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Genetics of Breast and Ovarian Cancer (PDQ®)

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Low- and Moderate-Penetrance Genes Associated With Breast and/or Ovarian Cancer

Breast Cancer Susceptibility Genes Identified Through Candidate Gene Approaches
        CASP8 and TGFB1
Genome-Wide Searches


Mutations in BRCA1, BRCA2, and the genes involved in other rare syndromes discussed in the High-Penetrance Breast and/or Ovarian Cancer Susceptibility Genes section of this summary account for less than 25% of the familial risk of breast cancer.[1] Despite intensive genetic linkage studies, there do not appear to be other BRCA1/BRCA2-like high-penetrance genes that account for a significant fraction of the remaining multiple-case familial clusters.[2] These observations suggest that the remaining breast cancer susceptibility is polygenic in nature, meaning that a relatively large number of low-penetrance genes are involved.[3] On its own, each low-penetrance locus would be expected to have a relatively small effect on breast cancer risk and would not produce dramatic familial aggregation or influence patient management. However, in combination with other genetic loci and/or environmental factors, particularly given how common these can be, variants of this kind might significantly alter breast cancer risk. These types of genetic variations are sometimes referred to as “polymorphisms,” meaning that the gene or locus occurs in several “forms” within the population (and more formally defined as polymorphic when a specific variation in a given locus occurs in more than 1% of the population). Most loci that are polymorphic have no influence on disease risk or human traits (benign polymorphisms), while those that are associated with a difference in risk of disease or a human trait (however subtle) are sometimes termed “disease-associated polymorphisms” or “functionally relevant polymorphisms.” This polygenic model of susceptibility is consistent with the observed patterns of familial aggregation of breast cancer.[4] Although the clinical significance and causality of associations with breast cancer are often difficult to evaluate and establish, genetic polymorphisms may account for why some individuals are more sensitive than others to environmental carcinogens.[5]

Polymorphisms underlying polygenic susceptibility to breast cancer are considered low penetrance, a term often applied to sequence variants associated with a minimal to moderate risk. This is in contrast to “high-penetrance” variants or alleles that are typically associated with more severe phenotypes, for example those BRCA1/BRCA2 mutations leading to an autosomal dominant inheritance patterns in a family. The definition of a “moderate” risk of cancer is arbitrary, but it is usually considered to be in the range of a relative risk (RR) of 1.5 to 2.0. Because these types of sequence variants (also called low-penetrance genes, alleles, mutations, and polymorphisms) are relatively common in the general population, their contribution to cancer risk overall is estimated to be much greater than the attributable risk in the population from mutations in BRCA1 and BRCA2. For example, it is estimated by segregation analysis that half of all breast cancer occurs in 12% of the population that is deemed most susceptible.[3] There are no known low-penetrance variants in BRCA1/BRCA2. The N372H variation in BRCA2, initially thought to be a low-penetrance allele, was not verified in a large combined analysis.[6]

Two strategies have been taken to identify low-penetrance polymorphisms leading to breast cancer susceptibility: candidate gene and genome-wide searches. Both involve the epidemiologic case-control study design. The candidate gene approach involves selecting genes based on their known or presumed biological function, relevance to carcinogenesis or organ physiology, and searching for or testing known genetic variants for an association with cancer risk. This strategy relies on imperfect and incomplete biological knowledge, and, despite some confirmed associations (described below), has been relatively disappointing.[6,7] The candidate gene approach has largely been replaced by the genome-wide association studies (GWAS) in which a very large number of single nucleotide polymorphisms (SNPs) (potentially 1 million or more) are chosen within the genome and tested, mostly without regard to their possible biological function, but instead to capture all genetic variation throughout the genome more uniformly.

Breast Cancer Susceptibility Genes Identified Through Candidate Gene Approaches

There is a very large literature of genetic epidemiology studies describing associations between various loci and breast cancer risk. Many of these studies suffer from significant design limitations. Perhaps as a consequence, most reported associations do not replicate in follow-up studies. This section is not a comprehensive review of all reported associations. This section describes associations that are believed by the editors to be clinically valid, in that they have been described in several studies or are supported by robust meta-analyses. The clinical utility of these observations remains unclear, however, as the risks associated with these variations usually fall below a threshold that would justify a clinical response.


CHEK2 (OMIM) is a gene involved in the DNA damage repair response pathway. Based on numerous studies, a polymorphism, 1100delC, appears to be a rare, moderate-penetrance cancer susceptibility allele.[8-13] One study identified the mutation in 1.2% of the European controls, 4.2% of the European BRCA1/BRCA2-negative familial breast cancer cases, and 1.4% of unselected female breast cancer cases.[8] In a group of 1,479 Dutch women younger than 50 years with invasive breast cancer, 3.7% were found to have the CHEK2 1100delC mutation.[14] In additional European and U.S. (where the mutation appears to be slightly less common) studies, including a large prospective study,[15] the frequency of CHEK2 mutations detected in familial breast or ovarian cancer cases has ranged from 0% [16] to 11%; overall, these studies have found an approximately 1.5-fold to 3-fold increased risk of female breast cancer.[15,17-20] A multicenter combined analysis and reanalysis of nearly 20,000 subjects from ten case-control studies, however, has verified a significant 2.3-fold excess of breast cancer among mutation carriers.[21] A subsequent meta-analysis based on 29,154 cases and 37,064 controls from 25 case-control studies found a significant association between CHEK2 1100delC heterozygotes and breast cancer risk (odds ratio [OR], 2.75; 95% confidence interval [CI], 2.25–3.36). The ORs and CIs in unselected, familial, and early-onset breast cancer subgroups were 2.33 (1.79–3.05), 3.72 (2.61–5.31), and 2.78 (2.28–3.39), respectively. However, study limitations included pooling of populations without subgroup analysis, using a mix of population-based and hospital-based controls, and basing results on unadjusted estimates (as cases and controls were matched on only a few common factors); therefore, results should be interpreted in the context of these limitations.[22]

Two studies have suggested that the risk associated with a CHEK2 1100delC mutation was stronger in the families of probands ascertained because of bilateral breast cancer.[23,24] Furthermore, a meta-analysis of 1100delC mutation carriers estimated the risk of breast cancer to be 42% by age 70 years in women with a family history of breast cancer.[25] Similarly, a Polish study reported that CHEK2 truncating mutations confer breast cancer risks based on a family history of breast cancer as follows: no family history: 20%; one second-degree relative: 28%; one first-degree relative: 34%; and both first- and second-degree relatives: 44%.[26] Moreover, a Dutch study suggested that female homozygotes for the CHEK2 1100delC mutation have a greater-than-twofold increased breast cancer risk compared with heterozygotes.[27] Although there have been conflicting reports regarding cancers other than breast cancer associated with CHEK2 mutations, this may be dependent on mutation type (i.e., missense vs. truncating) or population studied and is not currently of clinical utility.[13,18,28-33] The contribution of CHEK2 mutations to breast cancer may depend on the population studied, with a potentially higher mutation prevalence in Poland.[34] CHEK2 mutation carriers in Poland may be more susceptible to ER-positive breast cancer.[35]

Currently, the clinical applicability of CHEK mutations remains uncertain because of low mutation prevalence and lack of guidelines for clinical management.[36]

(Refer to the CHEK2 section in the PDQ summary on Genetics of Colorectal Cancer for more information.)


Ataxia telangiectasia (AT) (OMIM) is an autosomal recessive disorder characterized by neurologic deterioration, telangiectasias, immunodeficiency states, and hypersensitivity to ionizing radiation. It is estimated that 1% of the general population may be heterozygote carriers of ATM mutations (OMIM).[37] More than 300 mutations in the gene have been identified, most of which are truncating mutations.[38] ATM proteins have been shown to play a role in cell cycle control.[39-41] In vitro, AT-deficient cells are sensitive to ionizing radiation and radiomimetic drugs, and lack cell cycle regulatory properties after exposure to radiation.[42]

Initial studies searching for an excess of ATM mutations among breast cancer patients provided conflicting results, perhaps due to study design and mutation testing strategies.[43-53] However, two large epidemiologic studies have demonstrated a statistically increased risk of breast cancer among female heterozygote carriers, with an estimated RR of approximately 2.0.[53,54] Despite this convincing epidemiologic association, the clinical application of testing for ATM mutations is unclear due to the wide mutational spectrum and the logistics of testing. Because the presence of a mutation could pose a risk in screening-related radiation exposure, further investigation is needed.


