Open Access

Variation in breast cancer risk associated with factors related to pregnancies according to truncating mutation location, in the French National BRCA1 and BRCA2 mutations carrier cohort (GENEPSO)

  • Julie Lecarpentier1, 2, 3,
  • Catherine Noguès4,
  • Emmanuelle Mouret-Fourme4,
  • Marion Gauthier-Villars5,
  • Christine Lasset6, 7, 8,
  • Jean-Pierre Fricker9,
  • Olivier Caron10,
  • Dominique Stoppa-Lyonnet5, 11, 12,
  • Pascaline Berthet13,
  • Laurence Faivre14, 15,
  • Valérie Bonadona6, 7, 8,
  • Bruno Buecher5,
  • Isabelle Coupier16, 17,
  • Laurence Gladieff18,
  • Paul Gesta19,
  • François Eisinger20, 21,
  • Marc Frénay22,
  • Elisabeth Luporsi23,
  • Alain Lortholary24,
  • Chrystelle Colas25,
  • Catherine Dugast26,
  • Michel Longy27,
  • Pascal Pujol16,
  • Julie Tinat28,
  • GENEPSO,
  • Rosette Lidereau29 and
  • Nadine Andrieu1, 2, 3Email author
Breast Cancer Research201214:R99

DOI: 10.1186/bcr3218

Received: 22 February 2012

Accepted: 3 July 2012

Published: 3 July 2012

Abstract

Introduction

Mutations in BRCA1 and BRCA2 confer a high risk of breast cancer (BC), but the magnitude of this risk seems to vary according to the study and various factors. Although controversial, there are data to support the hypothesis of allelic risk heterogeneity.

Methods

We assessed variation in BC risk according to factors related to pregnancies by location of mutation in the homogeneous risk region of BRCA1 and BRCA2 in 990 women in the French study GENEPSO by using a weighted Cox regression model.

Results

Our results confirm the existence of the protective effect of an increasing number of full-term pregnancies (FTPs) toward BC among BRCA1 and BRCA2 mutation carriers (≥3 versus 0 FTPs: hazard ratio (HR) = 0.51, 95% confidence interval (CI) = 0.33 to 0.81). Additionally, the HR shows an association between incomplete pregnancies and a higher BC risk, which reached 2.39 (95% CI = 1.28 to 4.45) among women who had at least three incomplete pregnancies when compared with women with zero incomplete pregnancies. This increased risk appeared to be restricted to incomplete pregnancies occurring before the first FTP (HR = 1.77, 95% CI = 1.19 to 2.63). We defined the TMAP score (defined as the Time of Breast Mitotic Activity during Pregnancies) to take into account simultaneously the opposite effect of full-term and interrupted pregnancies. Compared with women with a TMAP score of less than 0.35, an increasing TMAP score was associated with a statistically significant increase in the risk of BC (P trend = 0.02) which reached 1.97 (95% CI = 1.19 to 3.29) for a TMAP score >0.5 (versus TMAP ≤0.35). All these results appeared to be similar in BRCA1 and BRCA2. Nevertheless, our results suggest a variation in BC risk associated with parity according to the location of the mutation in BRCA1. Indeed, parity seems to be associated with a significantly decreased risk of BC only among women with a mutation in the central region of BRCA1 (low-risk region) (≥1 versus 0 FTP: HR = 0.27, 95% CI = 0.13 to 0.55) (Pinteraction <10-3).

Conclusions

Our findings show that, taking into account environmental and lifestyle modifiers, mutation position might be important for the clinical management of BRCA1 and BRCA2 mutation carriers and could also be helpful in understanding how BRCA1 and BRCA2 genes are involved in BC.

Introduction

Carriers of mutations in the BRCA1 and BRCA2 genes are at very high risk of developing breast cancer (BC) and ovarian cancer. Estimates of the lifetime risk of developing BC for BRCA1 and BRCA2 mutation carriers range from 30% to 80% and from 9% to 84%, respectively [1]. Incomplete penetrance and the range of these risk estimates suggest the existence within families of genetic or shared environmental or lifestyle factors that modify the risk of BC.

Many studies have established that women who had their first full-term pregnancy (FTP) at a young age have a lower risk of BC than nulliparous women or women who had their first FTP when they were older than 30 years of age; additional pregnancies are associated with even lower risks (for example, [2, 3]). Long-term breastfeeding is also associated with a decreased risk of BC in the general population [4]. Controversial conclusions have been drawn from studies that have examined the risk of BC associated with incomplete pregnancies. While some older studies found a possible positive association between interrupted pregnancies and BC risk [59], the most recent meta-analyses concluded that an increased number of either spontaneous or induced abortions was not associated with an increased BC risk [1012].

The few studies that have assessed the risk of BC associated with incomplete pregnancies [1315], breast-feeding [13, 1619] and parity [13, 15, 16, 2023] among BRCA1/2 mutations carriers, have shown inconsistent results. For parity, studies have found either no association [16, 20, 21] or a positive [15] or negative association [13, 22] with BC risk. Among studies which have performed analyses according to the gene mutated, one has reported a differential effect of parity on BC risk [23] and one, a differential effect of age at first FTP [13].

Some authors have suggested that the effect of pregnancies in BC development is related to the breast mitotic activity, driven by estrogen and progesterone exposure [24]. This activity appears high during the first three months of pregnancy and is followed by a dramatic decrease and by the differentiation of breast tissue during the last six months [25]. Although lasting and high mitotic activity and incomplete differentiation of breast tissue may have a critical effect on cells with inherited mutations, no study has assessed the effect of breast mitotic activity during pregnancy in BRCA1 and BRCA2 mutation carriers.

Genotype-phenotype correlations have been found in both BRCA1 and BRCA2 showing heterogeneity in BC risk according to the location of the mutation (for example, [2629]). Moreover, inconsistencies in the effect of pregnancy-related factors among BRCA1 and BRCA2 mutation carriers between studies could be explained by an additional heterogeneity due to a differential effect of these factors according to location of the mutation. Thus, we first studied the effect of pregnancy-related factors on the risk of BC for BRCA1 and BRCA2 mutation carriers taken together, and by gene. Then we studied the effect of parity, incomplete pregnancies and breast-feeding for homogeneous regions previously described in our data [30] where a central low BC risk region in BRCA1 and BRCA2 was confirmed [27, 28, 3134], and a new high-risk region in BRCA2 was described [30].

Materials and methods

Data

The GENEPSO study was initiated in 2000 to estimate the risk of breast, ovarian, and other cancers in BRCA1 and BRCA2 mutation carriers and to assess potential risk-modifying factors, either lifestyle or genetic. Subjects were ascertained from the family cancer clinics of the Genetic and Cancer Group of Unicancer. Any woman who was known to carry a deleterious mutation in the BRCA1 or BRCA2 gene was eligible, including those diagnosed with cancer and those currently unaffected. They had to be at least 18 years old, mentally capable of giving informed consent to participate in the study, and had been counseled about their mutation status. The research protocol was approved by the relevant ethics committees, and all participants provided written informed consent.

The study population was based on the women enrolled in the GENEPSO study from 2000 to 2010. A total of 1,337 women (from 987 different families) were recruited, 863 (65%) were BRCA1 mutation carriers and 474 (35%) were BRCA2 mutation carriers. To assess variation in BC risk according to mutation position, a sample with one subject per family was randomly selected to avoid overmatching on the mutation, except for one family where two related women carried two different mutations and thus were considered independent. Additionally, two women were counted twice because they carried two mutations in BRCA1 and BRCA2. Thus, 990 women were considered for assessing risk factor main effects and for the analyses by mutation location.

A standardized questionnaire on reproductive factors and lifestyle factors was administered to the study subjects by mail. The questionnaire collected detailed information on pregnancy history. Subjects who indicated that they had at least one pregnancy were asked to provide, for each pregnancy, the month and year when the pregnancy started or was terminated, its duration, and its outcome (live birth, still birth, miscarriage, induced abortion), and the duration of breast-feeding, if applicable.

Genotyping

The mutation screening strategy was similar for all the clinics, that is, the youngest living affected family member was tested first and, if a BRCA1 or/and BRCA2 mutation was found, affected and unaffected family members were offered testing. Mutations were defined as deleterious when their putative protein products were truncated, that is, nonsense mutations and frameshift mutations (nucleotide insertions or deletions, large gene rearrangements, and splicing defects). Some mutations, without disruption of the reading frame, were considered deleterious when they were classified deleterious by the ENIGMA group (Evidence-based network for the interpretation of germline mutant alleles)[35].

