- Open Access
- Open Peer Review
Hereditary cancer risk assessment: essential tools for a better approach
© Gomy and Estevez Diz; licensee BioMed Central Ltd. 2013
- Received: 26 June 2013
- Accepted: 21 October 2013
- Published: 28 October 2013
Hereditary cancer risk assessment (HCRA) is a multidisciplinary process of estimating probabilities of germline mutations in cancer susceptibility genes and assessing empiric risks of cancer, based on personal and family history. It includes genetic counseling, testing and management of at-risk individuals so that they can make well-informed choices about cancer surveillance, surgical treatment and chemopreventive measures, including biomolecular cancer therapies. Providing patients and family members with an appropriate HCRA will contribute to a better process of making decisions about their personal and family risks of cancer. Following individuals at high risk through screening protocols, reassuring those at low risk, and referring those at increased risk of hereditary cancer to a cancer genetics center may be the best suitable approach of HCRA.
- Genetic testing
- Hereditary cancer
Within the last decade, emerging biomolecular technologies, such as whole-exome and genome sequencing and high-throughput genotyping have been rapidly growing and enlightening the knowledge of inherited cancer susceptibility. Meanwhile, important issues on bench-to-bedside translation of these major breakthroughs into clinical practice have been equally addressed. Nevertheless, one essential component of these aspects includes the counseling of individuals with hereditary cancer risk. The increased public awareness of the genetic aspects of cancer susceptibility has resulted in more enquiries from clinical and surgical oncologists about which would be the best approach for their patients so that appropriate management could be provided.
Hereditary cancer syndromes
Hereditary breast and/or ovarian cancer
MMR cancer syndrome
Familial adenomatous polyposis
Polymerase proofreading-associated polyposis
FANC genes (includes BRCA2, PALB2, BRIP1)
Li-Fraumeni like syndrome
Hereditary diffuse gastric cancer
Diffuse gastric cancer
Lobular Breast cancer
Giant cell astrocytoma
Von Hippel-Lindau syndrome
Renal cell cancer
Renal cell cancer
Papillary renal cancer syndromes
Renal cell cancer
SDH (A, B, C, D)
Multiple Endocrine Neoplasia1
Multiple Endocrine Neoplasia2
Medular thyroid cancer
This review aims to describe a high-quality approach of delivering hereditary cancer risk assessment (HCRA) within a multidisciplinary context.
In addition to age, a positive family history of cancer is the single most important constitutional risk factor for which early recognition and intervention could be lifesaving.
Possible indications of referrals for hereditary cancer risk assessment
Early onset of cancer diagnosis (e.g. breast cancer < 45 years, colorectal cancer < 50 years)
Three close relatives (same side) with cancer of the same or syndromically related type (breast/ovary, colorectal/endometrium)
Multiple associated primary cancers: breast/ovary, colorectal/endometrium
Two close relatives (same side) with cancer of the same or related type with at least one affected under 50 years
Male breast cancer
One first-degree relative with early onset cancer (breast < 45 years, colorectal < 50 years)
Ovarian, fallopian tube, primary peritoneal cancer
One first-degree relative with multiple primary cancers
Breast cancer and thyroid, sarcoma, adrenocortical carcinoma
Two or more relatives with uncommon cancers (sarcoma, glioma, hemangioblastoma, etc.)
Multiple colon polyps (>10 cumulative)
Relatives of patients with known BRCA, APC, MUTYH, mismatch repair mutations
Colorectal or endometrial cancer with microsattelite instability and/or lack of expression of mismatch repair protein(s) by immunohistochemistry
Many relatives with cancer but no criteria for testing are fulfilled
The genetic risk assessment of an individual with cancer is based upon the careful analysis of the personal history, detailed family history and physical examination when appropriate. It requires confirmation of the diagnosis in affected relatives, preferably through biopsies or, whenever possible, death certificates or autopsies.