BRIP1 (also known as BACH1) encodes a helicase that interacts with the BRCA1 C-terminal (BRCT) domain. This gene also has a role in BRCA1-dependent DNA repair and cell cycle checkpoint function. Biallelic mutations in BRIP1 are a cause of Fanconi anemia,[55-57] much like such mutations in BRCA2. Inactivating mutations of BRIP1 are associated with an increased risk of breast cancer. In one study, more than 3,000 individuals from BRCA1/BRCA2 mutation negative families were examined for BRIP1 mutations. Mutations were identified in 9 of 1,212 individuals with breast cancer but in only 2 of 2,081 controls (P = .003). The RR of breast cancer was estimated to be 2.0 (95% CI, 1.2–3.2; P = .012). Of note, in families with BRIP1 mutations and multiple cases of breast cancer, there was incomplete segregation of the mutation with breast cancer, consistent with a low penetrance allele and similar to that seen with CHEK2.[58]


PALB2 (partner and localizer of BRCA2) interacts with the BRCA2 protein and plays a role in homologous recombination and double-stranded DNA repair. Similar to BRIP1 and BRCA2, biallelic mutations in PALB2 have also been shown to cause Fanconi anemia.[59]

PALB2 mutations have been screened for in multiple small studies of familial and early-onset breast cancer in multiple populations.[60-72] Mutation prevalence has ranged from 0.4% to 3.4%. Similar to BRIP1 and CHEK2, there was incomplete segregation of PALB2 mutations in families with hereditary breast cancer.[61] Among 559 cases with contralateral breast cancer and 565 matched controls with unilateral breast cancer, pathogenic (truncating) PALB2 mutations were identified in 0.9% of cases and in none of the controls (RR, 5.3; 95% CI, 1.8–13.2).[72]

Data based on 154 families with loss-of-function PALB2 mutations suggest that this gene may be an important cause of hereditary breast cancer with risks that overlap with BRCA2.[73] In this study, analysis of 362 family members from 154 families with PALB2 mutations indicated that the absolute risk of female breast cancer by age 70 years ranged from 33% (95% CI, 24–44) for those with no family history of breast cancer to 58% (95% CI, 50–66) for those with two or more first-degree relatives with early-onset breast cancer. Furthermore, among 63 breast cancer cases in which HER2 status was known, 30% had triple-negative disease. Another Finnish study reported on a PALB2 founder mutation (c.1592delT) that confers a 40% risk of breast cancer to age 70 years [62] and that is associated with a high incidence (54%) of triple-negative disease and lower survival.[63] Mutations have been observed in early-onset and familial breast cancer in many populations.[64,65]

Male breast cancer has been observed in PALB2 mutation–positive breast cancer families.[60,66,73] In a study of 115 male breast cancer cases in which 18 men had BRCA2 mutations, an additional two men had either a pathogenic or predicted pathogenic PALB2 mutation (accounting for about 10% of germline mutations in the study and 1%–2% of the total sample).[60] The RR of breast cancer for male PALB2 mutation carriers compared with that seen in the general population was estimated to be 8.30 (95% CI, 0.77–88.56; P = .08) in the study of 154 families.[73]

After the identification of PALB2 mutations in pancreatic tumors and the detection of germline mutations in 3% of 96 familial pancreatic patients,[74] numerous studies have pointed to a role for PALB2 in pancreatic cancer. PALB2 mutations were detected in 3.7% of 81 familial pancreatic cancer families [75] and in 2.1% of 94 BRCA1/2 mutation–negative breast cancer patients who had either a personal or family history of pancreatic cancer.[76] Two relatively small studies, one of 77 BRCA1/2 mutation–negative probands with a personal or family history of pancreatic cancer, one-half of whom were of Ashkenazi Jewish descent, and another study of 29 Italian pancreatic cancer patients with a personal or family history of breast or ovarian cancer, failed to detect any PALB2 mutations.[77,78] A sixfold increase in pancreatic cancer was observed in the relatives of 33 BRCA1/2-negative, PALB2 mutation–positive breast cancer probands.[66]

Overall, the observed prevalence of PALB2 mutations in familial breast cancer varied depending on ascertainment relative to personal and family history of pancreatic and ovarian cancers, but in all studies, the observed mutation rate was less than 4%. Data suggest that the RR of breast cancer may overlap with that of BRCA2, particularly in those with a strong family history; thus, it remains important to refine cancer risk estimates in larger studies. Furthermore, the risk of other cancers (e.g., pancreatic) is poorly defined. Given the low PALB2 mutation prevalence in the population, additional data are needed to define best candidates for testing and appropriate management.


