A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

Biobanks and personalized medicine

We provide a mini-review of how biobanks can support clinical genetics in the era of personalized medicine. We discuss types of biobanks, including disease specific and general biobanks not focused on one disease. We present considerations in setting up a biobank, including consenting and governance, biospecimens, risk factor and related data, informatics, and linkage to electronic health records for phenotyping. We also discuss the uses of biobanks and ongoing considerations, including genotype-driven recruitment, investigations of gene-environment associations, and the re-use of data generated from studies. Finally, we present a brief discussion of some of the unresolved issues, such as return of research results and sustaining biobanks over time. In summary, carefully designed biobanks can provide critical research and infrastructure support for clinical genetics in the era of personalized medicine.

Localized provoked vestibulodynia: outcomes after modified vestibulectomy

OBJECTIVE

To describe and estimate both short-term and long-term effectiveness of a large cohort of women treated with modified vestibulectomy in a single surgical service.

STUDY DESIGN

A total of 202 patients who were treated with modified vestibulectomy for localized provoked vestibulodynia at Mayo Clinic in Rochester, Minnesota, were mailed a questionnaire to document severity of vulvar pain or discomfort before and after the surgery.

RESULTS

In total, 115 patients returned the questionnaire. Of the 71 patients who before surgery reported pain when inserting a tampon, 52 reported attempting to insert a tampon after surgery. Of these 52 patients, 47 (90.4%) noticed moderate to substantial improvement. Pain with sexual intercourse occurred in 97.3% (107/ 110) of patients before surgery. After surgery, 90 (84.1%) of those 107 patients noted moderate to substantial improvement in their pain with intercourse.

CONCLUSION

Modified vestibulectomy was a successful treatment for patients with localized provoked vestibulodynia and resulted in strong patient satisfaction, long-term effectiveness, minimal scarring, and few postoperative complications.

FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

BACKGROUND

Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium.

METHODS

Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression.

RESULTS

Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95% confidence interval=1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2.

CONCLUSION

Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2.

Preemptive genotyping for personalized medicine: design of the right drug, right dose, right time-using genomic data to individualize treatment protocol

OBJECTIVE

To report the design and implementation of the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment protocol that was developed to test the concept that prescribers can deliver genome-guided therapy at the point of care by using preemptive pharmacogenomics (PGx) data and clinical decision support (CDS) integrated into the electronic medical record (EMR).

PATIENTS AND METHODS

We used a multivariate prediction model to identify patients with a high risk of initiating statin therapy within 3 years. The model was used to target a study cohort most likely to benefit from preemptive PGx testing among the Mayo Clinic Biobank participants, with a recruitment goal of 1000 patients. We used a Cox proportional hazards model with variables selected through the Lasso shrinkage method. An operational CDS model was adapted to implement PGx rules within the EMR.

RESULTS

The prediction model included age, sex, race, and 6 chronic diseases categorized by the Clinical Classifications Software for International Classification of Diseases, Ninth Revision codes (dyslipidemia, diabetes, peripheral atherosclerosis, disease of the blood-forming organs, coronary atherosclerosis and other heart diseases, and hypertension). Of the 2000 Biobank participants invited, 1013 (51%) provided blood samples, 256 (13%) declined participation, 555 (28%) did not respond, and 176 (9%) consented but did not provide a blood sample within the recruitment window (October 4, 2012, through March 20, 2013). Preemptive PGx testing included CYP2D6 genotyping and targeted sequencing of 84 PGx genes. Synchronous real-time CDS was integrated into the EMR and flagged potential patient-specific drug-gene interactions and provided therapeutic guidance.

CONCLUSION

This translational project provides an opportunity to begin to evaluate the impact of preemptive sequencing and EMR-driven genome-guided therapy. These interventions will improve understanding and implementation of genomic data in clinical practice.

