Publications by authors named "Mark N Brook"

31 Publications

The BARCODE1 Pilot: a feasibility study of using germline single nucleotide polymorphisms to target prostate cancer screening.

BJU Int 2021 Jul 2. Epub 2021 Jul 2.

Oncogenetics Team, Institute of Cancer Research, London, UK.

Objectives: To assess the feasibility and uptake of a community-based prostate cancer (PCa) screening programme selecting men according to their genetic risk of PCa. To assess the uptake of PCa screening investigations by men invited for screening. The uptake of the pilot study would guide the opening of the larger BARCODE1 study recruiting 5000 men.

Subjects And Methods: Healthy males aged 55-69 years were invited to participate via their general practitioners (GPs). Saliva samples were collected via mailed collection kits. After DNA extraction, genotyping was conducted using a study specific assay. Genetic risk was based on genotyping 130 germline PCa risk single nucleotide polymorphisms (SNPs). A polygenic risk score (PRS) was calculated for each participant using the sum of weighted alleles for 130 SNPs. Study participants with a PRS lying above the 90th centile value were invited for PCa screening by prostate magnetic resonance imaging (MRI) and biopsy.

Results: Invitation letters were sent to 1434 men. The overall study uptake was 26% (375/1436) and 87% of responders were eligible for study entry. DNA genotyping data were available for 297 men and 25 were invited for screening. After exclusions due to medical comorbidity/invitations declined, 18 of 25 men (72%) underwent MRI and biopsy of the prostate. There were seven diagnoses of PCa (38.9%). All cancers were low-risk and were managed with active surveillance.

Conclusion: The BARCODE1 Pilot has shown this community study in the UK to be feasible, with an overall uptake of 26%. The main BARCODE1 study is now open and will recruit 5000 men. The results of BARCODE1 will be important in defining the role of genetic profiling in targeted PCa population screening. Patient Summary What is the paper about? Very few prostate cancer screening programmes currently exist anywhere in the world. Our pilot study investigated if men in the UK would find it acceptable to have a genetic test based on a saliva sample to examine their risk of prostate cancer development. This test would guide whether men are offered prostate cancer screening tests. What does it mean for patients? We found that the study design was acceptable: 26% of men invited to take part agreed to have the test. The majority of men who were found to have an increased genetic risk of prostate cancer underwent further tests offered (prostate MRI scan and biopsy). We have now expanded the study to enrol 5000 men. The BARCODE1 study will be important in examining whether this approach could be used for large-scale population prostate cancer screening.
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http://dx.doi.org/10.1111/bju.15535DOI Listing
July 2021

Comparative validation of the BOADICEA and Tyrer-Cuzick breast cancer risk models incorporating classical risk factors and polygenic risk in a population-based prospective cohort of women of European ancestry.

Breast Cancer Res 2021 02 15;23(1):22. Epub 2021 Feb 15.

Division of Cancer Epidemiology and Genetics, National Cancer Institute of Health, 9609 Medical Center Drive 7E-342, Rockville, MD, 20850, USA.

Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and the Tyrer-Cuzick breast cancer risk prediction models are commonly used in clinical practice and have recently been extended to include polygenic risk scores (PRS). In addition, BOADICEA has also been extended to include reproductive and lifestyle factors, which were already part of Tyrer-Cuzick model. We conducted a comparative prospective validation of these models after incorporating the recently developed 313-variant PRS.

Methods: Calibration and discrimination of 5-year absolute risk was assessed in a nested case-control sample of 1337 women of European ancestry (619 incident breast cancer cases) aged 23-75 years from the Generations Study.

Results: The extended BOADICEA model with reproductive/lifestyle factors and PRS was well calibrated across risk deciles; expected-to-observed ratio (E/O) at the highest risk decile :0.97 (95 % CI 0.51 - 1.86) for women younger than 50 years and 1.09 (0.66 - 1.80) for women 50 years or older. Adding reproductive/lifestyle factors and PRS to the BOADICEA model improved discrimination modestly in younger women (area under the curve (AUC) 69.7 % vs. 69.1%) and substantially in older women (AUC 64.6 % vs. 56.8%). The Tyrer-Cuzick model with PRS showed evidence of overestimation at the highest risk decile: E/O = 1.54(0.81 - 2.92) for younger and 1.73 (1.03 - 2.90) for older women.

Conclusion: The extended BOADICEA model identified women in a European-ancestry population at elevated breast cancer risk more accurately than the Tyrer-Cuzick model with PRS. With the increasing availability of PRS, these analyses can inform choice of risk models incorporating PRS for risk stratified breast cancer prevention among women of European ancestry.
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http://dx.doi.org/10.1186/s13058-021-01399-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885342PMC
February 2021

Rare Germline Variants in ATM Predispose to Prostate Cancer: A PRACTICAL Consortium Study.

Eur Urol Oncol 2021 Aug 9;4(4):570-579. Epub 2021 Jan 9.

Institute of Biomedicine, University of Turku, Turku, Finland.

Background: Germline ATM mutations are suggested to contribute to predisposition to prostate cancer (PrCa). Previous studies have had inadequate power to estimate variant effect sizes.