The Breast Cancer Association Consortium (BCAC), an international group of investigators, investigated SNPs identified in previous studies as possibly associated with excess breast cancer risk in 15,000 to 20,000 cases and 15,000 to 20,000 controls. Two SNPs, CASP8 D302H and TGFB1 L10P, were associated with invasive breast cancer with RRs of 0.88 (95% CI, 0.84–0.92) and 1.08 (95% CI, 1.04–1.11), respectively.[79]


RAD51 and the family of RAD51-related genes, also known as RAD51 paralogs, are thought to encode proteins that are involved in DNA damage repair through homologous recombination and interaction with numerous other DNA repair proteins, including BRCA1 and BRCA2. RAD51 protein plays a central role in single-strand annealing in the DNA damage response. RAD51 recruitment to break sites and recombinational DNA repair depend on the RAD51 paralogs, although their precise cellular functions are poorly characterized.[80] Mutations in these genes are thought to result in loss of RAD51 focus formation in response to DNA damage.[81]

One of five RAD51-related genes, RAD51C has been reported to be linked to both Fanconi anemia–like disorders and familial breast and ovarian cancers. The literature, however, has produced contradictory findings. In a study of 480 German families characterized by breast and ovarian cancers who were negative for BRCA1 and BRCA2 mutations, six monoallelic mutations in RAD51C were found (frequency of 1.3%).[82] No mutations were found in breast cancer–only families or in healthy controls. Another study screened 286 BRCA1/2-negative patients with breast cancer and/or ovarian cancer and found one likely deleterious mutation in RAD51C-G153D.[83] RAD51C mutations have also been reported in Australian, Finnish, and Spanish non-BRCA1/2 ovarian cancer–only and breast/ovarian cancer families, and in unselected ovarian cancer cases.[84-88] In a sample of 206 high-risk Jewish women (including 79 of Ashkenazi origin) previously tested for the common Jewish mutations, two previously described and possibly pathogenic missense mutations were detected.[89] Four additional studies were unable to confirm an association between the RAD51C gene and hereditary breast cancer or ovarian cancer.[70,90-92]

In addition to RAD51C mutation carriers, there are other RAD51 paralogs, including RAD51D and RAD51L1, that may be associated with breast and/or ovarian cancer risk,[93-97] although the clinical significance of these findings is unknown.

In addition to germline mutations, different polymorphisms of RAD51 have been hypothesized to have reduced capacity to repair DNA defects, resulting in increased susceptibility to familial breast cancer. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) pooled data from 8,512 BRCA1 and BRCA2 mutation carriers and found evidence of an increased risk of breast cancer among women who were BRCA2 carriers and who were homozygous for CC at the RAD51 135G→C SNP (hazard ratio, 1.17; 95% CI, 0.91–1.51).[98]

Several meta-analyses have investigated the association between the RAD51 135G→C polymorphism and breast cancer risk. There is significant overlap in the studies reported in these meta-analyses, significant variability in the characteristics of the populations included, and significant methodologic limitations to their findings.[99-102] A meta-analysis of nine epidemiologic studies involving 13,241 cases and 13,203 controls of unknown BRCA1/2 status found that women carrying the CC genotype had an increased risk of breast cancer compared with women with the GG or GC genotype (OR, 1.35; 95% CI, 1.04–1.74). A meta-analysis of 14 case-control studies involving 12,183 cases and 10,183 controls confirmed an increased risk only for women who were known BRCA2 carriers (OR, 4.92; 95% CI, 1.10–21.83).[103] Another meta-analysis of 12 studies included only studies of known BRCA-negative cases and found no association between RAD51 135G→C and breast cancer.[104]

In summary, among this conflicting data there is substantial evidence for a weak association between germline mutations in RAD51C and breast cancer and ovarian cancer. There is also evidence of an association between polymorphisms in RAD51 135G→C among women with homozygous CC genotypes and breast cancer, particularly among BRCA2 carriers. These associations are plausible given the known role of RAD51 in the maintenance of genomic stability.


Mutations in the BRCA1-interacting gene Abraxas were found in three Finnish breast cancer families and no controls.[105] The significance of this finding outside of this population is not yet known.

Genome-Wide Searches

In contrast to assessing candidate genes and/or alleles, GWAS involve comparing a very large set of genetic variants spread throughout the genome. The current paradigm uses sets of as many as 5 million SNPs that are chosen to capture a large portion of common variation within the genome based on the HapMap and the 1000 Genomes Project.[106,107] By comparing allele frequencies between a large number of cases and controls, typically 1,000 or more of each, and validating promising signals in replication sets of subjects, very robust statistical signals of association have been obtained.[108-110] The strong correlation between many SNPs that are physically close to each other on the chromosome (linkage disequilibrium) allows one to “scan” the genome for susceptibility alleles even if the biologically relevant variant is not within the tested set of SNPs. Although this between-SNP correlation allows one to interrogate the majority of the genome without having to assay every SNP, when a validated association is obtained, it is not usually obvious which of the many correlated variants is causal.