Fine-scale mapping of the FGFR2 breast cancer risk locus: putative functional variants differentially bind FOXA1 and E2F1

The 10q26 locus in the second intron of FGFR2 is the locus most strongly associated with estrogen-receptor-positive breast cancer in genome-wide association studies. We conducted fine-scale mapping in case-control studies genotyped with a custom chip (iCOGS), comprising 41 studies (n = 89,050) of European ancestry, 9 Asian ancestry studies (n = 13,983), and 2 African ancestry studies (n = 2,028) from the Breast Cancer Association Consortium. We identified three statistically independent risk signals within the locus. Within risk signals 1 and 3, genetic analysis identified five and two variants, respectively, highly correlated with the most strongly associated SNPs. By using a combination of genetic fine mapping, data on DNase hypersensitivity, and electrophoretic mobility shift assays to study protein-DNA binding, we identified rs35054928, rs2981578, and rs45631563 as putative functional SNPs. Chromatin immunoprecipitation showed that FOXA1 preferentially bound to the risk-associated allele (C) of rs2981578 and was able to recruit ERα to this site in an allele-specific manner, whereas E2F1 preferentially bound the risk variant of rs35054928. The risk alleles were preferentially found in open chromatin and bound by Ser5 phosphorylated RNA polymerase II, suggesting that the risk alleles are associated with changes in transcription. Chromatin conformation capture demonstrated that the risk region was able to interact with the promoter of FGFR2, the likely target gene of this risk region. A role for FOXA1 in mediating breast cancer susceptibility at this locus is consistent with the finding that the FGFR2 risk locus primarily predisposes to estrogen-receptor-positive disease.

Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: a genome-wide interaction study

Women using menopausal hormone therapy (MHT) are at increased risk of developing breast cancer (BC). To detect genetic modifiers of the association between current use of MHT and BC risk, we conducted a meta-analysis of four genome-wide case-only studies followed by replication in 11 case-control studies. We used a case-only design to assess interactions between single-nucleotide polymorphisms (SNPs) and current MHT use on risk of overall and lobular BC. The discovery stage included 2920 cases (541 lobular) from four genome-wide association studies. The top 1391 SNPs showing P values for interaction (Pint) <3.0 × 10(-3) were selected for replication using pooled case-control data from 11 studies of the Breast Cancer Association Consortium, including 7689 cases (676 lobular) and 9266 controls. Fixed-effects meta-analysis was used to derive combined Pint. No SNP reached genome-wide significance in either the discovery or combined stage. We observed effect modification of current MHT use on overall BC risk by two SNPs on chr13 near POMP (combined Pint≤8.9 × 10(-6)), two SNPs in SLC25A21 (combined Pint≤4.8 × 10(-5)), and three SNPs in PLCG2 (combined Pint≤4.5 × 10(-5)). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7 × 10(-5)), one SNP in CD80 (combined Pint≤8.2 × 10(-6)), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10(-6)), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6 × 10(-5)). In conclusion, polymorphisms in genes related to solute transportation in mitochondria, transmembrane signaling, and immune cell activation are potentially modifying BC risk associated with current use of MHT. These findings warrant replication in independent studies.

Fatty acids found in dairy, protein and unsaturated fatty acids are associated with risk of pancreatic cancer in a case-control study

Although many studies have investigated meat and total fat in relation to pancreatic cancer risk, few have investigated dairy, fish and specific fatty acids (FAs). We evaluated the association between intake of meat, fish, dairy, specific FAs and related nutrients and pancreatic cancer. In our American-based Mayo Clinic case-control study 384 cases and 983 controls frequency matched on recruitment age, race, sex and residence area (Minnesota, Wisconsin or Iowa, USA) between 2004 and 2009. All subjects provided demographic information and completed 144-item food frequency questionnaire. Logistic regression-calculated odds ratios (ORs) and 95% confidence intervals (95% CIs) were adjusted for age, sex, cigarette smoking, body mass index and diabetes mellitus. Significant inverse association (trend p-value < 0.05) between pancreatic cancer and the groupings (highest vs. lowest consumption quintile OR [95% CI]) was as follows: meat replacement (0.67 [0.43-1.02]), total protein (0.58 [0.39-0.86]), vitamin B12 (0.67 [0.44, 1.01]), zinc (0.48 [0.32, 0.71]), phosphorus (0.62 [0.41, 0.93]), vitamin E (0.51 [0.33, 0.78]), polyunsaturated FAs (0.64 [0.42, 0.98]) and linoleic acid (FA 18:2) (0.62 [0.40-0.95]). Increased risk associations were observed for saturated FAs (1.48 [0.97-2.23]), butyric acid (FA 4:0) (1.77 [1.19-2.64]), caproic acid (FA 6:0) (2.15 [1.42-3.27]), caprylic acid (FA 8:0) (1.87 [1.27-2.76]) and capric acid (FA 10:0) (1.83 [1.23-2.74]). Our study suggests that eating a diet high in total protein and certain unsaturated FAs is associated with decreased risk of developing pancreatic cancer in a dose-dependent manner, whereas fats found in dairy increase risk.

The Mayo Clinic Biobank: a building block for individualized medicine

OBJECTIVE

To report the design and implementation of the first 3 years of enrollment of the Mayo Clinic Biobank.

PATIENTS AND METHODS

Preparations for this biobank began with a 4-day Deliberative Community Engagement with local residents to obtain community input into the design and governance of the biobank. Recruitment, which began in April 2009, is ongoing, with a target goal of 50,000. Any Mayo Clinic patient who is 18 years or older, able to consent, and a US resident is eligible to participate. Each participant completes a health history questionnaire, provides a blood sample, and allows access to existing tissue specimens and all data from their Mayo Clinic electronic medical record. A community advisory board provides ongoing advice and guidance on complex decisions.

RESULTS

After 3 years of recruitment, 21,736 individuals have enrolled. Fifty-eight percent (12,498) of participants are female and 95% (20,541) of European ancestry. Median participant age is 62 years. Seventy-four percent (16,171) live in Minnesota, with 42% (9157) from Olmsted County, where the Mayo Clinic in Rochester, Minnesota, is located. The 5 most commonly self-reported conditions are hyperlipidemia (8979, 41%), hypertension (8174, 38%), osteoarthritis (6448, 30%), any cancer (6224, 29%), and gastroesophageal reflux disease (5669, 26%). Among patients with self-reported cancer, the 5 most common types are nonmelanoma skin cancer (2950, 14%), prostate cancer (1107, 12% in men), breast cancer (941, 4%), melanoma (692, 3%), and cervical cancer (240, 2% in women). Fifty-six percent (12,115) of participants have at least 15 years of electronic medical record history. To date, more than 60 projects and more than 69,000 samples have been approved for use.

CONCLUSION

The Mayo Clinic Biobank has quickly been established as a valuable resource for researchers.

Hospitalizations and emergency department use in Mayo Clinic Biobank participants within the employee and community health medical home

OBJECTIVE

To evaluate the participants in the Mayo Clinic Biobank for their representativeness to the entire Employee and Community Health program (ECH) primary care population with regard to hospital utilization.

PATIENTS AND METHODS

Participants enrolled in the Mayo Clinic Biobank from April 1, 2009, to December 31, 2010, were linked to the ECH population. These individuals were categorized into risk tiers (0-4) on the basis of the number of health conditions present as of December 31, 2010. Outcomes were ascertained through December 31, 2011. Hazard ratios (HRs) and 95% CIs for risk of hospitalization, emergency department (ED) visits, and for risk of hospitalization and emergency department (ED) visits were estimated.

RESULTS

The 8927 Biobank participants were part of ECH (N=84,872). Compared with the entire ECH population, the Biobank-ECH participants were more likely to be female (64.3% vs 54.6%), older (median age, 58 years vs 47 years), and categorized to tier 0 (6.4% vs 24.0%). There were strong positive associations between tier (tier 4 vs combined tiers 0 and 1) and risk of hospitalization (HR, 5.8; 95% CI, 4.6-7.5) and ED visits (HR, 5.4; 95% CI, 4.2-6.8) among Biobank-ECH participants. Similar associations for risk of hospitalization (HR, 8.5; 95% CI, 7.8-9.3) and ED visits (HR, 6.9; 95% CI, 6.4-7.5) were observed for the entire ECH population.

CONCLUSION

Although the Biobank-ECH participants were older and had more chronic conditions compared with the overall ECH population, the associations of risk tier with utilization outcomes were similar, supporting the use of the Biobank participants to assess biomarkers for health care outcomes in the primary care setting.

CYP2B6*6 is associated with increased breast cancer risk

The cytochrome P450 2B6 (CYP2B6) is involved in the metabolism of testosterone. Functional changes in this enzyme may influence endogenous hormone exposure, which has been associated with risk of breast cancer. To assess potential associations between two functional polymorphisms CYP2B6_516_G>T (rs3745274) and CYP2B6_785_A>G (rs2279343) and breast cancer risk, we established a specific matrix-assisted laser desorption/ionization time-of-flight mass spectrometry assay. The GENICA breast cancer case-control study showed associations between the variant genotypes CYP2B6_516_TT and CYP2B6_785_GG and breast cancer risk with odds ratios (ORs) of 1.34 (p = 0.001) and 1.31 (p = 0.002), respectively. A similar effect was observed for carriers of the CYP2B6_516_T allele in a validation study including four independent studies from Germany, Sweden and USA. In a pooled analysis of all five studies involving 4,638 breast cancer cases and 3,594 controls of European ancestry, carriers of the CYP2B6_516_G and the CYP2B6_785_G variant had an increased breast cancer risk with ORs of 1.10 (p = 0.027) and 1.10 (p = 0.031), respectively. We conclude that the genetic variants CYP2B6_516_G and CYP2B6_785_G (designated CYP2B6*6), which are known to decrease activity of the CYP2B6 enzyme, contribute to an increased breast cancer risk.

