An Assessment of Database-Validated microRNA Target Genes in Normal Colonic Mucosa: Implications for Pathway Analysis.

BACKGROUND: Determination of functional pathways regulated by microRNAs (miRNAs), while an essential step in developing therapeutics, is challenging. Some miRNAs have been studied extensively; others have limited information. In this study, we focus on 254 miRNAs previously identified as being associated with colorectal cancer and their database-identified validated target genes. METHODS: We use RNA-Seq data to evaluate messenger RNA (mRNA) expression for 157 subjects who also had miRNA expression data. In the replication phase of the study, we replicated associations between 254 miRNAs associated with colorectal cancer and mRNA expression of database-identified target genes in normal colonic mucosa. In the discovery phase of the study, we evaluated expression of 18 miR-NAs (those with 20 or fewer database-identified target genes along with miR-21-5p, miR-215-5p, and miR-124-3p which have more than 500 database-identified target genes) with expression of 17 434 mRNAs to identify new targets in colon tissue. Seed region matches between miRNA and newly identified targeted mRNA were used to help determine direct miRNA-mRNA associations. RESULTS: From the replication of the 121 miRNAs that had at least 1 database-identified target gene using mRNA expression methods, 97.9% were expressed in normal colonic mucosa. Of the 8622 target miRNA-mRNA associations identified in the database, 2658 (30.2%) were associated with gene expression in normal colonic mucosa after adjusting for multiple comparisons. Of the 133 miRNAs with database-identified target genes by non-mRNA expression methods, 97.2% were expressed in normal colonic mucosa. After adjustment for multiple comparisons, 2416 miRNA-mRNA associations remained significant (19.8%). Results from the discovery phase based on detailed examination of 18 miRNAs identified more than 80 000 miRNA-mRNA associations that had not previously linked to the miRNA. Of these miRNA-mRNA associations, 15.6% and 14.8% had seed matches for CRCh38 and CRCh37, respectively. CONCLUSIONS: Our data suggest that miRNA target gene databases are incomplete; pathways derived from these databases have similar deficiencies. Although we know a lot about several miRNAs, little is known about other miRNAs in terms of their targeted genes. We encourage others to use their data to continue to further identify and validate miRNA-targeted genes.

Cigarette Smoking and Breast Cancer Risk in Hispanic and Non-Hispanic White Women: The Breast Cancer Health Disparities Study.

OBJECTIVE: Few epidemiological studies have included Hispanics with the evaluation of the effects of cigarette smoking and breast cancer. We examined the relationship between cigarette smoking, ethnicity, and breast cancer risk using data from the Breast Cancer Health Disparities Study (BCHDS). MATERIALS AND METHODS: The BCHDS is a consortium of three population-based case-control studies, including U.S. non-Hispanic whites (NHWs) (1,525 cases; 1,593 controls), U.S. Hispanics/Native Americans (1,265 cases; 1,495 controls), and Mexican women (990 cases; 1,049 controls). Multivariable logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: Breast cancer risk was elevated among Mexican former smokers (OR 1.43, 95% CI 1.04-1.96) and among those who smoked ≥ 31 years (OR 1.95, 95% CI 1.13-3.35), compared to never smokers. In addition, Mexican former smokers with a history of alcohol consumption had increased breast cancer risk (OR 2.30, 95% CI 1.01-5.21). Among NHW premenopausal women, breast cancer risk was increased for smoking ≥ 20 cigarettes per day (OR 1.61, 95% CI 1.07-2.41). CONCLUSION: Our findings suggest the possibility of ethnic differences with the associations between cigarette smoking and breast cancer risk.

Accounting for dependence induced by weighted KNN imputation in paired samples, motivated by a colorectal cancer study.

Missing data can arise in bioinformatics applications for a variety of reasons, and imputation methods are frequently applied to such data. We are motivated by a colorectal cancer study where miRNA expression was measured in paired tumor-normal samples of hundreds of patients, but data for many normal samples were missing due to lack of tissue availability. We compare the precision and power performance of several imputation methods, and draw attention to the statistical dependence induced by K-Nearest Neighbors (KNN) imputation. This imputation-induced dependence has not previously been addressed in the literature. We demonstrate how to account for this dependence, and show through simulation how the choice to ignore or account for this dependence affects both power and type I error rate control.

MAPK genes interact with diet and lifestyle factors to alter risk of breast cancer: the Breast Cancer Health Disparities Study.

Mitogen-activated protein kinases (MAPK) are integration points for multiple biochemical signals. We evaluated 13 MAPK genes with breast cancer risk and determined if diet and lifestyle factors mediated risk. Data from 3 population-based case-control studies conducted in Southwestern United States, California, and Mexico included 4183 controls and 3592 cases. Percent Indigenous American (IA) ancestry was determined from 104 ancestry informative markers. The adaptive rank truncated product (ARTP) was used to determine the significance of each gene and the pathway with breast cancer risk, by menopausal status, genetic ancestry level, and estrogen receptor (ER)/progesterone receptor (PR) strata. MAP3K9 was associated with breast cancer overall (P(ARTP) = 0.02) with strongest association among women with the highest IA ancestry (P(ARTP) = 0.04). Several SNPs in MAP3K9 were associated with ER+/PR+ tumors and interacted with dietary oxidative balance score (DOBS), dietary folate, body mass index (BMI), alcohol consumption, cigarette smoking, and a history of diabetes. DUSP4 and MAPK8 interacted with calories to alter breast cancer risk; MAPK1 interacted with DOBS, dietary fiber, folate, and BMI; MAP3K2 interacted with dietary fat; and MAPK14 interacted with dietary folate and BMI. The patterns of association across diet and lifestyle factors with similar biological properties for the same SNPs within genes provide support for associations.

Diet and lifestyle factors modify immune/inflammation response genes to alter breast cancer risk and prognosis: the Breast Cancer Health Disparities Study.

Tumor necrosis factor-α (TNF) and toll-like receptors (TLR) are important mediators of inflammation. We examined 10 of these genes with respect to breast cancer risk and mortality in a genetically admixed population of Hispanic/Native American (NA) (2111 cases, 2597 controls) and non-Hispanic white (NHW) (1481 cases, 1585 controls) women. Additionally, we explored if diet and lifestyle factors modified associations with these genes. Overall, these genes (collectively) were associated with breast cancer risk among women with >70% NA ancestry (P(ARTP) = 0.0008), with TLR1 rs7696175 being the primary risk contributor (OR 1.77, 95% CI 1.25, 2.51). Overall, TLR1 rs7696175 (HR 1.40, 95% CI 1.03, 1.91; P(adj) = 0.032), TLR4 rs5030728 (HR 1.96, 95% CI 1.30, 2.95; P(adj) = 0.014), and TNFRSF1A rs4149578 (HR 2.71, 95% CI 1.28, 5.76; P(adj) = 0.029) were associated with increased breast cancer mortality. We observed several statistically significant interactions after adjustment for multiple comparisons, including interactions between our dietary oxidative balance score and CD40LG and TNFSF1A; between cigarette smoking and TLR1, TLR4, and TNF; between body mass index (BMI) among pre-menopausal women and TRAF2; and between regular use of aspirin/non-steroidal anti-inflammatory drugs and TLR3 and TRA2. In conclusion, our findings support a contributing role of certain TNF-α and TLR genes in both breast cancer risk and survival, particularly among women with higher NA ancestry. Diet and lifestyle factors appear to be important mediators of the breast cancer risk associated with these genes.

Diet and lifestyle factors interact with MAPK genes to influence survival: the Breast Cancer Health Disparities Study.

INTRODUCTION: MAPK genes are activated by a variety of factors related to growth factors, hormones, and environmental stress. METHODS: We evaluated associations between 13 MAPK genes and survival among 1,187 nonHispanic White and 1,155 Hispanic/Native American (NA) women diagnosed with breast cancer. We assessed the influence of diet, lifestyle, and genetic ancestry on these associations. Percent NA ancestry was determined from 104 Ancestry Informative Markers. Adaptive rank truncation product (ARTP) was used to determine gene and pathway significance. RESULTS: Associations were predominantly observed among women with lower NA ancestry. Specifically, the mitogen-activated protein kinases (MAPK) pathway was associated with all-cause mortality (P ARTP = 0.02), but not with breast cancer-specific mortality (P ARTP = 0.10). However, MAP2K1 and MAP3K9 were associated with both breast cancer-specific and all-cause mortality. MAPK12 (P ARTP = 0.05) was only associated with breast cancer-specific mortality, and MAP3K1 (P ARTP = 0.02) and MAPK1 (P ARTP = 0.05) were only associated with all-cause mortality. Among women with higher NA ancestry, MAP3K2 was significantly associated with all-cause mortality (P ARTP = 0.04). Several diet and lifestyle factors, including alcohol consumption, caloric intake, dietary folate, and cigarette smoking, significantly modified the associations with MAPK genes and all-cause mortality. CONCLUSIONS: Our study supports an association between MAPK genes and survival after diagnosis with breast cancer, especially among women with low NA ancestry. The interaction between genetic variation in the MAPK pathway with diet and lifestyle factors for all women supports the important role of these factors for breast cancer survivorship.

VEGFA, FLT1, KDR and colorectal cancer: assessment of disease risk, tumor molecular phenotype, and survival.

