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1. Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results.

Author

John E.M., Terry M.B., Hopper J.L., Macinnis R.J., Liao Y., Knight J.A., Milne R.L., Whittemore A.S., Chung W.K., Leoce N., Buchsbaum R., Zeinomar N., Dite G.S., Southey M.C., Goldgar D., Phillips K.A., Giles G.G., Buys S.S., Daly M.B., McLachlan S.-A., Weideman P.C., Nesci S., Friedlander M.L., Glendon G., Andrulis I.L., John E.M., Terry M.B., Hopper J.L., Macinnis R.J., Liao Y., Knight J.A., Milne R.L., Whittemore A.S., Chung W.K., Leoce N., Buchsbaum R., Zeinomar N., Dite G.S., Southey M.C., Goldgar D., Phillips K.A., Giles G.G., Buys S.S., Daly M.B., McLachlan S.-A., Weideman P.C., Nesci S., Friedlander M.L., Glendon G., and Andrulis I.L.

Abstract

The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models.Copyright © 2019 The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Published
2020

2. Use of folfirinox chemotherapy in an Australasian population of pancreatic cancer.

Author

Harris M., Lee B., Gibbs P., Tebbutt N., Croagh D., Jalali A., Lee M., Semira C., Banks S., Wong H.-L., Ananda S., Lipton L., Shapiro J.D., Cooray P., Clarke K., Burge M., Wong R., Shapiro J.A., McLachlan S.-A., Harris M., Lee B., Gibbs P., Tebbutt N., Croagh D., Jalali A., Lee M., Semira C., Banks S., Wong H.-L., Ananda S., Lipton L., Shapiro J.D., Cooray P., Clarke K., Burge M., Wong R., Shapiro J.A., and McLachlan S.-A.

Published
2020

3. Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results.

Author

John E.M., Terry M.B., Hopper J.L., Macinnis R.J., Liao Y., Knight J.A., Milne R.L., Whittemore A.S., Chung W.K., Leoce N., Buchsbaum R., Zeinomar N., Dite G.S., Southey M.C., Goldgar D., Phillips K.A., Giles G.G., Buys S.S., Daly M.B., McLachlan S.-A., Weideman P.C., Nesci S., Friedlander M.L., Glendon G., Andrulis I.L., John E.M., Terry M.B., Hopper J.L., Macinnis R.J., Liao Y., Knight J.A., Milne R.L., Whittemore A.S., Chung W.K., Leoce N., Buchsbaum R., Zeinomar N., Dite G.S., Southey M.C., Goldgar D., Phillips K.A., Giles G.G., Buys S.S., Daly M.B., McLachlan S.-A., Weideman P.C., Nesci S., Friedlander M.L., Glendon G., and Andrulis I.L.

Abstract

The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models.Copyright © 2019 The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Published
2020

4. Use of folfirinox chemotherapy in an Australasian population of pancreatic cancer.

Author

Harris M., Lee B., Gibbs P., Tebbutt N., Croagh D., Jalali A., Lee M., Semira C., Banks S., Wong H.-L., Ananda S., Lipton L., Shapiro J.D., Cooray P., Clarke K., Burge M., Wong R., Shapiro J.A., McLachlan S.-A., Harris M., Lee B., Gibbs P., Tebbutt N., Croagh D., Jalali A., Lee M., Semira C., Banks S., Wong H.-L., Ananda S., Lipton L., Shapiro J.D., Cooray P., Clarke K., Burge M., Wong R., Shapiro J.A., and McLachlan S.-A.

Published
2020

5. Alcohol consumption, cigarette smoking, and familial breast cancer risk: Findings from the Prospective Family Study Cohort (ProF-SC).

Author

John E.M., Andrulis I.L., Buys S.S., MacInnis R.J., Terry M.B., Hopper J.L., Zeinomar N., Knight J.A., Genkinger J.M., Phillips K.-A., Daly M.B., Milne R.L., Dite G.S., Kehm R.D., Liao Y., Southey M.C., Chung W.K., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., Nesci S., John E.M., Andrulis I.L., Buys S.S., MacInnis R.J., Terry M.B., Hopper J.L., Zeinomar N., Knight J.A., Genkinger J.M., Phillips K.-A., Daly M.B., Milne R.L., Dite G.S., Kehm R.D., Liao Y., Southey M.C., Chung W.K., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., and Nesci S.

Abstract

Background: Alcohol consumption and cigarette smoking are associated with an increased risk of breast cancer (BC), but it is unclear whether these associations vary by a woman's familial BC risk. Method(s): Using the Prospective Family Study Cohort, we evaluated associations between alcohol consumption, cigarette smoking, and BC risk. We used multivariable Cox proportional hazard models to estimate hazard ratios (HR) and 95% confidence intervals (CI). We examined whether associations were modified by familial risk profile (FRP), defined as the 1-year incidence of BC predicted by Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), a pedigree-based algorithm. Result(s): We observed 1009 incident BC cases in 17,435 women during a median follow-up of 10.4 years. We found no overall association of smoking or alcohol consumption with BC risk (current smokers compared with never smokers HR 1.02, 95% CI 0.85-1.23; consuming >= 7 drinks/week compared with non-regular drinkers HR 1.10, 95% CI 0.92-1.32), but we did observe differences in associations based on FRP and by estrogen receptor (ER) status. Women with lower FRP had an increased risk of ER-positive BC associated with consuming >= 7 drinks/week (compared to non-regular drinkers), whereas there was no association for women with higher FRP. For example, women at the 10th percentile of FRP (5-year BOADICEA = 0.15%) had an estimated HR of 1.46 (95% CI 1.07-1.99), whereas there was no association for women at the 90th percentile (5-year BOADICEA = 4.2%) (HR 1.07, 95% CI 0.80-1.44). While the associations with smoking were not modified by FRP, we observed a positive multiplicative interaction by FRP (p interaction = 0.01) for smoking status in women who also consumed alcohol, but not in women who were non-regular drinkers. Conclusion(s): Moderate alcohol intake was associated with increased BC risk, particularly for women with ER-positive BC, but only for those at lower predicted famili

Published
2019

6. Homologous recombination DNA repair defects in PALB2-associated breast cancers.

Author

Duijf P., Kentwell M., Kirk J., Kollias J., Lakhani S., Lindeman G., Lipton L., Lobb L., Lok S., Macrea F., Mann G., Marsh D., McLachlan S.-A., Meiser B., Milne R., Nightingale S., O'Connell S., Pachter N., Patterson B., Phillips K., Saleh M., Salisbury E., Saunders C., Saunus J., Scott C., Scott R., Sexton A., Shelling A., Simpson P., Spigelman A., Spurdle M., Stone J., Taylor J., Thorne H., Trainer A., Trench G., Walker L., Wallis M., Williams R., Winship I., Wu K., Young M.A., Rezoug Z., Nguyen-Dumont T., Peterlongo P., Tondini C., Terkelsen T., Ronlund K., Boonen S.E., Mannerma A., Winqvist R., Janatova M., Rajadurai P., Xia B., Norton L., Robson M.E., Ng P.-S., Looi L.-M., Southey M.C., Weigelt B., Soo-Hwang T., Tischkowitz M., Foulkes W.D., Reis-Filho J.S., Harris M., Tucker K., Visvader J., Li A., Geyer F.C., Blecua P., Lee J.Y., Selenica P., Brown D.N., Pareja F., Lee S.S.K., Kumar R., Rivera B., Bi R., Piscuoglio S., Wen H.Y., Lozada J.R., Gularte-Merida R., Cavallone L., Aghmesheh M., Amor D., Andrews L., Antill Y., Balleine R., Beesley J., Blackburn A., Bogwitz M., Brown M., Burgess M., Burke J., Butow P., Caldon L., Campbell I., Christian A., Clarke C., Cohen P., Crook A., Cui J., Cummings M., Dawson S.-J., De Fazio A., Delatycki M., Dobrovic A., Dudding T., Edkins E., Edwards S., Farshid G., Fellows A., Field M., Flanagan J., Fong P., Forbes J., Forrest L., Fox S., French J., Friedlander M., Ortega D.G., Gattas M., Giles G., Gill G., Gleeson M., Greening S., Haan E., Hayward N., Hickie I., Hopper J., Hunt C., James P., Jenkins M., Kefford R., Duijf P., Kentwell M., Kirk J., Kollias J., Lakhani S., Lindeman G., Lipton L., Lobb L., Lok S., Macrea F., Mann G., Marsh D., McLachlan S.-A., Meiser B., Milne R., Nightingale S., O'Connell S., Pachter N., Patterson B., Phillips K., Saleh M., Salisbury E., Saunders C., Saunus J., Scott C., Scott R., Sexton A., Shelling A., Simpson P., Spigelman A., Spurdle M., Stone J., Taylor J., Thorne H., Trainer A., Trench G., Walker L., Wallis M., Williams R., Winship I., Wu K., Young M.A., Rezoug Z., Nguyen-Dumont T., Peterlongo P., Tondini C., Terkelsen T., Ronlund K., Boonen S.E., Mannerma A., Winqvist R., Janatova M., Rajadurai P., Xia B., Norton L., Robson M.E., Ng P.-S., Looi L.-M., Southey M.C., Weigelt B., Soo-Hwang T., Tischkowitz M., Foulkes W.D., Reis-Filho J.S., Harris M., Tucker K., Visvader J., Li A., Geyer F.C., Blecua P., Lee J.Y., Selenica P., Brown D.N., Pareja F., Lee S.S.K., Kumar R., Rivera B., Bi R., Piscuoglio S., Wen H.Y., Lozada J.R., Gularte-Merida R., Cavallone L., Aghmesheh M., Amor D., Andrews L., Antill Y., Balleine R., Beesley J., Blackburn A., Bogwitz M., Brown M., Burgess M., Burke J., Butow P., Caldon L., Campbell I., Christian A., Clarke C., Cohen P., Crook A., Cui J., Cummings M., Dawson S.-J., De Fazio A., Delatycki M., Dobrovic A., Dudding T., Edkins E., Edwards S., Farshid G., Fellows A., Field M., Flanagan J., Fong P., Forbes J., Forrest L., Fox S., French J., Friedlander M., Ortega D.G., Gattas M., Giles G., Gill G., Gleeson M., Greening S., Haan E., Hayward N., Hickie I., Hopper J., Hunt C., James P., Jenkins M., and Kefford R.

Abstract

Mono-allelic germline pathogenic variants in the Partner And Localizer of BRCA2 (PALB2) gene predispose to a high-risk of breast cancer development, consistent with the role of PALB2 in homologous recombination (HR) DNA repair. Here, we sought to define the repertoire of somatic genetic alterations in PALB2-associated breast cancers (BCs), and whether PALB2-associated BCs display bi-allelic inactivation of PALB2 and/or genomic features of HR-deficiency (HRD). Twenty-four breast cancer patients with pathogenic PALB2 germline mutations were analyzed by whole-exome sequencing (WES, n = 16) or targeted capture massively parallel sequencing (410 cancer genes, n = 8). Somatic genetic alterations, loss of heterozygosity (LOH) of the PALB2 wild-type allele, large-scale state transitions (LSTs) and mutational signatures were defined. PALB2-associated BCs were found to be heterogeneous at the genetic level, with PIK3CA (29%), PALB2 (21%), TP53 (21%), and NOTCH3 (17%) being the genes most frequently affected by somatic mutations. Bi-allelic PALB2 inactivation was found in 16 of the 24 cases (67%), either through LOH (n = 11) or second somatic mutations (n = 5) of the wild-type allele. High LST scores were found in all 12 PALB2-associated BCs with bi-allelic PALB2 inactivation sequenced by WES, of which eight displayed the HRD-related mutational signature 3. In addition, bi-allelic inactivation of PALB2 was significantly associated with high LST scores. Our findings suggest that the identification of bi-allelic PALB2 inactivation in PALB2-associated BCs is required for the personalization of HR-directed therapies, such as platinum salts and/or PARP inhibitors, as the vast majority of PALB2-associated BCs without PALB2 bi-allelic inactivation lack genomic features of HRD.Copyright © 2019, The Author(s).

Published
2019

7. 10-year performance of four models of breast cancer risk: a validation study.

Author

John E.M., Daly M.B., Buys S.S., Hopper J.L., MacInnis R.J., Chung W.K., Knight J.A., Southey M.C., Milne R.L., Goldgar D., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Phillips K.-A., Terry M.B., Liao Y., Whittemore A.S., Leoce N., Buchsbaum R., Zeinomar N., Dite G.S., John E.M., Daly M.B., Buys S.S., Hopper J.L., MacInnis R.J., Chung W.K., Knight J.A., Southey M.C., Milne R.L., Goldgar D., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Phillips K.-A., Terry M.B., Liao Y., Whittemore A.S., Leoce N., Buchsbaum R., Zeinomar N., and Dite G.S.

Abstract

Background: Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance. Method(s): In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20-70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and partic

Published
2019

8. Publisher Correction: Homologous recombination DNA repair defects in PALB2-associated breast cancers (npj Breast Cancer, (2019), 5, 1, (23), 10.1038/s41523-019-0115-9).

Author

Cummings M., Walker L., Wallis M., Williams R., Winship I., Wu K., Young M.A., Rezoug Z., Nguyen-Dumont T., Peterlongo P., Tondini C., Terkelsen T., Ronlund K., Boonen S.E., Mannerma A., Winqvist R., Janatova M., Rajadurai P., Xia B., Norton L., Robson M.E., Ng P.-S., Looi L.-M., Southey M.C., Weigelt B., Soo-Hwang T., Tischkowitz M., Foulkes W.D., Reis-Filho J.S., Li A., Geyer F.C., Blecua P., Lee J.Y., Selenica P., Brown D.N., Pareja F., Lee S.S.K., Kumar R., Rivera B., Bi R., Piscuoglio S., Wen H.Y., Lozada J.R., Gularte-Merida R., Cavallone L., Aghmesheh M., Amor D., Andrews L., Antill Y., Balleine R., Beesley J., Blackburn A., Bogwitz M., Brown M., Burgess M., Burke J., Butow P., Caldon L., Campbell I., Christian A., Clarke C., Cohen P., Crook A., Cui J., Dawson S.-J., De Fazio A., Delatycki M., Dobrovic A., Dudding T., Duijf P., Edkins E., Edwards S., Farshid G., Fellows A., Field M., Flanagan J., Fong P., Forbes J., Forrest L., Fox S., French J., Friedlander M., Ortega D.G., Gattas M., Giles G., Gill G., Gleeson M., Greening S., Haan E., Harris M., Hayward N., Hickie I., Hopper J., Hunt C., James P., Jenkins M., Kefford R., Kentwell M., Kirk J., Kollias J., Lakhani S., Lindeman G., Lipton L., Lobb L., Lok S., Macrea F., Mann G., Marsh D., McLachlan S.-A., Meiser B., Milne R., Nightingale S., O'Connell S., Pachter N., Patterson B., Phillips K., Saleh M., Salisbury E., Saunders C., Saunus J., Scott C., Scott R., Sexton A., Shelling A., Simpson P., Spigelman A., Spurdle M., Stone J., Taylor J., Thorne H., Trainer A., Trench G., Tucker K., Visvader J., Cummings M., Walker L., Wallis M., Williams R., Winship I., Wu K., Young M.A., Rezoug Z., Nguyen-Dumont T., Peterlongo P., Tondini C., Terkelsen T., Ronlund K., Boonen S.E., Mannerma A., Winqvist R., Janatova M., Rajadurai P., Xia B., Norton L., Robson M.E., Ng P.-S., Looi L.-M., Southey M.C., Weigelt B., Soo-Hwang T., Tischkowitz M., Foulkes W.D., Reis-Filho J.S., Li A., Geyer F.C., Blecua P., Lee J.Y., Selenica P., Brown D.N., Pareja F., Lee S.S.K., Kumar R., Rivera B., Bi R., Piscuoglio S., Wen H.Y., Lozada J.R., Gularte-Merida R., Cavallone L., Aghmesheh M., Amor D., Andrews L., Antill Y., Balleine R., Beesley J., Blackburn A., Bogwitz M., Brown M., Burgess M., Burke J., Butow P., Caldon L., Campbell I., Christian A., Clarke C., Cohen P., Crook A., Cui J., Dawson S.-J., De Fazio A., Delatycki M., Dobrovic A., Dudding T., Duijf P., Edkins E., Edwards S., Farshid G., Fellows A., Field M., Flanagan J., Fong P., Forbes J., Forrest L., Fox S., French J., Friedlander M., Ortega D.G., Gattas M., Giles G., Gill G., Gleeson M., Greening S., Haan E., Harris M., Hayward N., Hickie I., Hopper J., Hunt C., James P., Jenkins M., Kefford R., Kentwell M., Kirk J., Kollias J., Lakhani S., Lindeman G., Lipton L., Lobb L., Lok S., Macrea F., Mann G., Marsh D., McLachlan S.-A., Meiser B., Milne R., Nightingale S., O'Connell S., Pachter N., Patterson B., Phillips K., Saleh M., Salisbury E., Saunders C., Saunus J., Scott C., Scott R., Sexton A., Shelling A., Simpson P., Spigelman A., Spurdle M., Stone J., Taylor J., Thorne H., Trainer A., Trench G., Tucker K., and Visvader J.

Abstract

In the original version of this paper, the link to the data record in the Data Availability Statement was incorrectly listed as https:// doi.org/10.6084/m9.figshare.8138912.44. The link has been corrected to https://doi.org/10.6084/m9.figshare.8138912. This has been corrected in the HTML and PDF versions of this article.Copyright © 2019, The Author(s).

Published
2019

9. Alcohol consumption, cigarette smoking, and familial breast cancer risk: Findings from the Prospective Family Study Cohort (ProF-SC).

Author

John E.M., Andrulis I.L., Buys S.S., MacInnis R.J., Terry M.B., Hopper J.L., Zeinomar N., Knight J.A., Genkinger J.M., Phillips K.-A., Daly M.B., Milne R.L., Dite G.S., Kehm R.D., Liao Y., Southey M.C., Chung W.K., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., Nesci S., John E.M., Andrulis I.L., Buys S.S., MacInnis R.J., Terry M.B., Hopper J.L., Zeinomar N., Knight J.A., Genkinger J.M., Phillips K.-A., Daly M.B., Milne R.L., Dite G.S., Kehm R.D., Liao Y., Southey M.C., Chung W.K., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., and Nesci S.

Abstract

Background: Alcohol consumption and cigarette smoking are associated with an increased risk of breast cancer (BC), but it is unclear whether these associations vary by a woman's familial BC risk. Method(s): Using the Prospective Family Study Cohort, we evaluated associations between alcohol consumption, cigarette smoking, and BC risk. We used multivariable Cox proportional hazard models to estimate hazard ratios (HR) and 95% confidence intervals (CI). We examined whether associations were modified by familial risk profile (FRP), defined as the 1-year incidence of BC predicted by Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), a pedigree-based algorithm. Result(s): We observed 1009 incident BC cases in 17,435 women during a median follow-up of 10.4 years. We found no overall association of smoking or alcohol consumption with BC risk (current smokers compared with never smokers HR 1.02, 95% CI 0.85-1.23; consuming >= 7 drinks/week compared with non-regular drinkers HR 1.10, 95% CI 0.92-1.32), but we did observe differences in associations based on FRP and by estrogen receptor (ER) status. Women with lower FRP had an increased risk of ER-positive BC associated with consuming >= 7 drinks/week (compared to non-regular drinkers), whereas there was no association for women with higher FRP. For example, women at the 10th percentile of FRP (5-year BOADICEA = 0.15%) had an estimated HR of 1.46 (95% CI 1.07-1.99), whereas there was no association for women at the 90th percentile (5-year BOADICEA = 4.2%) (HR 1.07, 95% CI 0.80-1.44). While the associations with smoking were not modified by FRP, we observed a positive multiplicative interaction by FRP (p interaction = 0.01) for smoking status in women who also consumed alcohol, but not in women who were non-regular drinkers. Conclusion(s): Moderate alcohol intake was associated with increased BC risk, particularly for women with ER-positive BC, but only for those at lower predicted famili

Published
2019

10. Regular use of aspirin and other non-steroidal anti-inflammatory drugs and breast cancer risk for women at familial or genetic risk: A cohort study.

Author

Buys S.S., Terry M.B., Kehm R.D., Hopper J.L., Daly M.B., John E.M., Phillips K.-A., MacInnis R.J., Dite G.S., Milne R.L., Liao Y., Zeinomar N., Knight J.A., Southey M.C., Vahdat L., Kornhauser N., Cigler T., Chung W.K., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Buys S.S., Terry M.B., Kehm R.D., Hopper J.L., Daly M.B., John E.M., Phillips K.-A., MacInnis R.J., Dite G.S., Milne R.L., Liao Y., Zeinomar N., Knight J.A., Southey M.C., Vahdat L., Kornhauser N., Cigler T., Chung W.K., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., Nesci S., and Andrulis I.L.

Abstract

Background: The use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been associated with reduced breast cancer risk, but it is not known if this association extends to women at familial or genetic risk. We examined the association between regular NSAID use and breast cancer risk using a large cohort of women selected for breast cancer family history, including 1054 BRCA1 or BRCA2 mutation carriers. Method(s): We analyzed a prospective cohort (N = 5606) and a larger combined, retrospective and prospective, cohort (N = 8233) of women who were aged 18 to 79 years, enrolled before June 30, 2011, with follow-up questionnaire data on medication history. The prospective cohort was further restricted to women without breast cancer when medication history was asked by questionnaire. Women were recruited from seven study centers in the United States, Canada, and Australia. Associations were estimated using multivariable Cox proportional hazards regression models adjusted for demographics, lifestyle factors, family history, and other medication use. Women were classified as regular or non-regular users of aspirin, COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen (control) based on self-report at follow-up of ever using the medication for at least twice a week for >=1 month prior to breast cancer diagnosis. The main outcome was incident invasive breast cancer, based on self- or relative-report (81% confirmed pathologically). Result(s): From fully adjusted analyses, regular aspirin use was associated with a 39% and 37% reduced risk of breast cancer in the prospective (HR = 0.61; 95% CI = 0.33-1.14) and combined cohorts (HR = 0.63; 95% CI = 0.57-0.71), respectively. Regular use of COX-2 inhibitors was associated with a 61% and 71% reduced risk of breast cancer (prospective HR = 0.39; 95% CI = 0.15-0.97; combined HR = 0.29; 95% CI = 0.23-0.38). Other NSAIDs and acetaminophen were not associated with breast cancer risk in either cohort. Associ

Published
2019

11. Homologous recombination DNA repair defects in PALB2-associated breast cancers.

Author

Duijf P., Kentwell M., Kirk J., Kollias J., Lakhani S., Lindeman G., Lipton L., Lobb L., Lok S., Macrea F., Mann G., Marsh D., McLachlan S.-A., Meiser B., Milne R., Nightingale S., O'Connell S., Pachter N., Patterson B., Phillips K., Saleh M., Salisbury E., Saunders C., Saunus J., Scott C., Scott R., Sexton A., Shelling A., Simpson P., Spigelman A., Spurdle M., Stone J., Taylor J., Thorne H., Trainer A., Trench G., Walker L., Wallis M., Williams R., Winship I., Wu K., Young M.A., Rezoug Z., Nguyen-Dumont T., Peterlongo P., Tondini C., Terkelsen T., Ronlund K., Boonen S.E., Mannerma A., Winqvist R., Janatova M., Rajadurai P., Xia B., Norton L., Robson M.E., Ng P.-S., Looi L.-M., Southey M.C., Weigelt B., Soo-Hwang T., Tischkowitz M., Foulkes W.D., Reis-Filho J.S., Harris M., Tucker K., Visvader J., Li A., Geyer F.C., Blecua P., Lee J.Y., Selenica P., Brown D.N., Pareja F., Lee S.S.K., Kumar R., Rivera B., Bi R., Piscuoglio S., Wen H.Y., Lozada J.R., Gularte-Merida R., Cavallone L., Aghmesheh M., Amor D., Andrews L., Antill Y., Balleine R., Beesley J., Blackburn A., Bogwitz M., Brown M., Burgess M., Burke J., Butow P., Caldon L., Campbell I., Christian A., Clarke C., Cohen P., Crook A., Cui J., Cummings M., Dawson S.-J., De Fazio A., Delatycki M., Dobrovic A., Dudding T., Edkins E., Edwards S., Farshid G., Fellows A., Field M., Flanagan J., Fong P., Forbes J., Forrest L., Fox S., French J., Friedlander M., Ortega D.G., Gattas M., Giles G., Gill G., Gleeson M., Greening S., Haan E., Hayward N., Hickie I., Hopper J., Hunt C., James P., Jenkins M., Kefford R., Duijf P., Kentwell M., Kirk J., Kollias J., Lakhani S., Lindeman G., Lipton L., Lobb L., Lok S., Macrea F., Mann G., Marsh D., McLachlan S.-A., Meiser B., Milne R., Nightingale S., O'Connell S., Pachter N., Patterson B., Phillips K., Saleh M., Salisbury E., Saunders C., Saunus J., Scott C., Scott R., Sexton A., Shelling A., Simpson P., Spigelman A., Spurdle M., Stone J., Taylor J., Thorne H., Trainer A., Trench G., Walker L., Wallis M., Williams R., Winship I., Wu K., Young M.A., Rezoug Z., Nguyen-Dumont T., Peterlongo P., Tondini C., Terkelsen T., Ronlund K., Boonen S.E., Mannerma A., Winqvist R., Janatova M., Rajadurai P., Xia B., Norton L., Robson M.E., Ng P.-S., Looi L.-M., Southey M.C., Weigelt B., Soo-Hwang T., Tischkowitz M., Foulkes W.D., Reis-Filho J.S., Harris M., Tucker K., Visvader J., Li A., Geyer F.C., Blecua P., Lee J.Y., Selenica P., Brown D.N., Pareja F., Lee S.S.K., Kumar R., Rivera B., Bi R., Piscuoglio S., Wen H.Y., Lozada J.R., Gularte-Merida R., Cavallone L., Aghmesheh M., Amor D., Andrews L., Antill Y., Balleine R., Beesley J., Blackburn A., Bogwitz M., Brown M., Burgess M., Burke J., Butow P., Caldon L., Campbell I., Christian A., Clarke C., Cohen P., Crook A., Cui J., Cummings M., Dawson S.-J., De Fazio A., Delatycki M., Dobrovic A., Dudding T., Edkins E., Edwards S., Farshid G., Fellows A., Field M., Flanagan J., Fong P., Forbes J., Forrest L., Fox S., French J., Friedlander M., Ortega D.G., Gattas M., Giles G., Gill G., Gleeson M., Greening S., Haan E., Hayward N., Hickie I., Hopper J., Hunt C., James P., Jenkins M., and Kefford R.

Abstract

Mono-allelic germline pathogenic variants in the Partner And Localizer of BRCA2 (PALB2) gene predispose to a high-risk of breast cancer development, consistent with the role of PALB2 in homologous recombination (HR) DNA repair. Here, we sought to define the repertoire of somatic genetic alterations in PALB2-associated breast cancers (BCs), and whether PALB2-associated BCs display bi-allelic inactivation of PALB2 and/or genomic features of HR-deficiency (HRD). Twenty-four breast cancer patients with pathogenic PALB2 germline mutations were analyzed by whole-exome sequencing (WES, n = 16) or targeted capture massively parallel sequencing (410 cancer genes, n = 8). Somatic genetic alterations, loss of heterozygosity (LOH) of the PALB2 wild-type allele, large-scale state transitions (LSTs) and mutational signatures were defined. PALB2-associated BCs were found to be heterogeneous at the genetic level, with PIK3CA (29%), PALB2 (21%), TP53 (21%), and NOTCH3 (17%) being the genes most frequently affected by somatic mutations. Bi-allelic PALB2 inactivation was found in 16 of the 24 cases (67%), either through LOH (n = 11) or second somatic mutations (n = 5) of the wild-type allele. High LST scores were found in all 12 PALB2-associated BCs with bi-allelic PALB2 inactivation sequenced by WES, of which eight displayed the HRD-related mutational signature 3. In addition, bi-allelic inactivation of PALB2 was significantly associated with high LST scores. Our findings suggest that the identification of bi-allelic PALB2 inactivation in PALB2-associated BCs is required for the personalization of HR-directed therapies, such as platinum salts and/or PARP inhibitors, as the vast majority of PALB2-associated BCs without PALB2 bi-allelic inactivation lack genomic features of HRD.Copyright © 2019, The Author(s).

Published
2019

12. 10-year performance of four models of breast cancer risk: a validation study.

Author

John E.M., Daly M.B., Buys S.S., Hopper J.L., MacInnis R.J., Chung W.K., Knight J.A., Southey M.C., Milne R.L., Goldgar D., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Phillips K.-A., Terry M.B., Liao Y., Whittemore A.S., Leoce N., Buchsbaum R., Zeinomar N., Dite G.S., John E.M., Daly M.B., Buys S.S., Hopper J.L., MacInnis R.J., Chung W.K., Knight J.A., Southey M.C., Milne R.L., Goldgar D., Giles G.G., McLachlan S.-A., Friedlander M.L., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Phillips K.-A., Terry M.B., Liao Y., Whittemore A.S., Leoce N., Buchsbaum R., Zeinomar N., and Dite G.S.

Abstract

Background: Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance. Method(s): In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20-70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and partic

Published
2019

13. Publisher Correction: Homologous recombination DNA repair defects in PALB2-associated breast cancers (npj Breast Cancer, (2019), 5, 1, (23), 10.1038/s41523-019-0115-9).

Author

Cummings M., Walker L., Wallis M., Williams R., Winship I., Wu K., Young M.A., Rezoug Z., Nguyen-Dumont T., Peterlongo P., Tondini C., Terkelsen T., Ronlund K., Boonen S.E., Mannerma A., Winqvist R., Janatova M., Rajadurai P., Xia B., Norton L., Robson M.E., Ng P.-S., Looi L.-M., Southey M.C., Weigelt B., Soo-Hwang T., Tischkowitz M., Foulkes W.D., Reis-Filho J.S., Li A., Geyer F.C., Blecua P., Lee J.Y., Selenica P., Brown D.N., Pareja F., Lee S.S.K., Kumar R., Rivera B., Bi R., Piscuoglio S., Wen H.Y., Lozada J.R., Gularte-Merida R., Cavallone L., Aghmesheh M., Amor D., Andrews L., Antill Y., Balleine R., Beesley J., Blackburn A., Bogwitz M., Brown M., Burgess M., Burke J., Butow P., Caldon L., Campbell I., Christian A., Clarke C., Cohen P., Crook A., Cui J., Dawson S.-J., De Fazio A., Delatycki M., Dobrovic A., Dudding T., Duijf P., Edkins E., Edwards S., Farshid G., Fellows A., Field M., Flanagan J., Fong P., Forbes J., Forrest L., Fox S., French J., Friedlander M., Ortega D.G., Gattas M., Giles G., Gill G., Gleeson M., Greening S., Haan E., Harris M., Hayward N., Hickie I., Hopper J., Hunt C., James P., Jenkins M., Kefford R., Kentwell M., Kirk J., Kollias J., Lakhani S., Lindeman G., Lipton L., Lobb L., Lok S., Macrea F., Mann G., Marsh D., McLachlan S.-A., Meiser B., Milne R., Nightingale S., O'Connell S., Pachter N., Patterson B., Phillips K., Saleh M., Salisbury E., Saunders C., Saunus J., Scott C., Scott R., Sexton A., Shelling A., Simpson P., Spigelman A., Spurdle M., Stone J., Taylor J., Thorne H., Trainer A., Trench G., Tucker K., Visvader J., Cummings M., Walker L., Wallis M., Williams R., Winship I., Wu K., Young M.A., Rezoug Z., Nguyen-Dumont T., Peterlongo P., Tondini C., Terkelsen T., Ronlund K., Boonen S.E., Mannerma A., Winqvist R., Janatova M., Rajadurai P., Xia B., Norton L., Robson M.E., Ng P.-S., Looi L.-M., Southey M.C., Weigelt B., Soo-Hwang T., Tischkowitz M., Foulkes W.D., Reis-Filho J.S., Li A., Geyer F.C., Blecua P., Lee J.Y., Selenica P., Brown D.N., Pareja F., Lee S.S.K., Kumar R., Rivera B., Bi R., Piscuoglio S., Wen H.Y., Lozada J.R., Gularte-Merida R., Cavallone L., Aghmesheh M., Amor D., Andrews L., Antill Y., Balleine R., Beesley J., Blackburn A., Bogwitz M., Brown M., Burgess M., Burke J., Butow P., Caldon L., Campbell I., Christian A., Clarke C., Cohen P., Crook A., Cui J., Dawson S.-J., De Fazio A., Delatycki M., Dobrovic A., Dudding T., Duijf P., Edkins E., Edwards S., Farshid G., Fellows A., Field M., Flanagan J., Fong P., Forbes J., Forrest L., Fox S., French J., Friedlander M., Ortega D.G., Gattas M., Giles G., Gill G., Gleeson M., Greening S., Haan E., Harris M., Hayward N., Hickie I., Hopper J., Hunt C., James P., Jenkins M., Kefford R., Kentwell M., Kirk J., Kollias J., Lakhani S., Lindeman G., Lipton L., Lobb L., Lok S., Macrea F., Mann G., Marsh D., McLachlan S.-A., Meiser B., Milne R., Nightingale S., O'Connell S., Pachter N., Patterson B., Phillips K., Saleh M., Salisbury E., Saunders C., Saunus J., Scott C., Scott R., Sexton A., Shelling A., Simpson P., Spigelman A., Spurdle M., Stone J., Taylor J., Thorne H., Trainer A., Trench G., Tucker K., and Visvader J.

Abstract

In the original version of this paper, the link to the data record in the Data Availability Statement was incorrectly listed as https:// doi.org/10.6084/m9.figshare.8138912.44. The link has been corrected to https://doi.org/10.6084/m9.figshare.8138912. This has been corrected in the HTML and PDF versions of this article.Copyright © 2019, The Author(s).

Published
2019

14. Age-specific breast cancer risk by body mass index and familial risk: Prospective family study cohort (ProF-SC) 11 Medical and Health Sciences 1112 Oncology and Carcinogenesis 11 Medical and Health Sciences 1117 Public Health and Health Services.

Author

Hopper J.L., Genkinger J.M., McLachlan S.-A., Friedlander M.L., Antoniou A.C., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Buys S.S., Daly M.B., John E.M., Phillips K.A., Terry M.B., Dite G.S., MacInnis R.J., Liao Y., Zeinomar N., Knight J.A., Southey M.C., Milne R.L., Chung W.K., Giles G.G., Hopper J.L., Genkinger J.M., McLachlan S.-A., Friedlander M.L., Antoniou A.C., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Buys S.S., Daly M.B., John E.M., Phillips K.A., Terry M.B., Dite G.S., MacInnis R.J., Liao Y., Zeinomar N., Knight J.A., Southey M.C., Milne R.L., Chung W.K., and Giles G.G.

Abstract

Background: The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk. Method(s): We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline. Result(s): The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk. Conclusion(s): The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.Copyright © 2018 The Author(s).

Published
2018

15. Heritable DNA methylation marks associated with susceptibility to breast cancer /631/67/69 /631/337/176/1988 /692/699/67/1347 /692/308/2056 /45 /45/61 article.

Author

Hickie I., Saunders C., Hunt C., Scott C., Amor D., Marsh D., Edkins E., Salisbury E., Haan E., Neidermayr E., Macrae F., Farshid G., Lindeman G., Chenevix-Trench G., Mann G., Gill G., Thorne H., Campbell I., Winship I., Goldblatt J., Flanagan J., Kollias J., Visvader J., Stone J., Taylor J., Burke J., Saunus J., Forbes J., Beesley J., Kirk J., French J., Tucker K., Wu K., Phillips K., Lipton L., Andrews L., Lobb E., Walker L., Kentwell M., Spurdle A., Cummings M., Gleeson M., Harris M., Jenkins M., Young M.A., Delatycki M., Wallis M., Burgess M., Price M., Brown M., Bogwitz M., Field M., Friedlander M., Gattas M., Saleh M., Hayward N., Pachter N., Cohen P., Duijf P., James P., Simpson P., Fong P., Butow P., Williams R., Kefford R., Scott R., Balleine R., Dawson S.-J., Lok S., O'Connell S., Greening S., Nightingale S., Edwards S., Fox S., McLachlan S.-A., Lakhani S., Thomas S., Antill Y., Joo J.E., Dowty J.G., Milne R.L., Wong E.M., Dugue P.-A., English D., Hopper J.L., Goldgar D.E., Giles G.G., Southey M.C., Sexton A., Christian A., Trainer A., Spigelman A., Fellows A., Shelling A., De Fazio A., Blackburn A., Crook A., Meiser B., Patterson B., Clarke C., Hickie I., Saunders C., Hunt C., Scott C., Amor D., Marsh D., Edkins E., Salisbury E., Haan E., Neidermayr E., Macrae F., Farshid G., Lindeman G., Chenevix-Trench G., Mann G., Gill G., Thorne H., Campbell I., Winship I., Goldblatt J., Flanagan J., Kollias J., Visvader J., Stone J., Taylor J., Burke J., Saunus J., Forbes J., Beesley J., Kirk J., French J., Tucker K., Wu K., Phillips K., Lipton L., Andrews L., Lobb E., Walker L., Kentwell M., Spurdle A., Cummings M., Gleeson M., Harris M., Jenkins M., Young M.A., Delatycki M., Wallis M., Burgess M., Price M., Brown M., Bogwitz M., Field M., Friedlander M., Gattas M., Saleh M., Hayward N., Pachter N., Cohen P., Duijf P., James P., Simpson P., Fong P., Butow P., Williams R., Kefford R., Scott R., Balleine R., Dawson S.-J., Lok S., O'Connell S., Greening S., Nightingale S., Edwards S., Fox S., McLachlan S.-A., Lakhani S., Thomas S., Antill Y., Joo J.E., Dowty J.G., Milne R.L., Wong E.M., Dugue P.-A., English D., Hopper J.L., Goldgar D.E., Giles G.G., Southey M.C., Sexton A., Christian A., Trainer A., Spigelman A., Fellows A., Shelling A., De Fazio A., Blackburn A., Crook A., Meiser B., Patterson B., and Clarke C.

Abstract

Mendelian-like inheritance of germline DNA methylation in cancer susceptibility genes has been previously reported. We aimed to scan the genome for heritable methylation marks associated with breast cancer susceptibility by studying 25 Australian multiple-case breast cancer families. Here we report genome-wide DNA methylation measured in 210 peripheral blood DNA samples provided by family members using the Infinium HumanMethylation450. We develop and apply a new statistical method to identify heritable methylation marks based on complex segregation analysis. We estimate carrier probabilities for the 1000 most heritable methylation marks based on family structure, and we use Cox proportional hazards survival analysis to identify 24 methylation marks with corresponding carrier probabilities significantly associated with breast cancer. We replicate an association with breast cancer risk for four of the 24 marks using an independent nested case-control study. Here, we report a novel approach for identifying heritable DNA methylation marks associated with breast cancer risk.Copyright © 2018 The Author(s).

Published
2018

16. Oral contraceptive use and breast cancer risk: Retrospective and prospective analyses from a BRCA1 and BRCA2 mutation carrier cohort study.

Author

Roos-Blom M.-J., Walker L., Bonadona V., Leroux D., Mouret-Fourme E., Venat-Bouvet L., Buys S.S., Southey M.C., John E.M., Chung W.K., Daly M.B., Bane A., van Asperen C.J., Garcia E.B.G., Mourits M.J., Friedlander M.L., McLachlan S.-A., Singer C.F., Foretova L., Gerdes A.-M., Caldes T., Olah E., Jakubowska A., Nogues C., Andrieu N., Easton D.F., van Leeuwen F.E., Hopper J.L., Milne R.L., Antoniou A.C., Rookus M.A., Laborde L., Pontois P., Stoppa-Lyonnet D., Gauthier-Villars M., Buecher B., Caron O., Fricker J.-P., Lasset C., Berthet P., Faivre L., Luporsi E., Frenay M., Gladieff L., Gesta P., Sobol H., Eisinger F., Moretta J., Longy M., Dugast C., Colas C., Soubrier F., Coupier I., Pujol P., Lortholary A., Vennin P., Adenis C., Nguyen T.D., Delnatte C., Rossi A., Tinat J., Tennevet I., Limacher J.-M., Maugard C., Bignon Y.-J., Demange L., Dreyfus H., Cohen-Haguenauer O., Gilbert B., Zattara-Cannoni H., Schrijver L.H., Olsson H., Phillips K.-A., Terry M.B., Goldgar D.E., Kast K., Engel C., Mooij T.M., Adlard J., Barrowdale D., Davidson R., Eeles R., Ellis S., Evans D.G., Frost D., Izatt L., Porteous M.E., Side L.E., Roos-Blom M.-J., Walker L., Bonadona V., Leroux D., Mouret-Fourme E., Venat-Bouvet L., Buys S.S., Southey M.C., John E.M., Chung W.K., Daly M.B., Bane A., van Asperen C.J., Garcia E.B.G., Mourits M.J., Friedlander M.L., McLachlan S.-A., Singer C.F., Foretova L., Gerdes A.-M., Caldes T., Olah E., Jakubowska A., Nogues C., Andrieu N., Easton D.F., van Leeuwen F.E., Hopper J.L., Milne R.L., Antoniou A.C., Rookus M.A., Laborde L., Pontois P., Stoppa-Lyonnet D., Gauthier-Villars M., Buecher B., Caron O., Fricker J.-P., Lasset C., Berthet P., Faivre L., Luporsi E., Frenay M., Gladieff L., Gesta P., Sobol H., Eisinger F., Moretta J., Longy M., Dugast C., Colas C., Soubrier F., Coupier I., Pujol P., Lortholary A., Vennin P., Adenis C., Nguyen T.D., Delnatte C., Rossi A., Tinat J., Tennevet I., Limacher J.-M., Maugard C., Bignon Y.-J., Demange L., Dreyfus H., Cohen-Haguenauer O., Gilbert B., Zattara-Cannoni H., Schrijver L.H., Olsson H., Phillips K.-A., Terry M.B., Goldgar D.E., Kast K., Engel C., Mooij T.M., Adlard J., Barrowdale D., Davidson R., Eeles R., Ellis S., Evans D.G., Frost D., Izatt L., Porteous M.E., and Side L.E.

Abstract

Background: For BRCA1 and BRCA2 mutation carriers, the association between oral contraceptive preparation (OCP) use and breast cancer (BC) risk is still unclear. Method(s): Breast camcer risk associations were estimated from OCP data on 6030 BRCA1 and 3809 BRCA2 mutation carriers using age-dependent Cox regression, stratified by study and birth cohort. Prospective, left-truncated retrospective and fullcohort retrospective analyses were performed. Result(s): For BRCA1 mutation carriers, OCP use was not associated with BC risk in prospective analyses (hazard ratio [HR] = 1.08, 95% confidence interval [CI] = 0.75 to 1.56), but in the left-truncated and full-cohort retrospective analyses, risks were increased by 26% (95% CI = 6% to 51%) and 39% (95% CI = 23% to 58%), respectively. For BRCA2mutation carriers, OCP use was associated with BC risk in prospective analyses (HR = 1.75, 95% CI = 1.03 to 2.97), but retrospective analyses were inconsistent (left-truncated: HR = 1.06, 95% CI = 0.85 to 1.33; full cohort: HR = 1.52, 95% CI = 1.28 to 1.81). There was evidence of increasing risk with duration of use, especially before the first full-termpregnancy (BRCA1: both retrospective analyses, P < .001 and P = .001, respectively; BRCA2: full retrospective analysis, P = .002). Conclusion(s): Prospective analyses did not show that past use of OCP is associated with an increased BC risk for BRCA1 mutation carriers in young middle-aged women (40-50 years). For BRCA2 mutation carriers, a causal association is also not likely at those ages. Findings between retrospective and prospective analyses were inconsistent and could be due to survival bias or a true association for younger women who were underrepresented in the prospective cohort. Given the uncertain safety of long-termOCP use for BRCA1/2 mutation carriers, indications other than contraception should be avoided and nonhormonal contraceptive methods should be discussed.Copyright © The Author(s) 2018.

Published
2018

17. Age-specific breast cancer risk by body mass index and familial risk: Prospective family study cohort (ProF-SC) 11 Medical and Health Sciences 1112 Oncology and Carcinogenesis 11 Medical and Health Sciences 1117 Public Health and Health Services.

Author

Hopper J.L., Genkinger J.M., McLachlan S.-A., Friedlander M.L., Antoniou A.C., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Buys S.S., Daly M.B., John E.M., Phillips K.A., Terry M.B., Dite G.S., MacInnis R.J., Liao Y., Zeinomar N., Knight J.A., Southey M.C., Milne R.L., Chung W.K., Giles G.G., Hopper J.L., Genkinger J.M., McLachlan S.-A., Friedlander M.L., Antoniou A.C., Weideman P.C., Glendon G., Nesci S., Andrulis I.L., Buys S.S., Daly M.B., John E.M., Phillips K.A., Terry M.B., Dite G.S., MacInnis R.J., Liao Y., Zeinomar N., Knight J.A., Southey M.C., Milne R.L., Chung W.K., and Giles G.G.

Abstract

Background: The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk. Method(s): We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline. Result(s): The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk. Conclusion(s): The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.Copyright © 2018 The Author(s).

Published
2018

18. Heritable DNA methylation marks associated with susceptibility to breast cancer /631/67/69 /631/337/176/1988 /692/699/67/1347 /692/308/2056 /45 /45/61 article.

Author

Hickie I., Saunders C., Hunt C., Scott C., Amor D., Marsh D., Edkins E., Salisbury E., Haan E., Neidermayr E., Macrae F., Farshid G., Lindeman G., Chenevix-Trench G., Mann G., Gill G., Thorne H., Campbell I., Winship I., Goldblatt J., Flanagan J., Kollias J., Visvader J., Stone J., Taylor J., Burke J., Saunus J., Forbes J., Beesley J., Kirk J., French J., Tucker K., Wu K., Phillips K., Lipton L., Andrews L., Lobb E., Walker L., Kentwell M., Spurdle A., Cummings M., Gleeson M., Harris M., Jenkins M., Young M.A., Delatycki M., Wallis M., Burgess M., Price M., Brown M., Bogwitz M., Field M., Friedlander M., Gattas M., Saleh M., Hayward N., Pachter N., Cohen P., Duijf P., James P., Simpson P., Fong P., Butow P., Williams R., Kefford R., Scott R., Balleine R., Dawson S.-J., Lok S., O'Connell S., Greening S., Nightingale S., Edwards S., Fox S., McLachlan S.-A., Lakhani S., Thomas S., Antill Y., Joo J.E., Dowty J.G., Milne R.L., Wong E.M., Dugue P.-A., English D., Hopper J.L., Goldgar D.E., Giles G.G., Southey M.C., Sexton A., Christian A., Trainer A., Spigelman A., Fellows A., Shelling A., De Fazio A., Blackburn A., Crook A., Meiser B., Patterson B., Clarke C., Hickie I., Saunders C., Hunt C., Scott C., Amor D., Marsh D., Edkins E., Salisbury E., Haan E., Neidermayr E., Macrae F., Farshid G., Lindeman G., Chenevix-Trench G., Mann G., Gill G., Thorne H., Campbell I., Winship I., Goldblatt J., Flanagan J., Kollias J., Visvader J., Stone J., Taylor J., Burke J., Saunus J., Forbes J., Beesley J., Kirk J., French J., Tucker K., Wu K., Phillips K., Lipton L., Andrews L., Lobb E., Walker L., Kentwell M., Spurdle A., Cummings M., Gleeson M., Harris M., Jenkins M., Young M.A., Delatycki M., Wallis M., Burgess M., Price M., Brown M., Bogwitz M., Field M., Friedlander M., Gattas M., Saleh M., Hayward N., Pachter N., Cohen P., Duijf P., James P., Simpson P., Fong P., Butow P., Williams R., Kefford R., Scott R., Balleine R., Dawson S.-J., Lok S., O'Connell S., Greening S., Nightingale S., Edwards S., Fox S., McLachlan S.-A., Lakhani S., Thomas S., Antill Y., Joo J.E., Dowty J.G., Milne R.L., Wong E.M., Dugue P.-A., English D., Hopper J.L., Goldgar D.E., Giles G.G., Southey M.C., Sexton A., Christian A., Trainer A., Spigelman A., Fellows A., Shelling A., De Fazio A., Blackburn A., Crook A., Meiser B., Patterson B., and Clarke C.

Abstract

Mendelian-like inheritance of germline DNA methylation in cancer susceptibility genes has been previously reported. We aimed to scan the genome for heritable methylation marks associated with breast cancer susceptibility by studying 25 Australian multiple-case breast cancer families. Here we report genome-wide DNA methylation measured in 210 peripheral blood DNA samples provided by family members using the Infinium HumanMethylation450. We develop and apply a new statistical method to identify heritable methylation marks based on complex segregation analysis. We estimate carrier probabilities for the 1000 most heritable methylation marks based on family structure, and we use Cox proportional hazards survival analysis to identify 24 methylation marks with corresponding carrier probabilities significantly associated with breast cancer. We replicate an association with breast cancer risk for four of the 24 marks using an independent nested case-control study. Here, we report a novel approach for identifying heritable DNA methylation marks associated with breast cancer risk.Copyright © 2018 The Author(s).

Published
2018

19. Oral contraceptive use and breast cancer risk: Retrospective and prospective analyses from a BRCA1 and BRCA2 mutation carrier cohort study.

Author

Roos-Blom M.-J., Walker L., Bonadona V., Leroux D., Mouret-Fourme E., Venat-Bouvet L., Buys S.S., Southey M.C., John E.M., Chung W.K., Daly M.B., Bane A., van Asperen C.J., Garcia E.B.G., Mourits M.J., Friedlander M.L., McLachlan S.-A., Singer C.F., Foretova L., Gerdes A.-M., Caldes T., Olah E., Jakubowska A., Nogues C., Andrieu N., Easton D.F., van Leeuwen F.E., Hopper J.L., Milne R.L., Antoniou A.C., Rookus M.A., Laborde L., Pontois P., Stoppa-Lyonnet D., Gauthier-Villars M., Buecher B., Caron O., Fricker J.-P., Lasset C., Berthet P., Faivre L., Luporsi E., Frenay M., Gladieff L., Gesta P., Sobol H., Eisinger F., Moretta J., Longy M., Dugast C., Colas C., Soubrier F., Coupier I., Pujol P., Lortholary A., Vennin P., Adenis C., Nguyen T.D., Delnatte C., Rossi A., Tinat J., Tennevet I., Limacher J.-M., Maugard C., Bignon Y.-J., Demange L., Dreyfus H., Cohen-Haguenauer O., Gilbert B., Zattara-Cannoni H., Schrijver L.H., Olsson H., Phillips K.-A., Terry M.B., Goldgar D.E., Kast K., Engel C., Mooij T.M., Adlard J., Barrowdale D., Davidson R., Eeles R., Ellis S., Evans D.G., Frost D., Izatt L., Porteous M.E., Side L.E., Roos-Blom M.-J., Walker L., Bonadona V., Leroux D., Mouret-Fourme E., Venat-Bouvet L., Buys S.S., Southey M.C., John E.M., Chung W.K., Daly M.B., Bane A., van Asperen C.J., Garcia E.B.G., Mourits M.J., Friedlander M.L., McLachlan S.-A., Singer C.F., Foretova L., Gerdes A.-M., Caldes T., Olah E., Jakubowska A., Nogues C., Andrieu N., Easton D.F., van Leeuwen F.E., Hopper J.L., Milne R.L., Antoniou A.C., Rookus M.A., Laborde L., Pontois P., Stoppa-Lyonnet D., Gauthier-Villars M., Buecher B., Caron O., Fricker J.-P., Lasset C., Berthet P., Faivre L., Luporsi E., Frenay M., Gladieff L., Gesta P., Sobol H., Eisinger F., Moretta J., Longy M., Dugast C., Colas C., Soubrier F., Coupier I., Pujol P., Lortholary A., Vennin P., Adenis C., Nguyen T.D., Delnatte C., Rossi A., Tinat J., Tennevet I., Limacher J.-M., Maugard C., Bignon Y.-J., Demange L., Dreyfus H., Cohen-Haguenauer O., Gilbert B., Zattara-Cannoni H., Schrijver L.H., Olsson H., Phillips K.-A., Terry M.B., Goldgar D.E., Kast K., Engel C., Mooij T.M., Adlard J., Barrowdale D., Davidson R., Eeles R., Ellis S., Evans D.G., Frost D., Izatt L., Porteous M.E., and Side L.E.

Abstract

Background: For BRCA1 and BRCA2 mutation carriers, the association between oral contraceptive preparation (OCP) use and breast cancer (BC) risk is still unclear. Method(s): Breast camcer risk associations were estimated from OCP data on 6030 BRCA1 and 3809 BRCA2 mutation carriers using age-dependent Cox regression, stratified by study and birth cohort. Prospective, left-truncated retrospective and fullcohort retrospective analyses were performed. Result(s): For BRCA1 mutation carriers, OCP use was not associated with BC risk in prospective analyses (hazard ratio [HR] = 1.08, 95% confidence interval [CI] = 0.75 to 1.56), but in the left-truncated and full-cohort retrospective analyses, risks were increased by 26% (95% CI = 6% to 51%) and 39% (95% CI = 23% to 58%), respectively. For BRCA2mutation carriers, OCP use was associated with BC risk in prospective analyses (HR = 1.75, 95% CI = 1.03 to 2.97), but retrospective analyses were inconsistent (left-truncated: HR = 1.06, 95% CI = 0.85 to 1.33; full cohort: HR = 1.52, 95% CI = 1.28 to 1.81). There was evidence of increasing risk with duration of use, especially before the first full-termpregnancy (BRCA1: both retrospective analyses, P < .001 and P = .001, respectively; BRCA2: full retrospective analysis, P = .002). Conclusion(s): Prospective analyses did not show that past use of OCP is associated with an increased BC risk for BRCA1 mutation carriers in young middle-aged women (40-50 years). For BRCA2 mutation carriers, a causal association is also not likely at those ages. Findings between retrospective and prospective analyses were inconsistent and could be due to survival bias or a true association for younger women who were underrepresented in the prospective cohort. Given the uncertain safety of long-termOCP use for BRCA1/2 mutation carriers, indications other than contraception should be avoided and nonhormonal contraceptive methods should be discussed.Copyright © The Author(s) 2018.

Published
2018

20. Rapid screening for depression - Validation of the Brief Case-Find for Depression (BCD) in medical oncology and palliative care patients.

Author

Antill Y., Matthews J.P., Zalcberg J., Jennens R., McLachlan S.-A., Wein S., Clarke D.M., Jefford M., Mileshkin L., Richards K., Thomson J., Antill Y., Matthews J.P., Zalcberg J., Jennens R., McLachlan S.-A., Wein S., Clarke D.M., Jefford M., Mileshkin L., Richards K., and Thomson J.

Abstract

Depression in oncology patients is under-recognised and associated with poor outcomes. Screening can increase case recognition. The Brief Case-Final for Depression (BCD) is a four-question, interviewer-administered instrument that has been previously validated in a general medical setting. The primary aim of this study was to validate the BCD in a medical oncology/palliative care setting, primarily by comparing its association with physical illness measures and with the Primary Care Evaluation of Mental Disorders (PRIME-MD), the Beck Depression Inventory (BDI) and the Hospital Anxiety and Depression Scale (HADS). Eligible adult oncology patients gave informed consent and completed the above measures and a pain scale. Agreement between the BCD and other instruments was assessed. Construct validity was determined by comparing depressed/nondepressed patients with respect to performance status, symptoms, pain score and functional impairment. A total of 100 patients had a median age of 58 (range 21-90) and ECOG performance status (PS) 2 (0-4). In all, 60% had metastatic disease. The therapeutic goal was curative/adjuvant in 39% and palliative in 61%. Prevalence of depression according to the various measures was: BCD 34%, PRIME-MD 12%, BDI 19% and HADS 14%. In total, 45% of patients responded positively to a single-item screening question. The BCD showed fair agreement with the PRIME-MD (kappa = 0.21), moderate agreement with the BDI (kappa = 0.43) and fair agreement with the HADS (kappa = 0.27). Against the PRIME-MD diagnosis of depression, the BCD had greater sensitivity, but lesser specificity and overall agreement, compared with the BDI and depression scale of the HADS. Patients with probable depression (according to BCD) had inferior PS (P = 0.0064), increased pain (P = 0.045) and greater impairment of functioning (PRIME-MD: P = 0.0003). There was no association with gender, age, disease status or therapeutic goal. Depression is common in oncology patients. The BCD

Published
2012

21. Rapid screening for depression - Validation of the Brief Case-Find for Depression (BCD) in medical oncology and palliative care patients.

Author

Antill Y., Matthews J.P., Zalcberg J., Jennens R., McLachlan S.-A., Wein S., Clarke D.M., Jefford M., Mileshkin L., Richards K., Thomson J., Antill Y., Matthews J.P., Zalcberg J., Jennens R., McLachlan S.-A., Wein S., Clarke D.M., Jefford M., Mileshkin L., Richards K., and Thomson J.