Nutrients from fruit and vegetable consumption reduce the risk of pancreatic cancer

PURPOSE

Pancreatic cancer is a devastating disease for which the role of dietary factors remains inconclusive. Our objective was to evaluate the risk of pancreatic cancer associated with nutrients found in fruits and vegetables and nutrient supplementation using a clinic-based case-control design.

METHODS

Our study included 384 rapidly ascertained cases and 983 controls frequency-matched on age at time of recruitment (in 5-year increments), race, sex, and region of residence. All subjects provided demographic information and completed a 144-item food frequency questionnaire in which they reported no change to their diet within 5 years prior to entering the study. Logistic regression was used to calculate odds ratios and 95 % confidence intervals, adjusted for age, sex, smoking, body mass index, energy intake, and alcohol consumption.

RESULTS

Results show a significant (trend p value < 0.05) inverse association between pancreatic cancer and nutrient/supplement groupings in a dose-dependent manner including magnesium, potassium, selenium, alpha-carotene, beta-carotene, beta-cryptoxanthin, lutein and zeaxanthin, niacin, total alpha-tocopherol, total vitamin A activity, vitamin B6, and vitamin C. Adjusting for diabetes or total sugar intake did not result in significant changes.

CONCLUSION

We conclude that most nutrients obtained through consumption of fruits and vegetables may reduce the risk of developing pancreatic cancer.

Meat-related mutagens and pancreatic cancer: null results from a clinic-based case-control study

BACKGROUND

Pancreatic cancer is a devastating disease for which the role of dietary factors remains inconclusive. The study objective was to evaluate risk of pancreatic cancer associated with meat preparation methods and meat-related mutagen consumption using a clinic-based case-control design.

METHODS

There were 384 cases and 983 controls; subjects provided demographic information and completed a 144-item food frequency questionnaire, which was used to estimate meat mutagen intake using the National Cancer Institute's CHARRED database (Bethesda, MD). Logistic regression was used to calculate ORs and 95% confidence intervals (CI), adjusted for factors including age, sex, cigarette smoking, body mass index, and diabetes mellitus.

RESULTS

Overall, the findings were null with respect to meat mutagen intake and pancreatic cancer.

CONCLUSIONS

The results do not support an association between well-done meat or meat-related mutagen intake and pancreatic cancer and contrast with generally increased risks reported in previous studies.

IMPACT

These data contribute to evidence about pancreatic cancer and potentially carcinogenic compounds in meat.

Abstract 2515: The Mayo Clinic Biobank - A growing resource for cancer related studies

BACKGROUND: Biobanks collect and store biological samples and data from participants for use in research by multiple investigators. The Mayo Clinic Biobank was established by the Mayo Clinic Center for Individualized Medicine with a goal to support a wide array of health-related research studies at Mayo Clinic, including cancer studies. The Biobank is not focused on any particular disease, however, through annotation by questionnaires, the Mayo electronic medical record (EMR), and the Mayo Cancer Registry, it is a useful clinical research resource for cancer related studies.

METHODS: Recruitment started in April 2009. Our goal is 50,000 enrollees. Eligible subjects are adult Mayo Clinic patients, U.S residents, and able to consent. Mailed invitations were sent to patients with appointments in certain Mayo Clinic departments. Each participant completed a health history questionnaire including a wide variety of health information as well as whether they or their 1st-degree relatives had ever been diagnosed with specific cancers. For self-reported cancers, subjects were asked to provide the age they were first diagnosed. Subjects also provided a blood sample and granted research access to clinically collected specimens and data from their Mayo Clinic record, at enrollment and into the future. All research projects utilizing samples from this resource are required to return to the Biobank the data generated from their projects.