Objective: To precisely estimate the contribution of germline ATM mutations to PrCa risk.

Design, Setting, And Participants: We analysed next-generation sequencing data from 13 PRACTICAL study groups comprising 5560 cases and 3353 controls of European ancestry.

Outcome Measurements And Statistical Analysis: Variant Call Format files were harmonised, annotated for rare ATM variants, and classified as tier 1 (likely pathogenic) or tier 2 (potentially deleterious). Associations with overall PrCa risk and clinical subtypes were estimated.

Results And Limitations: PrCa risk was higher in carriers of a tier 1 germline ATM variant, with an overall odds ratio (OR) of 4.4 (95% confidence interval [CI]: 2.0-9.5). There was also evidence that PrCa cases with younger age at diagnosis (<65 yr) had elevated tier 1 variant frequencies (p = 0.04). Tier 2 variants were also associated with PrCa risk, with an OR of 1.4 (95% CI: 1.1-1.7).

Conclusions: Carriers of pathogenic ATM variants have an elevated risk of developing PrCa and are at an increased risk for earlier-onset disease presentation. These results provide information for counselling of men and their families.

Patient Summary: In this study, we estimated that men who inherit a likely pathogenic mutation in the ATM gene had an approximately a fourfold risk of developing prostate cancer. In addition, they are likely to develop the disease earlier.
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http://dx.doi.org/10.1016/j.euo.2020.12.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8381233PMC
August 2021

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Nat Genet 2021 01 4;53(1):65-75. Epub 2021 Jan 4.

Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.
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http://dx.doi.org/10.1038/s41588-020-00748-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148035PMC
January 2021

Adult weight change and premenopausal breast cancer risk: A prospective pooled analysis of data from 628,463 women.

Int J Cancer 2020 09 15;147(5):1306-1314. Epub 2020 Feb 15.

Albert Einstein College of Medicine, Bronx, NY.

Early-adulthood body size is strongly inversely associated with risk of premenopausal breast cancer. It is unclear whether subsequent changes in weight affect risk. We pooled individual-level data from 17 prospective studies to investigate the association of weight change with premenopausal breast cancer risk, considering strata of initial weight, timing of weight change, other breast cancer risk factors and breast cancer subtype. Hazard ratios (HR) and 95% confidence intervals (CI) were obtained using Cox regression. Among 628,463 women, 10,886 were diagnosed with breast cancer before menopause. Models adjusted for initial weight at ages 18-24 years and other breast cancer risk factors showed that weight gain from ages 18-24 to 35-44 or to 45-54 years was inversely associated with breast cancer overall (e.g., HR per 5 kg to ages 45-54: 0.96, 95% CI: 0.95-0.98) and with oestrogen-receptor(ER)-positive breast cancer (HR per 5 kg to ages 45-54: 0.96, 95% CI: 0.94-0.98). Weight gain from ages 25-34 was inversely associated with ER-positive breast cancer only and weight gain from ages 35-44 was not associated with risk. None of these weight gains were associated with ER-negative breast cancer. Weight loss was not consistently associated with overall or ER-specific risk after adjusting for initial weight. Weight increase from early-adulthood to ages 45-54 years is associated with a reduced premenopausal breast cancer risk independently of early-adulthood weight. Biological explanations are needed to account for these two separate factors.
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http://dx.doi.org/10.1002/ijc.32892DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365745PMC
September 2020

Interim Results from the IMPACT Study: Evidence for Prostate-specific Antigen Screening in BRCA2 Mutation Carriers.

Eur Urol 2019 12 16;76(6):831-842. Epub 2019 Sep 16.

International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University in Szczecin, Szczecin, Poland.

Background: Mutations in BRCA2 cause a higher risk of early-onset aggressive prostate cancer (PrCa). The IMPACT study is evaluating targeted PrCa screening using prostate-specific-antigen (PSA) in men with germline BRCA1/2 mutations.

Objective: To report the utility of PSA screening, PrCa incidence, positive predictive value of PSA, biopsy, and tumour characteristics after 3 yr of screening, by BRCA status.

Design, Setting, And Participants: Men aged 40-69 yr with a germline pathogenic BRCA1/2 mutation and male controls testing negative for a familial BRCA1/2 mutation were recruited. Participants underwent PSA screening for 3 yr, and if PSA > 3.0 ng/ml, men were offered prostate biopsy.

Outcome Measurements And Statistical Analysis: PSA levels, PrCa incidence, and tumour characteristics were evaluated. Statistical analyses included Poisson regression offset by person-year follow-up, chi-square tests for proportion t tests for means, and Kruskal-Wallis for medians.

