Genetics of Breast and Ovarian Cancer Genetics of Breast and Ovarian Cancer
Source: National Cancer Institute
Women with a previous primary breast cancer have a 3-fold to 4-fold increase in risk of a second breast cancer in the contralateral breast. Most studies report an annual risk of development of a second breast cancer of 0.5% to 0.7%. While the risk of contralateral breast cancer persists for up to 30 years after the original diagnosis, the median interval between primary breast cancer and contralateral disease is approximately 4 years.
Although risk is similar following invasive and in situ ductal cancer, it is higher for women with a family history of breast cancer, and for those with a lobular histology in the original cancer. Lobular carcinoma in situ (LCIS), which is often an incidental finding in breast biopsies, is associated with an increased risk of subsequent invasive cancer. Long-term follow-up studies of women diagnosed with LCIS report relative risks of developing breast cancer ranging from 7 to 12. Risks are higher for women diagnosed at a younger age, and for those with a family history of breast cancer. Subsequent breast cancers are most often of ductal histology, and occur equally in either breast, suggesting that LCIS is a marker of risk rather than a precancerous lesion itself.
Other risk factors, including those that are only weakly associated with breast cancer and those that have been inconsistently associated with the disease in epidemiologic studies (e.g., cigarette smoking), may be important in subgroups of women defined according to genotype. For example, some studies have suggested that certain N-acetyl transferase alleles may influence female smokers’ risk of developing breast cancer. This possible gene-environment interaction has varied in some reported studies according to whether the breast cancers occurred premenopausally or postmenopausally. The clinical significance of these emerging findings remains to be defined.
Ethnicity has been inconsistently associated with breast cancer in earlier studies that did not examine associations with genetic mutations or polymorphisms. Even when associations with ethnic factors have been identified, the magnitude of the associations has often been modest. Such inconsistently identified, weak associations with ethnicity may well have been due to uncontrolled confounding by reproductive factors and other established risk factors for breast cancer, rather than to genetic factors such as specific mutations of BRCA1 and BRCA2 breast cancer genes that are now known to occur with increased frequency in certain populations due to founder effects. Nevertheless, the use of genetic markers in epidemiologic studies may help to clarify associations with purported risk factors for breast cancer where the causality of the associations or biologic mechanisms are uncertain.
Other Risk Factors for Ovarian Cancer
Other risk factors for ovarian cancer include age, demographics, and reproductive and surgical history. (Refer to the PDQ summary on Prevention of Ovarian Cancer for more information.) Relatively few studies have addressed the effect of these risk factors in women who are genetically susceptible to ovarian cancer.
Risk for ovarian cancer increases as a woman gets older. Before age 30 years, the risk of developing ovarian cancer is remote; even in hereditary cancer families, epithelial ovarian cancer is virtually nonexistent before age 20 years. Ovarian cancer incidence rises in a linear fashion from age 30 years to age 50 years and continues to increase, although at a slower rate, thereafter. The highest incidence is found in the eighth decade of life, with a rate of 57 cases per 100,000 women aged 75 to 79 years, compared with 16 cases per 100,000 women aged 40 to 44 years.
Ovarian cancer incidence varies significantly depending on country of birth, and ranges from a high of 14.9 cases per 100,000 women in Sweden to a low of 2.7 cases per 100,000 women in Japan. Incidence in the United States is 13.3 cases per 100,000 women. Immigration appears to alter the risk to match that of the host country. Offspring of Japanese immigrants to the United States have an increased risk of developing ovarian cancer that approaches the rate among women born in the United States, indicating a possible role for dietary and environmental factors.
Nulliparity is associated with an increased risk of ovarian cancer. Risk may also be increased among women who have used fertility drugs, especially those who remain nulligravid. A small subset from a large retrospective cohort study did not confirm a strong link between infertility drugs and ovarian cancer risk. Evidence is growing that the use of menopausal hormone replacement therapy is associated with an increased risk of ovarian cancer, particularly in long-time users and users of sequential estrogen-progesterone schedules.[72,73] In a prospective study of 329 incident ovarian cancer cases in the Breast Cancer Detection Demonstration Project, use of estrogen only was associated with a significant 60% increased risk of ovarian cancer, and the risk increased with increasing duration of use. In the WHI, 38 incident ovarian cancers were identified, and the hazard ratio for those taking estrogen plus progestin was 1.6 (95% CI 0.8-3.2) compared with the placebo group. No data exist regarding risk either in those with a family history of breast or ovarian cancer or in BRCA1/2 mutation carriers. Data on the role of age at menarche and age at menopause are inconsistent.
