Exploring the Associations of Inflammatory and Oxidative Stress Biomarkers with Pancreatic Diseases: An Observational and Mendelian Randomisation Study.

Identifying biomarkers linked to pancreatic ductal adenocarcinoma (PDAC) and chronic pancreatitis (CP) is crucial for early detection, treatment, and prevention. Methods: Association analyses of 10 serological biomarkers involved in cell signalling (IFN-γ, IL-6, IL-8, IL-10), oxidative stress (superoxide dismutase (SOD) and glutathione peroxidase (GPx) enzyme activities, total glutathione (GSH), malondialdehyde (MDA) levels), and intestinal permeability proteins (zonulin, I-FABP2) were conducted across PDAC (n = 12), CP (n = 21) and control subjects (n = 23). A Mendelian randomisation (MR) approach was used to assess causality of the identified significant associations in two large genetic cohorts (FinnGen and UK Biobank). Results: Observational results showed a downregulation of SOD and GPx antioxidant enzyme activities in PDAC and CP patients, respectively, and higher MDA levels in CP patients. Logistic regression models revealed significant associations between CP and SOD activity (OR = 0.21, 95% CI [0.05, 0.89], per SD), GPx activity (OR = 0.28, 95% CI [0.10, 0.79], per SD), and MDA levels (OR = 2.05, 95% CI [1.36, 3.08], per SD). MR analyses, however, did not support causality. Conclusions: These findings would not support oxidative stress-related biomarkers as potential targets for pancreatic diseases prevention. Yet, further research is encouraged to assess their viability as non-invasive tools for early diagnosis, particularly in pre-diagnostic CP populations.

Meta-Analysis and Validation of a Colorectal Cancer Risk Prediction Model Using Deep Sequenced Fecal Metagenomes.

The gut microbiome is a potential modifiable risk factor for colorectal cancer (CRC). We re-analyzed all eight previously published stool sequencing data and conducted an MWAS meta-analysis. We used cross-validated LASSO predictive models to identify a microbiome signature for predicting the risk of CRC and precancerous lesions. These models were validated in a new study, Colorectal Cancer Screening (COLSCREEN), including 156 participants that were recruited in a CRC screening context. The MWAS meta-analysis identified 95 bacterial species that were statistically significantly associated with CRC (FDR < 0.05). The LASSO CRC predictive model obtained an area under the receiver operating characteristic curve (aROC) of 0.81 (95%CI: 0.78−0.83) and the validation in the COLSCREEN dataset was 0.75 (95%CI: 0.66−0.84). This model selected a total of 32 species. The aROC of this CRC-trained model to predict precancerous lesions was 0.52 (95%CI: 0.41−0.63). We have identified a signature of 32 bacterial species that have a good predictive accuracy to identify CRC but not precancerous lesions, suggesting that the identified microbes that were enriched or depleted in CRC are merely a consequence of the tumor. Further studies should focus on CRC as well as precancerous lesions with the intent to implement a microbiome signature in CRC screening programs.

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

BACKGROUND: Aberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility. AIM: To assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent. METHODS: Odds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups. RESULTS: No genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR = 1.20; 95% CI 1.13-1.27; p = 5.6 × 10-10) and never smokers (e.g., maker rs1133683 Axin2; OR = 1.27; 95% CI 1.19-1.35; p = 1.0 × 10-12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants. CONCLUSIONS: The role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers.

Accounting for EGFR Mutations in Epidemiologic Analyses of Non-Small Cell Lung Cancers: Examples Based on the International Lung Cancer Consortium Data.

BACKGROUND: Somatic EGFR mutations define a subset of non-small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. METHODS: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. RESULTS: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74-0.77) in the training and 0.77 (95% CI, 0.74-0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. CONCLUSIONS: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. IMPACT: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

Hepcidin-regulating iron metabolism genes and pancreatic ductal adenocarcinoma: a pathway analysis of genome-wide association studies.

BACKGROUND: Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. OBJECTIVES: The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. METHODS: We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. RESULTS: The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. CONCLUSIONS: Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association.

Tumor-Associated Microbiome: Where Do We Stand?

