A Pooled Analysis of 15 Prospective Cohort Studies on the Association Between Fruit, Vegetable, and Mature Bean Consumption and Risk of Prostate Cancer.

BACKGROUND: Relationships between fruit, vegetable, and mature bean consumption and prostate cancer risk are unclear. METHODS: We examined associations between fruit and vegetable groups, specific fruits and vegetables, and mature bean consumption and prostate cancer risk overall, by stage and grade, and for prostate cancer mortality in a pooled analysis of 15 prospective cohorts, including 52,680 total cases and 3,205 prostate cancer deaths among 842,149 men. Diet was measured by a food frequency questionnaire or similar instrument at baseline. We calculated study-specific relative risks using Cox proportional hazards regression, and then pooled these estimates using a random effects model. RESULTS: We did not observe any statistically significant associations for advanced prostate cancer or prostate cancer mortality with any food group (including total fruits and vegetables, total fruits, total vegetables, fruit and vegetable juice, cruciferous vegetables, and tomato products), nor specific fruit and vegetables. Additionally, we observed few statistically significant results for other prostate cancer outcomes. Pooled multivariable relative risks comparing the highest versus lowest quantiles across all fruit and vegetable exposures and prostate cancer outcomes ranged from 0.89 to 1.09. There was no evidence of effect modification for any association by age or body mass index. CONCLUSIONS AND IMPACT: Results from this large, international, pooled analysis do not support a strong role of fruits, vegetables (including cruciferous vegetables and tomato products, although few studies assessed tomato sources of more bioavailable lycopene, the potential cancer preventive agent in tomatoes), or mature beans in prostate cancer

A comprehensive analysis of common genetic variation in prolactin (PRL) and PRL receptor (PRLR) genes in relation to plasma prolactin levels and breast cancer risk: the Multiethnic Cohort

<p>Abstract</p> <p>Background</p> <p>Studies in animals and humans clearly indicate a role for prolactin (PRL) in breast epithelial proliferation, differentiation, and tumorigenesis. Prospective epidemiological studies have also shown that women with higher circulating PRL levels have an increase in risk of breast cancer, suggesting that variability in PRL may also be important in determining a woman's risk.</p> <p>Methods</p> <p>We evaluated genetic variation in the PRL and PRL receptor (PRLR) genes as predictors of plasma PRL levels and breast cancer risk among African-American, Native Hawaiian, Japanese-American, Latina, and White women in the Multiethnic Cohort Study (MEC). We selected single nucleotide polymorphisms (SNPs) from both the public (dbSNP) and private (Celera) databases to construct high density SNP maps that included up to 20 kilobases (kb) upstream of the transcription initiation site and 10 kb downstream of the last exon of each gene, for a total coverage of 59 kb in PRL and 210 kb in PRLR. We genotyped 80 SNPs in PRL and 173 SNPs in PRLR in a multiethnic panel of 349 unaffected subjects to characterize linkage disequilibrium (LD) and haplotype patterns. We sequenced the coding regions of PRL and PRLR in 95 advanced breast cancer cases (19 of each racial/ethnic group) to uncover putative functional variation. A total of 33 and 60 haplotype "tag" SNPs (tagSNPs) that allowed for high predictability (R_h²≥ 0.70) of the common haplotypes in PRL and PRLR, respectively, were then genotyped in a multiethnic breast cancer case-control study of 1,615 invasive breast cancer cases and 1,962 controls in the MEC. We also assessed the association of common genetic variation with circulating PRL levels in 362 postmenopausal controls without a history of hormone therapy use at blood draw. Because of the large number of comparisons being performed we used a relatively stringent type I error criteria (p < 0.0005) for evaluating the significance of any single association to correct for performing approximately 100 independent tests, close to the number of tagSNPs genotyped for both genes.</p> <p>Results</p> <p>We observed no significant associations between PRL and PRLR haplotypes or individual SNPs in relation to breast cancer risk. A nominally significant association was noted between prolactin levels and a tagSNP (tagSNP 44, rs2244502) in intron 1 of PRL. This SNP showed approximately a 50% increase in levels between minor allele homozygotes vs. major allele homozygotes. However, this association was not significant (p = 0.002) using our type I error criteria to correct for multiple testing, nor was this SNP associated with breast cancer risk (p = 0.58).</p> <p>Conclusion</p> <p>In this comprehensive analysis covering 59 kb of the PRL locus and 210 kb of the PRLR locus, we found no significant association between common variation in these candidate genes and breast cancer risk or plasma PRL levels. The LD characterization of PRL and PRLR in this multiethnic population provide a framework for studying these genes in relation to other disease outcomes that have been associated with PRL, as well as for larger studies of plasma PRL levels.</p