Bilateral tubal ligation and hysterectomy have also been reported to be associated with reduced ovarian cancer risk.[70,76,77] A retrospective study and a prospective study have reported a >90% reduction in risk of ovarian cancer in women with documented BRCA1 or BRCA2 mutations who chose prophylactic oophorectomy. In this same population, prophylactic removal of the ovaries also resulted in a nearly 50% reduction in the risk of subsequent breast cancer.[78,79] For further information on these studies refer to the Ovarian Ablation section of this summary.
Models for Prediction of Breast Cancer Risk
Models to predict an individual’s lifetime risk for developing breast cancer are available. In addition, models exist to predict an individual’s likelihood of having a BRCA1 or BRCA2 mutation. Not all models can be appropriately applied for all patients. Each model is appropriate only when the patient’s characteristics and family history are similar to the study population on which the model was based. The table, Characteristics of the Gail and Claus Models, summarizes the salient aspects of the risk assessment models and is designed to aid in choosing the one that best applies to a particular individual.
Two models for predicting breast cancer risk, the Claus model  and the Gail model, are widely used in research studies and clinical counseling. Both have limitations, and the risk estimates derived from the 2 models may differ for an individual patient. These models, however, represent the best methods currently available for individual risk assessment.
It is important to note that these models will significantly underestimate breast cancer risk for women in families with hereditary breast cancer susceptibility syndromes. In those cases, Mendelian risks would apply. A 3-generation cancer family history is taken before applying any model. (Refer to the PDQ summary on Elements of Cancer Genetics Risk Assessment and Counseling for more information on Taking a Family History.) Generally, the Claus or Gail models should not be used for families with 1 of the following characteristics:
Three individuals with breast or ovarian cancer (especially when 1 or more breast cancers are diagnosed before age 50 years).
A woman who has both breast and ovarian cancer.
Ashkenazi Jewish ancestry with at least 1 case of breast or ovarian cancer (as these families are more likely to have a hereditary cancer susceptibility syndrome).
Characteristics of the Gail and Claus Models*
Enlarge Table Gail Model Claus Model
*Adapted from Domcheck et al., Rubenstein et al., and Rhodes.
Data derived from Breast Cancer Detection Demonstration Project (BCDDP) Study Cancer and Steroid Hormone (CASH) Study
Study population 2,852 cases, age ≥35 years 4,730 cases, age 20-54 years
In situ and invasive cancer Invasive cancer
3,146 controls 4,688 controls
Annual screening Not routinely screened
Family history characteristics First-degree relatives with breast cancer First-degree or second-degree relatives with breast cancer
Age of onset in relatives
Other characteristics Current age Current age
Age at menarche
Age at first live birth
Number of breast biopsies
Atypical hyperplasia in breast biopsy
Race (included in the most current version of the Gail model)
Strengths Incorporates: Incorporates:
Risk factors other than family history Paternal as well as maternal history
Age of onset of breast cancer
Family history of ovarian cancer
Limitations Underestimates risk in hereditary families May underestimate risk in hereditary families
Number of breast biopsies without atypical hyperplasia may cause inflated risk estimates May not be applicable to all combinations of affected relatives
Does not include risk factors other than family history
Does not incorporate:
Paternal family history of breast cancer or any family history of ovarian cancer
Age of onset of breast cancer in relatives
All known risk factors for breast cancer 
Best application For individuals with no family history of breast cancer or 1 first-degree relative with breast cancer at ≥age 50 years For individuals with 0, 1, or 2 first-degree or second-degree relatives with breast cancer
For determining eligibility for chemoprevention studies
The Gail model has been found to be reasonably accurate at predicting breast cancer risk in large groups of white women who undergo annual screening mammography.[83-87] While the model is reliable in predicting the number of breast cancer cases expected in a group of women from the same age-risk strata, it is less reliable in predicting risk for individual patients. Risk can be overestimated in:
Noncompliant women (i.e., not compliant with screening).[83,84]
Women in the highest risk strata.
Risk could be underestimated in the lowest risk strata. Earlier studies [83,84] suggested risk was overpredicted in younger women and underpredicted in older women. More recent studies [85,86] using the modified Gail model (which is currently used) found it performed well in all age groups. Further studies are needed to establish the validity of the Gail model in minority populations.
A study of 491 women aged 18 to 74 years with a family history of breast cancer compared the most recent Gail model and the Claus model in predicting breast cancer risk. The 2 models were positively correlated ®=.55). The Gail model estimates were higher than the Claus model estimates for most participants. Presentation and discussion of both the Gail and Claus models risk estimates may be useful in the counseling setting.
The Gail model is the basis for the Breast Cancer Risk Assessment Tool, a computer program that is available from the NCI by calling the Cancer Information Service at 1-800-4-CANCER (1-800-422-6237, or TTY at 1-800-332-8615). This version of the Gail Model estimates only the risk of invasive breast cancer.
American Cancer Society.: Cancer Facts and Figures 2004. Atlanta, Ga: American Cancer Society, 2004. Also available online. Last accessed September 27, 2004.
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