Family pedigrees drawings with at least three generations in both sides of family;
Patients and relatives:
Current age, age at diagnosis, age at death, primary site, pathologic features, treatments;
Ancestry (especially if Ashkenazi Jewish);
Previous surgeries, biopsies, diseases;
Endogenous risk factors: age at menarche, fertility history;
Exogenous risk factors: tobacco/alcohol use, food intake, hormones, exercises;
Cancer screening: mammography, gastrointestinal endoscopy, PSA;
Physical examination (when appropriate): skin, head circumference, tongue, oral mucosa, thyroid, hands and feet, abdomen;
Psychosocial and family dynamic;
Basic principles of cancer genetics;
Mutation probabilities and empiric risks;
Pre-test genetic counseling:
Indentify the best individuals to test;
Prioritize order of testing (germline, tumor);
Explain test techniques, limitations, sensitivity/specificity;
Facilitate informed consent: possible outcomes (positive, true-negative, uninformative), costs, turn-around-time, insurance coverage;
Address psychological, ethical, cultural, communication issues.
Post-test genetic counseling:
Disclosure and interpretation of results;
Address psychological and ethical concerns;
Identify at-risk family members;
Discuss communication of results to at-risk family members.
Personalized risk management strategies:
Risk reduction, cancer prevention (surgeries, chemoprevention);
Empiric strategies for uninformative results.
Several models are available to estimate the likelihood of detecting a mutation in a cancer-susceptibility gene and each model is utilized selectively based on the characteristics of the patient’s personal and family history.
If a mutation in the BRCA gene is suspected to be present in a hereditary breast and ovarian cancer family, there are several models available to predict the probability of an individual carrying such a mutation. These models include the Couch , Penn II , Myriad , BRCAPRO [9–11], Tyrer-Cuzick , and BOADICEA models . Such models incorporate breast and ovarian cancer in first- and second-degree relatives, age of onset of cancer, Ashkenazi Jewish ancestry, and some are starting to incorporate other ethnic backgrounds.
There are similar models for predicting mutation in DNA mismatch repair (MMR) genes in suspected Lynch syndrome families, including Wijnen , MMRpro , MMRpredict , and PREMM1,2,6 . However, in the HCRA of colon cancer families, it is more common to use established criteria as an indication for testing, including the Amsterdam I and II , or the revised Bethesda Guidelines , which determine eligibility for tumor analysis to detect microsatellite instability that would aid to guide genetic testing of the MMR genes.
Clinical criteria guidelines and mutation probability models utilized for HCRA
Clinical criteria/tumors included*
Hereditary breast and ovarian cancer
Couch, Penn II, Myriad, Tyrer-Cuzick, BRCAPRO, BOADICEA
Breast cancer (age<45, two primaries, male)
Family history (one side)
Wijnen, MMRpro, MMRPredict, PREMM1,2,6
Amsterdam I and II
Li-Fraumeni and Li-Fraumeni like
International Cowden Consortium
Thyroid, oral papillomas, acral keratoses, skin lipomas, trichilemmomas, uterine leiomyomas, gastrointestinal polyps, dysplastic cerebellar gangliocytoma, fibrocystic breast disease
The use of mutation predictability models is important for several reasons. First, calculating the likelihood of a germline mutation can help clinicians determine which family member is the best candidate for testing. Second, due to the high cost of genetic testing, numerical calculations of mutation probability may provide supportive evidence for insurance companies. Third, for psychosocial reasons, patients who are informed with a numerical estimation of a mutation may have more realistic expectations about the possibility of a positive result. Finally, for worried patients with a low probability of carrying a mutation, and for those with mutations without any influence in gene expression or stability, numerical presentations may provide substantial reassurance regarding screening guidelines based on empiric cancer risks. A recent study highlighted possible health benefits and the cost-effectiveness of primary genetic screening for Lynch syndrome in the general population .