Animal products, calcium and protein and prostate cancer risk in the Netherlands Cohort Study

Prostate cancer risk in relation to consumption of animal products, and intake of calcium and protein was investigated in the Netherlands Cohort Study. At baseline in 1986, 58,279 men aged 55-69 years completed a self-administered 150-item food frequency questionnaire and a questionnaire on other risk factors for cancer. After 6.3 years of follow-up, 642 prostate cancer cases were available for analysis. In multivariate case-cohort analyses adjusted for age, family history of prostate cancer and socioeconomic status, no associations were found for consumption of fresh meat, fish, cheese and eggs. Positive trends in risk were found for consumption of cured meat and milk products (P-values 0.04 and 0.02 respectively). For calcium and protein intake, no associations were observed. The hypothesis that dietary factors might be more strongly related to advanced prostate rumours could not be confirmed in our study. We conclude that, in this study, animal products are not strongly related to prostate cancer risk

Common genetic variation in IGF1, IGFBP-1, and IGFBP-3 in relation to mammographic density: a cross-sectional study

INTRODUCTION: Mammographic density is one of the strongest risk factors for breast cancer and is believed to represent epithelial and stromal proliferation. Because of the high heritability of breast density, and the role of the insulin-like growth factor (IGF) pathway in cellular proliferation and breast development, we examined the association between common genetic variation in this pathway and mammographic density. METHODS: We conducted a cross-sectional analysis among controls (n = 1,121) who were between the ages of 42 and 78 years at mammography, from a breast cancer case-control study nested within the Nurses' Health Study cohort. At the time of mammography, 204 women were premenopausal and 917 were postmenopausal. We genotyped 29 haplotype-tagging SNPs demonstrated to capture common genetic variation in IGF1, IGF binding protein (IGFBP)-1, and IGFBP-3. RESULTS: Common haplotype patterns in three of the four haplotype blocks spanning the gene encoding IGF1 were associated with mammographic density. Haplotype patterns in block 1 (p = 0.03), block 3 (p = 0.009), and block 4 (p = 0.007) were associated with mammographic density, whereas those in block 2 were not. None of the common haplotypes in the three haplotype blocks spanning the genes encoding IGFBP-1/IGFBP-3 were significantly associated with mammographic density. Two haplotype-tagging SNPs in IGF1, rs1520220 and rs2946834, showed a strong association with mammographic density. Those with the homozygous variant genotype for rs1520220 had a mean percentage mammographic density of 19.6% compared with those with the homozygous wild-type genotype, who had a mean percentage mammographic density of 27.9% (p for trend < 0.0001). Those that were homozygous variant for rs2946834 had a mean percentage mammographic density of 23.2% compared with those who were homozygous wild-type with a mean percentage mammographic density of 28.2% (p for trend = 0.0004). Permutation testing demonstrated that results as strong as these are unlikely to occur by chance (p = 0.0005). CONCLUSION: Common genetic variation in IGF1 is strongly associated with percentage mammographic density

Multi-center feasibility study evaluating recruitment, variability in risk factors and biomarkers for a diet and cancer cohort in India

