Most cases of breast cancer
are not hereditary.

The majority of breast cancer occurs in women who are over 50, with little to no family history of cancer. Identifying patients who are most at risk for sporadic breast cancer can lead to effective interventions, like risk-reducing medications, and enhanced screening protocols.

GeneType for Breast Cancer evaluates the genomic risk of developing breast cancer for women aged 35 or older who do not have a known pathogenic gene variant. This is the majority of women.

* Pathogenic variants include those in moderate and high penetrant genes,
including but not limited to ATM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, PALB2, PTEN, TP53

Polygenic risk identifies
patients at risk of disease.

In sporadic breast cancer, no single gene mutation is causal of disease. Rather, common DNA variations, called single nucleotide polymorphisms (SNPs), each contribute a small but measurable risk of developing disease. GeneType for Breast Cancer analyzes your patient’s DNA for 70+ SNPs that have been clinically validated in their association with breast cancer. By combining the effects of all of these SNPs into a single polygenic risk score (PRS), GeneType for Breast Cancer provides a superior risk stratification over standard risk assessments that incorporate only clinical factors.

Your Patient’s Personalized
Risk Assessment.

The comprehensive risk stratification will help you understand the likelihood your patient will develop sporadic breast cancer over a five-year period and in her lifetime.

Average Risk

A breast health plan may include regularly scheduled mammograms and breast self-awareness.

View sample report

Increased Risk

A breast health plan may include increased screening frequency, alternative screening options like MRI, increased clinical encounters and options for risk reducing medications. Risk reducing medications have been shown to decrease breast cancer incidence by upwards of 50% in at-risk women.

View sample report

Breast cancer is a multifactorial disease.

Many risk factors, including polygenic risk, family history, age and other clinical factors affect your patient’s risk for developing sporadic breast cancer.

GeneType for Breast Cancer incorporates all of these risk factors to provide you with a truly personalized risk assessment for your patient.

The GeneType for Breast Cancer risk assessment model

Standard risk assessment models calculate a patient’s risk for breast cancer based on family history and clinical factors. GeneType for Breast Cancer is a next generation risk assessment that further stratifies risk with the addition of mammographic density and a polygenic risk score.

Polygenic Risk

We analyze your patient’s DNA for 70+ single nucleotide polymorphisms (SNPs) that have been clinically validated for their association with breast cancer. In sporadic cancer, no single gene mutation is causal of disease. Rather, many individual SNPs contribute a small, but measurable risk of developing disease. The risks associated with each of the SNPs in the test are combined into a single polygenic risk score (PRS) for your patient.

Breast Density

Breast density is associated with an increased breast cancer risk because it can act as a “mask” in a mammogram image, causing a lesion to go undetected. In addition, the cellular composition of dense breast tissue may provide a conducive microenvironment for tumor growth. Make sure you have access to your patient’s Bi-Rad score or density percentage from her mammogram results when you order GeneType for Breast Cancer.

Family History

Although 85% percent of women diagnosed with breast cancer do not have a significant family history of the disease, family history is still an important part of a sporadic breast cancer risk assessment. GeneType for Breast Cancer incorporates both first and second degree relatives with breast cancer into your patients’ risk score.


GeneType for Breast Cancer is clinically validated for women 35 years of age or older.


GeneType for Breast Cancer is fully validated for Caucasian women. The risk model incorporates ethnicity-specific polygenic risk scores and population incidence data for patients of African American and Hispanic American descent derived from the Surveillance, Epidemiology, and End Results Program (SEER), however, the model has not been validated in these populations as yet. Currently, we cannot provide testing for other ethnicities. We will provide updates as we continuously improve our test and add fully validated models for additional ethnicities.

Menopausal status

Later age at menopause is associated with a higher risk for breast cancer.

Height and weight

BMI is a risk factor for breast cancer.

Additional Risk Factors

The following breast cancer risk factors are not included in GeneType for Breast Cancer, but are worth discussing with your patient:

  • Menarche: Earlier age at menarche is a risk factor.
  • Parity: Age at first live birth, multiparous status and breast feeding all influence risk.
  • Contraceptives/hormone replacement therapy: Hormone use poses a minor risk, depending on type and duration of hormone.
  • Biopsies: Previous breast biopsy history can increase risk of breast cancer. The variation of increased risk ranges from modest in non-proliferative lesions to significant in lesions with atypia.

GeneType for Breast Cancer identifies a woman’s risk of breast cancer by combining clinical risk with an analysis of specific genetic markers to provide a clinically validated risk stratification for women 35 and older.

The three most significant factors that define sporadic breast cancer risk are family history, breast density and polygenic risk.

women aged
35 or older

Who is a candidate
for testing?

  • Caucasian, African American or Hispanic women.
  • Women with or without a family history of breast cancer.
  • Women with no personal diagnosis of breast cancer or benign tumors (LCIS/DCIS)
  • Women with no known pathogenic variants* or genetic syndromes associated with breast cancer.

* Including, not limited to: ATM, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, FANCC, MRE11A, NBN, NF1, PALB2, PTEN, RAD50, RAD51C, RAD51D, STK11, TP53

Personalized Breast
Health Plans.

While guidelines for screening and prevention vary between medical bodies, GeneType for Breast Cancer can help you and your patient develop a personalized breast health plan.

For more information on breast health options for patients in each risk stratification, please see the recommendations from ACS, USPSTF, ASCO and NCCN.

Disclaimer: GeneType for Breast Cancer is not a diagnostic test. Results will not indicate whether your patient has breast cancer today or whether she definitely will or will not develop breast cancer in the future.

Everything you need is in the box.

GeneType for Breast Cancer is easy to integrate into a well-woman consultation.

The test is conducted at our CLIA certified laboratory
and results are delivered to you for discussion with your patient.

  • 1.
    Complete the Test Requisition
    Form and ask your patient to
    sign the consent form for your
  • 2.
    Swab your patient’s
    cheek and label
    the sample.
  • 3.
    Enclose the sample, along
    with the Test Requisition
    Form, in the pre-paid
    envelope provided and
    mail it to GeneType.


GeneType for Breast Cancer is a patient self-pay test. A credit card authorization form will be included in the test kit that list the payment options.

If you would like to
keep GeneType test
kits on hand at your
practice, please contact
our support team.

When to Rescreen

Risk assessment scores are dynamic over time. While your patient’s polygenic risk score will not change (until more disease-associated SNPs are discovered), some risk factors will change. Your patient’s age, for example, will always alter her risk score to some degree.

If your patient experiences a significant change in any of her risk factors, such as breast density or menopausal status, or if she has new information about her family history, we suggest a reassessment of her absolute risk.

You can also consider re-evaluating your patient every five years to ensure that she is receiving the optimal breast screening and prevention care. We have a program designed for re-evaluation of patient risk scores. Please contact us at for more information

Our Science.


The bottom line.

Our risk assessment model improves on current clinical models by streamlining the test to accommodate clinical practice without losing discriminatory power. GeneType for Breast Cancer does this by integrating the three most impactful breast cancer risk factors: polygenic risk, breast density and family history in combination with other clinical risk factors.

The history behind Polygenic Risk

Polygenic risk was enabled by large data generated in genome-wide association studies (GWAS). Large datasets comparing women with breast cancer to women without breast cancer have allowed for the isolation of otherwise common DNA markers, i.e. single nucleotide polymorphisms (SNPs) that show statistically significant association within the case/control datasets. A list of relevant peer-reviewed publications can be found below.

Improving on clinical risk assessment models

Clinical breast cancer risk assessment models have been used to identify women at increased risk of breast cancer for over 30 years. The breast cancer risk assessment test (BRCAT, or Gail) model was developed by Gail and used to identify women who participated in breast cancer risk reducing medication trials. Models like IBIS (Tyrer-Cuzick) were developed to assess a woman’s risk of breast cancer, but also her risk of carrying a mutation (pathogenic variant) in a high-risk gene such as BRCA1. Our goal as a research community is to continuously improve upon the accuracy of these risk assessment models. A list of relevant peer-reviewed publications can be found below.

Provider Resource Library.