Results And Limitations: A total of 3027 patients (2932 unique individuals) were recruited (919 BRCA1 carriers, 709 BRCA1 noncarriers, 902 BRCA2 carriers, and 497 BRCA2 noncarriers). After 3 yr of screening, 527 men had PSA > 3.0 ng/ml, 357 biopsies were performed, and 112 PrCa cases were diagnosed (31 BRCA1 carriers, 19 BRCA1 noncarriers, 47 BRCA2 carriers, and 15 BRCA2 noncarriers). Higher compliance with biopsy was observed in BRCA2 carriers compared with noncarriers (73% vs 60%). Cancer incidence rate per 1000 person years was higher in BRCA2 carriers than in noncarriers (19.4 vs 12.0; p =  0.03); BRCA2 carriers were diagnosed at a younger age (61 vs 64 yr; p =  0.04) and were more likely to have clinically significant disease than BRCA2 noncarriers (77% vs 40%; p =  0.01). No differences in age or tumour characteristics were detected between BRCA1 carriers and BRCA1 noncarriers. The 4 kallikrein marker model discriminated better (area under the curve [AUC] = 0.73) for clinically significant cancer at biopsy than PSA alone (AUC = 0.65).

Conclusions: After 3 yr of screening, compared with noncarriers, BRCA2 mutation carriers were associated with a higher incidence of PrCa, younger age of diagnosis, and clinically significant tumours. Therefore, systematic PSA screening is indicated for men with a BRCA2 mutation. Further follow-up is required to assess the role of screening in BRCA1 mutation carriers.

Patient Summary: We demonstrate that after 3 yr of prostate-specific antigen (PSA) testing, we detect more serious prostate cancers in men with BRCA2 mutations than in those without these mutations. We recommend that male BRCA2 carriers are offered systematic PSA screening.
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http://dx.doi.org/10.1016/j.eururo.2019.08.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6880781PMC
December 2019

Comparative Validation of Breast Cancer Risk Prediction Models and Projections for Future Risk Stratification.

J Natl Cancer Inst 2020 03;112(3):278-285

Johns Hopkins University, Baltimore, MD.

Background: External validation of risk models is critical for risk-stratified breast cancer prevention. We used the Individualized Coherent Absolute Risk Estimation (iCARE) as a flexible tool for risk model development and comparative model validation and to make projections for population risk stratification.

Methods: Performance of two recently developed models, one based on the Breast and Prostate Cancer Cohort Consortium analysis (iCARE-BPC3) and another based on a literature review (iCARE-Lit), were compared with two established models (Breast Cancer Risk Assessment Tool and International Breast Cancer Intervention Study Model) based on classical risk factors in a UK-based cohort of 64 874 white non-Hispanic women (863 patients) age 35-74 years. Risk projections in a target population of US white non-Hispanic women age 50-70 years assessed potential improvements in risk stratification by adding mammographic breast density (MD) and polygenic risk score (PRS).

Results: The best calibrated models were iCARE-Lit (expected to observed number of cases [E/O] = 0.98, 95% confidence interval [CI] = 0.87 to 1.11) for women younger than 50 years, and iCARE-BPC3 (E/O = 1.00, 95% CI = 0.93 to 1.09) for women 50 years or older. Risk projections using iCARE-BPC3 indicated classical risk factors can identify approximately 500 000 women at moderate to high risk (>3% 5-year risk) in the target population. Addition of MD and a 313-variant PRS is expected to increase this number to approximately 3.5 million women, and among them, approximately 153 000 are expected to develop invasive breast cancer within 5 years.

Conclusions: iCARE models based on classical risk factors perform similarly to or better than BCRAT or IBIS in white non-Hispanic women. Addition of MD and PRS can lead to substantial improvements in risk stratification. However, these integrated models require independent prospective validation before broad clinical applications.
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http://dx.doi.org/10.1093/jnci/djz113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073933PMC
March 2020

Correction: Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease.

Br J Cancer 2019 Apr;120(8):867

Oncogenetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.

This article was originally published under the standard License to Publish, but has now been made available under a CC BY 4.0 license. The PDF and HTML versions of the paper have been modified accordingly.
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http://dx.doi.org/10.1038/s41416-019-0419-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474270PMC
April 2019

Germline DNA Repair Gene Mutations in Young-onset Prostate Cancer Cases in the UK: Evidence for a More Extensive Genetic Panel.

Eur Urol 2019 09 15;76(3):329-337. Epub 2019 Feb 15.

Oncogenetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK.

Background: Rare germline mutations in DNA repair genes are associated with prostate cancer (PCa) predisposition and prognosis.

Objective: To quantify the frequency of germline DNA repair gene mutations in UK PCa cases and controls, in order to more comprehensively evaluate the contribution of individual genes to overall PCa risk and likelihood of aggressive disease.

Design, Setting, And Participants: We sequenced 167 DNA repair and eight PCa candidate genes in a UK-based cohort of 1281 young-onset PCa cases (diagnosed at ≤60yr) and 1160 selected controls.

Outcome Measurements And Statistical Analysis: Gene-level SKAT-O and gene-set adaptive combination of p values (ADA) analyses were performed separately for cases versus controls, and aggressive (Gleason score ≥8, n=201) versus nonaggressive (Gleason score ≤7, n=1048) cases.