<p>Abstract</p> <p>Background</p> <p>India's population exhibits diverse dietary habits and chronic disease patterns. Nutritional epidemiologic studies in India are primarily of cross-sectional or case-control design and subject to biases, including differential recall of past diet. The aim of this feasibility study was to evaluate whether a diet-focused cohort study of cancer could be established in India, providing insight into potentially unique diet and lifestyle exposures.</p> <p>Methods</p> <p>Field staff contacted 7,064 households within three regions of India (New Delhi, Mumbai, and Trivandrum) and found 4,671 eligible adults aged 35-69 years. Participants completed interviewer-administered questionnaires (demographic, diet history, physical activity, medical/reproductive history, tobacco/alcohol use, and occupational history), and staff collected biological samples (blood, urine, and toenail clippings), anthropometric measurements (weight, standing and sitting height; waist, hip, and thigh circumference; triceps, sub-scapula and supra-patella skin fold), and blood pressure measurements.</p> <p>Results</p> <p>Eighty-eight percent of eligible subjects completed all questionnaires and 67% provided biological samples. Unique protein sources by region were fish in Trivandrum, dairy in New Delhi, and pulses (legumes) in Mumbai. Consumption of meat, alcohol, fast food, and soft drinks was scarce in all three regions. A large percentage of the participants were centrally obese and had elevated blood glucose levels. New Delhi participants were also the least physically active and had elevated lipids levels, suggesting a high prevalence of metabolic syndrome.</p> <p>Conclusions</p> <p>A high percentage of participants complied with study procedures including biological sample collection. Epidemiologic expertise and sufficient infrastructure exists at these three sites in India to successfully carry out a modest sized population-based study; however, we identified some potential problems in conducting a cohort study, such as limited number of facilities to handle biological samples.</p

Non-randomness of the anatomical distribution of tumors

Background: Why does a tumor start where it does within an organ? Location is traditionally viewed as a random event, yet the statistics of the location of tumors argues against this being a random occurrence. There are numerous examples including that of breast cancer. More than half of invasive breast cancer tumors start in the upper outer quadrant of the breast near the armpit, even though it is estimated that only 35 to 40% of breast tissue is in this quadrant. This suggests that there is an unknown microenvironmental factor that significantly increases the risk of cancer in a spatial manner and that is not solely due to genes or toxins. We hypothesize that tumors are more prone to form in healthy tissue at microvascular ‘hot spots’ where there is a high local concentration of microvessels providing an increased blood flow that ensures an ample supply of oxygen, nutrients, and receptors for growth factors that promote the generation of new blood vessels. Results: To show the plausibility of our hypothesis, we calculated the fractional probability that there is at least one microvascular hot spot in each region of the breast assuming a Poisson distribution of microvessels in two-dimensional cross sections of breast tissue. We modulated the microvessel density in various regions of the breast according to the total hemoglobin concentration measured by near infrared diffuse optical spectroscopy in different regions of the breast. Defining a hot spot to be a circle of radius 200 μm with at least 5 microvessels, and using a previously measured mean microvessel density of 1 microvessel/mm2, we find good agreement of the fractional probability of at least one hot spot in different regions of the breast with the observed invasive tumor occurrence. However, there is no reason to believe that the microvascular distribution obeys a Poisson distribution. Conclusions: The spatial location of a tumor in an organ is not entirely random, indicating an unknown risk factor. Much work needs to be done to understand why a tumor occurs where it does. Electronic supplementary material The online version of this article (10.1186/s41236-017-0006-7) contains supplementary material, which is available to authorized users

Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer

We performed a multistage genome-wide association study (GWAS) including 7,683 individuals with pancreatic cancer and 14,397 controls of European descent. Four new loci reached genome-wide significance: rs6971499 at 7q32.3 (LINC-PINT; per-allele odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.74–0.84; P = 3.0×10−12), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2; OR = 1.46; 95% CI = 1.30–1.65; P = 1.1×10−10), rs9581943 at 13q12.2 (PDX1; OR = 1.15; 95% CI = 1.10–1.20; P = 2.4×10−9), and rs16986825 at 22q12.1 (ZNRF3; OR = 1.18; 95% CI = 1.12–1.25; P = 1.2×10−8). An independent signal was identified in exon 2 of TERT at the established region 5p15.33 (rs2736098; OR = 0.80; 95% CI = 0.76–0.85; P = 9.8×10−14). We also identified a locus at 8q24.21 (rs1561927; P = 1.3×10−7) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study has identified multiple new susceptibility alleles for pancreatic cancer worthy of follow-up studies

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling