A mixed methods evaluation of the unmet needs of early-onset colorectal cancer survivors.

PURPOSE: The incidence of colorectal cancer (CRC) is rising in people under age 50 (early-onset). Early-onset survivors face CRC during a critical point in their lives; many are establishing their families and careers. We sought to identify the unmet needs in a sample of early-onset CRC survivors and the resources they desired to address those needs. METHODS: We conducted a mixed methods study where participants completed the Cancer Survivors Unmet Needs (CaSUN) survey and a subsequent qualitative interview to expand on their unmet needs and desired resources. RESULTS: A total of 12 CRC survivors participated and 83% identified at least one unmet need, with an average of 13 unmet needs reported. Unmet needs were identified across every domain of the CaSUN measure, most commonly in the existential survivorship domain. Qualitative results demonstrated that survivors need more resources tailored for people their age and additional support for their families, including young children. CONCLUSION: Early-onset CRC survivors' needs are framed by the stage of their lives in which they are diagnosed, and the demand for interventions to support these survivors will continue to rise. The results of this study can inform future, tailored interventions for early-onset CRC survivors with substantial needs.

Machine Learning Approach to Facilitate Knowledge Synthesis at the Intersection of Liver Cancer, Epidemiology, and Health Disparities Research.

PURPOSE: Liver cancer is a global challenge, and disparities exist across multiple domains and throughout the disease continuum. However, liver cancer's global epidemiology and etiology are shifting, and the literature is rapidly evolving, presenting a challenge to the synthesis of knowledge needed to identify areas of research needs and to develop research agendas focusing on disparities. Machine learning (ML) techniques can be used to semiautomate the literature review process and improve efficiency. In this study, we detail our approach and provide practical benchmarks for the development of a ML approach to classify literature and extract data at the intersection of three fields: liver cancer, health disparities, and epidemiology. METHODS: We performed a six-phase process including: training (I), validating (II), confirming (III), and performing error analysis (IV) for a ML classifier. We then developed an extraction model (V) and applied it (VI) to the liver cancer literature identified through PubMed. We present precision, recall, F1, and accuracy metrics for the classifier and extraction models as appropriate for each phase of the process. We also provide the results for the application of our extraction model. RESULTS: With limited training data, we achieved a high degree of accuracy for both our classifier and for the extraction model for liver cancer disparities research literature performed using epidemiologic methods. The disparities concept was the most challenging to accurately classify, and concepts that appeared infrequently in our data set were the most difficult to extract. CONCLUSION: We provide a roadmap for using ML to classify and extract comprehensive information on multidisciplinary literature. Our technique can be adapted and modified for other cancers or diseases where disparities persist.

Genome-Wide Interaction Analyses between Genetic Variants and Alcohol Consumption and Smoking for Risk of Colorectal Cancer.

Genome-wide association studies (GWAS) have identified many genetic susceptibility loci for colorectal cancer (CRC). However, variants in these loci explain only a small proportion of familial aggregation, and there are likely additional variants that are associated with CRC susceptibility. Genome-wide studies of gene-environment interactions may identify variants that are not detected in GWAS of marginal gene effects. To study this, we conducted a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking using data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Interactions were tested using logistic regression. We identified interaction between CRC risk and alcohol consumption and variants in the 9q22.32/HIATL1 (Pinteraction = 1.76×10-8; permuted p-value 3.51x10-8) region. Compared to non-/occasional drinking light to moderate alcohol consumption was associated with a lower risk of colorectal cancer among individuals with rs9409565 CT genotype (OR, 0.82 [95% CI, 0.74-0.91]; P = 2.1×10-4) and TT genotypes (OR,0.62 [95% CI, 0.51-0.75]; P = 1.3×10-6) but not associated among those with the CC genotype (p = 0.059). No genome-wide statistically significant interactions were observed for smoking. If replicated our suggestive finding of a genome-wide significant interaction between genetic variants and alcohol consumption might contribute to understanding colorectal cancer etiology and identifying subpopulations with differential susceptibility to the effect of alcohol on CRC risk.