The study of the human microbiome in oncology is a growing and rapidly evolving field. In the past few years, there has been an exponential increase in the number of studies investigating associations of microbiome and cancer, from oncogenesis and cancer progression to resistance or sensitivity to specific anticancer therapies. The gut microbiome is now known to play a significant role in antitumor immune responses and in predicting the efficacy of immune-checkpoint inhibitors in cancer patients. Beyond the gut, the tumor-associated microbiome-microbe communities located either in the tumor or within its body compartment-seems to interact with the local microenvironment and the tumor immune contexture, ultimately impacting cancer progression and treatment outcome. However, pre-clinical research focusing on causality and mechanistic pathways as well as proof-of-concept studies are still needed to fully understand the potential clinical utility of microbiome in cancer patients. Moreover, there is a need for the standardization of methodology and the implementation of quality control across microbiome studies to allow for a better interpretation and greater comparability of the results reported between them. This review summarizes the accumulating evidence in the field and discusses the current and upcoming challenges of microbiome studies.

Smoking Modifies Pancreatic Cancer Risk Loci on 2q21.3.

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10-8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10-9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.

Identifying environmental risk factors for inflammatory bowel diseases: a Mendelian randomization study.

Several studies have examined environmental factors and inflammatory bowel diseases (IBD) using traditional approaches; however, provided results are still conflicting. Our aim was to determine whether lifestyle and nutrient exposures, related to IBD in observational meta-analyses, influence IBD risk using a Mendelian randomization (MR) approach. A two-sample MR approach was applied on summary-level genome-wide association results. Genetic variants strongly associated with measures of tobacco smoking, obesity and fat distribution, physical activity, and blood levels of vitamins and fatty acids were evaluated on genetic data from international IBD consortia including a total of 25,042 IBD cases (12,194 cases of Crohn's disease (CD) and 12,366 cases of ulcerative colitis (UC)) and 34,915 controls. Our results indicated that, among lifestyle exposures, being a smoker was positively associated with CD (OR 1.13, P = 0.02), but it was not associated with UC risk (OR 0.99, P = 0.88). Body-mass index (BMI) and body fat percentage were positively associated with CD (OR 1.11, P = 0.02, per standard deviation (SD) of 4.6 kg/m2; and OR 1.50, P = 3 × 10-10, per SD of 6.6%; respectively); while for UC, BMI was inversely associated (OR 0.85, P = 5 × 10-5; per SD) and body fat percentage showed a OR of 1.11 (P = 0.11; per SD). Additionally, among nutrient exposures, omega-3 fatty acids levels were inversely associated with CD (OR 0.67, P = 2 × 10-6). Our MR results did not support a protective effect for being a smoker on UC risk; however, they are compatible with a risk effect for higher body fat proportion and a protective role for higher levels of omega-3 fatty acids on CD etiology.

A new efficient method to detect genetic interactions for lung cancer GWAS.

BACKGROUND: Genome-wide association studies (GWAS) have proven successful in predicting genetic risk of disease using single-locus models; however, identifying single nucleotide polymorphism (SNP) interactions at the genome-wide scale is limited due to computational and statistical challenges. We addressed the computational burden encountered when detecting SNP interactions for survival analysis, such as age of disease-onset. To confront this problem, we developed a novel algorithm, called the Efficient Survival Multifactor Dimensionality Reduction (ES-MDR) method, which used Martingale Residuals as the outcome parameter to estimate survival outcomes, and implemented the Quantitative Multifactor Dimensionality Reduction method to identify significant interactions associated with age of disease-onset. METHODS: To demonstrate efficacy, we evaluated this method on two simulation data sets to estimate the type I error rate and power. Simulations showed that ES-MDR identified interactions using less computational workload and allowed for adjustment of covariates. We applied ES-MDR on the OncoArray-TRICL Consortium data with 14,935 cases and 12,787 controls for lung cancer (SNPs = 108,254) to search over all two-way interactions to identify genetic interactions associated with lung cancer age-of-onset. We tested the best model in an independent data set from the OncoArray-TRICL data. RESULTS: Our experiment on the OncoArray-TRICL data identified many one-way and two-way models with a single-base deletion in the noncoding region of BRCA1 (HR 1.24, P = 3.15 × 10-15), as the top marker to predict age of lung cancer onset. CONCLUSIONS: From the results of our extensive simulations and analysis of a large GWAS study, we demonstrated that our method is an efficient algorithm that identified genetic interactions to include in our models to predict survival outcomes.