Results And Limitations: We identified 233 unique protein truncating variants (PTVs) with minor allele frequency <0.5% in controls in 97 genes. The total proportion of PTV carriers was higher in cases than in controls (15% vs 12%, odds ratio [OR]=1.29, 95% confidence interval [CI] 1.01-1.64, p=0.036). Gene-level analyses selected NBN (p=2.4×10) for overall risk and XPC (p=1.6×10) for aggressive disease, both at candidate-level significance (p<3.1×10 and p<3.4×10, respectively). Gene-set analysis identified a subset of 20 genes associated with increased PCa risk (OR=3.2, 95% CI 2.1-4.8, p=4.1×10) and four genes that increased risk of aggressive disease (OR=11.2, 95% CI 4.6-27.7, p=5.6×10), three of which overlap the predisposition gene set.

Conclusions: The union of the gene-level and gene-set-level analyses identified 23 unique DNA repair genes associated with PCa predisposition or risk of aggressive disease. These findings will help facilitate the development of a PCa-specific sequencing panel with both predictive and prognostic potential.

Patient Summary: This large sequencing study assessed the rate of inherited DNA repair gene mutations between prostate cancer patients and disease-free men. A panel of 23 genes was identified, which may improve risk prediction or treatment pathways in future clinical practice.
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http://dx.doi.org/10.1016/j.eururo.2019.01.050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695475PMC
September 2019

Shared heritability and functional enrichment across six solid cancers.

Nat Commun 2019 01 25;10(1):431. Epub 2019 Jan 25.

Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Calle de Melchor Fernández Almagro, 3, 28029, Madrid, Spain.

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r = 0.57, p = 4.6 × 10), breast and ovarian cancer (r = 0.24, p = 7 × 10), breast and lung cancer (r = 0.18, p =1.5 × 10) and breast and colorectal cancer (r = 0.15, p = 1.1 × 10). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
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http://dx.doi.org/10.1038/s41467-018-08054-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347624PMC
January 2019

Author Correction: Germline variation at 8q24 and prostate cancer risk in men of European ancestry.

Nat Commun 2019 01 17;10(1):382. Epub 2019 Jan 17.

Department of Medical Genetics, Oslo University Hospital, 0424, Oslo, Norway.

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.
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http://dx.doi.org/10.1038/s41467-019-08293-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336778PMC
January 2019

Author Correction: Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Nat Genet 2019 02;51(2):363

Dame Roma Mitchell Cancer Research Centre, University of Adelaide, Adelaide, South Australia, Australia.

In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.
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http://dx.doi.org/10.1038/s41588-018-0330-6DOI Listing
February 2019

Prostate Cancer Risk-Associated Single-Nucleotide Polymorphism Affects Prostate-Specific Antigen Glycosylation and Its Function.

Clin Chem 2019 01 11;65(1):e1-e9. Epub 2018 Dec 11.

Australian Prostate Cancer Research Centre-Queensland and Cancer Program, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia;

Background: Genetic association studies have reported single-nucleotide polymorphisms (SNPs) at chromosome 19q13.3 to be associated with prostate cancer (PCa) risk. Recently, the rs61752561 SNP (Asp84Asn substitution) in exon 3 of the kallikrein-related peptidase 3 () gene encoding prostate-specific antigen (PSA) was reported to be strongly associated with PCa risk ( = 2.3 × 10). However, the biological contribution of the rs61752561 SNP to PCa risk has not been elucidated.

Methods: Recombinant PSA protein variants were generated to assess the SNP-mediated biochemical changes by stability and substrate activity assays. PC3 cell-PSA overexpression models were established to evaluate the effect of the SNP on PCa pathogenesis. Genotype-specific correlation of the SNP with total PSA (tPSA) concentrations and free/total (F/T) PSA ratio were determined from serum samples.

Results: Functional analysis showed that the rs61752561 SNP affects PSA stability and structural conformation and creates an extra glycosylation site. This PSA variant had reduced enzymatic activity and the ability to stimulate proliferation and migration of PCa cells. Interestingly, the minor allele is associated with lower tPSA concentrations and high F/T PSA ratio in serum samples, indicating that the amino acid substitution may affect PSA immunoreactivity to the antibodies used in the clinical immunoassays.

Conclusions: The rs61752561 SNP appears to have a potential role in PCa pathogenesis by changing the glycosylation, protein stability, and PSA activity and may also affect the clinically measured F/T PSA ratio. Accounting for these effects on tPSA concentration and F/T PSA ratio may help to improve the accuracy of the current PSA test.
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http://dx.doi.org/10.1373/clinchem.2018.295790DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6643286PMC
January 2019

Breast Cancer Risk After Recent Childbirth: A Pooled Analysis of 15 Prospective Studies.

Ann Intern Med 2019 01 11;170(1):22-30. Epub 2018 Dec 11.

School of Public Health, Imperial College London, London, United Kingdom (M.A.M., E.R.).

Background: Parity is widely recognized as protective for breast cancer, but breast cancer risk may be increased shortly after childbirth. Whether this risk varies with breastfeeding, family history of breast cancer, or specific tumor subtype has rarely been evaluated.

Objective: To characterize breast cancer risk in relation to recent childbirth.

Design: Pooled analysis of individual-level data from 15 prospective cohort studies.

