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== Classification ==
== Classification ==
[[File:Cost per Genome.png|thumb|Since the [[Human Genome Project]] first sequenced the [[human genome]] in 2001 at a cost of US$100 million, costs have fallen precipitously, outpacing even [[Moore's law]], and were ≈US$1,000 in 2015. More widely available genome sequencing has led to more available data on variants of uncertain significance.]]In 2015, the [[American College of Medical Genetics and Genomics]] (ACMG), the [https://www.amp.org/about/who-we-are/ Association for Molecular Pathology] (AMP), and the [[College of American Pathologists]] (CAP) published a third revision of their guidelines on variant interpretation in [[Genetic disorder|Mendelian disorders]].<ref name="PMID25741868" /> The publication recommended the following categories: ''pathogenic'', ''likely pathogenic'', ''uncertain significance'', ''likely benign'', and ''benign''. This guideline is one of many resources published by the ACMG in hopes of improving standardization of variant interpretation and reporting.<ref name="PMID25741868" /><ref>{{Cite web|title=Medical Genetics Practice Resources|url=https://www.acmg.net/ACMG/Medical-Genetics-Practice-Resources/Practice_Resources/ACMG/Medical-Genetics-Practice-Resources/Medical-Genetics-Practice-Resources.aspx?hkey=d56a0de8-cfb0-4c6e-bf1e-ffb96e5f86aa|access-date=2020-11-23|website=www.acmg.net}}</ref><ref name=":0">{{Cite journal|last=Kim|first=Young-Eun|last2=Ki|first2=Chang-Seok|last3=Jang|first3=Mi-Ae|date=September 2019|title=Challenges and Considerations in Sequence Variant Interpretation for Mendelian Disorders|url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6502951/|journal=Annals of Laboratory Medicine|volume=39|issue=5|pages=421–429|doi=10.3343/alm.2019.39.5.421|issn=2234-3806|pmc=6502951|pmid=31037860|via=}}</ref><ref name=":1">{{Cite journal|last=Amendola|first=Laura|last2=Jarvik|first2=Gail|last3=Leo|first3=Michael|last4=McLaughlin|first4=Heather|last5=Akkari|first5=Yassmine|last6=Amaral|first6=Michelle|last7=Berg|first7=Jonathan|last8=Biswas|first8=Sawona|last9=Bowling|first9=Kevin|last10=Conlin|first10=Laura|last11=Cooper|first11=Greg|date=June 2016|title=Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium|url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4908185/|journal=American Journal of Human Genetics|volume=98|issue=6|pages=1067–1076|doi=10.1016/j.ajhg.2016.03.024|issn=0002-9297|pmc=4908185|pmid=27181684|via=}}</ref><ref>{{Cite journal|last=Riggs|first=Erin Rooney|last2=Andersen|first2=Erica F.|last3=Cherry|first3=Athena M.|last4=Kantarci|first4=Sibel|last5=Kearney|first5=Hutton|last6=Patel|first6=Ankita|last7=Raca|first7=Gordana|last8=Ritter|first8=Deborah I.|last9=South|first9=Sarah T.|last10=Thorland|first10=Erik C.|last11=Pineda-Alvarez|first11=Daniel|date=February 2020|title=Technical standards for the interpretation and reporting of constitutional copy number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen)|url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7313390/|journal=Genetics in medicine : official journal of the American College of Medical Genetics|volume=22|issue=2|pages=245–257|doi=10.1038/s41436-019-0686-8|issn=1098-3600|pmc=7313390|pmid=31690835|via=}}</ref>
[[File:Cost per Genome.png|thumb|Since the [[Human Genome Project]] first sequenced the [[human genome]] in 2001 at a cost of US$100 million, costs have fallen precipitously, outpacing even [[Moore's law]], and were ≈US$1,000 in 2015. More widely available genome sequencing has led to more available data on variants of uncertain significance.]]