The Cancer Epidemiology Descriptive Cohort Database: A Tool to Support Population-Based Interdisciplinary Research.

BACKGROUND: We report on the establishment of a web-based Cancer Epidemiology Descriptive Cohort Database (CEDCD). The CEDCD's goals are to enhance awareness of resources, facilitate interdisciplinary research collaborations, and support existing cohorts for the study of cancer-related outcomes. METHODS: Comprehensive descriptive data were collected from large cohorts established to study cancer as primary outcome using a newly developed questionnaire. These included an inventory of baseline and follow-up data, biospecimens, genomics, policies, and protocols. Additional descriptive data extracted from publicly available sources were also collected. This information was entered in a searchable and publicly accessible database. We summarized the descriptive data across cohorts and reported the characteristics of this resource. RESULTS: As of December 2015, the CEDCD includes data from 46 cohorts representing more than 6.5 million individuals (29% ethnic/racial minorities). Overall, 78% of the cohorts have collected blood at least once, 57% at multiple time points, and 46% collected tissue samples. Genotyping has been performed by 67% of the cohorts, while 46% have performed whole-genome or exome sequencing in subsets of enrolled individuals. Information on medical conditions other than cancer has been collected in more than 50% of the cohorts. More than 600,000 incident cancer cases and more than 40,000 prevalent cases are reported, with 24 cancer sites represented. CONCLUSIONS: The CEDCD assembles detailed descriptive information on a large number of cancer cohorts in a searchable database. IMPACT: Information from the CEDCD may assist the interdisciplinary research community by facilitating identification of well-established population resources and large-scale collaborative and integrative research. Cancer Epidemiol Biomarkers Prev; 25(10); 1392-401. ©2016 AACR.

Fine-Mapping of Common Genetic Variants Associated with Colorectal Tumor Risk Identified Potential Functional Variants.

Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) associated with colorectal cancer risk. These SNPs may tag correlated variants with biological importance. Fine-mapping around GWAS loci can facilitate detection of functional candidates and additional independent risk variants. We analyzed 11,900 cases and 14,311 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. To fine-map genomic regions containing all known common risk variants, we imputed high-density genetic data from the 1000 Genomes Project. We tested single-variant associations with colorectal tumor risk for all variants spanning genomic regions 250-kb upstream or downstream of 31 GWAS-identified SNPs (index SNPs). We queried the University of California, Santa Cruz Genome Browser to examine evidence for biological function. Index SNPs did not show the strongest association signals with colorectal tumor risk in their respective genomic regions. Bioinformatics analysis of SNPs showing smaller P-values in each region revealed 21 functional candidates in 12 loci (5q31.1, 8q24, 11q13.4, 11q23, 12p13.32, 12q24.21, 14q22.2, 15q13, 18q21, 19q13.1, 20p12.3, and 20q13.33). We did not observe evidence of additional independent association signals in GWAS-identified regions. Our results support the utility of integrating data from comprehensive fine-mapping with expanding publicly available genomic databases to help clarify GWAS associations and identify functional candidates that warrant more onerous laboratory follow-up. Such efforts may aid the eventual discovery of disease-causing variant(s).

A Novel Pathway-Based Approach Improves Lung Cancer Risk Prediction Using Germline Genetic Variations.

BACKGROUND: Although genome-wide association studies (GWAS) have identified many genetic variants that are strongly associated with lung cancer, these variants have low penetrance and serve as poor predictors of lung cancer in individuals. We sought to increase the predictive value of germline variants by considering their cumulative effects in the context of biologic pathways. METHODS: For individuals in the Environment and Genetics in Lung Cancer Etiology study (1,815 cases/1,971 controls), we computed pathway-level susceptibility effects as the sum of relevant SNP variant alleles weighted by their log-additive effects from a separate lung cancer GWAS meta-analysis (7,766 cases/37,482 controls). Logistic regression models based on age, sex, smoking, genetic variants, and principal components of pathway effects and pathway-smoking interactions were trained and optimized in cross-validation and further tested on an independent dataset (556 cases/830 controls). We assessed prediction performance using area under the receiver operating characteristic curve (AUC). RESULTS: Compared with typical binomial prediction models that have epidemiologic predictors (AUC = 0.607) in addition to top GWAS variants (AUC = 0.617), our pathway-based smoking-interactive multinomial model significantly improved prediction performance in external validation (AUC = 0.656, P < 0.0001). CONCLUSIONS: Our biologically informed approach demonstrated a larger increase in AUC over nongenetic counterpart models relative to previous approaches that incorporate variants. IMPACT: This model is the first of its kind to evaluate lung cancer prediction using subtype-stratified genetic effects organized into pathways and interacted with smoking. We propose pathway-exposure interactions as a potentially powerful new contributor to risk inference. Cancer Epidemiol Biomarkers Prev; 25(8); 1208-15. ©2016 AACR.

