. DESIGN: Two single-blinded randomized controlled trials. SETTING: Stop Smoking Services in Liverpool (United Kingdom). PARTICIPANTS: Baseline current smokers (N = 297) and baseline recent former smokers (N = 216) were recruited. INTERVENTION: Participants allocated to intervention groups were provided with personalized lung cancer risk projections, calculated using the LLP risk model. MEASURES: Baseline and follow-up questionnaires explored sociodemographics, smoking behavior, and lung cancer risk perceptions. ANALYSIS: Bivariate analyses identified significant differences between randomization groups, and logistic regression models were developed to investigate the intervention effect on the outcome variables. RESULTS: Lung cancer risk projections were not found to predict follow-up smoking status in the trial of baseline current smokers; however, they did predict follow-up smoking status in the trial of baseline recent former smokers (odds ratio: 1.91; 95% confidence interval: 1.03-3.55). CONCLUSION: The current study suggests that lung cancer risk projections may help maintain abstinence among individuals who have quit smoking, but the results did not provide evidence to suggest that lung cancer risk projections motivate current smokers to quit.

Common TDP1 Polymorphisms in Relation to Survival among Small Cell Lung Cancer Patients: A Multicenter Study from the International Lung Cancer Consortium.

Purpose: DNA topoisomerase inhibitors are commonly used for treating small-cell lung cancer (SCLC). Tyrosyl-DNA phosphodiesterase (TDP1) repairs DNA damage caused by this class of drugs and may therefore influence treatment outcome. In this study, we investigated whether common TDP1 single-nucleotide polymorphisms (SNP) are associated with overall survival among SCLC patients.Experimental Design: Two TDP1 SNPs (rs942190 and rs2401863) were analyzed in 890 patients from 10 studies in the International Lung Cancer Consortium (ILCCO). The Kaplan-Meier method and Cox regression analyses were used to evaluate genotype associations with overall mortality at 36 months postdiagnosis, adjusting for age, sex, race, and tumor stage.Results: Patients homozygous for the minor allele (GG) of rs942190 had poorer survival compared with those carrying AA alleles, with a HR of 1.36 [95% confidence interval (CI): 1.08-1.72, P = 0.01), but no association with survival was observed for patients carrying the AG genotype (HR = 1.04, 95% CI, 0.84-1.29, P = 0.72). For rs2401863, patients homozygous for the minor allele (CC) tended to have better survival than patients carrying AA alleles (HR = 0.79; 95% CI, 0.61-1.02, P = 0.07). Results from the Genotype Tissue Expression (GTEx) Project, the Encyclopedia of DNA Elements (ENCODE), and the ePOSSUM web application support the potential function of rs942190.Conclusions: We found the rs942190 GG genotype to be associated with relatively poor survival among SCLC patients. Further investigation is needed to confirm the result and to determine whether this genotype may be a predictive marker for treatment efficacy of DNA topoisomerase inhibitors. Clin Cancer Res; 23(24); 7550-7. ©2017 AACR.

Age at menopause and hormone replacement therapy as risk factors for head and neck and oesophageal cancer (Review).

There were ~986,000 cases of head and neck cancer (HNC) and oesophageal cancer diagnosed worldwide in 2012. The incidence of these types of cancer is much higher in males than females, although this disparity decreases in the elderly population, suggesting a role for hormones as a risk factor. This systematic review investigates the potential role of female hormones [age at menopause and use of hormone replacement therapy (HRT)] as risk factors for HNC/oesophageal squamous cell carcinoma (SCC). The electronic databases MEDLINE, Web of Science, EMBASE and Cochrane were searched. Only studies with at least 50 cases of HNC/oesophageal SCC, with data on age at menopause, smoking, alcohol, age and socioeconomic status or educational attainment, were included. The Newcastle Ottawa Scale was used for assessing risk of bias. Eight studies met the inclusion criteria (5 oesophageal SCC, 2 HNC and 1 combined oesophageal SCC and HNC). HRT was shown to reduce the risk of HNC (HR, 0.78; 95% CI, 0.61-0.99) in one study. Our results showed that earlier age at menopause is a risk factor for oesophageal SCC, with women entering menopause at <45 years having double the risk of those entering menopause at age >50 years. Similar, but less striking, results were observed for HNC. HRT was found to reduce the risk of HNC/oesophageal SCC, but the evidence is inconclusive. We, therefore, recommend that consideration should be given to collecting data on reproductive factors and exposure to HRT, as routine practice, in future epidemiological and clinical studies of these cancers. The concept of oestrogen deficiency as a risk for HNC/oesophageal SCC deserves further exploration in future laboratory and clinical studies.

AURKA mRNA expression is an independent predictor of poor prognosis in patients with non-small cell lung cancer.

Deregulation of mitotic spindle genes has been reported to contribute to the development and progression of malignant tumours. The aim of the present study was to explore the association between the expression profiles of Aurora kinases (AURKA, AURKB and AURKC), cytoskeleton-associated protein 5 (CKAP5), discs large-associated protein 5 (DLGAP5), kinesin-like protein 11 (KIF11), microtubule nucleation factor (TPX2), monopolar spindle 1 kinase (TTK), and ß-tubulins (TUBB) and (TUBB3) genes and clinicopathological characteristics in human non-small cell lung carcinoma (NSCLC). Reverse transcription-quantitative polymerase chain reaction-based RNA gene expression profiles of 132 NSCLC and 44 adjacent wild-type tissues were generated, and Cox's proportional hazard regression was used to examine associations. With the exception of AURKC, all genes exhibited increased expression in NSCLC tissues. Of the 10 genes examined, only AURKA was significantly associated with prognosis in NSCLC. Multivariate Cox's regression analysis demonstrated that AURKA mRNA expression [hazard ratio (HR), 1.81; 95% confidence interval (CI), 1.16-2.84; P=0.009], age (HR, 1.03; 95% CI, 1.00-1.06; P=0.020), pathological tumour stage 2 (HR, 2.43; 95% CI, 1.16-5.10; P=0.019) and involvement of distal nodes (pathological node stage 2) (HR, 3.14; 95% CI, 1.24-7.99; P=0.016) were independent predictors of poor prognosis in patients with NSCLC. Poor prognosis of patients with increased AURKA expression suggests that those patients may benefit from surrogate therapy with AURKA inhibitors.

Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.

BACKGROUND: Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. METHODS AND FINDINGS: We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01-1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15-2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79-1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84-0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25-2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. CONCLUSIONS: Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior.