Association Studies Of Cancer Research Articles

Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations.

Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR.

Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types.

Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis. We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.

Pleiotropic Analysis of Lung Cancer and Blood Triglycerides.

Epidemiologically related traits may share genetic risk factors, and pleiotropic analysis could identify individual loci associated with these traits. Because of their shared epidemiological associations, we conducted pleiotropic analysis of genome-wide association studies of lung cancer (12 160 lung cancer case patients and 16 838 control subjects) and cardiovascular disease risk factors (blood lipids from 188 577 subjects, type 2 diabetes from 148 821 subjects, body mass index from 123 865 subjects, and smoking phenotypes from 74 053 subjects). We found that 6p22.1 (rs6904596, ZNF184) was associated with both lung cancer (P = 5.50x10(-6)) and blood triglycerides (P = 1.39x10(-5)). We replicated the association in 6097 lung cancer case patients and 204 657 control subjects (P = 2.40 × 10(-4)) and in 71 113 subjects with triglycerides data (P = .01). rs6904596 reached genome-wide significance in lung cancer meta-analysis (odds ratio = 1.15, 95% confidence interval = 1.10 to 1.21 ,: Pcombined = 5.20x10(-9)). The large sample size provided by the lipid GWAS data and the shared genetic risk factors between the two traits contributed to the uncovering of a hitherto unidentified genetic locus for lung cancer.

Classification of Missense Variants in XRCC2 by Functional Analysis: Implications for Breast Cancer Association Studies.

XRCC2 belongs to the family of RAD51 paralogs, which are involved in homologous recombination repair (HRR) of DNA double-strand breaks. Variants in XRCC2 have recently been suggested to increase the risk for breast cancer. However, this finding could not be confirmed in a second study. Both case-control studies lacked power due to the rarity of deleterious XRCC2 mutations, and therefore rare missense variants predicted to be damaging by in silico analysis had been included in the analyses. But is incorporating purely in silico predictions for variant pathogenicity advised when conducting association studies? In this issue, Hilbers et al. (Hum Mutat 37:914–925, 2016) examined 23 previously reported XRCC2 missense variants with four different in silico prediction algorithms, including AlignGVGD, SIFT, PolyPhen2, and CADD, to estimate whether the variants were likely to be pathogenic. The functional effects of the XRCC2 missense variants were subsequently examined by testing their ability to complement the DNA repair phenotype of XRCC2-deficient cells, as well as measuring the efficiency of the variants to perform HRR in hamster and human cells. The experiments revealed that the in silico predictions correlated poorly with the observed functional effects. When the novel functional data were included in case-control studies, there no longer was an association with breast cancer. The authors conclude that if XRCC2 variants predispose to breast cancer, the associated variants are likely to be restricted to protein-truncating mutations as well as few missense variants. Next-generation sequencing is expected to increase the number of rare variants identified in novel cancer-predisposing genes, which poses challenges to risk estimation through patient cohorts and cosegregation analysis. The study by Hilbers et al. highlights the importance of functional analysis of variants of unknown clinical significance and demonstrates the pitfalls in establishing an association between rare missense variants and disease risk.

Abstract 2569: A genome wide association study of lung cancer identifies 11 novel susceptibility loci

Abstract Background Genome wide association studies (GWAS) of lung cancer have identified susceptibility loci at 15q25, 5p15, 6p21, 13q13 and 22q12 that contain relevant candidate genes such as CHRNA3/5, TERT, HLA, BRCA2 and CHEK2, respectively. Many of these alleles appear more relevant to a particularly histological type of lung cancer. With the aim of identifying novel lung cancer susceptibility loci, The Transdisciplinary Research in Cancer of the Lung (TRICL), the International Lung Cancer Consortium (ILCCO) and Lung Cancer Cohort Consortium (LC3) have undertaken a very large collaborative GWAS across 29 lung cancer studies, including analysis of the predominant lung cancer histological subtypes. Methods In collaboration with the Center for Disease Research (CIDR), TRICL, ILCCO and LC3 have genotyped 18,000 case-control pairs on the GAME-On Oncoarray. SNP imputation was undertaken using the 1,000 Genomes v3 reference panel, followed by logistic regression of each genetic variant with lung cancer and considering ancestry inferred by genetic profile to correct for cryptic population structure. The OncoArray and our previous GWAS results were combined using meta-analysis. This allowed for a GWAS of 10,155,682 SNPs for 25,655 lung cancer cases and 52,451 controls, as well as histology specific analysis of 6,629 squamous cell and 9,817 adenocarcinomas. Alternate genotyping techniques (Affymetrix, Taqman) were used to confirm the fidelity of the genotyping for variants of interest. Results We have identified common genetic variants exceeding genome wide significance (p&amp;lt;5×10-8) at eleven novel susceptibility loci. This included two associated with overall lung cancer (1p31, 19q13), eight with lung adenocarcinomas (3q28, 6p25, 8p12, 9p21, 10q25, 11q23, 15q21, 20q13) and one with squamous-cell lung carcinomas (10q24). These genetic variants are located near several intriguing candidate genes, such as telomere function genes (OBFC1, RTEL1), nicotine metabolism genes (CYP2A6), genes somatically mutated in lung cancer (NRG1) and genetic susceptibility loci linked to other cancers (IRF4, CDNK2A). In additional, we noted several borderline (p&amp;lt;10-6) associations with common variants located near nicotine addiction genes (CHRNB2, CHRNA2, CHRNA4, DBH) and other genes somatically translocated in lung cancer (ROS1). Integration of eQTL databases suggests that many of the associated genetic variants influence gene expression levels of these candidate genes. Conclusion We have identified eleven novel lung cancer susceptibility loci, doubling the number implicated by GWAS. These genetic variants were common (MAF 0.05-0.49) with modest to small genetic effects (OR's 1.10-1.17). Further expansion of GWAS efforts, particularly within histological subtypes of lung cancer, is likely to identify additional susceptibility loci and further increase our understanding of lung cancer aetiology. Citation Format: James Dowling Mckay, Yafang Li, Younghun Han, Xiangjun Xioa, John Field, Xuchen Zong, Heike Bickeböller, David C. Christiani, Paul Brennan, Maria-Teresa Landi, Rayjean Hung, Christopher I. Amos, on behalf of the OncoArray Lung Cancer Group. A genome wide association study of lung cancer identifies 11 novel susceptibility loci. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2569.

Abstract 2568: Meta-analysis of genome-wide association studies identifies multiple lung cancer susceptibility loci in never-smoking Asian women

Abstract Background: The incidence rates of lung cancer among never-smoking females in some parts of East Asia are among the highest in the world. Genome-wide association studies (GWAS) of lung cancer in Asian never-smoking women have previously identified six susceptibility loci associated with lung cancer risk including 3q28, 5p15.33, 6p21.32, 6q22.2, 10q25.2 and 17q24.3. This study aims to discover additional lung cancer susceptibility loci among never-smoking Asian females. Methods: We imputed data from four GWAS of Asian non-smoking female lung cancer (6,877 cases and 6,277 controls) using the 1,000 Genomes Project (Phase 1 Release 3) data as the reference and genotyped additional samples (5,878 cases and 7,046 controls) for potential replication. Results: In our meta-analysis, three new loci achieved genome-wide significance, marked by the single nucleotide polymorphisms rs7741164 at 6p21.1 (per-allele odds ratio (OR) = 1.17; P = 5.8 × 10-13), rs72658409 at 9p21.3 (per-allele OR = 0.77; P = 1.41 ×10-10), and rs11610143 at 12q13.13 (per-allele OR = 0.89; P = 4.96 ×10-9). Conclusions: We identified new genetic susceptibility alleles for lung cancer in never-smoking women in Asia. These findings merit follow-up to understand their biological underpinnings and potential interactions with environmental exposures. Citation Format: Qing Lan, Zhaoming Wang, Wei Jie Seow, Kouya Shiraishi, Hongbing Shen, Chao A. Hsiung, Keitaro Matsuo, Jie Liu, Kexin Chen, Taiki Yamji, Yang Yang, I-Shou Chang, Chen Wu, Meredith Yeager, Takashi Kohno, Wei Zheng, Xiao-Ou Shu, Pan-Chyr Yang, Tangchun Wu, Dongxin Lin, Baosen Zhou, Jinming Yu, Michiaki Kubo, Stephen J. Chanock, Nathaniel Rothman. Meta-analysis of genome-wide association studies identifies multiple lung cancer susceptibility loci in never-smoking Asian women. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2568.

Genome-Wide Association Study of Bladder Cancer in a Chinese Cohort Reveals a New Susceptibility Locus at 5q12.3

Genome-wide association studies (GWAS) of bladder cancer have identified a number of susceptibility loci in European populations but have yet to uncover the genetic determinants underlying bladder cancer incidence among other ethnicities. Therefore, we performed the first GWAS in a Chinese cohort comprising 3,406 cases of bladder cancer and 4,645 controls. We identified a new susceptibility locus for bladder cancer at 5q12.3, located in the intron of CWC27 (rs2042329), that was significantly associated with disease risk (OR = 1.40; P = 4.61 × 10(-11)). However, rs2042329 was not associated with bladder cancer risk in patients of European descent. The rs2042329 risk allele was also related to significantly increased expression levels of CWC27 mRNA and protein in bladder cancer tissues from Chinese patients. Additional functional analyses suggested that CWC27 played an oncogenic role in bladder cancer by inducing cell proliferation and suppressing apoptosis. In conclusion, the identification of a risk-associated locus at 5q12.3 provides new insights into the inherited susceptibility to bladder cancer in Chinese populations and may help to identify high-risk individuals. Cancer Res; 76(11); 3277-84. ©2016 AACR.

Genome-wide association study confirms lung cancer susceptibility loci on chromosomes 5p15 and 15q25 in an African-American population

ObjectivesGenome-wide association studies (GWAS) of lung cancer have identified regions of common genetic variation with lung cancer risk in Europeans who smoke and never-smoking Asian women. This study aimed to conduct a GWAS in African Americans, who have higher rates of lung cancer despite smoking fewer cigarettes per day when compared with Caucasians. This population provides a different genetic architecture based on underlying African ancestry allowing the identification of new regions and exploration of known regions for finer mapping. Materials and methodsWe genotyped 1,024,001 SNPs in 1737 cases and 3602 controls in stage 1, followed by a replication phase of 20 SNPs (p<1.51×10−5) in an independent set of 866 cases and 796 controls in stage 2. Results and conclusionIn the combined analysis, we confirmed two loci to be associated with lung cancer that achieved the threshold of genome-wide significance: 15q25.1 marked by rs2036527 (p=1.3×10−9; OR=1.32; 95% CI=1.20–1.44) near CHRNA5, and 5p15.33 marked by rs2853677 (p=2.8×10−9; OR=1.28; 95% CI=1.18–1.39) near TERT. The association with rs2853677 is driven by the adenocarcinoma subtype of lung cancer (p=1.3×10−8; OR=1.37; 95% CI=1.23–1.54). No SNPs reached genome-wide significance for either of the main effect models examining smoking − cigarettes per day and current or former smoker. Our study was powered to identify strong risk loci for lung cancer in African Americans; we confirmed results previously reported in African Americans and other populations for two loci near plausible candidate genes, CHRNA5 and TERT, on 15q25.1 and 5p15.33 respectively, are associated with lung cancer. Additional work is required to map and understand the biological underpinnings of the strong association of these loci with lung cancer risk in African Americans.

Systematic meta-analyses of gene-specific genetic association studies in prostate cancer.

In the past twenty-five years, over 700 case-control association studies on the risk of prostate cancer have been published worldwide, but their results were largely inconsistent. To facilitate following and explaining these findings, we performed a systematic meta-analysis using allelic contrasts for gene-specific SNVs from at least three independent population-based case-control studies, which were published in the field of prostate cancer between August 1, 1990 and August 1, 2015. Across 66 meta-analyses, a total of 20 genetic variants involving 584,100 subjects in 19 different genes (KLK3, IGFBP3, ESR1, SOD2, CAT, CYP1B1, VDR, RFX6, HNF1B, SRD5A2, FGFR4, LEP, HOXB13, FAS, FOXP4, SLC22A3, LMTK2, EHBP1 and MSMB) exhibited significant association with prostate cancer. The average summary OR was 1.33 (ranging from: 1.016–3.788) for risk alleles and 0.838 (ranging from: 0.757–0.896) for protective alleles. Of these positive variants, FOXP4 rs1983891, LMTK2 rs6465657 and RFX6 rs339331 had not been previously meta-analyzed. Further analyses with sufficient power design and investigations of the potential biological roles of these genetic variants in prostate cancer should be conducted.

Meta-analysis of genome-wide association studies identifies multiple lung cancer susceptibility loci in never-smoking Asian women.

Genome-wide association studies (GWAS) of lung cancer in Asian never-smoking women have previously identified six susceptibility loci associated with lung cancer risk. To further discover new susceptibility loci, we imputed data from four GWAS of Asian non-smoking female lung cancer (6877 cases and 6277 controls) using the 1000 Genomes Project (Phase 1 Release 3) data as the reference and genotyped additional samples (5878 cases and 7046 controls) for possible replication. In our meta-analysis, three new loci achieved genome-wide significance, marked by single nucleotide polymorphism (SNP) rs7741164 at 6p21.1 (per-allele odds ratio (OR) = 1.17; P = 5.8 × 10(-13)), rs72658409 at 9p21.3 (per-allele OR = 0.77; P = 1.41 × 10(-10)) and rs11610143 at 12q13.13 (per-allele OR = 0.89; P = 4.96 × 10(-9)). These findings identified new genetic susceptibility alleles for lung cancer in never-smoking women in Asia and merit follow-up to understand their biological underpinnings.

Identification of new susceptibility loci for gastric non-cardia adenocarcinoma: pooled results from two Chinese genome-wide association studies

ObjectiveAlthough several genome-wide association studies (GWAS) of non-cardia gastric cancer have been published, more novel association signals could be exploited by combining individual studies together, which will further elucidate the...

Hard Work Ahead: Fine Mapping and Functional Follow-up of Susceptibility Alleles in Cancer GWAS

Genome-wide association studies (GWAS) in cancer have successfully identified over 450 regions that harbor susceptibility alleles with small effects contributing to the risk of one or more cancers. Less than 10 % of the regions identified thus far are common to more than one cancer, but it is these regions which display pleiotropy that are especially informative and provide new opportunities to gain insights into common mechanisms of carcinogenesis. Since the GWAS age has been notable for scalability, large-scale consortia have successfully combined many studies to identify novel regions associated with risk for cancer. In fact, for common cancers, a substantial fraction of markers for common alleles have been identified, and additional studies of the cumulative “polygenic” effect of large scans further suggest that many additional alleles remain to be characterized. The emerging catalog of common variants, which represents a fraction of the underlying genetic architecture of cancer susceptibility, already constitutes a set for common cancers that could be used in stratification and public health measures. On the other hand, the discovery of many regions is occurring at a rate that exceeds our capacity to understand the underlying biology contributing to each risk allele. Nearly all susceptibility regions harbor one or more variants that point towards changes in the regulation of key genes and pathways and not protein coding changes resulting in “drivers” of somatic alterations. Further investigation of each region depends upon the sequence of fine mapping (e.g., identification of correlated variants) using in silico functional tools to nominate the most promising variants for detailed laboratory follow-up studies. Each region has to be interrogated individually, taking into account the unique features of each genomic locale in order to understand the biological underpinnings of the susceptibility variants. Building a comprehensive catalog of susceptibility alleles, across a spectrum of frequencies and effect sizes, and functional annotation of these should be instrumental in revealing new cancer biology and eventually used in precision prevention.

Genome-wide association study of gastric adenocarcinoma in Asia: a comparison of associations between cardia and non-cardia tumours

Genome-wide association studies (GWAS) of gastric cancer have reported differences in single-nucleotide polymorphism (SNP) associations for tumour subtypes, particularly when divided by location into the gastric cardia versus the non-cardia. Here we present results for a GWAS using 2350 East Asian gastric cancer cases divided as 1189 gastric cardia and 1027 gastric non-cardia cases and 2708 controls. We also included up to 3042 cardia cases, 4359 non-cardia cases and 7548 controls for replication from two Chinese studies and one Korean study. From the GWAS, we selected 12 top SNPs for each gastric cancer subtype, 4 top SNPs for total gastric cancer and 1 SNP in MUC1 for replication testing. We observed genome-wide significant associations for rs10074991 in PRKAA1 at 5p13.1 for cardia (p=7.36×10(-12)) and non-cardia cancers (p=2.42×10(-23)) with per allele OR (95% CI) for the combined endpoint of 0.80 (0.77 to 0.83). At 6p21.1, rs2294693 near UNC5CL was significantly associated with gastric non-cardia cancer risk (p=2.50×10(-8)), with OR (95% CI) of 1.18 (1.12 to 1.26), but there was only a nominal association for cardia cancer (p=1.47×10(-2)). We also confirmed a previously reported association for rs4072037 in MUC1 with p=6.59×10(-8) for total gastric cancer and similar estimates for cardia and non-cardia cancers. Three SNPs in PSCA previously reported to be associated with gastric non-cardia cancer showed no apparent association for cardia cancer. Our results suggest that associations for SNPs with gastric cancer show some different results by tumour location in the stomach.

A new GWAS and meta-analysis with 1000Genomes imputation identifies novel risk variants for colorectal cancer.

Genome-wide association studies (GWAS) of colorectal cancer (CRC) have identified 23 susceptibility loci thus far. Analyses of previously conducted GWAS indicate additional risk loci are yet to be discovered. To identify novel CRC susceptibility loci, we conducted a new GWAS and performed a meta-analysis with five published GWAS (totalling 7,577 cases and 9,979 controls of European ancestry), imputing genotypes utilising the 1000 Genomes Project. The combined analysis identified new, significant associations with CRC at 1p36.2 marked by rs72647484 (minor allele frequency [MAF] = 0.09) near CDC42 and WNT4 (P = 1.21 × 10−8, odds ratio [OR] = 1.21 ) and at 16q24.1 marked by rs16941835 (MAF = 0.21, P = 5.06 × 10−8; OR = 1.15) within the long non-coding RNA (lncRNA) RP11-58A18.1 and ~500 kb from the nearest coding gene FOXL1. Additionally we identified a promising association at 10p13 with rs10904849 intronic to CUBN (MAF = 0.32, P = 7.01 × 10-8; OR = 1.14). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC. Additionally, our analysis further demonstrates that imputation can be used to exploit GWAS data to identify novel disease-causing variants.

Association of 42 SNPs with genetic risk for cervical cancer: an extensive meta-analysis.

BackgroundA large number of single nucleotide polymorphisms (SNPs) associated with cervical cancer have been identified through candidate gene association studies and genome-wide association studies (GWAs). However, some studies have yielded different results for the same SNP. To obtain a more comprehensive understanding, we performed a meta-analysis on previously published case–control studies involving the SNPs associated with cervical cancer.MethodsElectronic searches of PubMed and Embase were conducted for all publications about the association between gene polymorphisms and cervical cancer. One-hundred and sixty-seven association studies were included in our research. For each SNP, three models (the allele, dominant and recessive effect models) were adopted in the meta-analysis. For each model, the effect summary odds ratio (OR) and 95% CI were calculated. Heterogeneity between studies was evaluated by Cochran’s Q test. If the p value of Q test was less than 0.01, a random effect model was used; otherwise, a fixed effect model was used.ResultsThe results of our meta-analysis showed that: (1) There were 8, 2 and 8 SNPs that were significantly associated with cervical cancer (P < 0.01) in the allele, dominant and recessive effect models, respectively. (2) rs1048943 (CYP1A1 A4889G) showed the strongest association with cervical cancer in the allele effect model (1.83[1.57, 2.13]); in addition, rs1048943 (CYP1A1 A4889G) had a very strong association in the dominant and recessive effect model. (3) 15, 11 and 10 SNPs had high heterogeneity (P < 0.01) in the three models, respectively. (4) There was no published bias for most of the SNPs according to Egger’s test (P < 0.01) and Funnel plot analysis. For some SNPs, their association with cervical cancer was only tested in a few studies and, therefore, might have been subjected to published bias. More studies on these loci are required.ConclusionOur meta-analysis provides a comprehensive evaluation of cervical cancer association studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12881-015-0168-z) contains supplementary material, which is available to authorized users.

Use of a urinary sugars biomarker to assess measurement error in self-reported sugars intake in the nutrition and physical activity assessment study (NPAAS).

Measurement error in self-reported sugars intake may be obscuring the association between sugars and cancer risk in nutritional epidemiologic studies. We used 24-hour urinary sucrose and fructose as a predictive biomarker for total sugars, to assess measurement error in self-reported sugars intake. The Nutrition and Physical Activity Assessment Study (NPAAS) is a biomarker study within the Women's Health Initiative (WHI) Observational Study that includes 450 postmenopausal women ages 60 to 91 years. Food Frequency Questionnaires (FFQ), four-day food records (4DFR), and three 24-hour dietary recalls (24HRs) were collected along with sugars and energy dietary biomarkers. Using the biomarker, we found self-reported sugars to be substantially and roughly equally misreported across the FFQ, 4DFR, and 24HR. All instruments were associated with considerable intake- and person-specific bias. Three 24HRs would provide the least attenuated risk estimate for sugars (attenuation factor, AF = 0.57), followed by FFQ (AF = 0.48) and 4DFR (AF = 0.32), in studies of energy-adjusted sugars and disease risk. In calibration models, self-reports explained little variation in true intake (5%-6% for absolute sugars and 7%-18% for sugars density). Adding participants' characteristics somewhat improved the percentage variation explained (16%-18% for absolute sugars and 29%-40% for sugars density). None of the self-report instruments provided a good estimate of sugars intake, although overall 24HRs seemed to perform the best. Assuming the calibrated sugars biomarker is unbiased, this analysis suggests that measuring the biomarker in a subsample of the study population for calibration purposes may be necessary for obtaining unbiased risk estimates in cancer association studies.

Multiple functional risk variants in a SMAD7 enhancer implicate a colorectal cancer risk haplotype.