CYP24A1 variant modifies the association between use of oestrogen plus progestogen therapy and colorectal cancer risk.

BACKGROUND: Menopausal hormone therapy (MHT) use has been consistently associated with a decreased risk of colorectal cancer (CRC) in women. Our aim was to use a genome-wide gene-environment interaction analysis to identify genetic modifiers of CRC risk associated with use of MHT. METHODS: We included 10 835 postmenopausal women (5419 cases and 5416 controls) from 10 studies. We evaluated use of any MHT, oestrogen-only (E-only) and combined oestrogen-progestogen (E+P) hormone preparations. To test for multiplicative interactions, we applied the empirical Bayes (EB) test as well as the Wald test in conventional case-control logistic regression as primary tests. The Cocktail test was used as secondary test. RESULTS: The EB test identified a significant interaction between rs964293 at 20q13.2/CYP24A1 and E+P (interaction OR (95% CIs)=0.61 (0.52-0.72), P=4.8 × 10(-9)). The secondary analysis also identified this interaction (Cocktail test OR=0.64 (0.52-0.78), P=1.2 × 10(-5) (alpha threshold=3.1 × 10(-4)). The ORs for association between E+P and CRC risk by rs964293 genotype were as follows: C/C, 0.96 (0.61-1.50); A/C, 0.61 (0.39-0.95) and A/A, 0.40 (0.22-0.73), respectively. CONCLUSIONS: Our results indicate that rs964293 modifies the association between E+P and CRC risk. The variant is located near CYP24A1, which encodes an enzyme involved in vitamin D metabolism. This novel finding offers additional insight into downstream pathways of CRC etiopathogenesis.

Common genetic variation and survival after colorectal cancer diagnosis: a genome-wide analysis.

Genome-wide association studies have identified several germline single nucleotide polymorphisms (SNPs) significantly associated with colorectal cancer (CRC) incidence. Common germline genetic variation may also be related to CRC survival. We used a discovery-based approach to identify SNPs related to survival outcomes after CRC diagnosis. Genome-wide genotyping arrays were conducted for 3494 individuals with invasive CRC enrolled in six prospective cohort studies (median study-specific follow-up = 4.2-8.1 years). In pooled analyses, we used Cox regression to assess SNP-specific associations with CRC-specific and overall survival, with additional analyses stratified by stage at diagnosis. Top findings were followed-up in independent studies. A P value threshold of P < 5×10(-8) in analyses combining discovery and follow-up studies was required for genome-wide significance. Among individuals with distant-metastatic CRC, several SNPs at 6p12.1, nearest the ELOVL5 gene, were statistically significantly associated with poorer survival, with the strongest associations noted for rs209489 [hazard ratio (HR) = 1.8, P = 7.6×10(-10) and HR = 1.8, P = 3.7×10(-9) for CRC-specific and overall survival, respectively). No SNPs were statistically significantly associated with survival among all cases combined or in cases without distant-metastases. SNPs in 6p12.1/ELOVL5 were associated with survival outcomes in individuals with distant-metastatic CRC, and merit further follow-up for functional significance. Findings from this genome-wide association study highlight the potential importance of genetic variation in CRC prognosis and provide clues to genomic regions of potential interest.