Genome-wide searches are showing great promise in identifying common, low-penetrance susceptibility alleles for many complex diseases,[111] including breast cancer.[112-115] The first study involved an initial scan in familial breast cancer cases followed by replication in two large sample sets of sporadic breast cancer, the final being a collection of over 20,000 cases and 20,000 controls from the BCAC.[112] Five distinct genomic regions were identified that were within or near the FGFR2, TNRC9, MAP3K1, and LSP1 genes or at the chromosome 8q region. The 8q region and others may harbor multiple independent loci associated with risk, but these regions are included only once in Table 11. Subsequent genome-wide studies have replicated these loci and identified additional ones, as summarized in Table 11.[113,114,116,116-121] Numerous SNPs identified through large studies of sporadic breast cancer appear to be associated more strongly with estrogen receptor–positive disease;[122] however, some are associated primarily or exclusively with other subtypes, including triple-negative disease.[123,124] An online catalog of SNP-trait associations from published GWAS for use in investigating genomic characteristics of trait/disease-associated SNPs (TASs) is available.

Table 11. High-probability Breast Cancer Susceptibility Loci Identified Through Genome-Wide Association Studies
Putative Gene(s) Chromosome  SNP Study Citationa Odds Ratio (OR) (95% Confidence Interval [CI])b Comments 
Intergenic /NOTCH21p11.2rs11249433[94]1.08 (1.02–1.15) [115]Stronger in ER+, low-grade [115]; also in BRCA2 [125]
ERBB2 2q34rs13393577[126]1.53 (1.37–1.70) [126]Identified in Korean subjects [126]
Intergenic2q35rs13387042[113]1.21 (1.14–1.29) [115]Stronger in bilateral and lobular [122]; also in BRCA1 and BRCA2 [127]
SLC4A7, NEK103p24rs4973768[121]1.16 (1.10–1.24) [115]Also in BRCA2 [127]
MRPS30 5p12rs10941679[120]1.11c (1.04–1.19) [115]Strongest in PR+, low-grade [128]; also in BRCA2 [127]
TERT-/CLPTM15p15rs10069690[123]1.25 (1.16–1.34) [123]Strongest in triple-negative [123]
MAP3K1 5q11.2rs889312[112]1.22 (1.14–1.30) [115]Stronger in ER+ [115]; also in BRCA2 [127]
RNF146 6q22rs2180341[116]1.24 (1.13–1.36) [129]Stronger in Ashkenazi Jews [129]
ESR1 6q25.1rs2046210[117]1.15c (1.08–1.22) [115]Also in BRCA1 [125]
TAB2 6q25.1rs9485372[130]0.90 (0.87–0.92) [130]Identified in Chinese subjects [130]
Intergenic7q32.3rs2048672[131]1.11 (1.05–1.17) [131]Identified in East Asian subjects [131]
Intergenic/MYC8q24.21rs13281615[112]1.14 (1.07–1.21) [115]Stronger in ER+ [115]
CDKN2A, CDKN2B 9p21rs1011970[115]1.09 (1.04–1.14) [115]Stronger in ER+ [115]; also in BRCA2 [132]
Intergenic9q31.2rs865686[133]0.89(0.85–0.92) [133]Also in BRCA2 [132]
ANKRD16, FBXO18 10p15.1rs2380205[115]0.94 (0.91–0.98) [115]
ZNF365 10q21.2rs10995190[115]0.86 (0.82–0.91) [115]Stronger in ER+ in general population [115]; also in BRCA2 [134]
ZMIZ1 10q22.3rs704010[115]1.07 (1.03–1.11) [115]
FGFR2 10q26.13rs2981582[112]1.43 (1.35–1.53) [115]Strongest for ER+, low-grade [122]; also in BRCA2 [127]
LSP1 11p15.5rs3817198[112]1.12 (1.05–1.19) [115]Also in BRCA2 [127]
Intergenic11q13rs614367[115]1.15 (1.10–1.20) [115]Restricted to ER+ tumors; strongest for ER+/PR+[115]
BARX211q24.3rs7107217[130]1.08 (1.05–1.11) [130]Identified in Chinese subjects [130]
PTHLH 12p11rs10771399[135]0.85 (0.83–0.88) [135]Also in BRCA1 [132]
Intergenic12q24rs1292011[135]0.92 (0.91–0.94) [135]Restricted to ER+ [135]; also in BRCA2 [132]
RAD51B 14q24.1rs999737[94]0.89 (0.83–0.95) [115]Associated with all subtypes, including triple-negative [95]; also in BRCA2 [132]
TOX3 16q12.1rs3803662[112]1.30 (1.22–1.39) [115]Stronger in ER+ [122]; also in BRCA1 and BRCA2 [127]
COX11 17q23.2rs6504950[121]0.92c (0.86–0.99) [115]
BABAM1 19p13.1rs8170[124]1.26 (1.17–1.35) [136]Restricted to triple-negative in general population [124]; also in BRCA1 [136]
NRIP1 21q21rs2823093[135]0.94 (0.92–0.96) [135]Restricted to ER+ [135]

