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• W2022268077 abstract "In the last few years, several studies have focused on the interpretation of unclassified variants (UVs) of BRCA1 and BRCA2 genes. Analysis of UVs through a unique approach is not sufficient to understand their role in the development of tumors. Thus, it is clear that assembling results from different sources (genetic and epidemiological data, histopathological features, and in vitro and in silico analyses) represents a powerful way to classify such variants. Building reliable integrated models for UV classification requires the joining of many working groups to collaborative consortia, allowing data exchange and improvements of methods. This will lead to improvement in the predictivity of gene testing in BRCA1 and BRCA2 and, consequently, to an increase in the number of families that can be correctly classified as linked or unlinked to these genes, allowing more accurate genetic counseling and clinical management. In the last few years, several studies have focused on the interpretation of unclassified variants (UVs) of BRCA1 and BRCA2 genes. Analysis of UVs through a unique approach is not sufficient to understand their role in the development of tumors. Thus, it is clear that assembling results from different sources (genetic and epidemiological data, histopathological features, and in vitro and in silico analyses) represents a powerful way to classify such variants. Building reliable integrated models for UV classification requires the joining of many working groups to collaborative consortia, allowing data exchange and improvements of methods. This will lead to improvement in the predictivity of gene testing in BRCA1 and BRCA2 and, consequently, to an increase in the number of families that can be correctly classified as linked or unlinked to these genes, allowing more accurate genetic counseling and clinical management. Similarly to other human cancer susceptibility genes, the utility of testing in genes associated with hereditary breast and ovarian cancer, such as BRCA1 and BRCA2, strongly relies on the possibility of establishing a relationship between the nature of the observed genetic alterations and their consequences on the functionality of the corresponding protein products, whose impairment is though to be responsible for cancer predisposition. This can be generally inferred for mutations that introduce premature stop codons (i.e. truncation) or affect mRNA integrity and/or stability, giving rise to functionally compromised proteins. Additional bona fide pathogenic mutations include missense mutations affecting the translation start codon or modifying structurally critical amino acid positions, such as the cystein residues in the ring finger domain of the BRCA1 protein. However, apart from common polymorphisms, the assessment of the clinical relevance of other allelic variants may not be equally straightforward. These are globally referred to as unclassified variants (UVs) or variants of uncertain significance (VUSs) and include: (i) missense mutations or small in-frame deletions whose effect on the protein structure cannot be immediately inferred; (ii) variants, both exonic and intronic, that may potentially affect pre-mRNA splicing, but for which no direct evidence is available; and (iii) variants in regulatory sequences. Most of them are extremely rare and their effect on cancer risk cannot be established through case–control association studies. As a consequence, counseling of families in which only UVs are detected is problematic, since the result of the genetic test cannot be used to unambiguously identify at-risk family members and to address them to adequate programs of prevention and surveillance. These families cannot benefit from genetic testing and are usually treated as families with a negative (undetermined) test result, in which, at present, risk assessment is based purely on family history. Although most allelic variants identified in BRCA1 and BRCA2 are deleterious mutations or common polymorphisms, at present ∼15% of BRCA gene testing in index cases of high-risk families report one or more UVs in the absence of any clearly pathogenic variant. Nowadays, several research groups are involved in the analysis of UVs, with the aim of providing evidence in favor of or against their pathogenicity, and thus increasing the informativeness of genetic testing in cancer-predisposed families. The classification of UVs is based mainly on the use of integrated analyses. In particular multifactorial likelihood prediction models have been developed and applied [1.Goldgar D.E. Easton D.F. Deffenbaugh A.M. et al.Integrated evaluation of DNA sequence variants of unknown clinical significance: application to BRCA1 and BRCA2.Am J Hum Genet. 