Nevertheless, several models may underestimate mutation probability in certain situations such as a limited family structure or specific tumor characteristics . Thus, probabilities predicted by a model must be interpreted in the context of an individual’s personal and family history. The National Comprehensive Cancer Network (NCCN) in USA publishes guidelines annually in order to help clinicians to select which patients are appropriate candidates for either genetic referral or genetic testing [27, 28].
In the absence of an identified gene mutation, counseling unaffected individuals about their empiric risk of cancer requires careful consideration of the patient’s personal and family history.
Most risk estimates for cancer development are empirical, based on the probability of a genetic component in the individual, and this risk estimate increases if the proband has several affected relatives on the same side of family with the same or related cancers, multiple or early onset cancers, or if the individual has clinical features of a hereditary cancer syndrome .
For breast cancer, there are several models that estimate empiric risks, including the Gail , Claus , BRCAPRO [9–11], Tyrer-Cuzick  and BOADICEA  models. All of these models incorporate first-degree relatives with breast cancer along with hormone risk factors, although they may vary in which known breast cancer risk factors are incorporated. There are also some published tools available to assess risks for colon, ovarian, lung and melanoma, but few are validated . However, for prostate cancer, whose familial risk is known to be associated with dozens of low-penetrant variants , there is not a genetic model so far. Predictability based on the number of affected relatives, degree of consanguinity and also ancestry could be calculated by mathematical models to estimate empiric risks and possibly guide recommendations for appropriate screening. The undergoing discovery of functional alleles reinforces the need for new models to incorporate them better address cancer risk assessment.
Moreover, because those models that convert genotypes into absolute risks are empirically derived, prospective research is needed to confirm the accuracy of these predictions and evaluate the effectiveness of interventions based on individual genetic testing. For instance, the National Institute for Health and Care Excellence (NICE) in the United Kingdom recently released guidelines concerning risk assessment and management of familial breast cancer, even when testing is not performed .
How should risks be communicated? They can be given as cancer risk per year, or before a certain age, or within a decade, or as an overall lifetime risk in comparison with the population risk in terms of relative risks. The individual perception of cancer risk should be assessed, as should its possible effects on the health and lifestyle behaviors.
After establishing risks of identifying a pathogenic germline mutation in a family and indicating the best candidates to be tested, it follows the information process of pre-test genetic counseling, which requires informed consent for testing for a mutation in a cancer susceptibility gene (see list below). It explains the eventual limitations of testing, its possible results, the emotional impact that may arise, and its relevance for employment and insurance. This approach must be nondirective, letting patients make their own decisions after knowing all possible scenarios . In some circumstances, a pathogenic mutation will not be identified but genetic variants with unknown clinical significance, requiring further testing and reclassification. When a known deleterious mutation is detected in a family member, and when the affected individual agrees to release his/her results to the family, predictive testing can be offered to at-risk relatives. Predictive testing often requires two pre-test counseling interviews with up to three months between them, when family, emotional, employment and insurance issues are discussed, as well inheritance and penetrance of the mutation are explained. Screening and preventive options should also be discussed and it must be stressed that no surveillance guideline is flawless, so individuals must bear in mind that abnormal symptoms should never be ignored between screening exams .
Basic elements of informed consent for testing cancer susceptibility genes
information on the specific mutation(s) being tested, including whether the range of risk associated with the variant will impact medical care;
implications of a positive and negative result;
possibility that the test will not be informative;
options for risk estimation without genetic testing;
risk of passing a genetic variant to children;
technical accuracy of the test including where required by law, licensure of the laboratory;
fees involved in testing and counselling;
psychological implications of test results (benefits and risks);
risks and protections against genetic discrimination by employers or insurers;
confidentiality issues, including policies related to privacy and data security;
possible use of DNA testing samples in future research;
options and limitations of medical surveillance and strategies for prevention after genetic testing;
importance of sharing genetic test results with at-risk relatives so that they may benefit from this information;
plans for follow-up after testing.