ER- = estrogen receptor–negative; ER+ = estrogen receptor–positive; PR- = progesterone receptor–negative; PR+ = progesterone receptor–positive; SNP = single nucleotide polymorphism; triple-negative = ER-/PR-/HER2/neu-.
aInitial study that demonstrated genome-wide significance for each locus.
bAll associations observed in the general population, unless otherwise indicated; when relevant, if association was also observed in BRCA1 or BRCA2 mutation carriers, it is indicated.
cOR for best tag SNP was used [115] as a surrogate for published SNP.

Table 12. High-probability Ovarian Cancer Susceptibility Loci Identified Through Genome-Wide Association Studies
Putative Gene(s) Chromosome SNP Study Citation Odds Ratio (95% Confidence Interval) Comment 
SNP = single nucleotide polymorphism.
HOXD1 2q31.1rs2072590[137]1.16 (1.12–1.21)Stronger in serous cancers
TIPARP 3q25.31rs2665390[137]1.19 (1.11–1.27)
Intergenic/MYC, THEM758q24.21rs10088218[137]0.84 (0.80–0.89)
BNC2 9p22.2rs3814113[138]0.82 (0.79–0.86)Stronger in serous cancers; also in BRCA1 and BRCA2 [139]
SKAP1 17q21.32rs9303542[137]1.11 (1.06–1.16)
BABAM1 19p13.11rs8170[140]1.18 (1.12–1.25)Serous cancers only
ANKLE1 19p13.11rs2363956[140]1.16 (1.11–1.21)

Although the statistical evidence for an association between genetic variation at these loci and breast and ovarian cancer risk is overwhelming, the biologically relevant variants and the mechanism by which they lead to increased risk are unknown and will require further genetic and functional characterization. Additionally, these loci are associated with very modest risk (typically, OR <1.5), with more risk variants likely to be identified. No interaction between the SNPs and epidemiologic risk factors for breast cancer have been identified.[141,142] At this time, because their individual and collective influences on cancer risk have not been evaluated prospectively, they are not considered clinically relevant. Furthermore, theoretical models have suggested that common moderate-risk SNPs have limited potential to improve models for individualized risk assessment.[143-145] These models used receiver operating characteristic (ROC) curve analysis to calculate the area under the curve (AUC) as a measure of discriminatory accuracy. A more recent study used ROC curve analysis to examine the utility of SNPs in a clinical dataset of greater than 5,500 breast cancer cases and nearly 6,000 controls, using a model with traditional risk factors compared with a model using both standard risk factors and ten previously identified SNPs. The addition of genetic information modestly changed the AUC from 58% to 61.8%, a result that was not felt to be clinically significant. Despite this, 32.5% of patients were in a higher quintile of breast cancer risk when genetic information was included, and 20.4% were in a lower quintile of risk. Whether such information has clinical utility is unclear.[143,146]

More limited data are available regarding ovarian cancer risk. Three GWAS involving staged analysis of more than 10,000 cases and 13,000 controls have been carried out for ovarian cancer.[137,138,140] The seven loci that reached genome-wide significance are shown in Table 12. As in other GWAS, the ORs are modest, generally about 1.2 or weaker, but implicate a number of genes with plausible biological ties to ovarian cancer, such as BABAM1, whose protein complexes with and may regulate BRCA1, and TIRAPR, which codes for a poly (ADP-ribose) polymerase, molecules that may be important in BRCA1/BRCA2-deficient cells.

In addition to genome-wide studies interrogating common genetic variants, sequencing-based studies involving whole-genome or whole-exome sequencing [147] are also identifying genes associated with breast cancer, such as XRCC2, a rare, moderate-penetrance, breast cancer susceptibility gene.[148]

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