Angiogenesis is essential for tumor progression. Vascular endothelial growth factor (VEGFA) and its receptors 1 (FLT1) and 2 (KDR), have been identified as major mediators of this process. We hypothesized that genetic variation in FLT1 (38 SNPs), KDR (22 SNPS), and VEGFA (11 SNPs) would be associated with colon and rectal cancer development and survival. Data from a case-control study of 1555 colon cancer cases and 1956 controls and 754 rectal cancer cases and 959 controls were used. An adaptive rank truncation product (ARTP), based on 10,000 permutations, was used to determine the statistical significance of the candidate genes and angiogenesis pathway. Based on ARTP results, FLT1 was significantly associated with risk of colon cancer (P(ARTP) = 0.045) and VEGFA was significantly associated with rectal cancer (P(ARTP) = 0.036). After stratifying by tumor molecular subtype, SNP associations observed for colon cancer were: VEGFA rs2010963 with CIMP+ colon tumors; FLT1 rs4771249 and rs7987649 with TP53; FLT1 rs3751397, rs7337610, rs7987649, and rs9513008 and KDR rs10020464, rs11941492, and rs12498529 with MSI+ and CIMP+/KRAS2-mutated tumors. FLT1 rs2296189 and rs600640 were associated with CIMP+ rectal tumors and FLT1 rs7983774 was associated with TP53-mutated rectal tumors. Four SNPs in FLT1 were associated with colon cancer survival while three SNPs in KDR were associated with survival after diagnosis with rectal cancer. Aspirin/NSAID use, smoking cigarettes, and BMI modified the associations. These findings suggest the importance of inflammation and angiogenesis in the etiology of colorectal cancer and that genetic and lifestyle factors may be targets for modulating disease risk.

Diet and colorectal cancer: analysis of a candidate pathway using SNPS, haplotypes, and multi-gene assessment.

There is considerable biologic plausibility to the hypothesis that genetic variability in pathways involved in insulin signaling and energy homeostasis may modulate dietary risk associated with colorectal cancer. We utilized data from 2 population-based case-control studies of colon (n = 1,574 cases, 1,970 controls) and rectal (n = 791 cases, 999 controls) cancer to evaluate genetic variation in candidate SNPs identified from 9 genes in a candidate pathway: PDK1, RP6KA1, RPS6KA2, RPS6KB1, RPS6KB2, PTEN, FRAP1 (mTOR), TSC1, TSC2, Akt1, PIK3CA, and PRKAG2 with dietary intake of total energy, carbohydrates, fat, and fiber. We employed SNP, haplotype, and multiple-gene analysis to evaluate associations. PDK1 interacted with dietary fat for both colon and rectal cancer and with dietary carbohydrates for colon cancer. Statistically significant interaction with dietary carbohydrates and rectal cancer was detected by haplotype analysis of PDK1. Evaluation of dietary interactions with multiple genes in this candidate pathway showed several interactions with pairs of genes: Akt1 and PDK1, PDK1 and PTEN, PDK1 and TSC1, and PRKAG2 and PTEN. Analyses show that genetic variation influences risk of colorectal cancer associated with diet and illustrate the importance of evaluating dietary interactions beyond the level of single SNPs or haplotypes when a biologically relevant candidate pathway is examined.

Exploring multilocus associations of inflammation genes and colorectal cancer risk using hapConstructor.

BACKGROUND: In candidate-gene association studies of single nucleotide polymorphisms (SNPs), multilocus analyses are frequently of high dimensionality when considering haplotypes or haplotype pairs (diplotypes) and differing modes of expression. Often, while candidate genes are selected based on their biological involvement in a given pathway, little is known about the functionality of SNPs to guide association studies. Investigators face the challenge of exploring multiple SNP models to elucidate which variants, independently or in combination, might be associated with a disease of interest. A data mining module, hapConstructor (freely-available in Genie software) performs systematic construction and association testing of multilocus genotype data in a Monte Carlo framework. Our objective was to assess its utility to guide statistical analyses of haplotypes within a candidate region (or combined genotypes across candidate genes) beyond that offered by a standard logistic regression approach. METHODS: We applied the hapConstructor method to a multilocus investigation of candidate genes involved in pro-inflammatory cytokine IL6 production, IKBKB, IL6, and NFKB1 (16 SNPs total) hypothesized to operate together to alter colorectal cancer risk. Data come from two U.S. multicenter studies, one of colon cancer (1,556 cases and 1,956 matched controls) and one of rectal cancer (754 cases and 959 matched controls). RESULTS: hapConstructor enabled us to identify important associations that were further analyzed in logistic regression models to simultaneously adjust for confounders. The most significant finding (nominal P = 0.0004; false discovery rate q = 0.037) was a combined genotype association across IKBKB SNP rs5029748 (1 or 2 variant alleles), IL6 rs1800797 (1 or 2 variant alleles), and NFKB1 rs4648110 (2 variant alleles) which conferred an ~80% decreased risk of colon cancer. CONCLUSIONS: Strengths of hapConstructor were: systematic identification of multiple loci within and across genes important in CRC risk; false discovery rate assessment; and efficient guidance of subsequent logistic regression analyses.