Identification of shared and unique susceptibility pathways among cancers of the lung, breast, and prostate from genome-wide association studies and tissue-specific protein interactions.

Results from genome-wide association studies (GWAS) have indicated that strong single-gene effects are the exception, not the rule, for most diseases. We assessed the joint effects of germline genetic variations through a pathway-based approach that considers the tissue-specific contexts of GWAS findings. From GWAS meta-analyses of lung cancer (12 160 cases/16 838 controls), breast cancer (15 748 cases/18 084 controls) and prostate cancer (14 160 cases/12 724 controls) in individuals of European ancestry, we determined the tissue-specific interaction networks of proteins expressed from genes that are likely to be affected by disease-associated variants. Reactome pathways exhibiting enrichment of proteins from each network were compared across the cancers. Our results show that pathways associated with all three cancers tend to be broad cellular processes required for growth and survival. Significant examples include the nerve growth factor (P = 7.86 × 10(-33)), epidermal growth factor (P = 1.18 × 10(-31)) and fibroblast growth factor (P = 2.47 × 10(-31)) signaling pathways. However, within these shared pathways, the genes that influence risk largely differ by cancer. Pathways found to be unique for a single cancer focus on more specific cellular functions, such as interleukin signaling in lung cancer (P = 1.69 × 10(-15)), apoptosis initiation by Bad in breast cancer (P = 3.14 × 10(-9)) and cellular responses to hypoxia in prostate cancer (P = 2.14 × 10(-9)). We present the largest comparative cross-cancer pathway analysis of GWAS to date. Our approach can also be applied to the study of inherited mechanisms underlying risk across multiple diseases in general.

A genome-wide association study for colorectal cancer identifies a risk locus in 14q23.1.

Over 50 loci associated with colorectal cancer (CRC) have been uncovered by genome-wide association studies (GWAS). Identifying additional loci has the potential to help elucidate aspects of the underlying biological processes leading to better understanding of the pathogenesis of the disease. We re-evaluated a GWAS by excluding controls that have family history of CRC or personal history of colorectal polyps, as we hypothesized that their inclusion reduces power to detect associations. This is supported empirically and through simulations. Two-phase GWAS analysis was performed in a total of 16,517 cases and 14,487 controls. We identified rs17094983, a SNP associated with risk of CRC [p = 2.5 × 10(-10); odds ratio estimated by re-including all controls (OR) = 0.87, 95% confidence interval (CI) 0.83-0.91; minor allele frequency (MAF) = 13%]. Results were replicated in samples of African descent (1894 cases and 4703 controls; p = 0.01; OR = 0.86, 95% CI 0.77-0.97; MAF = 16 %). Gene expression data in 195 colon adenocarcinomas and 59 normal colon tissues from two different studies revealed that this locus has genotypes that are associated with RTN1 (Reticulon 1) expression (p = 0.001), a protein-coding gene involved in survival and proliferation of cancer cells which is highly expressed in normal colon tissues but has significantly reduced expression in tumor cells (p = 1.3 × 10(-8)).

A large multiethnic genome-wide association study of prostate cancer identifies novel risk variants and substantial ethnic differences.

UNLABELLED: A genome-wide association study (GWAS) of prostate cancer in Kaiser Permanente health plan members (7,783 cases, 38,595 controls; 80.3% non-Hispanic white, 4.9% African-American, 7.0% East Asian, and 7.8% Latino) revealed a new independent risk indel rs4646284 at the previously identified locus 6q25.3 that replicated in PEGASUS (N = 7,539) and the Multiethnic Cohort (N = 4,679) with an overall P = 1.0 × 10(-19) (OR, 1.18). Across the 6q25.3 locus, rs4646284 exhibited the strongest association with expression of SLC22A1 (P = 1.3 × 10(-23)) and SLC22A3 (P = 3.2 × 10(-52)). At the known 19q13.33 locus, rs2659124 (P = 1.3 × 10(-13); OR, 1.18) nominally replicated in PEGASUS. A risk score of 105 known risk SNPs was strongly associated with prostate cancer (P < 1.0 × 10(-8)). Comparing the highest to lowest risk score deciles, the OR was 6.22 for non-Hispanic whites, 5.82 for Latinos, 3.77 for African-Americans, and 3.38 for East Asians. In non-Hispanic whites, the 105 risk SNPs explained approximately 7.6% of disease heritability. The entire GWAS array explained approximately 33.4% of heritability, with a 4.3-fold enrichment within DNaseI hypersensitivity sites (P = 0.004). SIGNIFICANCE: Taken together, our findings of independent risk variants, ethnic variation in existing SNP replication, and remaining unexplained heritability have important implications for further clarifying the genetic risk of prostate cancer. Our findings also suggest that there may be much promise in evaluating understudied variation, such as indels and ethnically diverse populations.