2004; 75: 535-544Abstract Full Text Full Text PDF PubMed Scopus (313) Google Scholar, 2.Chenevix-Trench G. Healey S. Lakhani S. et al.Genetic and histopathologic evaluation of BRCA1 and BRCA2 DNA sequence variants of unknown clinical significance.Cancer Res. 2006; 66: 2019-2027Crossref PubMed Scopus (138) Google Scholar, 3.Osorio A. Milne R.L. Honrado E. et al.Classification of missense variants of unknown significance in BRCA1 based on clinical and tumor information.Hum Mutat. 2007; 28: 477-485Crossref PubMed Scopus (40) Google Scholar, 4.Easton D.F. Deffenbaugh A.M. Pruss D. et al.A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer-predisposition genes.Am J Hum Genet. 2007; 81: 873-883Abstract Full Text Full Text PDF PubMed Scopus (373) Google Scholar, 5.Malacrida S. Agata S. Callegaro M. et al.BRCA1 p.Val1688del is a deleterious mutation that recurs in breast and ovarian cancer families from Northeast Italy.J Clin Oncol. 2008; 26: 26-31Crossref PubMed Scopus (31) Google Scholar, 6.Spurdle A.B. Lakhani S.R. Healey S. et al.Clinical classification of BRCA1 and BRCA2 DNA sequence variants: the value of cytokeratin profiles and evolutionary analysis–a report from the kConFab Investigators.J Clin Oncol. 2008; 26: 1657-1663Crossref PubMed Scopus (64) Google Scholar]. These models take into account several factors, including both direct (genetic) and indirect evidence. The former includes the frequency of the variant in cases and controls, its co-segregation with the disease in families, co-occurrence with a deleterious mutation in the same gene, and personal and family history of cancer of the carriers of the UV. Indirect evidence includes histopathological tumor features, the occurrence of loss of heterozygosity (LOH) in tumor DNA and, limited to missense variants, the severity of the amino acid change and its conservation across species. The multifactorial classification models are based on likelihood ratios (LRs), which are generated independently for each factor considered. Each LR is calculated based on the probability of the observed data occurring in the presence of a pathogenic or neutral variant. Individual LRs are then multiplied together to achieve a final cumulative LR. For missense variants in BRCA genes, the latter may be combined with a prior probability value of pathogenicity based on amino acid evolutionary conservation and physicochemical properties [7.Goldgar D.E. Easton D.F. Byrnes G.B. et al.Genetic evidence and integration of various data sources for classifying uncertain variants into a single model.Hum Mutat. 2008; 29: 1265-1272Crossref PubMed Scopus (150) Google Scholar], to compute a posterior probability of pathogenicity [8.Tavtigian S.V. Byrnes G.B. Goldgar D.E. Thomas A. Classification of rare missense substitutions, using risk surfaces, with genetic- and molecular-epidemiology applications.Hum Mutat. 2008; 29: 1342-1354Crossref PubMed Scopus (174) Google Scholar]. Each of the above approaches present advantages and disadvantages. Case–control studies are potentially very powerful and may provide a direct estimate of the actual cancer risk associated with a specific allelic variant [9.Pharoah P.D. Dunning A.M. Ponder B.A. Easton D.F. Association studies for finding cancer-susceptibility genetic variants.Nat Rev Cancer. 2004; 4: 850-860Crossref PubMed Scopus (418) Google Scholar], but require a large number of individuals and, consequently, are difficult to apply to the analysis of UVs in cancer-predisposing genes that are usually very rare in the population. The study of personal and family history, a method used to classify UVs in the database of Myriad Genetics Laboratories (Salt Lake City, UT, USA) is based on the fact that the presence of a variant in a family with a high frequency of disease indicates that it is more likely to be associated with cancer. Although this information is usually available and can be obtained without the need for additional data or sample collection, it must be noted that reference samples from a dataset can not be used to classify variants from another dataset that utilizes different ascertainment criteria [10.Spurdle A.B. Clinical relevance of rare germline sequence variants in cancer genes: evolution and application of classification models.Curr Opin Genet Dev. 2010; 20: 315-323Crossref PubMed Scopus (33) Google Scholar]. The observation of the segregation of UVs with the disease is another powerful resource for their classification and this approach has been recently facilitated by the development of a web-based method for calculation of corresponding LRs to integrate into multifactorial models [11.Mohammadi L. Vreeswijk M.P. Oldenburg R. et al.A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example.BMC Cancer. 2009; 9: 211Crossref PubMed Scopus (55) Google Scholar]. However, this requires the typing of additional family members in addition to the index case, in particular those affected, which may not be easy to accomplish, mainly for ethical reasons. The co-occurrence in the same individual of a UV with a pathogenic mutation (particularly if in trans) may be, by itself or in the absence of a particular phenotype, highly indicative of its non-pathogenicity. In particular, it has been observed that BRCA1 knockout mice are embryonically lethal, indicating that individuals with biallelic pathogenic BRCA1 mutations are not viable [12.Hakem R. de la Pompa J.L. Elia A. et al.The tumor suppressor gene BRCA1 is required for embryonic cellular proliferation in the mouse.Cell. 1996; 85: 1009-1023Abstract Full Text Full Text PDF PubMed Scopus (573) Google Scholar]. Furthermore, carriers of pathogenic homozygous or compound heterozygous BRCA2 mutations exhibit the clinical features of Fanconi anemia, a rare autosomal recessive disorder characterized by progressive bone marrow failure and cellular hypersensitivity to DNA cross-linking agents [13.Howlett N.G. Taniguchi T. Olson S. et al.Biallelic inactivation of BRCA2 in Fanconi anemia.Science. 2002; 297: 606-609Crossref PubMed Scopus (958) Google Scholar]. As concerns tumor characteristics, the investigation of histological, immunohistochemical and molecular features previously found to be preferentially associated with pathogenic mutations is potentially very helpful in classifying a UV as of likely clinical significance. However, it must be noted that the contribution of these analyses to multifactorial models depends on the nature of the gene under investigation. For example, while the majority of sporadic breast cancers are hormone receptor positive, breast cancers in carriers of pathogenic BRCA1 mutations usually exhibit a basal-like phenotype, characterized by the absence of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) protein expression and overexpression of cytokeratins 5/6, 14 and 17 [14.Honrado E. Benitez J. Palacios J. Histopathology of BRCA1- and BRCA2-associated breast cancer.Crit Rev Oncol Hematol. 2006; 59: 27-39Crossref PubMed Scopus (73) Google Scholar]. In contrast, BRCA2-linked tumors do not exhibit a similar preferentially associated phenotype and are difficult to distinguish from sporadic cases, although a few studies have used tubule formation, which has been reported to be an independent predictor of BRCA2 mutation status [15.Lakhani S.R. Gusterson B.A. Jacquemier J. et al.The pathology of familial breast cancer: histological features of cancers in families not attributable to mutations in BRCA1 or BRCA2.Clin Cancer Res. 2000; 6: 782-789PubMed Google Scholar], to classify UVs in this gene [16.Spurdle A.B. Lakhani S.R. Da Silva L.M. et al.Bayes analysis provides evidence of pathogenicity for the BRCA1 c.135–1G>T (IVS3-1) and BRCA2 c.7977–1G>C (IVS17-1) variants displaying in vitro splicing results of equivocal clinical significance.Hum Mutat. 2010; 31: E1141-E1145Crossref PubMed Scopus (9) Google Scholar, 10.Spurdle A.B. Clinical relevance of rare germline sequence variants in cancer genes: evolution and application of classification models.Curr Opin Genet Dev. 2010; 20: 315-323Crossref PubMed Scopus (33) Google Scholar]. Moreover, it is not yet clear whether the histopathological features of tumors in carriers of cancer-predisposing truncating mutations are identical to those associated with germline missense mutations. This points to a need for large datasets to clarify the correlation between mutations and tumor phenotype. LOH analyses are integrated into multifactorial classification models under the assumption that in the case of pathogenic mutations the loss of the constitutional wild-type allele is selected for. However, this has been recently disputed by a few studies that reported the loss in tumor DNA of the constitutional BRCA mutated allele [17.King T.A. Li W. Brogi E. et al.Heterogenic loss of the wild-type BRCA allele in human breast tumorigenesis.Ann Surg Oncol. 2007; 14: 2510-2518Crossref PubMed Scopus (75) Google Scholar, 18.Beristain E. Guerra I. Vidaurrazaga N. et al.LOH analysis should not be used as a tool to assess whether UVs of BRCA1/2 are pathogenic or not.Fam Cancer. 2010; 9: 289-290Crossref PubMed Scopus (10) Google Scholar]. Moreover, the probability values of the parameters that are employed to calculate LRs for LOH have not been verified. When this information is integrated into prediction models, the expected frequency in breast cancers from carriers of neutral variants is assumed to be the same as that observed in sporadic cases, i.e. ∼30% [2.Chenevix-Trench G. Healey S. Lakhani S. et al.Genetic and histopathologic evaluation of BRCA1 and BRCA2 DNA sequence variants of unknown clinical significance.Cancer Res. 2006; 66: 2019-2027Crossref PubMed Scopus (138) Google Scholar]. However, UVs are generally identified following the analysis of familial cases and accurate estimates of the actual frequencies of LOH at BRCA1 and BRCA2 loci in familial breast cancers unlinked to BRCA genes, which may differ from those of sporadic cases, are not available at present. Finally, a few recent studies have shown the feasibility of genome-wide analyses of tumor DNA in order to derive BRCA1 and BRCA2 classifiers that can help to distinguish pathogenic BRCA alleles from those without clinical importance [19.Joosse S.A. van Beers E.H. Tielen I.H. et al.Prediction of BRCA1-association in hereditary non- BRCA1/2 breast carcinomas with array-CGH.Breast Cancer Res Treat. 