When an affected or unaffected patient chooses to undergo testing, post-test counseling helps individuals to interpret and understand their results, whether positive, negative, undetermined or inconclusive. Psychological support may be provided as ambiguity and uncertainty may arise . For example, individuals with a low-risk result may suffer from “the survivor guilt”. High-risk individuals may need to explain positive results to their at-risk closest relatives and counselors (or geneticists) can help sharing this information. It should be emphasized that individuals who have had cancer may be psychologically affected and feel guilty by knowing their pathogenic germline mutation may be passed on through their offspring. In addition, since early diagnosis of cancer improves outcome, a clear protocol for surveillance and possible prophylactic measures must be offered to those at greater risks, even if they refuse or could not afford genetic testing. For example, risk-reducing bilateral mastectomy when treating unilateral breast cancer in a BRCA1/BRCA2 mutation carrier or hysterectomy and bilateral salpingo-ooforectomy in a MSH6 mutation carrier. However, the application of such a system requires robust audit of outcomes, both related to cancer morbidity and mortality, and of psychological effects. Establishing a threshold level of risk at which to offer screening is needed in order to assess outcome. Those at moderately increased risk must engage in surveillance strategies whose specificity, sensitivity and cost-effectiveness should be addressed in the long term .
Very recently, the American College of Medical Genetics and Genomics (ACMG) published a policy statement on recommendations for reporting incidental findings–those not related to the primary indication for testing but with potential medical utility–in clinical exome and genome sequencing. This working group presented a “minimum list” of Mendelian disorders for which any known pathogenic and expected pathogenic secondary variants would be routinely reported to the clinician who ordered clinical sequencing. The ACMG estimated that about 1% of sequencing results would include an incidental finding from this list. Remarkably, 16 of 24 disorders (67%) are hereditary cancer syndromes and 13/16 (81%) may be manifested during childhood. As recommended, these variants would be reported independently from patients’ preferences and age, and the ordering physician would be responsible for providing patients and family members with pre-, post test counseling and follow up. The informed consent guidelines for this clinical context are expected to be released soon .
In summary, HCRA is an information process of estimating probabilities of germline mutations in cancer susceptibility genes and assessing empiric risks of cancer based on personal and family history in order to offer molecular diagnosis and clinical management. Providing patients with pre-and post-test genetic counseling can help them to achieve a better informed decision making. Following individuals at high risk with surveillance protocols (such as from NCCN and NICE), reassuring those at low risk, and referring those at increased risk of a hereditary cancer (whether carriers of primary or secondary variants) to a cancer genetics center with multidisciplinary outpatient clinics may allow the best suitable approach of HCRA. Specialized nurses can be settled in district hospitals to undertake pedigrees and risk assessment so they can refer individuals at moderately increased risk for surveillance, those at highly increased risk to the local cancer genetics center and reassure those at low risk.
In Brazil, a National Familial Cancer Network has been built in order to provide families with hereditary cancer a prompt access to diagnosis, management and counseling of the most common hereditary cancer syndromes in a public health care setting .
Collaboration with associations of patients and non-governmental foundations would be extremely helpful to provide families with a better support and care.