Identification of a common variant with potential pleiotropic effect on risk of inflammatory bowel disease and colorectal cancer.

Although genome-wide association studies (GWAS) have separately identified many genetic susceptibility loci for ulcerative colitis (UC), Crohn's disease (CD) and colorectal cancer (CRC), there has been no large-scale examination for pleiotropy, or shared genetic susceptibility, for these conditions. We used logistic regression modeling to examine the associations of 181 UC and CD susceptibility variants previously identified by GWAS with risk of CRC using data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. We also examined associations of significant variants with clinical and molecular characteristics in a subset of the studies. Among 11794 CRC cases and 14190 controls, rs11676348, the susceptibility single nucleotide polymorphism (SNP) for UC, was significantly associated with reduced risk of CRC (P = 7E-05). The multivariate-adjusted odds ratio of CRC with each copy of the T allele was 0.93 (95% CI 0.89-0.96). The association of the SNP with risk of CRC differed according to mucinous histological features (P heterogeneity = 0.008). In addition, the (T) allele was associated with lower risk of tumors with Crohn's-like reaction but not tumors without such immune infiltrate (P heterogeneity = 0.02) and microsatellite instability-high (MSI-high) but not microsatellite stable or MSI-low tumors (P heterogeneity = 0.03). The minor allele (T) in SNP rs11676348, located downstream from CXCR2 that has been implicated in CRC progression, is associated with a lower risk of CRC, particularly tumors with a mucinous component, Crohn's-like reaction and MSI-high. Our findings offer the promise of risk stratification of inflammatory bowel disease patients for complications such as CRC.

Mendelian randomization study of height and risk of colorectal cancer.

BACKGROUND: For men and women, taller height is associated with increased risk of all cancers combined. For colorectal cancer (CRC), it is unclear whether the differential association of height by sex is real or is due to confounding or bias inherent in observational studies. We performed a Mendelian randomization study to examine the association between height and CRC risk. METHODS: To minimize confounding and bias, we derived a weighted genetic risk score predicting height (using 696 genetic variants associated with height) in 10,226 CRC cases and 10,286 controls. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) for associations between height, genetically predicted height and CRC. RESULTS: Using conventional methods, increased height (per 10-cm increment) was associated with increased CRC risk (OR = 1.08, 95% CI = 1.02-1.15). In sex-specific analyses, height was associated with CRC risk for women (OR = 1.15, 95% CI = 1.05-1.26), but not men (OR = 0.98, 95% CI = 0.92-1.05). Consistent with these results, carrying greater numbers of (weighted) height-increasing alleles (per 1-unit increase) was associated with higher CRC risk for women and men combined (OR = 1.07, 95% CI = 1.01-1.14) and for women (OR = 1.09, 95% CI = .01-1.19). There was weaker evidence of an association for men (OR = 1.05, 95% CI = 0.96-1.15). CONCLUSION: We provide evidence for a causal association between height and CRC for women. The CRC-height association for men remains unclear and warrants further investigation in other large studies.

Mendelian Randomization Study of Body Mass Index and Colorectal Cancer Risk.