2009; 116: 479-489Crossref PubMed Scopus (112) Google Scholar, 20.Joosse S.A. Brandwijk K.I. Devilee P. et al.Prediction of BRCA2-association in hereditary breast carcinomas using array-CGH.Breast Cancer Res Treat. 2010; (July 8 [Epub ahead of print])PubMed Google Scholar]. The usefulness of the multifactorial models that have been developed to date for the analysis of UVs in BRCA genes is limited by the amount of data necessary to reach the odds ratios in favor of or against causality that are required for their reliable classification. Indeed, presently available likelihood methods are not able to classify as pathogenic or neutral the majority of UVs in BRCA1 and BRCA2, since these are usually detected in few families only, often in a single family [4.Easton D.F. Deffenbaugh A.M. Pruss D. et al.A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer-predisposition genes.Am J Hum Genet. 2007; 81: 873-883Abstract Full Text Full Text PDF PubMed Scopus (373) Google Scholar]. This provides a strong rationale for the use of complementary approaches for the analysis of UVs, such as mRNA transcript analysis and functional assays, under the assumption that these are highly accurate in detecting deleterious mutations. Moreover, it has been suggested that functional analyses could not only distinguish high-risk alleles from neutral variants, but also identify those associated with a moderate, although greater than the average, level of risk [21.Lovelock P.K. Spurdle A.B. Mok M.T. et al.Identification of BRCA1 missense substitutions that confer partial functional activity: potential moderate risk variants?.Breast Cancer Res. 2007; 9: R82Crossref PubMed Scopus (51) Google Scholar]. A large number of studies have demonstrated that in vitro analyses can efficiently identify spliceogenic allelic variants. i.e. those affecting the stability and integrity of mRNA transcripts of BRCA genes [22.Bonnet C. Krieger S. Vezain M. et al.Screening BRCA1 and BRCA2 unclassified variants for splicing mutations using reverse transcription PCR on patient RNA and an ex vivo assay based on a splicing reporter minigene.J Med Genet. 2008; 45: 438-446Crossref PubMed Scopus (103) Google Scholar, 23.Campos B. Diez O. Domenech M. et al.RNA analysis of eight BRCA1 and BRCA2 unclassified variants identified in breast/ovarian cancer families from Spain.Hum Mutat. 2003; 22: 337Crossref PubMed Scopus (35) Google Scholar, 24.Chen X. Truong T.T. Weaver J. et al.Intronic alterations in BRCA1 and BRCA2: effect on mRNA splicing fidelity and expression.Hum Mutat. 2006; 27: 427-435Crossref PubMed Scopus (59) Google Scholar, 25.Claes K. Poppe B. Machackova E. et al.Differentiating pathogenic mutations from polymorphic alterations in the splice sites of BRCA1 and BRCA2.Genes Chromosomes Cancer. 2003; 37: 314-320Crossref PubMed Scopus (74) Google Scholar, 26.Sanz D.J. Acedo A. Infante M. et al.A high proportion of DNA variants of BRCA1 and BRCA2 is associated with aberrant splicing in breast/ovarian cancer patients.Clin Cancer Res. 2010; 16: 1957-1967Crossref PubMed Scopus (83) Google Scholar, 27.Tesoriero A.A. Wong E.M. Jenkins M.A. et al.Molecular characterization and cancer risk associated with BRCA1 and BRCA2 splice site variants identified in multiple-case breast cancer families.Hum Mutat. 2005; 26: 495Crossref PubMed Scopus (45) Google Scholar, 28.Vreeswijk M.P. Kraan J.N. van der Klift H.M. et al.Intronic variants in BRCA1 and BRCA2 that affect RNA splicing can be reliably selected by splice-site prediction programs.Hum Mutat. 2009; 30: 107-114Crossref PubMed Scopus (83) Google Scholar]. Following these observations, guidelines have been developed for the clinical classification of tested UVs according to experimental results [29.Spurdle A.B. Couch F.J. Hogervorst F.B. et al.Prediction and assessment of splicing alterations: implications for clinical testing.Hum Mutat. 2008; 29: 1304-1313Crossref PubMed Scopus (100) Google Scholar]. A few aspects of mRNA analyses for the classification of UVs remain to be clarified. It has been observed that some UVs can alter the expression level, as compared with the full-length transcript of physiological mRNA isoforms [30.Walker L.C. Whiley P.J. Couch F.J. et al.Detection of splicing aberrations caused by BRCA1 and BRCA2 sequence variants encoding missense substitutions: implications for prediction of pathogenicity.Hum Mutat. 2010; 31: E1484-E1505Crossref PubMed Scopus (51) Google Scholar]. In other instances, it has been reported that the mutated allele retains the capacity to transcribe, in addition to the mutated allele, also the wild-type allele. Whether and how these phenomena impact on the level of cancer risk is at present unclear [28.Vreeswijk M.P. Kraan J.N. van der Klift H.M. et al.Intronic variants in BRCA1 and BRCA2 that affect RNA splicing can be reliably selected by splice-site prediction programs.Hum Mutat. 