The full coding sequences and the exon-intron junctions of the BRCA1 and BRCA2 genes were screened for variants, based on pre-screening (denaturing gradient gel electrophoresis (DGGE), single strand conformation polymorphism (SSCP), protein truncation assay (PTA), denaturing high performance liquid chromatography (dHPLC), high resolution melting (HRM), or enhanced mismatch mutation analysis (EMMA)) and sequencing. Several large rearrangements were identified by large cDNA sequencing, multiplex ligation-dependent probe amplification (MLPA) [36], quantitative multiplex PCR of short fragments (QMPSF) [37], quantitative PCR (qPCR) [38], qPCR HRM [39], EMMA [40], bar code screening [41] or dedicated array comparative genomic hybridization (CGH) [42]. Mutation description was provided by each French laboratory, coded and standardized according to the international nomenclature [See Additional file 1 for the distribution of mutations in the study].

Statistical methods

The data presented here were analyzed using a modified Cox proportional hazards regression model. Standard Cox regression may lead to biased estimates of the hazard ratio (HR) because the women in this study were taken from high-risk families qualifying for genetic testing. The disease status may, therefore, have affected the likelihood of ascertainment and selection leading to an over-sampling of affected women. To correct for this potential bias, the Cox regression analyses were performed using the weighted regression approach described by Antoniou et al. [43]. Individuals were weighted such that the observed BC incidence rates in the study sample were consistent with established BC risk estimates for BRCA1 and BRCA2 carriers [1]. The affected mutation carriers were underweighted (weights <1) and the unaffected mutation carriers were overweighted (weights >1). The weights were applied to all person-years of each subject in the modified Cox model.

Subjects were followed up from birth and censored at the date of diagnosis, for women who were affected by any cancer, or the date of prophylactic bilateral mastectomy or interview, for unaffected women.

Parity, breast-feeding, incomplete pregnancies, menopausal status and oral contraceptive use changed over time, so it was analyzed as a time-dependent covariate and cumulative over life time. All analyses were stratified by period of birth (before 1940, 1940 to 1949, 1950 to1959, 1960 or later). In addition, because menopausal status, oral contraceptive use and gene may substantially modify the risk of BC and thus be a potential confounder, analyses were adjusted for these factors.

To avoid the potential bias due to BC detected during a pregnancy which may cause a bias either toward or away from the null depending on the effect of pregnancy on the risk of BC, pregnancies were included only if they occurred at least one year before the age at censure. Thus, we excluded ten pregnancies, seven among affected women and three among unaffected women.

To assess the variation of BC risk associated with pregnancies and breast-feeding by location of truncating mutations in BRCA1 and BRCA2, we used regions previously defined as homogeneous in BC risk by Lecarpentier et al. We considered two groups of mutation in BRCA1, those located in LR1 (for 'low-risk region in BRCA1': codons 374 to 1161) and those located outside LR1. In BRCA2, we considered three groups of mutation in BRCA2, those located in LR2 (for 'low-risk region in BRCA2': codons 957 to 1827), located in HR2 (for 'high-risk region in BRCA2': codons 2546 to 2968) and those located outside LR2 and HR2 [30]. Heterogeneity in risk by mutation location was assessed by testing the interaction between mutation location and the risk factor of interest.

All statistical analyses were two-sided and were performed using the STATA statistical package (version 10; Stata Corporation, College Station TX).

Results

Characteristics of the whole cohort and of one-woman-per-family cohorts are listed in Table 1. A total of 563 women had been diagnosed with BC at the time of their interview, but only 499 of them were considered as affected in this analysis after censoring. The remaining 838 women were censored at age of diagnosis of ovarian cancer (N = 89), at diagnosis of another cancer (N = 16), at prophylactic bilateral mastectomy (N = 11), or at interview (N = 722). The average age at censoring for the 838 participants without BC was 40.0 years (standard deviation (SD) = 0.4), which is similar to the age at diagnosis of the women with BC (41.0 years, SD = 0.4), although the age at interview was substantially higher for the BC patients, reflecting the pattern of genetic testing among participants. Sampling of one woman per family did not change any characteristic distribution or the average of age at censure (39.8 years, SD = 0.5 and 40.4 years, SD = 0.5, respectively, for women without and with BC). Year of birth, number of full-term and incomplete pregnancies, breast-feeding, menopausal status, and oral contraceptive use are also described. There was a total of 39,666 person-years of observation.
Table 1

Characteristics of the cohort study of BRCA1/2 mutation carriers.

Characteristics

Whole cohort

One woman per family sample cohort

  

All women

(N = 1337)

With BC

(N = 499)

Without BC (N = 838)

All women

(N = 990)

With BC

(N = 379)

Without BC (N = 611)

  

No

%

No

%

No

%

No

%

No

%

No

%

Mutation

 

BRCA1

863

64.5

332

66.5

531

63.4

635

64.1

240

63.3

395

64.6

 

BRCA2

474

35.5

167

33.5

307

36.6

355

35.9

139

36.7

216

35.4

Age at interview, years

            
 

Mean

44.1

 

49.4

 

41.0

 

43.7

 

48.6

 

40.7

 
 

SD

0.3

 

0.5

 

0.4

 

0.4

 

0.5

 

0.5

 

Age at diagnosis/censoring, years

 

Mean

40.4

 

41.0

 

40.0

 

40.1

 

40.4

 

39.8

 
 

SD

0.3

 

0.4

 

0.4

 

0.3

 

0.5

 

0.5

 
 

<30

196

14.7

34

6.8

162

19.3

142

14.3

29

7.7

113

18.5

 

30 to 39

487

36.4

205

41.1

282

33.7

371

37.5

159

42.0

212

34.7

 

40 to 49

403

30.1

176

35.3

227

27.1

306

30.9

133

35.1

173

28.3

 

50 to 59

180

13.5

67

13.4

113

13.5

126

12.7

47

12.4

79

12.9

 

≥60

71

5.3

17

3.4

54

6.4

45

4.5

11

2.9

34

5.6

Year of birth

 

<1950

354

26.5

201

40.3

153

18.3

237

23.9

139

36.7

98

16.0

 

1950 to 1959

324

24.2

165

33.1

159

19.0

248

25.1

128

33.8

120

19.6

 

1960 to1969

351

26.3

119

23.8

232

27.7

282

28.5

99

26.1

183

30.0

 

≥1970

308

23.0

14

2.8

294

35.1

223

22.5

13

3.4

210

34.4

Oral contraceptive use

 

Never

261

19.5

122

24.4

139

16.6

180

18.2

86

22.7

94

15.4

 

Ever

1,058

79.1

373

74.7

685

81.7

798

80.6

290

76.5

508

83.1

 

Missing

18

1.3

4

0.8

14

1.7

12

1.2

3

0.8

9

1.5

Number of full-term pregnancies

 

0

293

21.9

68

13.6

225

26.8

217

21.9

58

15.3

159

26.0

 

1

250

18.7

108

21.6

142

16.9

196

19.8

90

23.7

106

17.3

 

2

452

33.8

182

36.5

270

32.2

346

34.9

139

36.7

207

33.9

 

≥3

342

25.6

141

28.3

201

24.0

231

23.3

92

24.3

139

22.7

 

Missing

0

0.0

0

0.0

0

0.0

0

0.0

0

0.0

0

0.0

Induced abortion

 

0

1,060

79.3

383

76.8

677

80.8

776

78.4

286

75.5

490

80.2

 

1

213

15.9

81

16.2

132

15.8

168

17.0

67

17.7

101

16.5

 

2

44

3.3

22

4.4

22

2.6

31

3.1

15

4.0

16

2.6

 

≥3

12

0.9

8

1.6

4

0.5

9

0.9

7

1.8

2

0.3

 

Missing

8

0.6

5

1.0

3

0.4

6

0.6

4

1.1

2

0.3

Spontaneous abortion

 

0

1,085

81.2

387

77.6

698

83.3

791

79.9

293

77.3

498

81.5

 

1

173

12.9

78

15.6

95

11.3

144

14.5

64

16.9

80

13.1

 

2

50

3.7

22

4.4

28

3.3

34

3.4

12

3.2

22

3.6

 

≥3

21

1.6

8

1.6

13

1.6

16

1.6

7

1.8

9

1.5

 

Missing

8

0.6

4

0.8

4

0.5

5

0.5

3

0.8

2

0.3

Breast-feeding

 

Never

439

32.8

187

37.5

252

30.1

308

31.1

130

34.3

178

29.1

 

Ever

568

42.5

230

46.1

338

40.3

442

44.6

182

48.0

260

42.6

 

Missing

37

2.8

14

2.8

23

2.7

23

2.3

9

2.4

14

2.3

 

Nulliparous

293

21.9

68

13.6

225

26.8

217

21.9

58

15.3

159

26.0

Menopausal status

 

Premenopausal

1,068

79.9

404

81.0

664

79.2

795

80.3

312

82.3

483

79.1

 

Postmenopausal

240

18.0

86

17.2

154

18.4

171

17.3

60

15.8

111

18.2

 

Unknown

29

2.2

9

1.8

20

2.4

24

2.4

7

1.8

17

2.8

BC, breast cancer; N, number; SD, standard deviation.

The estimated risks of BC associated with parity, age at first FTP, and history of breast-feeding from the weighted Cox regression analysis are summarized in Table 2, both for the entire sample and for BRCA1 and BRCA2 mutation carriers separately. We also analyzed the parity according to attained age (40 years or younger versus older than 40 years).
Table 2

Risk of breast cancer associated with full-term pregnancies and breast feeding.

Reproductive Factors

One woman per family cohort: 39,666 person-years of follow-up

BRCA1mutation carriers: 25,045 person-years of follow-up

BRCA2mutation carriers: 14,621 person-years of follow-up

  

Person-yearsa

No. of casesa

HR

95% CI

Pvalue

Person-yearsa

No. of casesa

HR

95% CI

Pvalue

Person-yearsa

No. of casesa

HR

95% CI

Pvalue

Parityb

 

Nulliparous

25,333

58

1.00

  

16,215

38

1.00

  

9,118

20

1.00

  
 

Parous

14,333

321

0.77

0.53-1.13

 

8,830

202

0.76

0.49-1.19

 

5,503

119

0.78

0.39-1.55

 

No. of full-term pregnanciesb

 

0

25,333

58

1.00

  

16,215

38

1.00

  

9,118

20

1.00

  
 

1

4,435

90

1.10

0.72-1.68

 

2,777

58

1.04

0.63-1.72

 

1,658

32

1.24

0.59-2.61

 
 

2

5,640

138

0.79

0.52-1.20

 

3,540

87

0.81

0.50-1.30

 

2,100

51

0.73

0.35-1.55

 
 

≥3

4,243

92

0.51

0.33-0.81

<10-3

2,498

56

0.52

0.31-0.89

0.02

1,745

36

0.49

0.22-1.10

0.08

 

Trend

  

0.77

0.68-0.88

<10-3

  

0.78

0.67-0.91

<10-3

  

0.74

0.58-0.95

0.02

No. of full-term pregnancies by attained ageb

 

0

25,333

58

1.00

  

16,215

38

1.00

  

9,118

20

1.00

  
 

1-2 before age 40

8,146

131

1.05

0.68-1.63

 

5,169

88

1.04

0.62-1.77

 

2,977

43

1.12

0.53-2.37

 
 

≥3 before age 40

2,303

40

0.82

0.48-1.41

 

1,414

29

0.88

0.46-1.66

 

889

11

0.64

0.23-1.75

 
 

1-2 after age 40

1,929

97

0.70

0.36-1.36

 

1,148

57

0.70

0.32-1.50

 

781

40

0.61

0.19-1.99

 
 

≥3 after age 40

1,940

52

0.35

0.17-0.70

<10-3

1,084

27

0.34

0.15-0.76

0.01

856

25

0.36

0.11-1.16

0.09

Age at first full-term pregnancyc

 

< 20 years

1,866

39

1.00

  

1,217

27

1.00

  

649

12

1.00

  
 

20-24 years

7,158

152

0.91

0.55-1.50

 

4,296

93

0.91

0.52-1.61

 

2,862

59

0.87

0.32-2.34

 
 

25-29 years

3,994

85

0.62

0.36-1.06

0.08

2,492

53

0.57

0.31-1.06

0.08

1,502

32

0.63

0.22-1.80

 
 

≥30 years

1,315

45

0.67

0.36-1.23

 

825

29

0.64

0.32-1.31

 

490

16

0.65

0.20-2.13

 
 

Nulliparous

25,333

58

0.41

0.20-0.85

0.02

16,215

38

0.43

0.19-0.97

0.04

9,118

20

0.35

0.09-1.40

 

Breast-feedingc

 

Never

5,962

131

1.00

  

3,644

87

1.00

  

2,318

44

1.00

  
 

Ever

7,875

182

1.02

0.76-1.36

 

4,840

111

0.93

0.66-1.30

 

3,035

71

1.45

0.84-2.51

 
 

Nulliparous

25,333

58

0.61

0.37-1.02

0.06

16,215

38

0.62

0.33-1.14

 

9,118

20

0.53

0.21-1.30

 

a Not including missing data. b Adjusted for menopausal status (yes, no), oral contraceptives (never, ever), and gene mutated (BRCA1, BRCA2). c Adjusted for parity (0, 1, 2, ≥3), menopausal status (yes, no), oral contraceptives (never, ever), and gene mutated (BRCA1, BRCA2). HR hazard ratio; CI confidence interval, No., number.

Overall, compared with nulliparous women, parous women had a slightly lower but non significant risk of BC (HR = 0.77, 95% CI = 0.53 to 1.13). As the number of FTPs increased there was a statistically significant decrease in the risk of BC (P trend < 10-3). The reduction in risk was estimated with an HR = 0.51 (95% CI = 0.33 to 0.81) for women with at least three FTPs. This association remained significant only for the women who were older than 40 years (for women with at least three FTPs, HR = 0.35, 95% CI = 0.17 to 0.70). Among parous women, age at first FTP seems to be associated with BC risk. Indeed, women who had their first FTP when they were 25 years or older had a lower HR point estimate of BC than women who had their first FTP when they were younger than 20 years (between age 25 and 30 versus before age 20, HR = 0.62, 95% CI = 0.36 to 1.06 and after age 30 versus before age 20, HR = 0.67, 95% CI = 0.36 to 1.23). The reduction in risk associated with parity and age at first FTP was similar for carriers of BRCA1 and BRCA2 mutations. After adjusting for parity, we observed no association between ever having breast-fed and BC risk, either for the entire sample or separately for BRCA1 or BRCA2 mutation carriers. There was also no statistically significant association between duration of breast-feeding and BC risk even for long duration (that is, ≥10 months) (data not shown).

The estimated risks of BC associated with incomplete pregnancies, from the weighted Cox regression analysis, are summarized in Table 3. First, HR point estimates suggest an association between incomplete pregnancy (induced abortions and miscarriages considered together) and a higher BC risk in the entire sample (≥1 versus 0: HR = 1.28, 95% CI = 0.98 to 1.67), with a maximum risk among women who had at least three incomplete pregnancies (≥3 versus 0: HR = 2.39, 95% CI = 1.28 to 4.45). HR point estimates seem similar whatever the type of incomplete pregnancy (induced abortions or miscarriages) but were not significant. However, as the number of incomplete pregnancies increased, there was a statistically significant increase in the risk of BC for induced abortions (P trend = 0.02), but not for miscarriages. The maximum risk was observed among women who had at least three induced terminations (≥3 versus 0: HR = 3.84, 95% CI = 1.52 to 9.66). Among women who had induced terminations, an age of 20 years or older at first incomplete pregnancy led to a lower risk of BC than an age younger than 20 years (after age 20 versus before HR = 0.50, 95% CI = 0.28 to 0.90). When we considered this risk with respect to the first FTP, the association previously found persisted, but only before the first FTP (HR = 1.77, 95% CI = 1.19 to 2.63). Interestingly, point estimates associated with having miscarriages in the first three months of pregnancy were similar to those associated with induced termination (HR = 1.35, 95% CI = 0.95 to 1.93 and HR = 1.30, 95% CI = 0.93 to 1.82, respectively). There were no differences when stratified by gene.
Table 3

Risk of breast cancer associated with incomplete pregnancies and the TMAP score.

Reproductive factors

One woman per family cohort: 39,666 person-years of follow-up

BRCA1mutation carriers: 25,045 person-years of follow-up

BRCA2mutation carriers: 14,621 person-years of follow-up

  

Person-yearsa

No. of casesa

HR

95% CI

Pvalue

Person-yearsa

No. of casesa

HR

95% CI

Pvalue

Person-yearsa

No. of casesa

HR

95% CI

Pvalue

Incomplete pregnancies b

 

Never

33,455

219

1.00

  

21,291

135

1.00

  

12,164

84

1.00

  
 

Ever

5,995

155

1.28

0.98-1.67

0.07

3,673

103

1.30

0.95-1.76

 

2,322

52

1.07

0.64-1.78

 

No. of incomplete pregnancies b

 

0

33,455

219

1.00

  

21,291

135

1.00

  

12,164

84

1.00

  
 

1

4,208

103

1.25

0.93-1.69

 

2,544

70

1.27

0.89-1.82

 

1,664

33

0.96

0.53-1.73

 
 

2

1,320

32

1.07

0.69-1.66

 

841

21

1.08

0.65-1.79

 

479

11

1.01

0.46-2.24

 
 

≥3

467

20

2.39

1.28-4.45

0.01

288

12

2.45

1.19-5.04

0.02

179

8

2.69

0.71-10.3

 
 

Trend

  

1.19

1.02-1.39

0.03

  

1.20

1.00-1.43

0.05

  

1.15

0.84-1.58

 

Type of incomplete pregnancies b

 

No incomplete pregnancies

33,384

219

1.00

  

21,220

135

1.00

  

12,164

84

1.00

  
 

Induced abortion only

2,909

71

1.29

0.93-1.81

 

1,859

50

1.35

0.92-1.99

 

1,050

21

1.02

0.53-1.96

 
 

Miscarriage only

2,494

65

1.19

0.83-1.72

 

1,407

41

1.14

0.73-1.78

 

1,087

24

1.05

0.54-2.04

 
 

Induced abortion and miscarriage

535

18

1.49

0.84-2.65

 

350

11

1.51

0.79-2.91

 

185

7

1.43

0.45-4.51

 

No. of induced abortionsb

 

0

35,968

286

1.00

  

22,666

177

1.00

  

13,302

109

1.00

  
 

1

2,833

66

1.15

0.83-1.60

 

1,805

47

1.22

0.84-1.78

 

1,028

19

0.87

0.45-1.68

 
 

2

497

16

1.44

0.74-2.78

 

322

10

1.59

0.75-3.40

 

175

6

1.47

0.44-4.88

 
 

≥3

114

7

3.84

1.52-9.66

<10-3

82

4

3.31

1.13-9.71

0.03

32

3

7.85

1.74-35.5

0.01

 

Trend

  

1.28

1.04-1.58

0.02

  

1.32

1.04-1.67

0.02

  

1.26

0.81-1.95

 

No. of miscarriagesb

 

0

36,419

293

1.00

  

23,121

186

1.00

  

13,298

107

1.00

  
 

1

2,273

64

1.21

0.85-1.72

 

1,321

41

1.20

0.79-1.82

 

952

23

1.01

0.50-2.02

 
 

2

508

12

0.98

0.48-1.99

 

301

6

0.69

0.27-1.81

 

207

6

1.54

0.64-3.67

 
 

≥3

248

7

1.18

0.42-3.30

 

135

5

1.40

0.44-4.53

 

113

2

0.86

0.10-7.56

 
 

Trend

  

1.07

0.87-1.32

   

1.04

0.81-1.35

   

1.09

0.75-1.58

 

Age at first induced abortionc

 

<20 years

1,094

32

1.00

  

662

20

1.00

  

432

12

1.00

  
 

≥ 20 years

2,350

57

0.50

0.28-0.90

0.02

1,547

41

0.53

0.27-1.02

0.06

803

16

0.40

0.10-1.53

 
 

No induced abortion

35,968

286

0.74

0.31-1.78

 

22,666

177

0.70

0.27-1.84

 

13,302

109

1.10

0.12-10.5

 

Age at first miscarriagec

 

<20 years

220

5

1.00

  

202

5

1.00

  

18

0

   
 

≥ 20

2,809

78

1.04

0.25-4.28

 

1,555

47

0.87

0.20-3.73

 

1,254

31

   
 

No miscarriage

36,419

293

0.81

0.17-3.99

 

23,121

186

0.69

0.12-3.93

 

13,298

107

   

Induced abortion relative to the first full-term pregnancyb

 

No induced abortion

35,964

284

1.00

  

22,663

175

1.00

  

13,301

109

1.00

  
 

Before first full-term pregnancy

1,835

49

1.77

1.19-2.63

0.01

1,223

33

1.77

1.13-2.77

0.01

612

16

1.88

0.86-4.12

 
 

After first full-term pregnancy

1,613

42

0.97

0.65-1.45

 

989

30

1.14

0.72-1.79

 

624

12

0.55

0.26-1.18

 

Miscarriage relative to the first full-term pregnancyb

1.00

 

No miscarriage

36,414

291

   

23,118

186

1.00

  

13,296

105

1.00

  
 

Before first full-term pregnancy

1,138

29

1.07

0.65-1.77

 

729

20

1.01

0.55-1.84

 

409

9

0.89

0.36-2.16

 
 

After first full-term pregnancy

1,896

56

1.05

0.73-1.51

 

1,031

32

1.02

0.65-1.60

 

865

24

1.09

0.57-2.08

 

Type and length of incomplete pregnanciesb

 

No abortion

33,384

219

1.00

  

21,220

135

1.00

  

12,164

84

1.00

  
 

Induced abortion only

2,909

71

1.30

0.93-1.82

 

1,859

50

1.36

0.92-2.00

 

1,050

21

1.01

0.52-1.95

 
 

Miscarriage with length ≤3 months

2,492

74

1.35

0.95-1.93

0.09

1,461

45

1.27

0.84-1.94

 

1,031

29

1.35

0.69-2.67

 
 

Miscarriage with length >3 months

436

8

0.93

0.41-2.12

 

253

7

1.17

0.47-2.95

 

183

1

0.14

0.02-1.24

0.08

TMAP score (not including never pregnant women)d

 

]0-0.35]

7,545

141

1.00

  

4,564

85

1.00

  

2,981

56

1.00

  
 

]0.35-0.40]

3,416

88

1.05

0.75-1.48

 

2,154

59

0.99

0.66-1.48

 

1,262

29

1.09

0.60-1.98

 
 

]0.40-0.45]

1,735

51

1.23

0.81-1.86

 

1,034

30

1.12

0.67-1.87

 

701

21

1.33

0.68-2.59

 
 

]0.45-0.50]

589

17

1.53

0.80-2.93

 

433

14

1.41

0.68-2.92

 

156

3

1.70

0.37-7.71

 
 

]0.5-1.00]

1,186

22

1.97

1.19-3.29

0.01

722

12

1.91

1.07-3.42

0.03

464

10

2.04

0.79-5.24

 
 

Trend

  

1.16

1.03-1.30

0.02

  

1.14

0.99-1.32

0.07

  

1.17

0.95-1.44

 

a Not including missing data. bAdjusted for parity (0, 1, 2, ≥3), menopausal status (yes, no), oral contraceptives (never, ever), and gene mutated (BRCA1, BRCA2). cAdjusted for parity (0,1 2, ≥3), no. of incomplete pregnancies (0, 1, 2, ≥3), menopausal status (yes, no), oral contraceptives (never, ever), and gene mutated (BRCA1, BRCA2). dAdjusted for menopausal status (yes, no), oral contraceptives (never, ever), and gene mutated (BRCA1, BRCA2). HR, hazard ratio; CI, confidence interval.

To take into account simultaneously the contrary effect on BC risk of FTPs and pregnancies interrupted within the first three months, we determined the TMAP score defined as the Time of breast Mitotic Activity during Pregnancies. The TMAP score is the sum of pregnancies with a duration greater than or equal to three months multiplied by three plus the sum of the duration (in months) of each pregnancy with a duration of less than three months divided by the sum of the duration of each pregnancy whatever the outcome of the pregnancy. The TMAP score is a time-dependent variable.

Compared with women with a TMAP score of less than 0.35, an increasing TMAP score was associated with a statistically significant increase in the risk of BC (P trend = 0.02) and reached 1.97 (95% CI = 1.19-3.29) when the TMAP score was greater than 0.5.

Estimated risks of BC associated with parity, age at first FTP, and history of breast-feeding according to the mutation location were assessed by regions of BRCA1 and BRCA2 previously defined as homogeneous for the risk of BC [30]. Among BRCA2 mutation carriers, no variation of BC risk was found (data not shown). Estimated risks of BC associated with parity and incomplete pregnancy by homogeneous region in BRCA1 are shown in Table 4. Parity seems to be associated with a significantly decreased risk of BC only among women with a mutation in LR1 (≥1 versus 0 FTP: HR = 0.27, 95% CI = 0.13 to 0.55) (Pinteraction <10-3). Similarly, an increasing number of FTPs was associated with a statistically significant decrease in the risk of BC only in LR1 (HR = 0.20, 95% CI = 0.08 to 0.49 for women with at least three FTPs compared with nulliparous women). This protective effect persists whatever the age (HR = 0.33, 95% CI = 0.16 to 0.68 and HR = 0.21, 95% CI = 0.09 to 0.51 before and after age 40 respectively). The HR associated with breast-feeding did not differ between LR1 (ever versus never: HR = 0.73, 95% CI = 0.32 to 1.66) and outside LR1 (HR = 0.86, 95% CI = 0.58 to 1.27) (data not shown). There was also no significant interaction between incomplete pregnancy or age at first FTP and mutation location (data not shown).
Table 4

Variation of BC risk associated with full-term pregnancies and incomplete pregnancies according to location of the truncating mutation in BRCA1.

Reproductive factors

Location of truncating mutation in BRCA1mutation carriers

 

Outside LR1 (16,690 person-years of follow-up)

In LR1 (5,367 person-years of follow-up)

 

Person-yearsa

No. of casesa

HR

95% CI

P value

Person-yearsa

No. of casesa

HR

95% CI

P value

Parityb

          

   Nulliparous

10,911

21

1.00

  

3,378

9

1.00

  

   Parous

5,779

145

1.42

0.77-2.63

 

1,989

34

0.27

0.13-0.55

<10-3

No. of full-term pregnanciesb

          

   0

10,911

21

   

3,378

9

1.00

  

   1-2

4,218

108

1.63

0.88-3.05

 

1,354

23

0.32

0.15-0.68

<10-3

   ≥3

1,546

36

0.96

0.48-1.94

 

635

11

0.20

0.08-0.49

<10-3

Full-term pregnancies by attained ageb

          

   Nulliparous

10,911

21

1.00

  

3,378

9

1.00

  

   Before age 40

4,325

81

1.36

0.72-2.56

 

1,501

23

0.33

0.16-0.68

<10-3

   After age 40

1,439

63

1.49

0.70-3.19

 

488

11

0.21

0.09-0.51

<10-3

Incomplete pregnancies c

          

   Never

14,247

92

1.00

  

4,419

23

1.00

  

   Ever

2,404

73

1.43

0.98-2.07

0.06

948

20

0.95

0.47-1.96

 

No. of incomplete pregnancies c

          

   0

14,247

92

1.00

  

4,419

23

1.00

  

   1-2

2,254

66

1.36

0.93-2.00

 

820

16

0.82

0.39-1.73

 

   ≥3

150

7

2.59

1.24-5.40

0.01

128

4

2.05

0.48-8.76

 

Type and length of incomplete pregnancies c

          

   No incomplete pregnancies

14,204

92

1.00

  

4,419

23

1.00

  

   Induced abortion only

1,279

40

1.49

0.95-2.36

0.08

431

5

0.65

0.21-2.00

 

   Miscarriage with length ≤3 months

924

28

1.33

0.79-2.26

 

428

13

1.25

0.56-2.81

 

   Miscarriage with length >3 months

153

4

1.12

0.35-3.59

 

46

2

1.52

0.18-12.5

 

aNot including missing data. bAdjusted for menopausal status (yes, no) and oral contraceptives (never, ever). cAdjusted for parity (0, 1, 2, ≥3), menopausal status (yes, no) and oral contraceptives (never, ever). HR, hazard ratio; CI, confidence interval.

Discussion

Our results confirm the existence of a protective effect of an increasing number of FTPs toward BC among BRCA1 and BRCA2 mutation carriers. This risk reduction, however, appeared to be significant only for women older than 40 years. Additionally, we found some evidence of an association between pregnancies interrupted within the first three months (induced or spontaneous) and an increased risk of BC. This increased risk appeared to be restricted to incomplete pregnancies occurring before the first FTP. Whatever the outcome of the pregnancy, the results show that a first pregnancy before age 20 was associated with a higher risk of BC than a first pregnancy occurring later. We defined the TMAP score to take into account simultaneously the contrary effect of full-term and interrupted pregnancies. We found a significant positive association between the TMAP score and BC risk. All these results appeared to be similar in BRCA1 and BRCA2. Nevertheless, our results suggest a variation in BC risk associated with parity according to the location of the mutation in BRCA1.

Our study has several limitations. First, our results are based on retrospective information obtained from women who opted for BRCA1 and BRCA2 mutation screening and genetic testing. One assumption that underlies the method of weighting used in our analyses is that the absolute disease risks are well estimated and ascertainment is not dependent on the covariates of interest [43]. This assumption would be violated if any of the factors related to pregnancies changed the likelihood that women might opt to undergo genetic testing. We are unaware of any study that has assessed whether a woman's uptake of genetic testing differs according to these factors and we cannot assess this potential bias [13].

Second, since our data used prevalent cases with some women being interviewed a long time after their BC diagnosis, we cannot exclude that our findings on parity, breast-feeding and incomplete pregnancies are affected by a potential survival bias. However, we could not detect it in our data by performing extra analyses on subsamples of individuals diagnosed or censured within the five-year period before their interview, with a follow-up being counted only during this five-year period. We did not observe differences in our results using this pseudo-incident cohort.

It is well established that increasing parity and early age at first birth are associated with a lower risk of developing BC in the general population. There is evidence that the protective effect of parity may be restricted to women who are over 40 years old [4447]. The relationship between pregnancy and risk of BC in BRCA1 and BRCA2 carriers is less clear in the earliest publications [15, 16, 20, 21, 23]. Our results are more in line with more recent studies [13, 17, 22, 48] which found a decreased risk associated with an increasing number of FTPs among BRCA1 and BRCA2 mutation carriers. In agreement with our findings, three of these studies showed a reduced risk of BC only after age 40 years [13, 22, 48]. Among the studies which assessed the risk of BC associated with the age at first FTP [13, 15, 17, 1922, 48] results are inconsistent and only two studies found a reduced risk among BRCA1 or BRCA2 mutation carriers associated with a first FTP after age 20 [13, 20]. In contrast with our results, the International BRCA1/2 Carrier Cohort Study (IBCCS) study [13] found a variation in this risk by gene mutated. They found that a first FTP after the age of 30 years was associated with a significant decrease in BC risk in BRCA1 and a significant increase in BRCA2 mutation carriers. Antoniou et al. [48] subsequently carried out a similar analysis on 789 BRCA1/2 mutation carriers from the UK and found that in BRCA2 mutation carriers the risk is higher for those who have their first FTP later, that is, after age 30. We did not find such a variation although our data overlap for about one quarter of our subjects (319 out of 1,337) with those of the IBCCS study.

A number of studies have examined the risk of BC associated with interrupted pregnancies, but there has been some controversy in the past. A collaborative reanalysis of data from 53 epidemiological studies, including 83,000 women with BC from 16 countries, described inconsistent findings across studies and difficulties in evaluating these associations. It was concluded that BC risk did not appear to be associated with an increased number of either spontaneous or induced abortions [10]. Similar results were obtained subsequently from a prospective study of young women [12]. However, numerous studies have suggested that interrupted pregnancies may moderately increase the risk of BC [59, 49]. Few studies have examined this association in BRCA1 and BRCA2 mutation carriers. Two studies concluded that BC risk did not appear to be associated with an increased number of either spontaneous or induced abortions [13, 15]. Furthermore, Friedman et al. observed that among BRCA2 mutation carriers, two or more therapeutic abortions resulted in a 64% decrease in BC risk, but not among BRCA1 mutation carriers [14]. In 1995, evidence was found that the relative risk conferred by a family history of BC increased with the number of interrupted pregnancies and that this risk was highest for those who had an interrupted pregnancy before the first FTP [50]. Our findings seem consistent with this study. Although, as in many previous studies (for example [51]), a recall bias where BC cases declared interrupted pregnancies more often than controls, would lead to a BC bias away from the null hypothesis. Indeed, we found an increased BC risk associated with an increasing number of induced abortions. However, this risk appeared to be restricted to pregnancies with induced interruptions before the first FTP. This effect may be because the differentiation of mammary cells which occurs during an FTP [52] prevents the carcinogenic effect of subsequent interrupted pregnancies. In addition, our results indicate that spontaneous abortions occurring in the first three months were associated with an increased risk of BC. The difference in risk according to the pregnancy outcome (interrupted versus full-term) and according to the duration of interrupted pregnancy, whatever the nature of the interruption, and our TMAP scores highlight the importance of the duration of pregnancy as a BC risk factor. This is also illustrated by the findings of Vatten et al. [53] who reported that the shorter the length of gestation, the higher the BC risk, in a cohort of about 695,000 women. This score could be useful for the individual estimation of BC risk.

When stratified by homogeneous regions, our results suggest a variation of the BC risk associated with parity according to mutation location in BRCA1, but not in BRCA2. This is the first time that the effects of pregnancy-related factors according to mutation location have been studied. Although, the significance might occur by chance because of a limited power, parity seems to be associated with a significantly decreased risk of BC among women with a mutation in the LR1 region, but not outside this region. Therefore, pregnancies seem to have the same protective effect in LR1 as in the general population, while outside LR1 parity does not seems to have an effect on BC risk.

Although there is no obvious biological hypothesis to explain this variation, one can expect that BRCA1 acts during pregnancy. Indeed, BRCA1 is also involved in cellular anti-proliferation via inhibition of the transcriptional activity of estrogen receptor α (ERα) [5456]. Interestingly, this mechanism is postulated to occur through a protein-protein interaction involving domains of BRCA1 corresponding to regions outside of LR1: that is, the N-terminus (amino acids 1-300) and the C-terminal region [54]. In addition, Ma et al. [57] provide evidence for a difference in some hormone-related risk factor profiles between triple negative (TN) and other BC subtypes, especially, in line with a protective effect of parity in all subtypes except in TN. Thus, it would be of interest to study the relation between mutation location and the tumor subtype to determine whether the TN tumors are more often associated with mutations located outside LR1.

Conclusions

This study confirms the existence of a protective effect of FTPs toward BC among BRCA1 and BRCA2 mutation carriers which is restricted to women with mutation in the LR1 region for BRCA1 mutation carriers. We also showed the importance of the duration of pregnancies as a BC risk factor.

If our findings are confirmed, taking into account environmental and lifestyle modifiers, mutation position might be important for the clinical management of BRCA1 and BRCA2 mutation carriers and could also be helpful in understanding how BRCA1 and BRCA2 genes are involved in BC.

Author information

GENEPSO Collaborating Centers:

Coordinating Center, Hôpital René Huguenin/Institut Curie, Saint Cloud: Catherine Noguès, Emmanuelle Fourme, Rosette Lidereau; Etienne Rouleau, Sandrine Caputo, Shirley Wakselman

Collaborating Centers: Institut Curie, Paris: Dominique Stoppa-Lyonnet, Marion Gauthier-Villars; Bruno Buecher, Institut Gustave Roussy, Villejuif: Olivier Caron; Hôpital René Huguenin/Institut Curie, Saint Cloud: Catherine Noguès, Liliane Demange; Centre Paul Strauss, Strasbourg: Jean-Pierre Fricker; Centre Léon Bérard, Lyon: Christine Lasset, Valérie Bonadona; Centre François Baclesse, Caen: Pascaline Berthet; Hôpital d'Enfants CHU Dijon - Centre Georges François Leclerc, Dijon: Laurence Faivre; Centre Alexis Vautrin, Vandoeuvre-les-Nancy: Elisabeth Luporsi; Centre Antoine Lacassagne, Nice: Marc Frénay; Institut Claudius Regaud, Toulouse: Laurence Gladieff; Réseau Oncogénétique Poitou Charente, Niort: Paul Gesta; Institut Paoli-Calmettes, Marseille: Hagay Sobol, François Eisinger, Laetitia Huiart; Institut Bergonié, Bordeaux: Michel Longy, Centre Eugène Marquis, Rennes: Catherine Dugast; GH Pitié Salpétrière, Paris: Chrystelle Colas, Florent Soubrier; CHU Arnaud de Villeneuve, Montpellier: Isabelle Coupier, Pascal Pujol; Centres Paul Papin, and Catherine de Sienne, Angers, Nantes: Alain Lortholary; Centre Oscar Lambret, Lille: Philippe Vennin, Claude Adenis; Institut Jean Godinot, Reims: Tan Dat Nguyen; Centre René Gauducheau, Nantes: Capucine Delnatte; Centre Henri Becquerel, Rouen: Annick Rossi, Julie Tinat, Isabelle Tennevet; Hôpital Civil, Strasbourg: Jean-Marc Limacher; Christine Maugard; Hôpital Centre Jean Perrin, Clermont-Ferrand: Yves-Jean Bignon; Polyclinique Courlancy, Reims: Liliane Demange; Clinique Sainte Catherine, Avignon: Hélène Dreyfus; Hôpital Saint-Louis, Paris: Odile Cohen-Haguenauer; CHRU Dupuytren, Limoges: Brigitte Gilbert; Couple-Enfant-CHU de Grenoble: Dominique Leroux; Hôpital de la Timone, Marseille: Hélène Zattara-Cannoni; Inserm U900, Ecole des Mines de Paris, ParisTech, Service de Biostatistiques, Institut Curie, Paris: Nadine Andrieu; Inserm U535, Villejuif: Catherine Bonaïti; Inserm U379, Marseille: Claire Julian-Reynier; Inserm

Abbreviations

95%CI: 

95% confidence interval

BC: 

breast cancer

CGH: 

comparative genomic hybridization

DGGE: 

denaturing gradient gel electrophoresis

dHPLC: 

denaturing high performance liquid chromatography

EMMA: 

enhanced mismatch mutation analysis

ENIGMA: 

evidence-based network for the interpretation of germline mutant alleles

FTP: 

full-term pregnancy

HR: 

hazard ratio

HR2: 

high-risk region in BRCA2

HRM: 

high resolution melting

LR1: 

low-risk region in BRCA1

LR2: 

low-risk region in BRCA2

MLPA: 

multiplex ligation-dependent probe amplification

PTA: 

protein truncation assay

QMPSF: 

quantitative multiplex polymerase chain reaction of short fragments

qPCR: 

quantitative polymerase chain reaction

SSCP: 

single strand conformation polymorphism

TMAP: 

mitotic activity during pregnancies

TN: 

triple negative tumors.

Declarations

Acknowledgements

The GENEPSO study is supported by the Fondation de France and the Ligue Nationale Contre le Cancer. Shirley Waskelman (Institut Curie, Hôpital René Huguenin, Saint Cloud, France) provided technical assistance.

Authors’ Affiliations

(1)
Biostatistics, Institut Curie
(2)
Biostatistics, Inserm U900
(3)
Biostatistics, Mines ParisTech
(4)
Public Health, Institut Curie Hôpital René Huguenin
(5)
Genetic oncology service, Institut Curie
(6)
Université Claude Bernard Lyon 1
(7)
Epidemiological and Public Health, CNRS UMR 5558
(8)
Unit of genetic epidemiology and prevention, Centre Léon Bérard
(9)
Unit of oncology, Centre Paul Strauss
(10)
Unit of oncology, Institut de Cancérologie Gustave Roussy
(11)
Unit Genetics, Inserm U830
(12)
Université Paris-Descartes
(13)
Unit of gynecological pathology, Centre François Baclesse
(14)
Oncogenetics, Centre Georges François Leclerc
(15)
Medical genetics, Hôpital d'enfants
(16)
Unit medical genetics and oncology, Hôpital Arnaud de Villeneuve CHU Montpellier
(17)
Unit of oncology, Centre Val d'Aurelle
(18)
Unit of medical oncology, Institut Claudius Regaud
(19)
Oncology center for the regional cancer genetics consultation Poitou-Charentes, CH Georges Renon
(20)
Department of anticipation and monitoring of cancer, Institut Paoli-Calmettes, boulevard Sainte Marguerite 232
(21)
Unit of medical genetics and oncology, Inserm UMR 912, boulevard Sainte Marguerite 232
(22)
Unit of oncology, Centre Antoine Lacassagne
(23)
Unit of medical oncology, Centre Alexis Vautrin
(24)
Unit of gynecologic oncology, Centre Catherine de Sienne
(25)
Unit of genetics oncology, Groupe hospitalier Pitié Salpétrière
(26)
Unit Genetics, Centre Eugène Marquis
(27)
Laboratory of molecular genetics, Institut Bergonié
(28)
Unit of genetics, Hôpital Universitaire
(29)
Laboratory of genetics, Institut Curie Hôpital René Huguenin

References

  1. Antoniou A, Pharoah PD, Narod S, Risch HA, Eyfjord JE, Hopper JL, Loman N, Olsson H, Johannsson O, Borg A, Pasini B, Radice P, Manoukian S, Eccles DM, Tang N, Olah E, Anton-Culver H, Warner E, Lubinski J, Gronwald J, Gorski B, Tulinius H, Thorlacius S, Eerola H, Nevanlinna H, Syrjakoski K, Kallioniemi OP, Thompson D, Evans C, Peto J, et al: Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: a combined analysis of 22 studies. Am J Hum Genet. 2003, 72: 1117-1130. 10.1086/375033.View ArticlePubMedPubMed CentralGoogle Scholar
  2. Parsa P, Parsa B: Effects of reproductive factors on risk of breast cancer: a literature review. Asian Pac J Cancer Prev. 2009, 10: 545-550.PubMedGoogle Scholar
  3. National Breast and Ovarian Cancer Centre: Breast cancer risk factors, a review of the evidence. Australian Government, Cancer Australia. 2009, [http://canceraustralia.nbocc.org.au/view-document-details/rfrw-breast-cancer-risk-factors-a-review-of-the-evidence]Google Scholar
  4. Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease. Lancet. 2002, 360: 187-195.
  5. Newcomb PA, Storer BE, Longnecker MP, Mittendorf R, Greenberg ER, Willett WC: Pregnancy termination in relation to risk of breast cancer. JAMA. 1996, 275: 283-287. 10.1001/jama.1996.03530280035033.View ArticlePubMedGoogle Scholar
  6. Brind J, Chinchilli VM, Severs WB, Summy-Long J: Induced abortion as an independent risk factor for breast cancer: a comprehensive review and meta-analysis. J Epidemiol Community Health. 1996, 50: 481-496. 10.1136/jech.50.5.481.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Wingo PA, Newsome K, Marks JS, Calle EE, Parker SL: The risk of breast cancer following spontaneous or induced abortion. Cancer Causes Control. 1997, 8: 93-108. 10.1023/A:1018443507512.View ArticlePubMedGoogle Scholar
  8. Zografos GC, Panou M, Panou N: Common risk factors of breast and ovarian cancer: recent view. Int J Gynecol Cancer. 2004, 14: 721-740. 10.1111/j.1048-891X.2004.14503.x.View ArticlePubMedGoogle Scholar
  9. Daling JR, Brinton LA, Voigt LF, Weiss NS, Coates RJ, Malone KE, Schoenberg JB, Gammon M: Risk of breast cancer among white women following induced abortion. Am J Epidemiol. 1996, 144: 373-380. 10.1093/oxfordjournals.aje.a008938.View ArticlePubMedGoogle Scholar
  10. Beral V, Bull D, Doll R, Peto R, Reeves G: Breast cancer and abortion: collaborative reanalysis of data from 53 epidemiological studies, including 83 000 women with breast cancer from 16 countries. Lancet. 2004, 363: 1007-1016.View ArticlePubMedGoogle Scholar
  11. Palmer JR, Wise LA, Adams-Campbell LL, Rosenberg L: A prospective study of induced abortion and breast cancer in African-American women. Cancer Causes Control. 2004, 15: 105-111.View ArticlePubMedGoogle Scholar
  12. Mahue-Giangreco M, Ursin G, Sullivan-Halley J, Bernstein L: Induced abortion, miscarriage, and breast cancer risk of young women. Cancer Epidemiol Biomarkers Prev. 2003, 12: 209-214.PubMedGoogle Scholar
  13. Andrieu N, Goldgar DE, Easton DF, Rookus M, Brohet R, Antoniou AC, Peock S, Evans G, Eccles D, Douglas F, Nogues C, Gauthier-Villars M, Chompret A, Van Leeuwen FE, Kluijt I, Benitez J, Arver B, Olah E, Chang-Claude J: Pregnancies, breast-feeding, and breast cancer risk in the International BRCA1/2 Carrier Cohort Study (IBCCS). J Natl Cancer Inst. 2006, 98: 535-544. 10.1093/jnci/djj132.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Friedman E, Kotsopoulos J, Lubinski J, Lynch HT, Ghadirian P, Neuhausen SL, Isaacs C, Weber B, Foulkes WD, Moller P, Rosen B, Kim-Sing C, Gershoni-Baruch R, Ainsworth P, Daly M, Tung N, Eisen A, Olopade OI, Karlan B, Saal HM, Garber JE, Rennert G, Gilchrist D, Eng C, Offit K, Osborne M, Sun P, Narod SA: Spontaneous and therapeutic abortions and the risk of breast cancer among BRCA mutation carriers. Breast Cancer Res. 2006, 8: R15-10.1186/bcr1387.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Jernstrom H, Lerman C, Ghadirian P, Lynch HT, Weber B, Garber J, Daly M, Olopade OI, Foulkes WD, Warner E, Brunet JS, Narod SA: Pregnancy and risk of early breast cancer in carriers of BRCA1 and BRCA2. Lancet. 1999, 354: 1846-1850. 10.1016/S0140-6736(99)04336-6.View ArticlePubMedGoogle Scholar
  16. Tryggvadottir L, Olafsdottir EJ, Gudlaugsdottir S, Thorlacius S, Jonasson JG, Tulinius H, Eyfjord JE: BRCA2 mutation carriers, reproductive factors and breast cancer risk. Breast Cancer Res. 2003, 5: R121-R128. 10.1186/bcr619.View ArticlePubMedPubMed CentralGoogle Scholar
  17. Lee E, Ma H, McKean-Cowdin R, Van Den BD, Bernstein L, Henderson BE, Ursin G: Effect of reproductive factors and oral contraceptives on breast cancer risk in BRCA1/2 mutation carriers and noncarriers: results from a population-based study. Cancer Epidemiol Biomarkers Prev. 2008, 17: 3170-3178. 10.1158/1055-9965.EPI-08-0396.View ArticlePubMedGoogle Scholar
  18. Jernstrom H, Lubinski J, Lynch HT, Ghadirian P, Neuhausen S, Isaacs C, Weber BL, Horsman D, Rosen B, Foulkes WD, Friedman E, Gershoni-Baruch R, Ainsworth P, Daly M, Garber J, Olsson H, Sun P, Narod SA: Breast-feeding and the risk of breast cancer in BRCA1 and BRCA2 mutation carriers. J Natl Cancer Inst. 2004, 96: 1094-1098. 10.1093/jnci/djh211.View ArticlePubMedGoogle Scholar
  19. Kotsopoulos J, Lubinski J, Lynch HT, Klijn J, Ghadirian P, Neuhausen SL, Kim-Sing C, Foulkes WD, Moller P, Isaacs C, Domchek S, Randall S, Offit K, Tung N, Ainsworth P, Gershoni-Baruch R, Eisen A, Daly M, Karlan B, Saal HM, Couch F, Pasini B, Wagner T, Friedman E, Rennert G, Eng C, Weitzel J, Sun P, Narod SA, Garber J, et al: Age at first birth and the risk of breast cancer in BRCA1 and BRCA2 mutation carriers. Breast Cancer Res Treat. 2007, 105: 221-228. 10.1007/s10549-006-9441-3.View ArticlePubMedGoogle Scholar
  20. Hartge P, Chatterjee N, Wacholder S, Brody LC, Tucker MA, Struewing JP: Breast cancer risk in Ashkenazi BRCA1/2 mutation carriers: effects of reproductive history. Epidemiology. 2002, 13: 255-261. 10.1097/00001648-200205000-00004.View ArticlePubMedGoogle Scholar
  21. Rebbeck TR, Wang Y, Kantoff PW, Krithivas K, Neuhausen SL, Godwin AK, Daly MB, Narod SA, Brunet JS, Vesprini D, Garber JE, Lynch HT, Weber BL, Brown M: Modification of BRCA1- and BRCA2-associated breast cancer risk by AIB1 genotype and reproductive history. Cancer Res. 2001, 61: 5420-5424.PubMedGoogle Scholar
  22. Milne RL, Osorio A, Cajal T, Baiget M, Lasa A, Diaz-Rubio E, de la Hoya M, Caldes T, Teule A, Lazaro C, Blanco I, Balmana J, Sanchez-Olle G, Vega A, Blanco A, Chirivella I, Esteban CE, Duran M, Velasco E, Martinez de Duenas E, Tejada MI, Miramar MD, Calvo MT, Guillen-Ponce C, Salazar R, San Roman C, Urioste M, Benitez J: Parity and the risk of breast and ovarian cancer in BRCA1 and BRCA2 mutation carriers. Breast Cancer Res Treat. 2010, 119: 221-232. 10.1007/s10549-009-0394-1.View ArticlePubMedGoogle Scholar
  23. Cullinane CA, Lubinski J, Neuhausen SL, Ghadirian P, Lynch HT, Isaacs C, Weber B, Moller P, Offit K, Kim-Sing C, Friedman E, Randall S, Pasini B, Ainsworth P, Gershoni-Baruch R, Foulkes WD, Klijn J, Tung N, Rennert G, Olopade O, Couch F, Wagner T, Olsson H, Sun P, Weitzel JN, Narod SA: Effect of pregnancy as a risk factor for breast cancer in BRCA1/BRCA2 mutation carriers. Int J Cancer. 2005, 117: 988-991. 10.1002/ijc.21273.View ArticlePubMedGoogle Scholar
  24. Russo J, Russo IH: Development of the human breast. Maturitas. 2004, 49: 2-15. 10.1016/j.maturitas.2004.04.011.View ArticlePubMedGoogle Scholar
  25. Russo J, Russo IH: Cellular basis of breast cancer susceptibility. Oncol Res. 1999, 11: 169-178.PubMedGoogle Scholar
  26. Gayther SA, Mangion J, Russell P, Seal S, Barfoot R, Ponder BA, Stratton MR, Easton D: Variation of risks of breast and ovarian cancer associated with different germline mutations of the BRCA2 gene. Nat Genet. 1997, 15: 103-105. 10.1038/ng0197-103.View ArticlePubMedGoogle Scholar
  27. Thompson D, Easton D: Variation in cancer risks, by mutation position, in BRCA2 mutation carriers. Am J Hum Genet. 2001, 68: 410-419. 10.1086/318181.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Thompson D, Easton D: Variation in BRCA1 cancer risks by mutation position. Cancer Epidemiol Biomarkers Prev. 2002, 11: 329-336.PubMedGoogle Scholar
  29. Lubinski J, Phelan CM, Ghadirian P, Lynch HT, Garber J, Weber B, Tung N, Horsman D, Isaacs C, Monteiro AN, Sun P, Narod SA: Cancer variation associated with the position of the mutation in the BRCA2 gene. Fam Cancer. 2004, 3: 1-10.View ArticlePubMedGoogle Scholar
  30. Lecarpentier J, Nogues C, Mouret-Fourme E, Stoppa-Lyonnet D, Lasset C, Caron O, Fricker JP, Gladieff L, Faivre L, Sobol H, Gesta P, Frenay M, Luporsi E, Coupier I, Lidereau R, Andrieu N: Variation in breast cancer risk with mutation position, smoking, alcohol, and chest X-ray history, in the French National BRCA1/2 carrier cohort (GENEPSO). Breast Cancer Res Treat. 2011, 130: 927-938. 10.1007/s10549-011-1655-3.View ArticlePubMedGoogle Scholar
  31. Risch HA, McLaughlin JR, Cole DE, Rosen B, Bradley L, Kwan E, Jack E, Vesprini DJ, Kuperstein G, Abrahamson JL, Fan I, Wong B, Narod SA: Prevalence and penetrance of germline BRCA1 and BRCA2 mutations in a population series of 649 women with ovarian cancer. Am J Hum Genet. 2001, 68: 700-710. 10.1086/318787.View ArticlePubMedPubMed CentralGoogle Scholar
  32. Risch HA, McLaughlin JR, Cole DE, Rosen B, Bradley L, Fan I, Tang J, Li S, Zhang S, Shaw PA, Narod SA: Population BRCA1 and BRCA2 mutation frequencies and cancer penetrances: a kin-cohort study in Ontario, Canada. J Natl Cancer Inst. 2006, 98: 1694-1706. 10.1093/jnci/djj465.View ArticlePubMedGoogle Scholar
  33. Evans DG, Shenton A, Woodward E, Lalloo F, Howell A, Maher ER: Penetrance estimates for BRCA1 and BRCA2 based on genetic testing in a Clinical Cancer Genetics service setting: risks of breast/ovarian cancer quoted should reflect the cancer burden in the family. BMC Cancer. 2008, 8: 155-10.1186/1471-2407-8-155.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Begg CB, Haile RW, Borg A, Malone KE, Concannon P, Thomas DC, Langholz B, Bernstein L, Olsen JH, Lynch CF, Anton-Culver H, Capanu M, Liang X, Hummer AJ, Sima C, Bernstein JL: Variation of breast cancer risk among BRCA1/2 carriers. JAMA. 2008, 299: 194-201. 10.1001/jama.2007.55-a.View ArticlePubMedPubMed CentralGoogle Scholar
  35. ENIGMA. (Evidence-based network for the interpretation of germline mutant alleles). [http://www.enigmaconsortium.org]
  36. Schouten JP, McElgunn CJ, Waaijer R, Zwijnenburg D, Diepvens F, Pals G: Relative quantification of 40 nucleic acid sequences by multiplex ligation-dependent probe amplification. Nucleic Acids Res. 2002, 30: e57-10.1093/nar/gnf056.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Casilli F, Di Rocco ZC, Gad S, Tournier I, Stoppa-Lyonnet D, Frebourg T, Tosi M: Rapid detection of novel BRCA1 rearrangements in high-risk breast-ovarian cancer families using multiplex PCR of short fluorescent fragments. Hum Mutat. 2002, 20: 218-226. 10.1002/humu.10108.View ArticlePubMedGoogle Scholar
  38. Barrois M, Bieche I, Mazoyer S, Champeme MH, Bressac-de Paillerets B, Lidereau R: Real-time PCR-based gene dosage assay for detecting BRCA1 rearrangements in breast-ovarian cancer families. Clin Genet. 2004, 65: 131-136. 10.1111/j.0009-9163.2004.00200.x.View ArticlePubMedGoogle Scholar
  39. Rouleau E, Lefol C, Bourdon V, Coulet F, Noguchi T, Soubrier F, Bieche I, Olschwang S, Sobol H, Lidereau R: Quantitative PCR high-resolution melting (qPCR-HRM) curve analysis, a new approach to simultaneously screen point mutations and large rearrangements: application to MLH1 germline mutations in Lynch syndrome. Hum Mutat. 2009, 30: 867-875. 10.1002/humu.20947.View ArticlePubMedGoogle Scholar
  40. Weber J, Miserere S, Champ J, Looten R, Stoppa-Lyonnet D, Viovy JL, Houdayer C: High-throughput simultaneous detection of point mutations and large-scale rearrangements by CE. Electrophoresis. 2007, 28: 4282-4288. 10.1002/elps.200700010.View ArticlePubMedGoogle Scholar
  41. Gad S, Aurias A, Puget N, Mairal A, Schurra C, Montagna M, Pages S, Caux V, Mazoyer S, Bensimon A, Stoppa-Lyonnet D: Color bar coding the BRCA1 gene on combed DNA: a useful strategy for detecting large gene rearrangements. Genes Chromosomes Cancer. 2001, 31: 75-84. 10.1002/gcc.1120.View ArticlePubMedGoogle Scholar
  42. Rouleau E, Lefol C, Tozlu S, Andrieu C, Guy C, Copigny F, Nogues C, Bieche I, Lidereau R: High-resolution oligonucleotide array-CGH applied to the detection and characterization of large rearrangements in the hereditary breast cancer gene BRCA1. Clin Genet. 2007, 72: 199-207. 10.1111/j.1399-0004.2007.00849.x.View ArticlePubMedGoogle Scholar
  43. Antoniou AC, Goldgar DE, Andrieu N, Chang-Claude J, Brohet R, Rookus MA, Easton DF: A weighted cohort approach for analysing factors modifying disease risks in carriers of high-risk susceptibility genes. Genet Epidemiol. 2005, 29: 1-11. 10.1002/gepi.20074.View ArticlePubMedGoogle Scholar
  44. Negri E, La Vecchia C, Bruzzi P, Dardanoni G, Decarli A, Palli D, Parazzini F, Rosselli del TM: Risk factors for breast cancer: pooled results from three Italian case-control studies. Am J Epidemiol. 1988, 128: 1207-1215.PubMedGoogle Scholar
  45. Kelsey JL, Gammon MD, John EM: Reproductive factors and breast cancer. Epidemiol Rev. 1993, 15: 36-47.PubMedGoogle Scholar
  46. Beral V, Reeves G: Childbearing, oral contraceptive use, and breast cancer. Lancet. 1993, 341: 1102-View ArticlePubMedGoogle Scholar
  47. Lambe M, Hsieh C, Trichopoulos D, Ekbom A, Pavia M, Adami HO: Transient increase in the risk of breast cancer after giving birth. N Engl J Med. 1994, 331: 5-9. 10.1056/NEJM199407073310102.View ArticlePubMedGoogle Scholar
  48. Antoniou AC, Shenton A, Maher ER, Watson E, Woodward E, Lalloo F, Easton DF, Evans DG: Parity and breast cancer risk among BRCA1 and BRCA2 mutation carriers. Breast Cancer Res. 2006, 8: R72-10.1186/bcr1630.View ArticlePubMedPubMed CentralGoogle Scholar
  49. Daling JR, Malone KE, Voigt LF, White E, Weiss NS: Risk of breast cancer among young women: relationship to induced abortion. J Natl Cancer Inst. 1994, 86: 1584-1592. 10.1093/jnci/86.21.1584.View ArticlePubMedGoogle Scholar
  50. Andrieu N, Duffy SW, Rohan TE, Le MG, Luporsi E, Gerber M, Renaud R, Zaridze DG, Lifanova Y, Day NE: Familial risk, abortion and their interactive effect on the risk of breast cancer--a combined analysis of six case-control studies. Br J Cancer. 1995, 72: 744-751. 10.1038/bjc.1995.404.View ArticlePubMedPubMed CentralGoogle Scholar
  51. Rookus MA, Van Leeuwen FE: Induced abortion and risk for breast cancer: reporting (recall) bias in a Dutch case-control study. J Natl Cancer Inst. 1996, 88: 1759-1764. 10.1093/jnci/88.23.1759.View ArticlePubMedGoogle Scholar
  52. Russo J, Tay LK, Russo IH: Differentiation of the mammary gland and susceptibility to carcinogenesis. Breast Cancer Res Treat. 1982, 2: 5-73. 10.1007/BF01805718.View ArticlePubMedGoogle Scholar
  53. Vatten LJ, Romundstad PR, Trichopoulos D, Skjaerven R: Pregnancy related protection against breast cancer depends on length of gestation. Br J Cancer. 2002, 87: 289-290. 10.1038/sj.bjc.6600453.View ArticlePubMedPubMed CentralGoogle Scholar
  54. Fan S, Ma YX, Wang C, Yuan RQ, Meng Q, Wang JA, Erdos M, Goldberg ID, Webb P, Kushner PJ, Pestell RG, Rosen EM: Role of direct interaction in BRCA1 inhibition of estrogen receptor activity. Oncogene. 2001, 20: 77-87. 10.1038/sj.onc.1204073.View ArticlePubMedGoogle Scholar
  55. Razandi M, Pedram A, Rosen EM, Levin ER: BRCA1 inhibits membrane estrogen and growth factor receptor signaling to cell proliferation in breast cancer. Mol Cell Biol. 2004, 24: 5900-5913. 10.1128/MCB.24.13.5900-5913.2004.View ArticlePubMedPubMed CentralGoogle Scholar
  56. Cabanes A, Wang M, Olivo S, DeAssis S, Gustafsson JA, Khan G, Hilakivi-Clarke L: Prepubertal estradiol and genistein exposures up-regulate BRCA1 mRNA and reduce mammary tumorigenesis. Carcinogenesis. 2004, 25: 741-748.View ArticlePubMedGoogle Scholar
  57. Ma H, Wang Y, Sullivan-Halley J, Weiss L, Marchbanks PA, Spirtas R, Ursin G, Burkman RT, Simon MS, Malone KE, Strom BL, McDonald JA, Press MF, Bernstein L: Use of four biomarkers to evaluate the risk of breast cancer subtypes in the women's contraceptive and reproductive experiences study. Cancer Res. 2010, 70: 575-587. 10.1158/0008-5472.CAN-09-3460.View ArticlePubMedPubMed CentralGoogle Scholar

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