A consistent variant classification system is central to the use of [[genomics]] in patient care. However, in the USA (and probably the rest of the world) there are no federal laws governing the classification of variants or how they are presented to clients. {{As of|2017}}, US government agencies have limited involvement in regulating genomic testing.<ref>{{cite web|last1=anon|title=Regulation of Genetic Tests|url=https://www.genome.gov/10002335/regulation-of-genetic-tests/|website=NIH|publisher=National Human Genome Research Institute|accessdate=20 January 2017}}</ref> A publication from May 2015, based on a workgroup from 2013, lists 5 recommended classification categories based on expert opinion.<ref name="pmid25741868">{{cite journal | vauthors = Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL | title = Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology | journal = Genetics in Medicine | volume = 17 | issue = 5 | pages = 405–24 | year = 2015 | pmid = 25741868 | pmc = 4544753 | doi = 10.1038/gim.2015.30 | department = guideline }}</ref> Those categories are ''pathogenic'', ''likely pathogenic'', ''uncertain significance'', ''likely benign'', and ''benign''.
{{As of|2020|}}, there continues to be limited involvement from federal agencies to regulate the clinical validity (accuracy) and utility (risks and benefits) of genetic testing.<ref>{{cite web|last1=|first=|date=|title=Regulation of Genetic Tests|url=https://www.genome.gov/10002335/regulation-of-genetic-tests/|url-status=live|archive-url=|archive-date=|accessdate=20 January 2017|website=NIH|publisher=National Human Genome Research Institute}}</ref><ref>{{Cite journal|last=Burke|first=Wylie|date=2014-04-24|title=Genetic Tests:Clinical Validity and Clinical Utility|url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4084965/|journal=Current protocols in human genetics / editorial board, Jonathan L. Haines ... [et al.]|volume=81|pages=9.15.1–9.15.8|doi=10.1002/0471142905.hg0915s81|issn=1934-8266|pmc=4084965|pmid=24763995}}</ref><ref name=":2">{{Cite journal|last=Evans|first=Barbara J.|last2=Javitt|first2=Gail|last3=Hall|first3=Ralph|last4=Robertson|first4=Megan|last5=Ossorio|first5=Pilar|last6=Wolf|first6=Susan M.|last7=Morgan|first7=Thomas|last8=Clayton|first8=Ellen Wright|date=2020-03-01|title=How Can Law and Policy Advance Quality in Genomic Analysis and Interpretation for Clinical Care?|url=https://doi.org/10.1177/1073110520916995|journal=The Journal of Law, Medicine & Ethics|language=en|volume=48|issue=1|pages=44–68|doi=10.1177/1073110520916995|issn=1073-1105|pmc=PMC7447152|pmid=32342785}}</ref> Variant interpretation and classification is notably subjective, as laboratories developed their own criteria prior to the ACMG-AMP guidelines. <ref name=":0" /><ref name=":1" /><ref>{{Cite journal|last=Hoskinson|first=Derick C.|last2=Dubuc|first2=Adrian M.|last3=Mason-Suares|first3=Heather|date=February 2017|title=The Current State of Clinical Interpretation of Sequence Variants|url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5446800/|journal=Current opinion in genetics & development|volume=42|pages=33–39|doi=10.1016/j.gde.2017.01.001|issn=0959-437X|pmc=5446800|pmid=28157586|via=}}</ref> This subjectiveness is further problematic when there is evidence that variant significance changes over time.<ref name=":2" /> Due to the lack of consistency in official guidelines, the genomics community is left struggling to efficiently categorize genetic variants.<ref name=":1" /><ref>{{Cite journal|last=Amendola|first=Laura M.|last2=Dorschner|first2=Michael O.|last3=Robertson|first3=Peggy D.|last4=Salama|first4=Joseph S.|last5=Hart|first5=Ragan|last6=Shirts|first6=Brian H.|last7=Murray|first7=Mitzi L.|last8=Tokita|first8=Mari J.|last9=Gallego|first9=Carlos J.|last10=Kim|first10=Daniel Seung|last11=Bennett|first11=James T.|date=March 2015|title=Actionable exomic incidental findings in 6503 participants: challenges of variant classification|url=https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4352885/|journal=Genome Research|volume=25|issue=3|pages=305–315|doi=10.1101/gr.183483.114|issn=1088-9051|pmc=4352885|pmid=25637381|via=}}</ref><ref>{{Cite journal|last=Hoffman-Andrews|first=Lily|date=2017-12-01|title=The known unknown: the challenges of genetic variants of uncertain significance in clinical practice|url=https://academic.oup.com/jlb/article/4/3/648/4820755|journal=Journal of Law and the Biosciences|language=en|volume=4|issue=3|pages=648–657|doi=10.1093/jlb/lsx038}}</ref>