Genome-wide association studies (GWAS) of colorectal cancer (CRC) have led to the identification of a number of common variants associated with modest risk. Several risk variants map within the vicinity of TGFβ/BMP signaling pathway genes, including rs4939827 within an intron of SMAD7 at 18q21.1. A previous study implicated a novel SNP (novel 1 or rs58920878) as a functional variant within an enhancer element in SMAD7 intron 4. In this study, we show that four SNPs including novel 1 (rs6507874, rs6507875, rs8085824, and rs58920878) in linkage disequilibrium (LD) with the index SNP rs4939827 demonstrate allele-specific enhancer effects in a large, multi-component enhancer of SMAD7. All four SNPs demonstrate allele-specific protein binding to nuclear extracts of CRC cell lines. Furthermore, some of the risk-associated alleles correlate with increased expression of SMAD7 in normal colon tissues. Finally, we show that the enhancer is responsive to BMP4 stimulation. Taken together, we propose that the associated CRC risk at 18q21.1 is due to four functional variants that regulate SMAD7 expression and potentially perturb a BMP negative feedback loop in TGFβ/BMP signaling pathways.

Matrix metalloproteinases and genetic mouse models in cancer research: a mini-review.

Carcinogenesis is a multistep and also a multifactorial process that involves agents like genetic and environmental factors. Matrix metalloproteinases (MMPs) are major proteolytic enzymes which are involved in cancer cell migration, invasion, and metastasis. Genetic variations in genes encoding the MMPs were shown in human studies to influence cancer risk and phenotypic features of a tumor. The complex role of MMPs seems to be important in the mechanism of carcinogenesis, but it is not well recognized. Rodent studies concentrated particularly on the better understanding of the biological functions of the MMPs and their impact on the pathological process, also through the modification of Mmp genes. This review presents current knowledge and the existing evidence on the importance of selected MMPs in genetic mouse models of cancer and human genetic association studies. Further, this work can be useful for scientists studying the role of the genetic impact of MMPs in carcinogenesis.

Abstract 3269: QTLs in breast tumor and breast normal adjacent FFPE specimens from the Nurses’ Health Study

Abstract Rationale: Genome-wide association studies (GWAS) of breast cancer have identified 71 risk alleles, majority of which are located in intergenic or intronic regions. We used a network medicine approach to associate breast cancer risk single nucleotide polymorphisms (SNPs) with transcript abundance in formalin fixed paraffin embedded (FFPE) breast tissue. Identification of expression quantitative loci (eQTLs) may help to better understand the regulatory mechanisms by which these risk variants influence breast cancer susceptibility. Method: We identified invasive postmenopausal breast cancer cases in the Nurses’ Health Study (NHS) diagnosed from 1990-2004 with GWAS data and sufficient RNA for expression profiling in breast tumor and normal adjacent breast tissue. RNA was extracted using the Qiagen AllPrep RNA isolation kit, amplified using the NuGen Ovation FFPE WTA kit, and profiled using the Affymetrix Human Transcriptome Array (HTA 3.0v1). The HTA includes 6,892,960 features for measuring gene expression, alternative splicing, coding SNPs, and noncoding transcripts. After filtering and removing probes with a low dynamic range in our samples, we included 25,000 gene expression probes in our QTL analyses. We mapped these probes to genes using hg19. Results: Analyses were conducted separately for 376 breast tumor and 274 normal adjacent samples. We conducted quality control analyses, corrected for assay plate-to-plate variation and included patient's age at diagnosis and year of diagnosis as covariates in the multivariate linear regression model. We identified 11 trans eQTLs in normal adjacent breast tissue, 11 trans eQTLs in estrogen receptor (ER)+ breast tumor samples, and 12 trans eQTLs in ER- breast tumor samples (permutation adjusted p-value&amp;lt;0.05). We also developed a new method, functional quantitative trait loci (fQTL) analysis, to gain additional pathway insight into genetic associations important in breast cancer. In the fQTL analysis we tested for the association between SNPs and the expression of gene functional classes and pathways, evaluating the hypothesis that SNPs may also be associated with regulation of processes in addition to individual genes. Using a cutoff of false discovery rate &amp;lt;10%, we identified 2 SNPs associated with 2 Gene Ontology Molecular Functions in normal adjacent breast tissue, 1 SNP associated with 5 Molecular Functions in ER- tumor samples but no significant SNP associations in ER+ tumor samples. Integrated eQTL and fQTL analyses and variant annotation are ongoing. Conclusion: In summary, our results provide functional insights on the underlying biology of loci identified in breast cancer GWAS in the specimen type that is most impactful in translation to clinical practice. Identification of gene transcripts that can be measured in FFPE tissue and are associated with breast cancer risk loci is critical in understanding the mechanism by which these variants affect risk and mediate disease processes. Citation Format: Alejandro Quiroz-Zarate, Benjamin J. Harshfield, Rong Hu, Nick Knoblauch, Andrew H. Beck, Vincent Carey, Susan E. Hankinson, Rulla M. Tamimi, David J. Hunter, John Quackenbush, Aditi Hazra. QTLs in breast tumor and breast normal adjacent FFPE specimens from the Nurses’ Health Study. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3269. doi:10.1158/1538-7445.AM2014-3269