RESULTS: In the first three years, 21736 subjects consented to participate (30% response rate). Participants are 58% female, 95% White, and range in age from 18 to 97 with a median age of 62. At enrollment, 74% were residents in Minnesota, 6% in Iowa, 4% in Wisconsin, and 15% in the other states. Twelve percent reported being a current smoker, while 59% were never smokers. The most common self-reported cancers at baseline were non-melanoma skin cancer (n=2950), prostate cancer (n=1107), breast cancer (n=941), melanoma (n=692), colorectal cancer (n=296), cervical cancer (n=240), sarcoma (n=233), urinary/bladder (n=211), lymphoma (n=187), thyroid cancer (n=186), endometrial cancer (n=170), kidney cancer (n=163), lung cancer (n=145). Excluding non-melanoma skin cancer, 16188 (74%) (6516 male, 9672 female) self-reported being cancer free at baseline. Data will be presented on the frequency of incident cancers diagnosed since enrollment in the Biobank. To date, the Biobank has served as a source of controls for 17 cancer related studies on genetic susceptibility, including studies of the breast, colon, myeloma, brain, lung, pancreas, endometrium, and kidneys.

CONCLUSIONS: The Mayo Clinic Biobank has quickly been established as a valuable resource for cancer researchers at Mayo Clinic - primarily as a source of controls for genetic studies. As the Biobank continues to grow in sample size and length of follow-up, it will also serve as a cohort study of cancer incidence embedded within an EMR of a large health organization.

Citation Format: Janet E. Olson, Euijung Ryu, Kiley J. Johnson, Karen Maschke, Jody A. Morrisette, Mark Liebow, Paul Y. Takahashi, Ruchi G. Sharma, Kari S. Anderson, Matthew A. Hathcock, Jyotishman Pathak, Noralane M. Lindor, Timothy J. Beebe, Stephen N. Thibodeau, James R. Cerhan. The Mayo Clinic Biobank - A growing resource for cancer related studies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2515. doi:10.1158/1538-7445.AM2013-2515

Potential bias in the bank: what distinguishes refusers, nonresponders and participants in a clinic-based biobank?

BACKGROUND

Biobanks are an important resource for genetic and epidemiologic research, but bias may be introduced if those who accept the recruitment invitation differ systematically from those who do not in terms of attributes important to health-related investigations. To understand potential bias in a clinic-based biobank of biological samples, including genetic data linked to electronic health record information, we compared patient characteristics and self-reported information among participants, nonresponders and refusers. We also compared reasons for nonparticipation between refusers and nonresponders to elucidate potential pathways to reduce nonparticipation and any uncovered bias.

METHODS

We mailed recruitment packets to 1,600 adult patients with upcoming appointments at Mayo Clinic (Rochester, Minn., USA) and recorded their participation status. Administrative data were used to compare characteristics across groups. We used phone interviews with 26 nonresponders and 26 refusers to collect self-reported information, including reasons for nonparticipation. Participants were asked to complete a mailed questionnaire.

RESULTS

We achieved 26.2% participation (n=419) with 12.1% refusing (n=193) and 61.8% nonresponse (n=988). In multivariate analyses, sex, age, region of residence, and race/ethnicity were significantly associated with participation. The groups differed in information-seeking behaviors and research experience. Refusers more often cited privacy concerns, while nonresponders more often identified time constraints as the reason for nonparticipation.

CONCLUSION

For genomic medicine to advance, large, representative biobanks are required. Significant associations between patient characteristics and nonresponse, as well as systematic differences between refusers and nonresponders, could introduce bias. Oversampling or recruitment changes, including heightened attention to privacy protection and participation burden, may be necessary to increase participation among less-represented groups.

Epigenome-wide ovarian cancer analysis identifies a methylation profile differentiating clear-cell histology with epigenetic silencing of the HERG K+ channel

Ovarian cancer remains the leading cause of death in women with gynecologic malignancies, despite surgical advances and the development of more effective chemotherapeutics. As increasing evidence indicates that clear-cell ovarian cancer may have unique pathogenesis, further understanding of molecular features may enable us to begin to understand the underlying biology and histology-specific information for improved outcomes. To study epigenetics in clear-cell ovarian cancer, fresh frozen tumor DNA (n = 485) was assayed on Illumina Infinium HumanMethylation450 BeadChips. We identified a clear-cell ovarian cancer tumor methylation profile (n = 163) which we validated in two independent replication sets (set 1, n = 163; set 2, n = 159), highlighting 22 CpG loci associated with nine genes (VWA1, FOXP1, FGFRL1, LINC00340, KCNH2, ANK1, ATXN2, NDRG21 and SLC16A11). Nearly all of the differentially methylated CpGs showed a propensity toward hypermethylation among clear-cell cases. Several loci methylation inversely correlated with tumor gene expression, most notably KCNH2 (HERG, a potassium channel) (P = 9.5 × 10(-7)), indicating epigenetic silencing. In addition, a predicted methylation class mainly represented by the clear-cell cases (20 clear cell out of 23 cases) had improved survival time. Although these analyses included only 30 clear-cell carcinomas, results suggest that loss of expression of KCNH2 (HERG) by methylation could be a good prognostic marker, given that overexpression of the potassium (K(+)) channel Eag family members promotes increased proliferation and results in poor prognosis. Validation in a bigger cohort of clear-cell tumors of the ovary is warranted.

Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer

TERT-locus SNPs and leukocyte telomere measures are reportedly associated with risks of multiple cancers. Using the Illumina custom genotyping array iCOGs, we analyzed ∼480 SNPs at the TERT locus in breast (n = 103,991), ovarian (n = 39,774) and BRCA1 mutation carrier (n = 11,705) cancer cases and controls. Leukocyte telomere measurements were also available for 53,724 participants. Most associations cluster into three independent peaks. The minor allele at the peak 1 SNP rs2736108 associates with longer telomeres (P = 5.8 × 10(-7)), lower risks for estrogen receptor (ER)-negative (P = 1.0 × 10(-8)) and BRCA1 mutation carrier (P = 1.1 × 10(-5)) breast cancers and altered promoter assay signal. The minor allele at the peak 2 SNP rs7705526 associates with longer telomeres (P = 2.3 × 10(-14)), higher risk of low-malignant-potential ovarian cancer (P = 1.3 × 10(-15)) and greater promoter activity. The minor alleles at the peak 3 SNPs rs10069690 and rs2242652 increase ER-negative (P = 1.2 × 10(-12)) and BRCA1 mutation carrier (P = 1.6 × 10(-14)) breast and invasive ovarian (P = 1.3 × 10(-11)) cancer risks but not via altered telomere length. The cancer risk alleles of rs2242652 and rs10069690, respectively, increase silencing and generate a truncated TERT splice variant.

Genome-wide association studies identify four ER negative-specific breast cancer risk loci

Estrogen receptor (ER)-negative tumors represent 20-30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry. The etiology and clinical behavior of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10(-12) and LGR6, P = 1.4 × 10(-8)), 2p24.1 (P = 4.6 × 10(-8)) and 16q12.2 (FTO, P = 4.0 × 10(-8)), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.

Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors

Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer. Data from 24 studies of the Breast Cancer Association Consortium were pooled. Using up to 34,793 invasive breast cancers and 41,099 controls, we examined whether the relative risks associated with 23 single nucleotide polymorphisms were modified by 10 established environmental risk factors (age at menarche, parity, breastfeeding, body mass index, height, oral contraceptive use, menopausal hormone therapy use, alcohol consumption, cigarette smoking, physical activity) in women of European ancestry. We used logistic regression models stratified by study and adjusted for age and performed likelihood ratio tests to assess gene-environment interactions. All statistical tests were two-sided. We replicated previously reported potential interactions between LSP1-rs3817198 and parity (Pinteraction = 2.4 × 10(-6)) and between CASP8-rs17468277 and alcohol consumption (Pinteraction = 3.1 × 10(-4)). Overall, the per-allele odds ratio (95% confidence interval) for LSP1-rs3817198 was 1.08 (1.01-1.16) in nulliparous women and ranged from 1.03 (0.96-1.10) in parous women with one birth to 1.26 (1.16-1.37) in women with at least four births. For CASP8-rs17468277, the per-allele OR was 0.91 (0.85-0.98) in those with an alcohol intake of <20 g/day and 1.45 (1.14-1.85) in those who drank ≥ 20 g/day. Additionally, interaction was found between 1p11.2-rs11249433 and ever being parous (Pinteraction = 5.3 × 10(-5)), with a per-allele OR of 1.14 (1.11-1.17) in parous women and 0.98 (0.92-1.05) in nulliparous women. These data provide first strong evidence that the risk of breast cancer associated with some common genetic variants may vary with environmental risk factors.

Mammographic breast density response to aromatase inhibition

PURPOSE

Mammographic breast density (MBD) is decreased by tamoxifen, but the effect of aromatase inhibitors is less clear.