Incorporating multiple sets of eQTL weights into gene-by-environment interaction analysis identifies novel susceptibility loci for pancreatic cancer.

It is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene-by-environment interaction (G × E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data-adaptive G × E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case-Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome-wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking-related pancreatic cancer susceptibility genes, TRIP10 and KDM3A, were identified. The aGEw test is implemented in an R package aGE.

Gallbladder disease, cholecystectomy, and pancreatic cancer risk in the International Pancreatic Cancer Case-Control Consortium (PanC4).

BACKGROUND: The association among gallbladder disease, cholecystectomy, and pancreatic cancer is unclear. Moreover, time interval between gallbladder disease or cholecystectomy and pancreatic cancer diagnosis is not considered in most previous studies. AIM: To quantify the association among gallbladder disease, cholecystectomy, and pancreatic cancer, considering time since first diagnosis of gallbladder disease or cholecystectomy. METHODS: We used data from nine case-control studies within the Pancreatic Cancer Case-Control Consortium, including 5760 cases of adenocarcinoma of the exocrine pancreas and 8437 controls. We estimated pooled odds ratios and the corresponding 95% confidence intervals by estimating study-specific odds ratios through multivariable unconditional logistic regression models, and then pooling the obtained estimates using fixed-effects models. RESULTS: Compared with patients with no history of gallbladder disease, the pooled odds ratio of pancreatic cancer was 1.69 (95% confidence interval, 1.51-1.88) for patients reporting a history of gallbladder disease. The odds ratio was 4.90 (95% confidence interval, 3.45-6.97) for gallbladder disease diagnosed <2 years before pancreatic cancer diagnosis and 1.11 (95% confidence interval, 0.96-1.29) when ≥2 years elapsed. The pooled odds ratio was 1.64 (95% confidence interval, 1.43-1.89) for patients who underwent cholecystectomy, as compared to those without cholecystectomy. The odds ratio was 7.00 (95% confidence interval, 4.13-11.86) for a surgery <2 years before pancreatic cancer diagnosis and 1.28 (95% confidence interval, 1.08-1.53) for a surgery ≥2 years before. CONCLUSIONS: There appears to be no long-term effect of gallbladder disease on pancreatic cancer risk, and at most a modest one for cholecystectomy. The strong short-term association can be explained by diagnostic bias and reverse causation.

Genome-Wide Gene-Diabetes and Gene-Obesity Interaction Scan in 8,255 Cases and 11,900 Controls from PanScan and PanC4 Consortia.

BACKGROUND: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level. METHODS: We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics. RESULTS: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10-6) was observed in the meta-analysis (P GxE = 1.2 ×10-6, P Joint = 4.2 ×10-7). CONCLUSIONS: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans. IMPACT: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.

Associations between Genetically Predicted Blood Protein Biomarkers and Pancreatic Cancer Risk.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with few known risk factors and biomarkers. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of biomarkers, usually in small samples. In this study, we evaluated associations of circulating protein levels and PDAC risk using genetic instruments. METHODS: To identify novel circulating protein biomarkers of PDAC, we studied 8,280 cases and 6,728 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium, using genetic instruments of protein quantitative trait loci. RESULTS: We observed associations between predicted concentrations of 38 proteins and PDAC risk at an FDR of < 0.05, including 23 of those proteins that showed an association even after Bonferroni correction. These include the protein encoded by ABO, which has been implicated as a potential target gene of PDAC risk variant. Eight of the identified proteins (LMA2L, TM11D, IP-10, ADH1B, STOM, TENC1, DOCK9, and CRBB2) were associated with PDAC risk after adjusting for previously reported PDAC risk variants (OR ranged from 0.79 to 1.52). Pathway enrichment analysis showed that the encoding genes for implicated proteins were significantly enriched in cancer-related pathways, such as STAT3 and IL15 production. CONCLUSIONS: We identified 38 candidates of protein biomarkers for PDAC risk. IMPACT: This study identifies novel protein biomarker candidates for PDAC, which if validated by additional studies, may contribute to the etiologic understanding of PDAC development.

Menstrual Factors, Reproductive History, Hormone Use, and Urothelial Carcinoma Risk: A Prospective Study in the EPIC Cohort.