2009; 30: 107-114Crossref PubMed Scopus (83) Google Scholar, 30.Walker L.C. Whiley P.J. Couch F.J. et al.Detection of splicing aberrations caused by BRCA1 and BRCA2 sequence variants encoding missense substitutions: implications for prediction of pathogenicity.Hum Mutat. 2010; 31: E1484-E1505Crossref PubMed Scopus (51) Google Scholar]. Finally, mRNA analyses are usually carried out using lymphocytes of lymphoblastoid cell lines as a source of mRNA or through the use of a splicing minigene reporter. Whether the effect of spliceogenic mutations is different in tissues that are specific targets of cancer risks, as for example the breast and ovarian epithelia in the case of the BRCA genes, is still to be verified. A number of in vitro assays have been set up to study the effects of variants on gene function. However, it has to be remarked that these tests may have limited informativeness due to the multifunctionality of the examined genes. In addition, although it has been demonstrated by multifactorial models that the vast majority of pathogenic missense mutations lie in gene regions coding for functional domains [4.Easton D.F. Deffenbaugh A.M. Pruss D. et al.A systematic genetic assessment of 1,433 sequence variants of unknown clinical significance in the BRCA1 and BRCA2 breast cancer-predisposition genes.Am J Hum Genet. 2007; 81: 873-883Abstract Full Text Full Text PDF PubMed Scopus (373) Google Scholar] the correlation between the effect measured in vitro and cancer risk may be difficult to establish. Several important biological roles for BRCA1 and BRCA2 have been demonstrated, and a number of observations indicate that they function in similar cellular pathways. Both genes maintain genomic stability through their involvement in homologous recombination, transcription-coupled repair of oxidative DNA damage and double-strand break (DSB) repair, and represent substrates of enzymic reactions. This indicates that the cells in which BRCA1 and BRCA2 proteins are impaired, are more sensitive to DNA damage, which can be exploited to design a series of functional assays. A few of these assays are described below. The C-terminal region of BRCA1 acts as a transactivation domain when expressed as a fusion with a heterologous DNA binding domain (DBD) [31.Monteiro A.N. August A. Hanafusa H. Evidence for a transcriptional activation function of BRCA1 C-terminal region.Proc Natl Acad Sci USA. 1996; 93: 13595-13599Crossref PubMed Scopus (428) Google Scholar, 32.Monteiro A.N. Birge R.B. A nuclear function for the tumor suppressor BRCA1.Histol Histopathol. 2000; 15: 299-307PubMed Google Scholar] and cancer-predisposing mutations have been shown to confer loss of such activity [33.Vallon-Christersson J. Cayanan C. et al.Functional analysis of BRCA1 C-terminal missense mutations identified in breast and ovarian cancer families.Hum Mol Genet. 2001; 10: 353-360Crossref PubMed Scopus (148) Google Scholar, 34.Phelan C.M. Dapic V. Tice B. et al.Classification of BRCA1 missense variants of unknown clinical significance.J Med Genet. 2005; 42: 138-146Crossref PubMed Scopus (82) Google Scholar, 35.Carvalho M.A. Marsillac S.M. Karchin R. et al.Determination of cancer risk associated with germ line BRCA1 missense variants by functional analysis.Cancer Res. 2007; 67: 1494-1501Crossref PubMed Scopus (100) Google Scholar]. Fusion proteins encoding the DBD of the LexA or GAL4 transcription factor and the BRCA1 C terminus, wild-type and mutants (amino acids 1560–1863), expressed in yeast and mammalian cells respectively, are analyzed for the activation of transcription in vitro using the LacZ gene and luciferase gene as a reporter [35.Carvalho M.A. Marsillac S.M. Karchin R. et al.Determination of cancer risk associated with germ line BRCA1 missense variants by functional analysis.Cancer Res. 2007; 67: 1494-1501Crossref PubMed Scopus (100) Google Scholar]. Transformation of vectors encoding fusion proteins containing the C-terminus of BRCA1 in yeast cells inhibits growth and results in the formation of small colonies generating the so-called small colony phenotype (SCP), which can be evaluated qualitatively or quantitatively by counting the number of cells present in each colony. This growth phenotype is abolished by cancer-predisposing mutations; this result indicates that SCP may be due to a mechanism analogous to BRCA1 tumor suppression in human cells or to a generic transcriptional squelching [36.Humphrey J.S. Salim A. Erdos M.R. et al.Human BRCA1 inhibits growth in yeast: potential use in diagnostic testing.Proc Natl Acad Sci USA. 1997; 94: 5820-5825Crossref PubMed Scopus (98) Google Scholar, 37.Gill G. Sadowski I. Ptashne M. Mutations that increase the activity of a transcriptional activator in yeast and mammalian cells.Proc Natl Acad Sci USA. 1990; 87: 2127-2131Crossref PubMed Scopus (48) Google Scholar], and, importantly, it highlights its potential use in diagnostic testing [38.Coyne R.S. McDonald H.B. Edgemon K. Brody L.C. Functional characterization of BRCA1 sequence variants using a yeast small colony phenotype assay.Cancer Biol Ther. 2004; 3: 453-457Crossref PubMed Scopus (35) Google Scholar, 39.Caligo M.A. Bonatti F. Guidugli L. et al.A yeast recombination assay to characterize human BRCA1 missense variants of unknown pathological significance.Hum Mutat. 