EXPERIMENTAL DESIGN

We enrolled early-stage postmenopausal patients with breast cancer initiating adjuvant aromatase inhibitor therapy and ascertained mammograms before and at an average 10 months of aromatase inhibitor therapy. We matched cases to healthy postmenopausal women (controls) from a large mammography screening cohort on age, baseline body mass index, baseline MBD, and interval between mammograms. We estimated change in MBD using a computer-assisted thresholding program (Cumulus) and compared differences between cases and matched controls.

RESULTS

In predominantly White women (96%), we found 14% of the 387 eligible cases had a MBD reduction of at least 5% after an average of 10 months of aromatase inhibitor therapy. MBD reductions were associated with higher baseline MBD, aromatase inhibitor use for more than 12 months, and prior postmenopausal hormone use. Comparing each case with her matched control, there was no evidence of an association of change in MBD with aromatase inhibitor therapy [median case-control difference among 369 pairs was -0.1% (10th and 90th percentile: -5.9%, 5.2%) P = 0.51]. Case-control differences were similar by type of aromatase inhibitor (P's 0.41 and 0.56); prior use of postmenopausal hormones (P = 0.85); baseline MBD (P = 0.55); and length of aromatase inhibitor therapy (P = 0.08).

CONCLUSIONS

In postmenopausal women treated with aromatase inhibitors, 14% of cases had a MBD reduction of more than 5%, but these decreases did not differ from matched controls. These data suggest that MBD is not a clinically useful biomarker for predicting the value of aromatase inhibitor therapy in White postmenopausal women.

A genome-wide association study to identify genetic susceptibility loci that modify ductal and lobular postmenopausal breast cancer risk associated with menopausal hormone therapy use: a two-stage design with replication

Menopausal hormone therapy (MHT) is associated with an elevated risk of breast cancer in postmenopausal women. To identify genetic loci that modify breast cancer risk related to MHT use in postmenopausal women, we conducted a two-stage genome-wide association study (GWAS) with replication. In stage I, we performed a case-only GWAS in 731 invasive breast cancer cases from the German case-control study Mammary Carcinoma Risk Factor Investigation (MARIE). The 1,200 single nucleotide polymorphisms (SNPs) showing the lowest P values for interaction with current MHT use (within 6 months prior to breast cancer diagnosis), were carried forward to stage II, involving pooled case-control analyses including additional MARIE subjects (1,375 cases, 1,974 controls) as well as 795 cases and 764 controls of a Swedish case-control study. A joint P value was calculated for a combined analysis of stages I and II. Replication of the most significant interaction of the combined stage I and II was performed using 5,795 cases and 5,390 controls from nine studies of the Breast Cancer Association Consortium (BCAC). The combined stage I and II yielded five SNPs on chromosomes 2, 7, and 18 with joint P values <6 × 10(-6) for effect modification of current MHT use. The most significant interaction was observed for rs6707272 (P = 3 × 10(-7)) on chromosome 2 but was not replicated in the BCAC studies (P = 0.21). The potentially modifying SNPs are in strong linkage disequilibrium with SNPs in TRIP12 and DNER on chromosome 2 and SETBP1 on chromosome 18, previously linked to carcinogenesis. However, none of the interaction effects reached genome-wide significance. The inability to replicate the top SNP × MHT interaction may be due to limited power of the replication phase. Our study, however, suggests that there are unlikely to be SNPs that interact strongly enough with MHT use to be clinically significant in European women.

Risk factors for intrahepatic cholangiocarcinoma: association between metformin use and reduced cancer risk

The associations between diabetes, smoking, obesity, and intrahepatic cholangiocarcinoma (ICC) risk remain inconclusive. Metformin is purportedly associated with a reduced risk for various cancers. This case-control study evaluated risk factors for ICC and explored the effects of metformin on ICC risk in a clinic/hospital-based cohort. ICC patients observed at the Mayo Clinic (Rochester, MN) between January 2000 and May 2010 were identified. Age, sex, ethnicity, and residential area-matched controls were selected from among Mayo Clinic Biobank participants. The associations between potential factors and ICC risk were determined. Six hundred and twelve cases and 594 controls were identified. Factors associated with increased ICC risk included biliary tract diseases (adjusted odds ratio [AOR]: 81.8; 95% confidence interval [CI]: 11.2-598.8; P < 0.001), cirrhosis (AOR, 8.0; 95% CI: 1.8-36.5; P = 0.007), diabetes (AOR, 3.6; 95% CI: 2.3-5.5; P < 0.001), and smoking (AOR, 1.6; 95% CI: 1.3-2.1; P < 0.001). Compared to diabetic patients not treated with metformin, the odds ratio (OR) for ICC for diabetic patients treated with metformin was significantly decreased (OR, 0.4; 95% CI: 0.2-0.9; P = 0.04). Obesity and metabolic syndrome were not associated with ICC.