Abstract 942: Imputation from The 1000 Genomes Project identifies rare large effect variants of BRCA2-K3326X and CHEK2-I157T as risk factors for lung cancer; a study from the TRICL consortium

Abstract We conducted imputation to The 1000 Genomes Project of genome-wide association studies of lung cancer in populations of European ancestry, with 11,348 cases and 15,861 controls from four large studies, including subjects from 13 countries. As a follow-up, we conducted in-silico replication in two studies of 2,303 cases and 27,350 controls and directly genotyped an additional 7,943 cases and 10,945 controls from 14 countries. Data were imputed for all scans for over 10 million SNPs using data from The 1000 Genomes Project (Phase 1 integrated release 3, March 2012) as reference, using IMPUTE2, MaCH or minimac software. Tests of association between imputed SNPs and lung cancer were performed under a probabilistic dosage model in SNPTEST, ProbABEL, MaCH2dat or glm function in R. The fidelity of imputation as assessed by the correlation between imputed and directly typed SNPs was examined in a subset of samples from the four studies used for discovery and showed squared correlation coefficients ranging from 0.74 for the rare CHEK2 variant to 1.00 for the more common TP63 variant. The association between each SNP and lung cancer risk was assessed by the Cochran-Armitage trend test. Principle components generated using common SNPs were used to account for the possibility of inflation. Odds ratios (ORs) and associated 95% confidence intervals (CIs) were calculated by unconditional logistic regression. Meta-analysis was conducted using an inverse-variance approach. Cochran's Q-statistic to test for heterogeneity and the I2 statistic to quantify the proportion of the total variation due to heterogeneity were calculated. We identified large-effect genome-wide associations for squamous lung cancer with the rare variants of BRCA2-K3326X (rs11571833; odds ratio [OR]=2.47, P=4.74×10−20) and of CHEK2-I157T (rs17879961; OR=0.38 P=1.27×10−13). We also showed an association between common variation at 3q28 (TP63; rs13314271; OR=1.13, P=7.22×10−10) and lung adenocarcinoma previously only reported in Asians. There was no association between these loci and smoking quantity as measured by number of cigarettes smoked per day, using smoking information on 43,693 Icelandic subjects. These findings provide further evidence for inherited genetic susceptibility to lung cancer and its biological basis. Additionally, our analysis demonstrates that imputation can identify rare disease-causing variants having substantive effects on cancer risk from pre-existing GWAS data. Citation Format: Maria Teresa Landi, Yufei Wang, James D. Mckay, Thorunn Rafnar, Zhaoming Wang, Maria Timofeeva, Peter Broderick, Kari Stefansson, Angela Risch, Stephen J. Chanock, David C. Christiani, Rayjean J. Hung, Paul Brennan, Richard S. Houlston, Christopher I. Amos. Imputation from The 1000 Genomes Project identifies rare large effect variants of BRCA2-K3326X and CHEK2-I157T as risk factors for lung cancer; a study from the TRICL consortium. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 942. doi:10.1158/1538-7445.AM2014-942