Setting: The international Premenopausal Breast Cancer Collaborative Group.

Participants: Women younger than 55 years.

Measurements: During 9.6 million person-years of follow-up, 18 826 incident cases of breast cancer were diagnosed. Hazard ratios (HRs) and 95% CIs for breast cancer were calculated using Cox proportional hazards regression.

Results: Compared with nulliparous women, parous women had an HR for breast cancer that peaked about 5 years after birth (HR, 1.80 [95% CI, 1.63 to 1.99]) before decreasing to 0.77 (CI, 0.67 to 0.88) after 34 years. The association crossed over from positive to negative about 24 years after birth. The overall pattern was driven by estrogen receptor (ER)-positive breast cancer; no crossover was seen for ER-negative cancer. Increases in breast cancer risk after childbirth were pronounced when combined with a family history of breast cancer and were greater for women who were older at first birth or who had more births. Breastfeeding did not modify overall risk patterns.

Limitations: Breast cancer diagnoses during pregnancy were not uniformly distinguishable from early postpartum diagnoses. Data on human epidermal growth factor receptor 2 (HER2) oncogene overexpression were limited.

Conclusion: Compared with nulliparous women, parous women have an increased risk for breast cancer for more than 20 years after childbirth. Health care providers should consider recent childbirth a risk factor for breast cancer in young women.

Primary Funding Source: The Avon Foundation, the National Institute of Environmental Health Sciences, Breast Cancer Now and the UK National Health Service, and the Institute of Cancer Research.
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http://dx.doi.org/10.7326/M18-1323DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6760671PMC
January 2019

Homeobox B13 G84E Mutation and Prostate Cancer Risk.

Eur Urol 2019 05 8;75(5):834-845. Epub 2018 Dec 8.

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

Background: The homeobox B13 (HOXB13) G84E mutation has been recommended for use in genetic counselling for prostate cancer (PCa), but the magnitude of PCa risk conferred by this mutation is uncertain.

Objective: To obtain precise risk estimates for mutation carriers and information on how these vary by family history and other factors.

Design, Setting, And Participants: Two-fold: a systematic review and meta-analysis of published risk estimates, and a kin-cohort study comprising pedigree data on 11983 PCa patients enrolled during 1993-2014 from 189 UK hospitals and who had been genotyped for HOXB13 G84E.

Outcome Measurements And Statistical Analysis: Relative and absolute PCa risks. Complex segregation analysis with ascertainment adjustment to derive age-specific risks applicable to the population, and to investigate how these vary by family history and birth cohort.

Results And Limitations: A meta-analysis of case-control studies revealed significant heterogeneity between reported relative risks (RRs; range: 0.95-33.0, p<0.001) and differences by case selection (p=0.007). Based on case-control studies unselected for PCa family history, the pooled RR estimate was 3.43 (95% confidence interval [CI] 2.78-4.23). In the kin-cohort study, PCa risk for mutation carriers varied by family history (p<0.001). There was a suggestion that RRs decrease with age, but this was not significant (p=0.068). We found higher RR estimates for men from more recent birth cohorts (p=0.004): 3.09 (95% CI 2.03-4.71) for men born in 1929 or earlier and 5.96 (95% CI 4.01-8.88) for men born in 1930 or later. The absolute PCa risk by age 85 for a male HOXB13 G84E carrier varied from 60% for those with no PCa family history to 98% for those with two relatives diagnosed at young ages, compared with an average risk of 15% for noncarriers. Limitations include the reliance on self-reported cancer family history.

Conclusions: PCa risks for HOXB13 G84E mutation carriers are heterogeneous. Counselling should not be based on average risk estimates but on age-specific absolute risk estimates tailored to individual mutation carriers' family history and birth cohort.

Patient Summary: Men who carry a hereditary mutation in the homeobox B13 (HOXB13) gene have a higher than average risk for developing prostate cancer. In our study, we examined a large number of families of men with prostate cancer recruited across UK hospitals, to assess what other factors may contribute to this risk and to assess whether we could create a precise model to help in predicting a man's prostate cancer risk. We found that the risk of developing prostate cancer in men who carry this genetic mutation is also affected by a family history of prostate cancer and their year of birth. This information can be used to assess more personalised prostate cancer risks to men who carry HOXB13 mutations and hence better counsel them on more personalised risk management options, such as tailoring prostate cancer screening frequency.
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http://dx.doi.org/10.1016/j.eururo.2018.11.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6470122PMC
May 2019

Germline variation at 8q24 and prostate cancer risk in men of European ancestry.

Nat Commun 2018 11 5;9(1):4616. Epub 2018 Nov 5.

Department of Medical Genetics, Oslo University Hospital, 0424, Oslo, Norway.

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.
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http://dx.doi.org/10.1038/s41467-018-06863-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6218483PMC
November 2018

Association of Body Mass Index and Age With Subsequent Breast Cancer Risk in Premenopausal Women.

JAMA Oncol 2018 11 8;4(11):e181771. Epub 2018 Nov 8.

School of Public Health, Imperial College, London, England.