2009; 30: 123-133Crossref PubMed Scopus (33) Google Scholar]. BRCA1 exists a stable heterodimer with BARD1 [40.Wu L.C. Wang Z.W. Tsan J.T. et al.Identification of a RING protein that can interact in vivo with the BRCA1 gene product.Nat Genet. 1996; 14: 430-440Crossref PubMed Scopus (618) Google Scholar], which ensures genome stability through its role in protein ubiquitylation [41.Starita L.M. Machida Y. Sankaran S. et al.BRCA1-dependent ubiquitination of γ-tubulin regulates centrosome number.Mol Cell Biol. 2004; 24: 8457-8466Crossref PubMed Scopus (249) Google Scholar]. The clinical importance of the BRCA1–BARD1 ubiquitin ligase activity is shown by the presence of mutations on the RING domain of BRCA1 in tumor samples, which inactivate its enzymic activity [42.Hashizume R. Fukuda M. Maeda I. et al.The ring heterodimer BRCA1-BARD1 is a ubiquitin ligase inactivated by a breast cancer-derived mutation.J Biol Chem. 2001; 276: 14537-14540Crossref PubMed Scopus (543) Google Scholar]. Furthermore, variants that have been unambiguously classified as cancer predisposing, e.g. the C61G, lead to the inactivation of ubiquitin ligase activity. An approach to the systematic classification of BRCA1 variants mapped in the RING domain is described in Morris et al. [43.Morris J.R. Pangon L. Boutell C. et al.Genetic analysis of BRCA1 ubiquitin ligase activity and its relationship to breast cancer susceptibility.Hum Mol Genet. 2006; 15: 599-606Crossref PubMed Scopus (87) Google Scholar] and combines yeast two-hybrid screening of the mutagenized BRCA1 N-terminal region against BARD1 or UbcH5a and in vitro ubiquitination assay. BRCA1 expression restores radiation resistance in BRCA1-defective cancer cells through enhancement of transcription-coupled DNA repair. The test consists in a retroviral infection approach: HCC1937 cells, functionally null for BRCA1, are infected with the full-length BRCA1 wild-type and mutant constructs containing green fluorescent protein (GFP), acutely irradiated with ionizing radiation 48 h later, then allowed to grow for 18 days. γ-Radiation sensitivity is evaluated as growth of GFP-positive (expressing wild-type or variant BRCA1) cells compared with GFP-negative (non-infected control) cells by fluorescence-activated cell sorter analysis [44.Abbott D.W. Thompson M.E. Robinson-Benion C. et al.BRCA1 expression restores radiation resistance in BRCA1-defective cancer cells through enhancement of transcription-coupled DNA repair.J Biol Chem. 1999; 274: 18808-18812Crossref PubMed Scopus (205) Google Scholar]. The test is based on the observation that BRCA1 is essential for the viability of mouse embryonic stem (ES) cells [45.Gowen L.C. Johnson B.L. Latour A.M. et al.Brca1 deficiency results in early embryonic lethality characterized by neuroepithelial abnormalities.Nat Genet. 1996; 12: 191-194Crossref PubMed Scopus (394) Google Scholar, 12.Hakem R. de la Pompa J.L. Elia A. et al.The tumor suppressor gene BRCA1 is required for embryonic cellular proliferation in the mouse.Cell. 1996; 85: 1009-1023Abstract Full Text Full Text PDF PubMed Scopus (573) Google Scholar]. The experimental design is reported in Chang [46.Chang S. Biswas K. Martin B.K. et al.Expression of human BRCA1 variants in mouse ES cells allows functional analysis of BRCA1 mutations.J Clin Invest. 2009; 119: 3160-3171Crossref PubMed Scopus (59) Google Scholar]. Briefly, Brca1-null ES cells are complemented with BAC clones containing full-length human wild-type BRCA1 or variants, and assayed to determine the effects of BRCA1 variants on cell lethality, cell cycle regulation, differentiation and genomic stability. As expected, only wild-type and neutral variants rescue the lethality of Brca1-null ES cells and also complement known functions of BRCA1. Conversely, deleterious variants may either fail to rescue the ES cell lethality or may not be fully functional. To evaluate the fidelity of DSB repair and, in particular, that mediated by homologous recombination, the pDR-GFP-I-SceI approach is used [47.Pierce A.J. Johnson R.D. Thompson L.H. Jasin M. XRCC3 promotes homology-directed repair of DNA damage in mammalian cells.Genes Dev. 1999; 13: 2633-2638Crossref PubMed Scopus (1039) Google Scholar]. The I-SceI system can be used to examine the types of recombination events induced by DSBs at a defined chromosomal locus in mammalian cells by the nuclease I-SceI, which is known to stimulate recombination. The advantage of the pDR-GFP-I-SceI system is that it uses a GFP-modified gene as a recombination reporter [47.Pierce A.J. Johnson R.D. Thompson L.H. Jasin M. XRCC3 promotes homology-directed repair of DNA damage in mammalian cells.Genes Dev. 1999; 13: 2633-2638Crossref PubMed Scopus (1039) Google Scholar]. The 18-bp I-SceI site is inserted within the GFP gene and inactivates it. When the DSBs are induced by I-SceI endonuclease, a homologous repair event with a linked donor GFP gene fragment restores functional GFP expression. These gene conversion events can be readily detected by flow cytometry within 2–4 days [47.Pierce A.J. Johnson R.D. Thompson L.H. Jasin M. XRCC3 promotes homology-directed repair of DNA damage in mammalian cells.Genes Dev. 1999; 13: 2633-2638Crossref PubMed Scopus (1039) Google Scholar]. For this approach, BRCA2-deficient cells are transfected with the pDR-GFP-I-SceI constructs and the I-SceI endonuclease into cells made to express wild-type and mutant forms of BRCA [48.Farrugia D.J. Agarwal M.K. Pankratz V.S. et al.Functional assays for classification of BRCA2 variants of uncertain significance.Cancer Res. 2008; 68: 3523-3531Crossref PubMed Scopus (102) Google Scholar]. BRCA2-deficient cells are extremely sensitive to agents that induce interstrand cross-linking such as mitomycin C (MMC) [49.Kraakman-van der Zwet M. Wiegant W.W. Zdzienicka M.Z. Brca2 (XRCC11) deficiency results in enhanced mutagenesis.Mutagenesis. 2003; 18: 521-525Crossref PubMed Scopus (15) Google Scholar]. Thus a functional assay that uses clonogenic survival has been developed: BRCA2-deficient immortalized fibroblasts are complemented with exogenous wild-type or mutant forms of BRCA2 and assayed for MMC sensitivity evaluated as survival to increasing doses of MMC, or by estimating the percentage of cells with chromosomal aberrations [50.Godthelp B.C. Wiegant W.W. Waisfisz Q. et al.Inducibility of nuclear Rad51 foci after DNA damage distinguishes all Fanconi anemia complementation groups from D1/BRCA2.Mutat Res. 2006; 594: 39-48Crossref PubMed Scopus (66) Google Scholar]. BRCA2-deficient cells have significant aneuploidy and centrosome amplification [51.Tutt A. Gabriel A. Bertwistle D. et al.Absence of Brca2 causes genome instability by chromosome breakage and loss associated with centrosome amplification.Curr Biol. 1999; 9: 1107-1110Abstract Full Text Full Text PDF PubMed Scopus (258) Google Scholar, 52.Yu V.P. Koehler M. Steinlein C. et al.Gross chromosomal rearrangements and genetic exchange between non homologous chromosomes following BRCA2 inactivation.Genes Dev. 2000; 14: 1400-1406PubMed Google Scholar]. To measure the influence of BRCA2 variants on centrosome number a functional assay has been proposed. Briefly, 293T cells are transfected with GFP-tagged full-length wild-type or mutant forms of BRCA2 and after 72 h are subjected to direct immunofluorescence using α-centrin-2 antibodies to detect centrioles and centrosomes [53.Wu K. Hinson S.R. Ohashi A. et al.Functional evaluation and cancer risk assessment of BRCA2 unclassified variants.Cancer Res. 2005; 65: 417-426Crossref PubMed Scopus (148) Google Scholar]. Computational analysis is another widely used approach for the classification of UVs. Presently, many in silico programs can be used to assess the effects of UVs on mRNA splicing (reviewed in [29.Spurdle A.B. Couch F.J. Hogervorst F.B. et al.Prediction and assessment of splicing alterations: implications for clinical testing.Hum Mutat. 2008; 29: 1304-1313Crossref PubMed Scopus (100) Google Scholar]). However, the sensitivity and specificity of this these programs in correctly classifying an allelic variant as pathogenic or neutral are still to be precisely assessed and vary according to its position within the gene [10.Spurdle A.B. Clinical relevance of rare germline sequence variants in cancer genes: evolution and application of classification models.Curr Opin Genet Dev. 2010; 20: 315-323Crossref PubMed Scopus (33) Google Scholar]. Moreover, even mutations that are correctly predicted to be spliceogenic may not necessarily be pathogenic. In fact, while UVs that give rise to transcripts carrying a premature protein translation termination codon can reliably be assumed to be pathogenic, those leading to an in-frame deletion (or insertion) not altering a functional domain are considered of uncertain significance [29.Spurdle A.B. Couch F.J. Hogervorst F.B. et al.Prediction and assessment of splicing alterations: implications for clinical testing.Hum Mutat. 2008; 29: 1304-1313Crossref PubMed Scopus (100) Google Scholar]. As already mentioned, computational analyses based on sequence homology and physical properties of amino acids can provide the first calculation of prior probability of pathogenicity for UVs. Align-GVGD (http://agvgd.iarc.fr/alignments.php) predicts whether a mutation is neutral or not combining protein multiple sequence alignments with biophysical characteristics of amino acids. PolyPhen (http://genetics.bwh.harvard.edu/pph/) and SIFT (http://blocks.fhcrc.org/sift/SIFT.html) software predict the effects of UVs on structure and function of protein, when mutation leads to an amino acid substitution. Recently, bioinformatic analyses of the effect of missense variants on protein structure have also been applied to the classification of UVs [54.De Nicolo A. Parisini E. Zhong Q. et al.Multimodal assessment of protein functional deficiency supports pathogenicity of BRCA1 p.V1688del.Cancer Res. 2009; 69: 7030-7037Crossref PubMed Scopus (16) Google Scholar, 55.Karchin R. Agarwal M. Sali A. et al.Classifying variants of undetermined significance in BRCA2 with protein likelihood ratios.Cancer Inform. 2008; 6: 203-216Crossref PubMed Google Scholar]. Irrespective of the difficulties and limitations of the above-described methods, the use of quantitative measurements such as those derived from multifactorial prediction models, is considered the more appropriate approach for the clinical interpretation and use of UVs in cancer-predisposing genes. Along this line, in the course of a workshop recently held at the International Agency for Cancer Research (IARC), a panel of experts have developed a classification scheme including five different classes [56.Plon S.E. Eccles D.M. Easton D. et al.Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results.Hum Mutat. 2008; 29: 1282-1291Crossref PubMed Scopus (652) Google Scholar]. According to this scheme, an allelic variant with a probability of being pathogenic of >0.99 is classified as ‘definitely pathogenic’ (class 5), whereas those with a probability of <0.01 are classified as ‘non-pathogenic or of no clinical significance’ (class 1). Intermediate classes include variants with probabilities in favor of pathogenicity ranging from 0.95 to 0.99 (‘likely pathogenic’, class 4); from 0.05 to 0.95 (‘uncertain’, class 3); and from 0.01 to 0.05 (‘likely non-pathogenic or of little clinical significance’). This subdivision has important consequences for the clinical management of carriers of UVs. In fact, the IARC working group recommend that the testing of at-risk relatives be limited to variants classified as class 4 or 5, although testing relatives of carriers of class 2–4 variants may be recommended to further refine their classification. Carriers of class 4 and 5 variants are advised to undergo surveillance according to the guidelines recommendations for high-risk individuals, whereas for carriers of class 3 variants surveillance should be based on family history and other known risk factors for the disease. Finally, carriers of class 1 and 2 variants are treated as individuals with no mutation detected in the analyzed gene. Different working groups have organized UV databases, which include the results of analyses of different laboratories on each UV. Besides the BIC database (www.research.nhgri.nih.gov/bic/), which contains all freely reported BRCA1 and BRCA2 pathological, neutral and unclassified variants, two specific databases for UVs have been set up. IARC established a BRCA1 and BRCA2 database (http://brca.iarc.fr/LOVD/ in which UVs are classified according to the IARC classification scheme using a multifactorial likelihood model. As of 25 October 2009, this database contains 44 entries for BRCA1 and 21 entries for BRCA2. The Leiden University Medical Centre established a reference literature database of BRCA1 and BRCA2 UVs (http://chromium.liacs.nl/LOVD2/cancer/home.php). This database allows the times a variant is listed, i.e. the number of publications in which the variant is reported, to be counted. As of June 2010, this database contains 502 entries for BRCA1 and 487 entries for BRCA2. Recently, the ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles; http://www.enigmaconsortium.org) consortium has been established with the purpose of obtaining large datasets of data on UVs in cancer susceptibility genes. Given the rarity of UVs, the possibility of obtaining results from international studies could make feasible the establishment of a classification model with development of bioinformatic software. Integrated studies of UVs are the best way to understand their role in cancer risk and to improve diagnostic tests. Combination of genetic, epidemiological, in vitro and in silico data with tumor histopathological features allows reliable LRs to be obtained To this end, it is important to collect a large amount of data, which can be achieved through the collaboration of several working groups. The ENIGMA consortium is an initiative that can allow optimization of multifactorial models through implementation of currently employed approaches. Eventually, international efforts for the analysis of UVs will lead to univocal interpretation of each identified variant." @default.
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