- Stadler ZK, Tom P, Robson ME, Weitzel JN, Kauff ND, Hurley KE, Devlin V, Gold B, Klein RJ, Offit K: Genome-wide association studies of cancer. J Clin Oncol 2010, 28: 4255–4267. 10.1200/JCO.2009.25.7816View ArticlePubMedPubMed CentralGoogle Scholar
- Robson ME, Storm CD, Weitzel J, Wollins DS, Offit K: American society of clinical oncology policy statement update: genetic and genomic testing for cancer susceptibility. J Clin Oncol 2010, 28: 893–901. 10.1200/JCO.2009.27.0660View ArticlePubMedGoogle Scholar
- Trepanier A, Ahrens M, McKinnon W, Peters J, Stopfer J, Grumet SC, Manley S, Culver JO, Acton R, Larsen-Haidle J, Correia LA, Bennett R, Pettersen B, Ferlita TD, Costalas JW, Hunt K, Donlon S, Skrzynia C, Farrell C, Callif-Daley F, Vockley CW: Genetic cancer risk assessment and counseling: recommendations of the National society of genetic counselors. J Genet Couns 2004, 13: 83–114.View ArticlePubMedGoogle Scholar
- Oncology Nursing Society: Role of the oncology nurse in cancer genetic counseling. http://www.ons.org
- Weitzel JN, Blazer KR, Mac Donald DJ, Culver OJ, Offit K: Genetics, genomics and risk assessment: state of the art and future directions in the era of personalized medicine. CA Cancer J Clin 2011, 61: 327–359.PubMedPubMed CentralGoogle Scholar
- Couch F, DeShano ML, Blackwood MA, Calzone K, Stopfer J, Campeau L, Ganguly A, Rebbeck T, Weber BL: BRCA1 mutations in women attending clinics that evaluate the risk of breast cancer. N Engl J Med 1997, 336: 1409–1415. 10.1056/NEJM199705153362002View ArticlePubMedGoogle Scholar
- Lindor NM, Johnson KJ, Harvey H, Shane Pankratz V, Domchek SM, Hunt K, Wilson M, Cathie Smith M, Couch F: Predicting BRCA1 and BRCA2 gene mutationcarriers: comparison of PENN II model to previous study. Fam Cancer 2010, 9: 495–502. 10.1007/s10689-010-9348-3View ArticlePubMedPubMed CentralGoogle Scholar
- Frank TS, Deffenbaugh AM, Reid JE, Hulick M, Ward BE, Lingenfelter B, Gumpper KL, Scholl T, Tavtigian SV, Pruss DR, Critchfield GC: Clinical characteristics of individuals with germline mutations in BRCA1 and BRCA2: analysis of 10,000 individuals. J Clin Oncol 2002, 20: 1480–1490. 10.1200/JCO.20.6.1480View ArticlePubMedGoogle Scholar
- Berry DA, Iversen ES Jr, Gudbjartsson DF, Hiller EH, Garber JE, Peshkin BN, Lerman C, Watson P, Lynch HT, Hilsenbeck SG, Rubinstein WS, Hughes KS, Parmigiani G: BRCAPRO validation, sensitivity of genetic testing of BRCA1/BRCA2, and prevalence of other breast cancer susceptibility genes. J Clin Oncol 2002, 20: 2701–2712. 10.1200/JCO.2002.05.121View ArticlePubMedGoogle Scholar
- Berry DA, Parmigiani G, Sanchez J, Schildkraut J, Winer E: Probability of carrying a mutation of breast-ovarian cancer gene BRCA1 based on family history. J Natl Cancer Inst 1997, 89: 227–238. 10.1093/jnci/89.3.227View ArticlePubMedGoogle Scholar
- Parmigiani G, Berry D, Aguilar O: Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet 1998, 62: 145–158. 10.1086/301670View ArticlePubMedPubMed CentralGoogle Scholar
- Tyrer J, Duffy SW, Cuzick J: A breast cancer prediction model incorporating familial and personal risk factors. Stat Med 2004, 23: 1111–1130. 10.1002/sim.1668View ArticlePubMedGoogle Scholar
- Antoniou AC, Pharoah PP, Smith P, Easton DF: The BOADICEA model of genetic susceptibility to breast and ovarian cancer. Br J Cancer 2004, 91: 1580–1590.PubMedPubMed CentralGoogle Scholar