Abstract

Depression in oncology patients is under-recognised and associated with poor outcomes. Screening can increase case recognition. The Brief Case-Final for Depression (BCD) is a four-question, interviewer-administered instrument that has been previously validated in a general medical setting. The primary aim of this study was to validate the BCD in a medical oncology/palliative care setting, primarily by comparing its association with physical illness measures and with the Primary Care Evaluation of Mental Disorders (PRIME-MD), the Beck Depression Inventory (BDI) and the Hospital Anxiety and Depression Scale (HADS). Eligible adult oncology patients gave informed consent and completed the above measures and a pain scale. Agreement between the BCD and other instruments was assessed. Construct validity was determined by comparing depressed/nondepressed patients with respect to performance status, symptoms, pain score and functional impairment. A total of 100 patients had a median age of 58 (range 21-90) and ECOG performance status (PS) 2 (0-4). In all, 60% had metastatic disease. The therapeutic goal was curative/adjuvant in 39% and palliative in 61%. Prevalence of depression according to the various measures was: BCD 34%, PRIME-MD 12%, BDI 19% and HADS 14%. In total, 45% of patients responded positively to a single-item screening question. The BCD showed fair agreement with the PRIME-MD (kappa = 0.21), moderate agreement with the BDI (kappa = 0.43) and fair agreement with the HADS (kappa = 0.27). Against the PRIME-MD diagnosis of depression, the BCD had greater sensitivity, but lesser specificity and overall agreement, compared with the BDI and depression scale of the HADS. Patients with probable depression (according to BCD) had inferior PS (P = 0.0064), increased pain (P = 0.045) and greater impairment of functioning (PRIME-MD: P = 0.0003). There was no association with gender, age, disease status or therapeutic goal. Depression is common in oncology patients. The BCD

Published
2012

22. Genome-wide association study identifies novel breast cancer susceptibility loci.

Author

Cox A., Farshid G., Fawcett S., Field M., Firgaira F., Fleming J., Forbes J., Friedlander M., Gaff C., Gardner M., Gattas M., George P., Gill G., Goldblatt J., Greening S., Haan E., Hart S., Humphrey E., Jenkins M., Kefford R., Kirk J., Kollias J., Kovalenko S., Lakhani S., Leary J., Lim J., Lindeman G., Lipton L., Lobb L., Maclurcan M., Marsh D., McKay M., Anne McLachlan S., Mitchell G., Newman B., O'Loughlin I., Osborne R., Peters L., Price M., Reeve J., Reeve T., Richards R., Rinehart G., Robinson B., Rudzki B., Salisbury E., Saunders C., Scott E., Seshadri R., Shelling A., Suthers G., Taylor D., Tennant C., Townshend S., Tyler J., Venter D., Visvader J., Walpole I., Ward R., Warner B., Warren G., Watson E., Williams R., Winship I., Bowtell D., Green A., DeFazio A., Gertig D., Webb P., Milne R., Young M.A., Harris M., Wilson J., Easton D.F., Pooley K.A., Dunning A.M., Pharoah P.D.P., Thompson D., Ballinger D.G., Struewing J.P., Morrison J., Field H., Luben R., Wareham N., Ahmed S., Healey C.S., Bowman R., Meyer K.B., Haiman C.A., Kolonel L.K., Henderson B.E., Le Marchand L., Brennan P., Sangrajrang S., Gaborieau V., Odefrey F., Shen C.-Y., Wu P.-E., Wang H.-C., Eccles D., Evans D.G., Peto J., Fletcher O., Johnson N., Seal S., Stratton M.R., Rahman N., Chenevix-Trench G., Bojesen S.E., Nordestgaard B.G., Axelsson C.K., Garcia-Closas M., Brinton L., Chanock S., Lissowska J., Peplonska B., Nevanlinna H., Fagerholm R., Eerola H., Kang D., Yoo K.-Y., Noh D.-Y., Ahn S.-H., Hunter D.J., Hankinson S.E., Cox D.G., Hall P., Wedren S., Liu J., Low Y.-L., Bogdanova N., Schurmann P., Dork T., Tollenaar R.A.E.M., Jacobi C.E., Devilee P., Klijn J.G.M., Sigurdson A.J., Doody M.M., Alexander B.H., Zhang J., Brock I.W., MacPherson G., Reed M.W.R., Couch F.J., Goode E.L., Olson J.E., Meijers-Heijboer H., Van Den Ouweland A., Uitterlinden A., Rivadeneira F., Milne R.L., Ribas G., Gonzalez-Neira A., Benitez J., Hopper J., McCredie M., Southey M., Giles G., Schroen C., Justenhoven C., Brauch H., Hamann U., Ko Y.-D., Spurdle A.B., Beesley J., Chen X., Mannermaa A., Kosma V.-M., Kataja V., Hartikainen J., Day N.E., Cox D.R., Ponder B.A.J., Luccarini C., Conroy D., Shah M., Munday H., Jordan C., Perkins B., West J., Redman K., Driver K., Aghmesheh M., Amor D., Andrews L., Antill Y., Armes J., Armitage S., Arnold L., Balleine R., Begley G., Beilby J., Bennett I., Bennett B., Berry G., Blackburn A., Brennan M., Brown M., Buckley M., Burke J., Butow P., Byron K., Callen D., Campbell I., Clarke C., Colley A., Cotton D., Cui J., Culling B., Cummings M., Dawson S.-J., Dixon J., Dobrovic A., Dudding T., Edkins T., Eisenbruch M., Cox A., Farshid G., Fawcett S., Field M., Firgaira F., Fleming J., Forbes J., Friedlander M., Gaff C., Gardner M., Gattas M., George P., Gill G., Goldblatt J., Greening S., Haan E., Hart S., Humphrey E., Jenkins M., Kefford R., Kirk J., Kollias J., Kovalenko S., Lakhani S., Leary J., Lim J., Lindeman G., Lipton L., Lobb L., Maclurcan M., Marsh D., McKay M., Anne McLachlan S., Mitchell G., Newman B., O'Loughlin I., Osborne R., Peters L., Price M., Reeve J., Reeve T., Richards R., Rinehart G., Robinson B., Rudzki B., Salisbury E., Saunders C., Scott E., Seshadri R., Shelling A., Suthers G., Taylor D., Tennant C., Townshend S., Tyler J., Venter D., Visvader J., Walpole I., Ward R., Warner B., Warren G., Watson E., Williams R., Winship I., Bowtell D., Green A., DeFazio A., Gertig D., Webb P., Milne R., Young M.A., Harris M., Wilson J., Easton D.F., Pooley K.A., Dunning A.M., Pharoah P.D.P., Thompson D., Ballinger D.G., Struewing J.P., Morrison J., Field H., Luben R., Wareham N., Ahmed S., Healey C.S., Bowman R., Meyer K.B., Haiman C.A., Kolonel L.K., Henderson B.E., Le Marchand L., Brennan P., Sangrajrang S., Gaborieau V., Odefrey F., Shen C.-Y., Wu P.-E., Wang H.-C., Eccles D., Evans D.G., Peto J., Fletcher O., Johnson N., Seal S., Stratton M.R., Rahman N., Chenevix-Trench G., Bojesen S.E., Nordestgaard B.G., Axelsson C.K., Garcia-Closas M., Brinton L., Chanock S., Lissowska J., Peplonska B., Nevanlinna H., Fagerholm R., Eerola H., Kang D., Yoo K.-Y., Noh D.-Y., Ahn S.-H., Hunter D.J., Hankinson S.E., Cox D.G., Hall P., Wedren S., Liu J., Low Y.-L., Bogdanova N., Schurmann P., Dork T., Tollenaar R.A.E.M., Jacobi C.E., Devilee P., Klijn J.G.M., Sigurdson A.J., Doody M.M., Alexander B.H., Zhang J., Brock I.W., MacPherson G., Reed M.W.R., Couch F.J., Goode E.L., Olson J.E., Meijers-Heijboer H., Van Den Ouweland A., Uitterlinden A., Rivadeneira F., Milne R.L., Ribas G., Gonzalez-Neira A., Benitez J., Hopper J., McCredie M., Southey M., Giles G., Schroen C., Justenhoven C., Brauch H., Hamann U., Ko Y.-D., Spurdle A.B., Beesley J., Chen X., Mannermaa A., Kosma V.-M., Kataja V., Hartikainen J., Day N.E., Cox D.R., Ponder B.A.J., Luccarini C., Conroy D., Shah M., Munday H., Jordan C., Perkins B., West J., Redman K., Driver K., Aghmesheh M., Amor D., Andrews L., Antill Y., Armes J., Armitage S., Arnold L., Balleine R., Begley G., Beilby J., Bennett I., Bennett B., Berry G., Blackburn A., Brennan M., Brown M., Buckley M., Burke J., Butow P., Byron K., Callen D., Campbell I., Clarke C., Colley A., Cotton D., Cui J., Culling B., Cummings M., Dawson S.-J., Dixon J., Dobrovic A., Dudding T., Edkins T., and Eisenbruch M.

Abstract

Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2> 0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P < 10-7). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P < 0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach. ©2007 Nature Publishing Group.

Published
2007

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