BACKGROUND: Urothelial carcinoma is the predominant (95%) bladder cancer subtype in industrialized nations. Animal and epidemiologic human studies suggest that hormonal factors may influence urothelial carcinoma risk. METHODS: We used an analytic cohort of 333,919 women from the European Prospective Investigation into Cancer and Nutrition Cohort. Associations between hormonal factors and incident urothelial carcinoma (overall and by tumor grade, tumor aggressiveness, and non-muscle-invasive urothelial carcinoma) risk were evaluated using Cox proportional hazards models. RESULTS: During a mean of 15 years of follow-up, 529 women developed urothelial carcinoma. In a model including number of full-term pregnancies (FTP), menopausal status, and menopausal hormone therapy (MHT), number of FTP was inversely associated with urothelial carcinoma risk (HR≥5vs1 = 0.48; 0.25-0.90; P trend in parous women = 0.010) and MHT use (compared with nonuse) was positively associated with urothelial carcinoma risk (HR = 1.27; 1.03-1.57), but no dose response by years of MHT use was observed. No modification of HRs by smoking status was observed. Finally, sensitivity analyses in never smokers showed similar HR patterns for the number of FTP, while no association between MHT use and urothelial carcinoma risk was observed. Association between MHT use and urothelial carcinoma risk remained significant only in current smokers. No heterogeneity of the risk estimations in the final model was observed by tumor aggressiveness or by tumor grade. A positive association between MTH use and non-muscle-invasive urothelial carcinoma risk was observed. CONCLUSIONS: Our results support that increasing the number of FTP may reduce urothelial carcinoma risk. IMPACT: More detailed studies on parity are needed to understand the possible effects of perinatal hormone changes in urothelial cells.

Serologic markers of Chlamydia trachomatis and other sexually transmitted infections and subsequent ovarian cancer risk: Results from the EPIC cohort.

A substantial proportion of epithelial ovarian cancer (EOC) arises in the fallopian tube and other epithelia of the upper genital tract; these epithelia may incur damage and neoplastic transformation after sexually transmitted infections (STI) and pelvic inflammatory disease. We investigated the hypothesis that past STI infection, particularly Chlamydia trachomatis, is associated with higher EOC risk in a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort including 791 cases and 1669 matched controls. Serum antibodies against C. trachomatis, Mycoplasma genitalium, herpes simplex virus type 2 (HSV-2) and human papillomavirus (HPV) 16, 18 and 45 were assessed using multiplex fluorescent bead-based serology. Conditional logistic regression was used to estimate relative risks (RR) and 95% confidence intervals (CI) comparing women with positive vs. negative serology. A total of 40% of the study population was seropositive to at least one STI. Positive serology to C. trachomatis Pgp3 antibodies was not associated with EOC risk overall, but with higher risk of the mucinous histotype (RR = 2.30 [95% CI = 1.22-4.32]). Positive serology for chlamydia heat shock protein 60 (cHSP60-1) was associated with higher risk of EOC overall (1.36 [1.13-1.64]) and with the serous subtype (1.44 [1.12-1.85]). None of the other evaluated STIs were associated with EOC risk overall; however, HSV-2 was associated with higher risk of endometrioid EOC (2.35 [1.24-4.43]). The findings of our study suggest a potential role of C. trachomatis in the carcinogenesis of serous and mucinous EOC, while HSV-2 might promote the development of endometrioid disease.

Serum levels of hsa-miR-16-5p, hsa-miR-29a-3p, hsa-miR-150-5p, hsa-miR-155-5p and hsa-miR-223-3p and subsequent risk of chronic lymphocytic leukemia in the EPIC study.