- Wijnen JT, Vasen HFA, Khan PM, Zwinderman AH, van der Klift H, Mulder A, Tops C, Møller P, Fodde R: Clinical findings with implications for genetic testing in families with clustering of colorectal cancer. N Engl J Med 1998, 339: 511–518. 10.1056/NEJM199808203390804View ArticlePubMedGoogle Scholar
- Chen S, Wang W, Lee S, Nafa K, Lee J, Romans K, Watson P, Gruber SB, Euhus D, Kinzler KW, Jass J, Gallinger S, Lindor NM, Casey G, Ellis N, Giardiello FM, Offit K, Parmigiani G: Colon cancer family registry: prediction of germline mutations and cancer risk in the Lynch syndrome. JAMA 2006, 296: 1479–1487. 10.1001/jama.296.12.1479View ArticlePubMedPubMed CentralGoogle Scholar
- Barnetson RA, Tenesa A, Farrington SM, Nicholl ID, Cetnarskyj R, Porteous ME, Campbell H, Dunlop MG: Identification and survival of carriers of mutations in DNA mismatchrepair genes in colon cancer. N Engl J Med 2006, 354: 2751–2763. 10.1056/NEJMoa053493View ArticlePubMedGoogle Scholar
- Kastrinos F, Steyerberg EW, Mercado R, Balmaña J, Holter S, Gallinger S, Siegmund KD, Church JM, Jenkins MA, Lindor NM, Thibodeau SN, Burbidge LA, Wenstrup RJ, Syngal S: The PREMM(1,2,6) model predicts risk of MLH1, MSH2, and MSH6 germline mutations based on cancer history. Gastroenterology 2011, 140: 73–81. 10.1053/j.gastro.2010.08.021View ArticlePubMedGoogle Scholar
- Vasen HF, Watson P, Mecklin JP, Lynch HT: New clinical criteria for hereditary nonpolyposis colorectal cancer (HNPCC, Lynch syndrome) proposed by the International collaborative group on HNPCC. Gastroenterology 1999, 116: 1453–1456. 10.1016/S0016-5085(99)70510-XView ArticlePubMedGoogle Scholar
- Umar A, Boland CR, Terdiman JP, Syngal S, de la Chapelle A, Rüschoff J, Fishel R, Lindor NM, Burgart LJ, Hamelin R, Hamilton SR, Hiatt RA, Jass J, Lindblom A, Lynch HT, Peltomaki P, Ramsey SD, Rodriguez-Bigas MA, Vasen HF, Hawk ET, Barrett JC, Freedman AN, Srivastava S: Revised Bethesda guidelines for hereditary nonpolyposis colorectal cancer (Lynch syndrome) and microsatellite instability. J Natl Cancer Inst 2004, 96: 261–268. 10.1093/jnci/djh034View ArticlePubMedPubMed CentralGoogle Scholar
- Li PP, Fraumeni JF: Soft tissue sarcomas, breast cancer and other neoplasms: a familial syndrome? Ann Int Med 1969, 71: 747–752. 10.7326/0003-4819-71-4-747View ArticlePubMedGoogle Scholar
- Chompret A, Brugieres L, Ronsin M, Gardes M, Dessarps-Freichey F, Abel A, Hua D, Ligot L, Dondon MG, Bressac-de Paillerets B, Frébourg T, Lemerle J, Bonaïti-Pellié C, Feunteun J: P53 germline mutations in childhood cancers and cancer risk for carrier individuals. Br J Cancer 2000, 82: 1932–1937.View ArticlePubMedPubMed CentralGoogle Scholar
- Eng C: Will the real Cowden syndrome please stand up: revised diagnostic criteria. J Med Genet 2000, 37: 828–830. 10.1136/jmg.37.11.828View ArticlePubMedPubMed CentralGoogle Scholar
- Tan MH, Mester J, Peterson C, Yang Y, Chen JL, Rybicki LA, Milas K, Pederson H, Remzi B, Orloff MS, Eng C: A clinical scoring system for selection of patients for PTEN mutation testing is proposed on the basis of a prospective study of 3042 probands. Am J Hum Genet 2011, 88: 42–56. 10.1016/j.ajhg.2010.11.013View ArticlePubMedPubMed CentralGoogle Scholar