Importance: The association between increasing body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and risk of breast cancer is unique in cancer epidemiology in that a crossover effect exists, with risk reduction before and risk increase after menopause. The inverse association with premenopausal breast cancer risk is poorly characterized but might be important in the understanding of breast cancer causation.

Objective: To investigate the association of BMI with premenopausal breast cancer risk, in particular by age at BMI, attained age, risk factors for breast cancer, and tumor characteristics.

Design, Setting, And Participants: This multicenter analysis used pooled individual-level data from 758 592 premenopausal women from 19 prospective cohorts to estimate hazard ratios (HRs) of premenopausal breast cancer in association with BMI from ages 18 through 54 years using Cox proportional hazards regression analysis. Median follow-up was 9.3 years (interquartile range, 4.9-13.5 years) per participant, with 13 082 incident cases of breast cancer. Participants were recruited from January 1, 1963, through December 31, 2013, and data were analyzed from September 1, 2013, through December 31, 2017.

Exposures: Body mass index at ages 18 to 24, 25 to 34, 35 to 44, and 45 to 54 years.

Main Outcomes And Measures: Invasive or in situ premenopausal breast cancer.

Results: Among the 758 592 premenopausal women (median age, 40.6 years; interquartile range, 35.2-45.5 years) included in the analysis, inverse linear associations of BMI with breast cancer risk were found that were stronger for BMI at ages 18 to 24 years (HR per 5 kg/m2 [5.0-U] difference, 0.77; 95% CI, 0.73-0.80) than for BMI at ages 45 to 54 years (HR per 5.0-U difference, 0.88; 95% CI, 0.86-0.91). The inverse associations were observed even among nonoverweight women. There was a 4.2-fold risk gradient between the highest and lowest BMI categories (BMI≥35.0 vs <17.0) at ages 18 to 24 years (HR, 0.24; 95% CI, 0.14-0.40). Hazard ratios did not appreciably vary by attained age or between strata of other breast cancer risk factors. Associations were stronger for estrogen receptor-positive and/or progesterone receptor-positive than for hormone receptor-negative breast cancer for BMI at every age group (eg, for BMI at age 18 to 24 years: HR per 5.0-U difference for estrogen receptor-positive and progesterone receptor-positive tumors, 0.76 [95% CI, 0.70-0.81] vs hormone receptor-negative tumors, 0.85 [95% CI: 0.76-0.95]); BMI at ages 25 to 54 years was not consistently associated with triple-negative or hormone receptor-negative breast cancer overall.

Conclusions And Relevance: The results of this study suggest that increased adiposity is associated with a reduced risk of premenopausal breast cancer at a greater magnitude than previously shown and across the entire distribution of BMI. The strongest associations of risk were observed for BMI in early adulthood. Understanding the biological mechanisms underlying these associations could have important preventive potential.
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http://dx.doi.org/10.1001/jamaoncol.2018.1771DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248078PMC
November 2018

Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease.

Br J Cancer 2018 07 19;119(1):96-104. Epub 2018 Jun 19.

Oncogenetics, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK.

Background: Prostate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes.

Methods: We sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis ≥60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants.

Results: Protein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects.

Conclusions: Inherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application.
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http://dx.doi.org/10.1038/s41416-018-0141-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6035259PMC
July 2018

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

Nat Commun 2018 06 11;9(1):2256. Epub 2018 Jun 11.

Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, Brisbane, QLD, 4059, Australia.

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
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http://dx.doi.org/10.1038/s41467-018-04109-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5995836PMC
June 2018

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Nat Genet 2018 07 11;50(7):928-936. Epub 2018 Jun 11.

Dame Roma Mitchell Cancer Research Centre, University of Adelaide, Adelaide, South Australia, Australia.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa.
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http://dx.doi.org/10.1038/s41588-018-0142-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6568012PMC
July 2018

Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium.

Int J Epidemiol 2018 04;47(2):526-536

Department of Laboratory Medicine and Pathology.

Background: Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors.

Methods: Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status.

Results: The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests).

Conclusions: The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.
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http://dx.doi.org/10.1093/ije/dyx242DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5913605PMC
April 2018

The Premenopausal Breast Cancer Collaboration: A Pooling Project of Studies Participating in the National Cancer Institute Cohort Consortium.

Cancer Epidemiol Biomarkers Prev 2017 09 9;26(9):1360-1369. Epub 2017 Jun 9.

UiT (University of Tromsø), Tromsø, Norway.

Breast cancer is a leading cancer diagnosis among premenopausal women around the world. Unlike rates in postmenopausal women, incidence rates of advanced breast cancer have increased in recent decades for premenopausal women. Progress in identifying contributors to breast cancer risk among premenopausal women has been constrained by the limited numbers of premenopausal breast cancer cases in individual studies and resulting low statistical power to subcategorize exposures or to study specific subtypes. The Premenopausal Breast Cancer Collaborative Group was established to facilitate cohort-based analyses of risk factors for premenopausal breast cancer by pooling individual-level data from studies participating in the United States National Cancer Institute Cohort Consortium. This article describes the Group, including the rationale for its initial aims related to pregnancy, obesity, and physical activity. We also describe the 20 cohort studies with data submitted to the Group by June 2016. The infrastructure developed for this work can be leveraged to support additional investigations. .
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http://dx.doi.org/10.1158/1055-9965.EPI-17-0246DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5581673PMC
September 2017

Genetic predisposition to ductal carcinoma in situ of the breast.