GeneType for Breast Cancer Posters/Publications/Whitepapers
  • Dite GS, Mahmoodi M, Bickerstaffe A, et al: Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model. Breast Cancer Res Treat 139:887-896, 2013
  • Dite GS, MacInnis RJ, Bickerstaffe A, et al: Breast cancer risk prediction using clinical models and 77 independent risk-associated SNPs for women aged under 50 years: Australian breast cancer family registry. Cancer Epidemiol Biomarkers Prev 25:359-365, 2016
  • Allman R, Dite GS, Hopper JL, et al: SNPs and breast cancer risk prediction for african american and hispanic women. Breast Cancer Res Treat 154:583-589, 2015
  • Spaeth E, Starlard-Davenport A, Allman R: Bridging the data gap in breast cancer risk assessment to enable widespread clinical implementation across the multiethnic landscape of the US. J Cancer Treatment Diagn 2:1-6, 2018
  • White Paper – GeneType for Breast Cancer 2019
PRS Publications
  • Easton DF, Pooley KA, Dunning AM, et al: Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 447:1087-1093, 2007
  • Mealiffe ME, Stokowski RP, Rhees BK, et al: Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information. J Natl Cancer Inst 102:1618-1627, 2010
  • Mavaddat N, Pharoah PD, Michailidou K, et al: Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst 107:10.1093/jnci/djv036. Print 2015 May, 2015
  • Vachon CM, Pankratz VS, Scott CG, et al: The contributions of breast density and common genetic variation to breast cancer risk. J Natl Cancer Inst 107:10.1093/jnci/dju397. Print 2015 May, 2015
  • Cuzick J, Brentnall AR, Segal C, et al: Impact of a panel of 88 single nucleotide polymorphisms on the risk of breast cancer in high-risk women: Results from two randomized tamoxifen prevention trials. J Clin Oncol 35:743-750, 2017
  • Mavaddat N, Michailidou K, Dennis J, et al: Polygenic risk scores for prediction of breast cancer and breast cancer subtypes. Am J Hum Genet 104:21-34, 2019
  • Rudolph A, Song M, Brook MN, et al: Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the breast cancer association consortium. Int J Epidemiol 47:526-536, 2018
  • Kuchenbaecker KB, McGuffog L, Barrowdale D, et al: Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers. J Natl Cancer Inst 109:10.1093/jnci/djw302, 2017
  • Evans DGR, Harkness EF, Brentnall AR, et al: Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants. Breast Cancer Res Treat, 2019
  • Starlard-Davenport A, Allman R, Dite GS, et al: Validation of a genetic risk score for arkansas women of color. PLoS One 13:e0204834, 2018
Breast Cancer Screening and Prevention Publications
  • Freedman AN, Graubard BI, Rao SR, et al: Estimates of the number of US women who could benefit from tamoxifen for breast cancer chemoprevention. J Natl Cancer Inst 95:526-532, 2003
  • Fisher B, Costantino JP, Wickerham DL, et al: Tamoxifen for the prevention of breast cancer: Current status of the national surgical adjuvant breast and bowel project P-1 study. J Natl Cancer Inst 97:1652-1662, 2005
  • Vogel VG: The NSABP study of tamoxifen and raloxifene (STAR) trial. Expert review of anticancer therapy 9:51-60, 2009 • Cuzick J, Sestak I, Forbes JF, et al: Anastrozole for prevention of breast cancer in high-risk postmenopausal women (IBIS-II): An international, double-blind, randomised placebo-controlled trial. Lancet 383:1041-1048, 2014
  • Maunsell E, Goss PE, Chlebowski RT, et al: Quality of life in MAP.3 (mammary prevention 3): A randomized, placebo-controlled trial evaluating exemestane for prevention of breast cancer. J Clin Oncol 32:1427-1436, 2014
  • Pruthi S, Heisey RE, Bevers TB: Chemoprevention for breast cancer. Ann Surg Oncol 22:3230-3235, 2015
  • Hum S, Wu M, Pruthi S, et al: Physician and patient barriers to breast cancer preventive therapy. Curr Breast Cancer Rep 8:158-164, 2016
  • Esserman LJ, WISDOM Study and Athena Investigators: The WISDOM study: Breaking the deadlock in the breast cancer screening debate. NPJ Breast Cancer 3:34-017-0035-5. eCollection 2017, 2017
  • Rainey L, van der Waal D, Jervaeus A, et al: Are we ready for the challenge of implementing risk-based breast cancer screening and primary prevention? Breast 39:24-32, 2018 • Evans DG, Howell SJ, Howell A: Personalized prevention in high risk individuals: Managing hormones and beyond. Breast, 2018
  • Kehm RD, Hopper JL, John EM, et al: 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. Breast Cancer Research 21:52, 2019
  • Tchou J, et al. Acceptance of tamoxifen chemoprevention by physicians and women at risk. Cancer. 2004 May 1;100(9):1800-6.
  • Blakeslee et al. Deciding on breast cancer risk reduction: The role of counseling in individual decision-making – A qualitative study. Patient Educ Couns. 2017 Dec;100(12):2346-2354.