Chronic lymphocytic leukemia (CLL) is an incurable disease accounting for almost one-third of leukemias in the Western world. Aberrant expression of microRNAs (miRNAs) is a well-established characteristic of CLL, and the robust nature of miRNAs makes them eminently suitable liquid biopsy biomarkers. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC), the predictive values of five promising human miRNAs (hsa-miR-16-5p, hsa-miR-29a-3p, hsa-miR-150-5p, hsa-miR-155-5p and hsa-miR-223-3p), identified in a pilot study, were examined in serum of 224 CLL cases (diagnosed 3 months to 18 years after enrollment) and 224 matched controls using Taqman based assays. Conditional logistic regressions were applied to adjust for potential confounders. The median time from blood collection to CLL diagnosis was 10 years (p25-p75: 7-13 years). Overall, the upregulation of hsa-miR-150-5p, hsa-miR-155-5p and hsa-miR-29a-3p was associated with subsequent risk of CLL [OR1∆Ct-unit increase (95%CI) = 1.42 (1.18-1.72), 1.64 (1.31-2.04) and 1.75 (1.31-2.34) for hsa-miR-150-5p, hsa-miR-155-5p and hsa-miR-29a-3p, respectively] and the strongest associations were observed within 10 years of diagnosis. However, the predictive performance of these miRNAs was modest (area under the curve <0.62). hsa-miR-16-5p and hsa-miR-223-3p levels were unrelated to CLL risk. The findings of this first prospective study suggest that hsa-miR-29a, hsa-miR-150-5p and hsa-miR-155-5p were upregulated in early stages of CLL but were modest predictive biomarkers of CLL risk.

Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility.

Impaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1: rg = 0.098, p = 2.3 × 10-8) and the ratio of FEV1 to forced vital capacity (FEV1/FVC: rg = 0.137, p = 2.0 × 10-12). Mendelian randomization analyses demonstrate that reduced FEV1 increases squamous cell carcinoma risk (odds ratio (OR) = 1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR = 1.17, 1.01-1.35) and lung cancer in never smokers (OR = 1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis.

A Transcriptome-Wide Association Study Identifies Novel Candidate Susceptibility Genes for Pancreatic Cancer.

BACKGROUND: Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. METHODS: To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples). RESULTS: We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. CONCLUSIONS: By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

Healthy lifestyle and the risk of pancreatic cancer in the EPIC study.

Pancreatic cancer (PC) is a highly fatal cancer with currently limited opportunities for early detection and effective treatment. Modifiable factors may offer pathways for primary prevention. In this study, the association between the Healthy Lifestyle Index (HLI) and PC risk was examined. Within the European Prospective Investigation into Cancer and Nutrition cohort, 1113 incident PC (57% women) were diagnosed from 400,577 participants followed-up for 15 years (median). HLI scores combined smoking, alcohol intake, dietary exposure, physical activity and, in turn, overall and central adiposity using BMI (HLIBMI) and waist-to-hip ratio (WHR, HLIWHR), respectively. High values of HLI indicate adherence to healthy behaviors. Cox proportional hazard models with age as primary time variable were used to estimate PC hazard ratios (HR) and 95% confidence intervals (CI). Sensitivity analyses were performed by excluding, in turn, each factor from the HLI score. Population attributable fractions (PAF) were estimated assuming participants' shift to healthier lifestyles. The HRs for a one-standard deviation increment of HLIBMI and HLIWHR were 0.84 (95% CI: 0.79, 0.89; ptrend = 4.3e-09) and 0.77 (0.72, 0.82; ptrend = 1.7e-15), respectively. Exclusions of smoking from HLIWHR resulted in HRs of 0.88 (0.82, 0.94; ptrend = 4.9e-04). The overall PAF estimate was 19% (95% CI: 11%, 26%), and 14% (6%, 21%) when smoking was removed from the score. Adherence to a healthy lifestyle was inversely associated with PC risk, beyond the beneficial role of smoking avoidance. Public health measures targeting compliance with healthy lifestyles may have an impact on PC incidence.

Consumption of nuts and seeds and pancreatic ductal adenocarcinoma risk in the European Prospective Investigation into Cancer and Nutrition.

Four epidemiologic studies have assessed the association between nut intake and pancreatic cancer risk with contradictory results. The present study aims to investigate the relation between nut intake (including seeds) and pancreatic ductal adenocarcinoma (PDAC) risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Cox proportional hazards models were used to estimate hazards ratio (HR) and 95% confidence intervals (95% CI) for nut intake and PDAC risk. Information on intake of nuts was obtained from the EPIC country-specific dietary questionnaires. After a mean follow-up of 14 years, 476,160 participants were eligible for the present study and included 1,283 PDAC cases. No association was observed between consumption of nuts and PDAC risk (highest intake vs nonconsumers: HR, 0.89; 95% CI, 0.72-1.10; p-trend = 0.70). Furthermore, no evidence for effect-measure modification was observed when different subgroups were analyzed. Overall, in EPIC, the highest intake of nuts was not statistically significantly associated with PDAC risk.