=== Pathogenic ===
=== Pathogenic ===

Revision as of 22:26, 23 November 2020

A variant of uncertain (or unknown) significance (VUS) is a genetic variant that has been identified through genetic testing but whose significance to the function or health of an organism is not known.[1] Two related terms are "gene of uncertain significance" (GUS), which refers to a gene that has been identified through genome sequencing but whose connection to a human disease has not been established, and "insignificant mutation", referring to a gene variant that has no impact on the health or function of an organism. The term "variant' is favored in clinical practice over "mutation" because it can be used to describe an allele more precisely (i.e. without inherently connoting pathogenicity). When the variant has no impact on health, it is called a "benign variant". When it is associated with a disease, it is called a "pathogenic variant". A "pharmacogenomic variant" has an effect only when an individual takes a particular drug and therefore is neither benign nor pathogenic.[1]

A VUS is most commonly encountered by people when they get the results of a lab test looking for a mutation in a particular gene. For example, many people know that mutations in the BRCA1 gene are involved in the development of breast cancer because of the publicity surrounding Angelina Jolie's preventative treatment.[2] Few people are aware of the immense number of other genetic variants in and around BRCA1 and other genes that may predispose to hereditary breast and ovarian cancer. A recent study of the genes ATM, BRCA1, BRCA2, CDH1, CHEK2, PALB2 and TP53 found 15,311 DNA sequence variants in only 102 patients.[3] Many of those 15,311 variants have no significant phenotypic effect. That is, a difference can be seen in the DNA sequence, but the differences have no effect on the growth or health of the person.[3]

Identifying variants that are significant or likely to be significant is a difficult task that may require expert human and in silico analysis, laboratory experiments and even information theory.[3] In spite of those efforts, many people may be worried about their particular VUS, even though it has not been determined to be significant or likely to be significant. Most discovered VUSs will not be investigated in a peer-reviewed research paper, as this effort is usually reserved for likely pathogenic variants.

History

This blood smear shows a white blood cell and several "sickled" cells (one at the tip of the arrow) mixed in with many normal red blood cells.

Sickle cell anemia is widely considered to be the first "molecular disease".[4] From earlier protein biochemistry, it was known that the disease was caused by a mutation in the β-globin gene. In 1977, in the third of a series of 3 research papers published in The Journal of Biological Chemistry, this mutation was identified as a single base transversion of adenosine to uridine.[5]

In 2001, an initial draft of the human genome was published by the International Human Genome Sequencing Consortium.[6] With the development of next-generation sequencing, the cost of sequencing has plummeted and the number of human genomes and exomes sequenced each year is increasing dramatically.[7] As of 2017, the cost of a quality whole genome sequence is $1,000 or less.[8] If the ratio of approximately 20 DNA sequence variants per gene[3] holds over the entire genome (with approximately 20,000 genes) that means that every person who elects to have their genome sequenced will be provided with almost half a million Variants of Unknown Significance. To assist people to understand the meaning of all these variants, classification is a first step.

Classification

Since the Human Genome Project first sequenced the human genome in 2001 at a cost of US$100 million, costs have fallen precipitously, outpacing even Moore's law, and were ≈US$1,000 in 2015. More widely available genome sequencing has led to more available data on variants of uncertain significance.