CONCLUSION

This study confirmed diabetes and smoking as independent risk factors for ICC. A novel finding was that treatment with metformin was significantly associated with a 60% reduction in ICC risk in diabetic patients.

The influence of mammogram acquisition on the mammographic density and breast cancer association in the Mayo Mammography Health Study cohort

Introduction

Mammographic density is a strong risk factor for breast cancer. Image acquisition technique varies across mammograms to limit radiation and produce a clinically useful image. We examined whether acquisition technique parameters at the time of mammography were associated with mammographic density and whether the acquisition parameters confounded the density and breast cancer association.

Methods

We examined this question within the Mayo Mammography Health Study (MMHS) cohort, comprised of 19,924 women (51.2% of eligible) seen in the Mayo Clinic mammography screening practice from 2003 to 2006. A case-cohort design, comprising 318 incident breast cancers diagnosed through December 2009 and a random subcohort of 2,259, was used to examine potential confounding of mammogram acquisition technique parameters (x-ray tube voltage peak (kVp), milliampere-seconds (mAs), thickness and compression force) on the density and breast cancer association. The Breast Imaging Reporting and Data System four-category tissue composition measure (BI-RADS) and percent density (PD) (Cumulus program) were estimated from screen-film mammograms at time of enrollment. Spearman correlation coefficients (r) and means (standard deviations) were used to examine the relationship of density measures with acquisition parameters. Hazard ratios (HR) and C-statistics were estimated using Cox proportional hazards regression, adjusting for age, menopausal status, body mass index and postmenopausal hormones. A change in the HR of at least 15% indicated confounding.

Results

Adjusted PD and BI-RADS density were associated with breast cancer (p-trends < 0.001), with a 3 to 4-fold increased risk in the extremely dense vs. fatty BI-RADS categories (HR: 3.0, 95% CI, 1.7 - 5.1) and the ≥ 25% vs. ≤ 5% PD categories (HR: 3.8, 95% CI, 2.5 - 5.9). Of the acquisition parameters, kVp was not correlated with PD (r = 0.04, p = 0.07). Although thickness (r = -0.27, p < 0.001), compression force (r = -0.16, p < 0.001), and mAs (r = -0.06, p = 0.008) were inversely correlated with PD, they did not confound the PD or BI-RADS associations with breast cancer and their inclusion did not improve discriminatory accuracy. Results were similar for associations of dense and non-dense area with breast cancer.

Conclusions

We confirmed a strong association between mammographic density and breast cancer risk that was not confounded by mammogram acquisition technique.

CHEK2*1100delC heterozygosity in women with breast cancer associated with early death, breast cancer-specific death, and increased risk of a second breast cancer

PURPOSE

We tested the hypotheses that CHEK2*1100delC heterozygosity is associated with increased risk of early death, breast cancer-specific death, and risk of a second breast cancer in women with a first breast cancer.

PATIENTS AND METHODS

From 22 studies participating in the Breast Cancer Association Consortium, 25,571 white women with invasive breast cancer were genotyped for CHEK2*1100delC and observed for up to 20 years (median, 6.6 years). We examined risk of early death and breast cancer-specific death by estrogen receptor status and risk of a second breast cancer after a first breast cancer in prospective studies.

RESULTS

CHEK2*1100delC heterozygosity was found in 459 patients (1.8%). In women with estrogen receptor-positive breast cancer, multifactorially adjusted hazard ratios for heterozygotes versus noncarriers were 1.43 (95% CI, 1.12 to 1.82; log-rank P = .004) for early death and 1.63 (95% CI, 1.24 to 2.15; log-rank P < .001) for breast cancer-specific death. In all women, hazard ratio for a second breast cancer was 2.77 (95% CI, 2.00 to 3.83; log-rank P < .001) increasing to 3.52 (95% CI, 2.35 to 5.27; log-rank P < .001) in women with estrogen receptor-positive first breast cancer only.

CONCLUSION

Among women with estrogen receptor-positive breast cancer, CHEK2*1100delC heterozygosity was associated with a 1.4-fold risk of early death, a 1.6-fold risk of breast cancer-specific death, and a 3.5-fold risk of a second breast cancer. This is one of the few examples of a genetic factor that influences long-term prognosis being documented in an extensive series of women with breast cancer.