BACKGROUND: High body mass index (BMI) is consistently linked to increased risk of colorectal cancer for men, whereas the association is less clear for women. As risk estimates from observational studies may be biased and/or confounded, we conducted a Mendelian randomization study to estimate the causal association between BMI and colorectal cancer. METHODS: We used data from 10,226 colorectal cancer cases and 10,286 controls of European ancestry. The Mendelian randomization analysis used a weighted genetic risk score, derived from 77 genome-wide association study-identified variants associated with higher BMI, as an instrumental variable (IV). We compared the IV odds ratio (IV-OR) with the OR obtained using a conventional covariate-adjusted analysis. RESULTS: Individuals carrying greater numbers of BMI-increasing alleles had higher colorectal cancer risk [per weighted allele OR, 1.31; 95% confidence interval (CI), 1.10-1.57]. Our IV estimation results support the hypothesis that genetically influenced BMI is directly associated with risk for colorectal cancer (IV-OR per 5 kg/m(2), 1.50; 95% CI, 1.13-2.01). In the sex-specific IV analyses higher BMI was associated with higher risk of colorectal cancer among women (IV-OR per 5 kg/m(2), 1.82; 95% CI, 1.26-2.61). For men, genetically influenced BMI was not associated with colorectal cancer (IV-OR per 5 kg/m(2), 1.18; 95% CI, 0.73-1.92). CONCLUSIONS: High BMI was associated with increased colorectal cancer risk for women. Whether abdominal obesity, rather than overall obesity, is a more important risk factor for men requires further investigation. IMPACT: Overall, conventional epidemiologic and Mendelian randomization studies suggest a strong association between obesity and the risk of colorectal cancer.

Association of aspirin and NSAID use with risk of colorectal cancer according to genetic variants.

IMPORTANCE: Use of aspirin and other nonsteroidal anti-inflammatory drugs (NSAIDs) is associated with lower risk of colorectal cancer. OBJECTIVE: To identify common genetic markers that may confer differential benefit from aspirin or NSAID chemoprevention, we tested gene × environment interactions between regular use of aspirin and/or NSAIDs and single-nucleotide polymorphisms (SNPs) in relation to risk of colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS: Case-control study using data from 5 case-control and 5 cohort studies initiated between 1976 and 2003 across the United States, Canada, Australia, and Germany and including colorectal cancer cases (n=8634) and matched controls (n=8553) ascertained between 1976 and 2011. Participants were all of European descent. EXPOSURES: Genome-wide SNP data and information on regular use of aspirin and/or NSAIDs and other risk factors. MAIN OUTCOMES AND MEASURES: Colorectal cancer. RESULTS: Regular use of aspirin and/or NSAIDs was associated with lower risk of colorectal cancer (prevalence, 28% vs 38%; odds ratio [OR], 0.69 [95% CI, 0.64-0.74]; P = 6.2 × 10(-28)) compared with nonregular use. In the conventional logistic regression analysis, the SNP rs2965667 at chromosome 12p12.3 near the MGST1 gene showed a genome-wide significant interaction with aspirin and/or NSAID use (P = 4.6 × 10(-9) for interaction). Aspirin and/or NSAID use was associated with a lower risk of colorectal cancer among individuals with rs2965667-TT genotype (prevalence, 28% vs 38%; OR, 0.66 [95% CI, 0.61-0.70]; P = 7.7 × 10(-33)) but with a higher risk among those with rare (4%) TA or AA genotypes (prevalence, 35% vs 29%; OR, 1.89 [95% CI, 1.27-2.81]; P = .002). In case-only interaction analysis, the SNP rs16973225 at chromosome 15q25.2 near the IL16 gene showed a genome-wide significant interaction with use of aspirin and/or NSAIDs (P = 8.2 × 10(-9) for interaction). Regular use was associated with a lower risk of colorectal cancer among individuals with rs16973225-AA genotype (prevalence, 28% vs 38%; OR, 0.66 [95% CI, 0.62-0.71]; P = 1.9 × 10(-30)) but was not associated with risk of colorectal cancer among those with less common (9%) AC or CC genotypes (prevalence, 36% vs 39%; OR, 0.97 [95% CI, 0.78-1.20]; P = .76). CONCLUSIONS AND RELEVANCE: In this genome-wide investigation of gene × environment interactions, use of aspirin and/or NSAIDs was associated with lower risk of colorectal cancer, and this association differed according to genetic variation at 2 SNPs at chromosomes 12 and 15. Validation of these findings in additional populations may facilitate targeted colorectal cancer prevention strategies.