Breast Cancer Res 2016 Feb 17;18(1):22. Epub 2016 Feb 17.

Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia.

Background: Ductal carcinoma in situ (DCIS) is a non-invasive form of breast cancer. It is often associated with invasive ductal carcinoma (IDC), and is considered to be a non-obligate precursor of IDC. It is not clear to what extent these two forms of cancer share low-risk susceptibility loci, or whether there are differences in the strength of association for shared loci.

Methods: To identify genetic polymorphisms that predispose to DCIS, we pooled data from 38 studies comprising 5,067 cases of DCIS, 24,584 cases of IDC and 37,467 controls, all genotyped using the iCOGS chip.

Results: Most (67 %) of the 76 known breast cancer predisposition loci showed an association with DCIS in the same direction as previously reported for invasive breast cancer. Case-only analysis showed no evidence for differences between associations for IDC and DCIS after considering multiple testing. Analysis by estrogen receptor (ER) status confirmed that loci associated with ER positive IDC were also associated with ER positive DCIS. Analysis of DCIS by grade suggested that two independent SNPs at 11q13.3 near CCND1 were specific to low/intermediate grade DCIS (rs75915166, rs554219). These associations with grade remained after adjusting for ER status and were also found in IDC. We found no novel DCIS-specific loci at a genome wide significance level of P < 5.0x10(-8).

Conclusion: In conclusion, this study provides the strongest evidence to date of a shared genetic susceptibility for IDC and DCIS. Studies with larger numbers of DCIS are needed to determine if IDC or DCIS specific loci exist.
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http://dx.doi.org/10.1186/s13058-016-0675-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4756509PMC
February 2016

Mitochondrial DNA Copy Number in Peripheral Blood Cells and Risk of Developing Breast Cancer.

Cancer Res 2015 Jul 14;75(14):2844-50. Epub 2015 May 14.

The Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, United Kingdom. Division of Breast Cancer Research, The Institute of Cancer Research, London, United Kingdom. Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.

Increased mitochondrial DNA (mtDNA) copy number in peripheral blood cells (PBC) has been associated with the risk of developing several tumor types. Here we evaluate sources of variation of this biomarker and its association with breast cancer risk in a prospective cohort study. mtDNA copy number was measured using quantitative real-time PCR on PBC DNA samples from participants in the UK-based Breakthrough Generations Study. Temporal and assay variation was evaluated in a serial study of 91 women, with two blood samples collected approximately 6-years apart. Then, associations with breast cancer risk factors and risk were evaluated in 1,108 cases and 1,099 controls using a nested case-control design. In the serial study, mtDNA copy number showed low assay variation but large temporal variation [assay intraclass correlation coefficient (ICC), 79.3%-87.9%; temporal ICC, 38.3%). Higher mtDNA copy number was significantly associated with younger age at blood collection, being premenopausal, having an older age at menopause, and never taking HRT, both in cases and controls. Based on measurements in a single blood sample taken on average 6 years before diagnosis, higher mtDNA copy number was associated with increased breast cancer risk [OR (95% CI) for highest versus lowest quartile, 1.37 (1.02-1.83); P trend = 0.007]. In conclusion, mtDNA copy number is associated with breast cancer risk and represents a promising biomarker for risk assessment. The relatively large temporal variation should be taken into account in future analyses.
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http://dx.doi.org/10.1158/0008-5472.CAN-14-1692DOI Listing
July 2015

Prediction of breast cancer risk based on profiling with common genetic variants.

J Natl Cancer Inst 2015 May 8;107(5). Epub 2015 Apr 8.

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK (NM, PDPP, KM, MKB, QW, JD, RL, JBr, DFE); Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK (PDPP, JT, AMD, MS, CL, CB, SA, MM, CSH, DFE); Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK (MNB, ASw, MJS); Copenhagen General Population Study, Herlev Hospital, Copenhagen University Hospital, Copenhagen, Denmark (SEB, BGN, SFN); Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark (SEB, BGN, SFN); Faculty of Health and Medical Sciences, Copenhagen University Hospital, Copenhagen, Herlev, Denmark (SEB, BGN); Department of Breast Surgery, Herlev Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark (HF); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (KC, HD, ME, KH, PHa); Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK (JP, IdSS, FD); Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK (NJ, AA, NO, MGC); Netherlands Cancer Institute, Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands (MKS, AB, SV, EJR); Division of Breast Cancer Research, Institute of Cancer Research, London, UK (ASw); Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD (JF, SJC, LB, ASi, MD); Department of Cancer Epidemiology and Prevention, M. Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland (JLis); Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN (FJC); Department of Health Sciences Research, Mayo Clinic, Rochester, MN (JEO, CV, VSP, SS); Vesalius Research Center, VIB, Leuven, Belgium (DL); Laboratory for Translational Genetics, Department of Oncology, University of

Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking.

Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates.

Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer.

Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.
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http://dx.doi.org/10.1093/jnci/djv036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4754625PMC
May 2015

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium.

J Pathol Clin Res 2015 Jan 4;1(1):18-32. Epub 2014 Dec 4.

Division of Cancer Epidemiology and Genetics National Cancer Institute Rockville Maryland USA.

Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large-scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65-70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose-response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96-98%), but yielded many false positives (positive predictive value = 30-32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large-scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker-specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.
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http://dx.doi.org/10.1002/cjp2.3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4858117PMC
January 2015

Temporal stability and determinants of white blood cell DNA methylation in the breakthrough generations study.

Cancer Epidemiol Biomarkers Prev 2015 Jan 4;24(1):221-9. Epub 2014 Nov 4.

Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom. Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, United Kingdom.

Background: Epigenome-wide association studies (EWAS) using measurements of blood DNA methylation are performed to identify associations of methylation changes with environmental and lifestyle exposures and disease risk. However, little is known about the variation of methylation markers in the population and their stability over time, both important factors in the design and interpretation of EWAS. We aimed to identify stable variable methylated probes (VMP), i.e., markers that are variable in the population, yet stable over time.

Methods: We estimated the intraclass correlation coefficient (ICC) for each probe on the Illumina 450K methylation array in paired samples collected approximately 6 years apart from 92 participants in the Breakthrough Generations Study. We also evaluated relationships with age, reproductive and hormonal history, weight, alcohol intake, and smoking.

Results: Approximately 17% of probes had an ICC > 0.50 and were considered stable VMPs (stable-VMPs). Stable-VMPs were enriched for probes located in "shores" bordering CpG islands, and at approximately 1.3 kb downstream from the transcription start site in the transition between the unmethylated promoter and methylated gene body. Both cross-sectional and longitudinal data analyses provided strong evidence for associations between changes in methylation levels and aging. Smoking-related probes at 2q37.1 and AHRR were stable-VMPs and related to time since quitting. We also observed associations between methylation and weight changes.

Conclusion: Our results provide support for the use of white blood cell DNA methylation as a biomarker of exposure in EWAS.

Impact: Larger studies, preferably with repeated measures over time, will be required to establish associations between specific probes and exposures.
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http://dx.doi.org/10.1158/1055-9965.EPI-14-0767DOI Listing
January 2015

Genetic predisposition to in situ and invasive lobular carcinoma of the breast.

PLoS Genet 2014 04 17;10(4):e1004285. Epub 2014 Apr 17.

David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, California, United States of America; Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany.

Invasive lobular breast cancer (ILC) accounts for 10-15% of all invasive breast carcinomas. It is generally ER positive (ER+) and often associated with lobular carcinoma in situ (LCIS). Genome-wide association studies have identified more than 70 common polymorphisms that predispose to breast cancer, but these studies included predominantly ductal (IDC) carcinomas. To identify novel common polymorphisms that predispose to ILC and LCIS, we pooled data from 6,023 cases (5,622 ILC, 401 pure LCIS) and 34,271 controls from 36 studies genotyped using the iCOGS chip. Six novel SNPs most strongly associated with ILC/LCIS in the pooled analysis were genotyped in a further 516 lobular cases (482 ILC, 36 LCIS) and 1,467 controls. These analyses identified a lobular-specific SNP at 7q34 (rs11977670, OR (95%CI) for ILC = 1.13 (1.09-1.18), P = 6.0 × 10(-10); P-het for ILC vs IDC ER+ tumors = 1.8 × 10(-4)). Of the 75 known breast cancer polymorphisms that were genotyped, 56 were associated with ILC and 15 with LCIS at P<0.05. Two SNPs showed significantly stronger associations for ILC than LCIS (rs2981579/10q26/FGFR2, P-het = 0.04 and rs889312/5q11/MAP3K1, P-het = 0.03); and two showed stronger associations for LCIS than ILC (rs6678914/1q32/LGR6, P-het = 0.001 and rs1752911/6q14, P-het = 0.04). In addition, seven of the 75 known loci showed significant differences between ER+ tumors with IDC and ILC histology, three of these showing stronger associations for ILC (rs11249433/1p11, rs2981579/10q26/FGFR2 and rs10995190/10q21/ZNF365) and four associated only with IDC (5p12/rs10941679; rs2588809/14q24/RAD51L1, rs6472903/8q21 and rs1550623/2q31/CDCA7). In conclusion, we have identified one novel lobular breast cancer specific predisposition polymorphism at 7q34, and shown for the first time that common breast cancer polymorphisms predispose to LCIS. We have shown that many of the ER+ breast cancer predisposition loci also predispose to ILC, although there is some heterogeneity between ER+ lobular and ER+ IDC tumors. These data provide evidence for overlapping, but distinct etiological pathways within ER+ breast cancer between morphological subtypes.
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http://dx.doi.org/10.1371/journal.pgen.1004285DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3990493PMC
April 2014
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