- Wang W, Niendorf KB, Patel D, Blackford A, Marroni F, Sober AJ, Parmigiani G, Tsao H: Estimating CDKN2A carrier probability and personalizing cancer risk assessments in hereditary melanoma using MelaPRO. Cancer Res 2010, 70: 552–559. 10.1158/0008-5472.CAN-09-2653View ArticlePubMedPubMed CentralGoogle Scholar
- Dinh TA, Rosner BI, Atwood JC, Boland CR, Syngal S, Vasen HF, Gruber SB, Burt RW: Health benefits and cost-effectiveness of primary genetic screening for Lynch syndrome in the general population. Cancer Prev Res (Phila) 2011, 4: 9–22. 10.1158/1940-6207.CAPR-10-0262View ArticleGoogle Scholar
- Kwon JS, Gutierrez-Barrera AM, Young D, Sun CC, Daniels MS, Lu KH, Arun B: Expanding the criteria for BRCA mutation testing in breast cancer survivors. J Clin Oncol 2010, 28: 4214–4220. 10.1200/JCO.2010.28.0719View ArticlePubMedGoogle Scholar
- National Comprehensive Cancer Network: NCCN practice guidelines V.1.2013: genetic/familial high-risk assessment: breast and ovarian. Fort Washington, PA: National Comprehensive Cancer Network; 2013. http://www.nccn.org Google Scholar
- National Comprehensive Cancer Network: NCCN practice guidelines V.2.2012: colorectal cancer screening. Fort Washington, PA: National Comprehensive Cancer Network; 2012. http://www.nccn.org Google Scholar
- Hampel H, Sweet K, Westman JA, Offit K, Eng C: Referral for cancer genetics consultation: a review and compilation of risk assessment criteria. J Med Genet 2004, 41: 81–91. 10.1136/jmg.2003.010918View ArticlePubMedPubMed CentralGoogle Scholar
- Gail MH, Brinton LA, Byar DP, Corle DK, Green SB, Schairer C, Mulvihill JJ: Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 1989, 81: 1879–1886. 10.1093/jnci/81.24.1879View ArticlePubMedGoogle Scholar
- Claus EB, Risch N, Thompson WD: Autosomal dominant inheritance of earlyonset breast cancer: implications for risk prediction. Cancer 1994, 73: 643–651. 10.1002/1097-0142(19940201)73:3<643::AID-CNCR2820730323>3.0.CO;2-5View ArticlePubMedGoogle Scholar
- National Cancer Institute (NCI): Risk factor monitoring and methods. http://appliedresearch.cancer.gov/about/rfmmb/research.html
- Fletcher O, Houlston RS: Architecture of inherited susceptibility to common cancer. Nature Rev Cancer 2010, 10: 353–361.View ArticleGoogle Scholar
- National Institute for Health and Care Excellence (NICE): Classification and care of people at risk of familial breast cancer and management of breast cancer and related risks in people with a family history of breast cancer. http://guidance.nice.org.uk/cg164
- Garber J, Zon R, Weitzel J: Genetic counseling: an indispensable step in the genetic testing process. J Oncol Pract 2008,4(2):96–98.View ArticleGoogle Scholar
- Hodgson SV, Foulkes WD, Eng C, Maher ER: A practical guide to human cancer genetics. 3rd edition. Cambridge, UK: Cambridge University Press; 2007.Google Scholar
- Green RC, Berg JS, Grody WW, Kalia SS, Korf BR, Martin CL, McGuire AL, Nussbaum RL, O’Daniel JM, Ormond KE, Rehm HL, Watson MS, Williams MS, Biesecker LG: ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing. Genet Med 2013,15(7):565–574. 10.1038/gim.2013.73View ArticlePubMedPubMed CentralGoogle Scholar
- Ministério da Saúde. Instituto Nacional de Câncer (INCA): Rede nacional de câncer familial: manual operacional. Rio de Janeiro, Brazil: Coordenação de Educação (CEDC); 2009.Google Scholar
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.