A model to determine colorectal cancer risk using common genetic susceptibility loci.

BACKGROUND & AIMS: Risk for colorectal cancer (CRC) can be greatly reduced through screening. To aid in the development of screening strategies, we refined models designed to determine risk of CRC by incorporating information from common genetic susceptibility loci. METHODS: By using data collected from more than 12,000 participants in 6 studies performed from 1990 through 2011 in the United States and Germany, we developed risk determination models based on sex, age, family history, genetic risk score (number of risk alleles carried at 27 validated common CRC susceptibility loci), and history of endoscopic examinations. The model was validated using data collected from approximately 1800 participants in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, conducted from 1993 through 2001 in the United States. RESULTS: We identified a CRC genetic risk score that independently predicted which patients in the training set would develop CRC. Compared with determination of risk based only on family history, adding the genetic risk score increased the discriminatory accuracy from 0.51 to 0.59 (P = .0028) for men and from 0.52 to 0.56 (P = .14) for women. We calculated age- and sex-specific 10-year CRC absolute risk estimates based on the number of risk alleles, family history, and history of endoscopic examinations. A model that included a genetic risk score better determined the recommended starting age for screening in subjects with and without family histories of CRC. The starting age for high-risk men (family history of CRC and genetic risk score, 90%) was 42 years, and for low-risk men (no family history of CRC and genetic risk score, 10%) was 52 years. For men with no family history and a high genetic risk score (90%), the starting age would be 47 years; this is an intermediate value that is 5 years earlier than it would be for men with a genetic risk score of 10%. Similar trends were observed in women. CONCLUSIONS: By incorporating information on CRC risk alleles, we created a model to determine the risk for CRC more accurately. This model might be used to develop screening and prevention strategies.

Genetic variants of adiponectin and risk of colorectal cancer.

Circulating adiponectin has been associated with lower risk of colorectal cancer (CRC). Genome-wide association studies have identified several single-nucleotide polymorphisms (SNPs) associated with adiponectin levels. However, it is unclear whether these SNPs are associated with CRC risk. In addition, previous data on SNPs in the adiponectin pathway and their associations with CRC are inconsistent. Therefore, we examined 19 SNPs in genes related to adiponectin or its receptors and their associations with CRC using logistic regression among 7,020 cases and 7,631 controls drawn from ten studies included in the Genetics and Epidemiology of Colorectal Cancer Consortium. Using data from a subset of two large cohort studies, we also assessed the contribution of individual SNPs and an adiponectin genetic score to plasma adiponectin after accounting for lifestyle factors among 2,217 women and 619 men. We did not find any statistically significant association between the 19 adiponectin-associated SNPs and CRC risk (multivariable-adjusted odds ratios ranged from 0.89 to 1.05, all p > 0.05). Each SNP explained less than 2.50% of the variance of plasma adiponectin, and the genetic score collectively accounted for 2.95 and 1.42% of the variability of adiponectin in women and men, respectively, after adjustment for age, body mass index, physical activity, smoking, alcohol consumption, regular use of aspirin or nonsteroidal anti-inflammatory drug and postmenopausal hormone use. In conclusion, our findings do not support an association between known adiponectin-related common SNPs and CRC incidence. However, known common SNPs account for only a limited proportion of the interindividual variance in circulating adiponectin. Further work is warranted to investigate the relationship between adiponectin and CRC while accounting for other components in the pathway.

Red meat intake, NAT2, and risk of colorectal cancer: a pooled analysis of 11 studies.

BACKGROUND: Red meat intake has been associated with risk of colorectal cancer, potentially mediated through heterocyclic amines. The metabolic efficiency of N-acetyltransferase 2 (NAT2) required for the metabolic activation of such amines is influenced by genetic variation. The interaction between red meat intake, NAT2 genotype, and colorectal cancer has been inconsistently reported. METHODS: We used pooled individual-level data from the Colon Cancer Family Registry and the Genetics and Epidemiology of Colorectal Cancer Consortium. Red meat intake was collected by each study. We inferred NAT2 phenotype based on polymorphism at rs1495741, highly predictive of enzyme activity. Interaction was assessed using multiplicative interaction terms in multivariate-adjusted models. RESULTS: From 11 studies, 8,290 colorectal cancer cases and 9,115 controls were included. The highest quartile of red meat intake was associated with increased risk of colorectal cancer compared with the lowest quartile [OR, 1.41; 95% confidence interval (CI), 1.29-1.55]. However, a significant association was observed only for studies with retrospective diet data, not for studies with diet prospectively assessed before cancer diagnosis. Combining all studies, high red meat intake was similarly associated with colorectal cancer in those with a rapid/intermediate NAT2 genotype (OR, 1.38; 95% CI, 1.20-1.59) as with a slow genotype (OR, 1.43; 95% CI, 1.28-1.61; P interaction = 0.9). CONCLUSION: We found that high red meat intake was associated with increased risk of colorectal cancer only from retrospective case-control studies and not modified by NAT2 enzyme activity. IMPACT: Our results suggest no interaction between NAT2 genotype and red meat intake in mediating risk of colorectal cancer.

BRCA1, BRCA2, PALB2, and CDKN2A mutations in familial pancreatic cancer: a PACGENE study.

PURPOSE: Familial pancreatic cancer kindreds contain at least two affected first-degree relatives. Comprehensive data are needed to assist clinical risk assessment and genetic testing. METHODS: Germ-line DNA samples from 727 unrelated probands with positive family history (521 met criteria for familial pancreatic cancer) were tested in compliance with the Clinical Laboratory Improvement Amendments for mutations in BRCA1 and BRCA2 (including analysis of deletions and rearrangements), PALB2, and CDKN2A. We compared prevalence of deleterious mutations between familial pancreatic cancer probands and nonfamilial pancreatic cancer probands (kindreds containing at least two affected biological relatives, but not first-degree relatives). We also examined the impact of family history on breast and ovarian cancers and melanoma. RESULTS: Prevalence of deleterious mutations (excluding variants of unknown significance) among familial pancreatic cancer probands was: BRCA1, 1.2%; BRCA2, 3.7%; PALB2, 0.6%; and CDKN2A, 2.5%. Four novel deleterious mutations were detected. Familial pancreatic cancer probands carry more mutations in the four genes (8.0%) than nonfamilial pancreatic cancer probands (3.5%) (odds ratio: 2.40; 95% confidence interval: 1.06-5.44; P = 0.03). The probability of testing positive for deleterious mutations in any of the four genes ranges up to 10.4%, depending on family history of cancers. BRCA2 and CDKN2A account for the majority of mutations in familial pancreatic cancer. CONCLUSION: Genetic testing of multiple relevant genes in probands with a positive family history is warranted, particularly for familial pancreatic cancer.

No evidence of gene-calcium interactions from genome-wide analysis of colorectal cancer risk.

BACKGROUND: Calcium intake may reduce risk of colorectal cancer, but the mechanisms remain unclear. Studies of interaction between calcium intake and SNPs in calcium-related pathways have yielded inconsistent results. METHODS: To identify gene-calcium interactions, we tested interactions between approximately 2.7 million SNPs across the genome with self-reported calcium intake (from dietary or supplemental sources) in 9,006 colorectal cancer cases and 9,503 controls of European ancestry. To test for multiplicative interactions, we used multivariable logistic regression and defined statistical significance using the conventional genome-wide α = 5E-08. RESULTS: After accounting for multiple comparisons, there were no statistically significant SNP interactions with total, dietary, or supplemental calcium intake. CONCLUSIONS: We found no evidence of SNP interactions with calcium intake for colorectal cancer risk in a large population of 18,509 individuals. IMPACT: These results suggest that in genome-wide analysis common genetic variants do not strongly modify the association between calcium intake and colorectal cancer in European populations.