In 2015, the American College of Medical Genetics and Genomics (ACMG), the Association for Molecular Pathology (AMP), and the College of American Pathologists (CAP) published a third revision of their guidelines on variant interpretation in Mendelian disorders.[1] The publication recommended the following categories: pathogenic, likely pathogenic, uncertain significance, likely benign, and benign. This guideline is one of many resources published by the ACMG in hopes of improving standardization of variant interpretation and reporting.[1][9][10][11][12]

As of 2020, there continues to be limited involvement from federal agencies to regulate the clinical validity (accuracy) and utility (risks and benefits) of genetic testing.[13][14][15] Variant interpretation and classification is notably subjective, as laboratories developed their own criteria prior to the ACMG-AMP guidelines. [10][11][16] This subjectiveness is further problematic when there is evidence that variant significance changes over time.[15] Due to the lack of consistency in official guidelines, the genomics community is left struggling to efficiently categorize genetic variants.[11][17][18]

Pathogenic

This category is for variants that are identical to previously-described variants for which there is excellent data indicating it causes a particular disease.

Likely pathogenic

This category is for variants that have never been found before. However, they are in a gene that is known to cause disease, and appear to affect important structure or function of the encoded protein.

Uncertain significance

This category is for variants that have not been reported previously. These variants change an amino acid residue that is conserved in the corresponding protein in other mammals.

Likely benign

This category is for variants that have been seen before, are not exceedingly rare, and for which in silico analysis predicts a benign effect on the encoded protein.

Benign

This category is for variants that have been seen previously at a higher frequency, in silico analysis predicts a benign effect on the encoded protein, and a sibling of the patient with the same disease symptoms does not have the variant.

Limitations of the classifications

Less than 5% of the human genome encodes proteins, and the rest is associated with non-coding RNA molecules, regulatory DNA sequences, LINEs, SINEs, introns, and sequences for which as yet no function has been determined.[6] Thus, only a small fraction of the almost half-million VUS's that are expected to be identified by whole genome sequencing can be categorized into the 5 categories above, leaving the patient nearly as uninformed about their variants as they would have been without this information.

Most of the base sequences regulating gene expression are found outside of protein-coding sequences, either within introns or outside of genes in intergenic regions. Changes in those regulatory regions can lead to dysfunction of a gene(s) and produce phenotypic effects that can be relevant to health and function.[19]

An example of a variant in an intergenic enhancer is one that is associated with blond hair color in northern Europeans. The variant in an enhancer of the KITLG gene causes only a 20% change in gene expression, yet causes hair lightening.[19][20]

An example of an intronic VUS controlling gene expression is the SNP found in an intron of the FTO gene. The FTO gene encodes the fat mass and obesity-associated protein, and the SNP (or VUS) found in its intron was shown by genome-wide association studies to be associated with an increased risk for obesity and diabetes. The initial assumption was that this mutation was misregulating FTO to cause the disease risk. However, it was later shown that the intronic variant was in fact regulating the distant IRX3 gene and not the FTO gene.[21] That is just one example of how difficult it can be to determine the significance of a VUS even when many research labs are focused on it, and it illustrates that clinicians cannot reliably interpret genetic results that have not been fully clarified by prior research.

Applications

The number of VUS reports makes it impossible to mention all such reports. To give a flavor for some applications in one field, it is perhaps of most interest to focus on breast cancer. Remember, this is only a fraction of the information available world-wide about VUS reports related to breast cancer, and as always, your results may vary.

In a 2009 US study of over 200 women who received BRCA VUS reports and were surveyed for one year thereafter, distress over the result persisted for the year.[22]

A 2012 survey of patient outcomes in the Netherlands found that, after genetic counseling for BRCA VUS, patients perceived themselves to have different cancer risks than what had been explained to them by genetic counselors, and that this misperception influenced decisions about radical medical procedures.[23]

In a 2015 study in the UK, where BRCA VUSs occur in 10-20% of tests, 39% of breast cancer specialists taking part in the study did not know how to explain a VUS report to a patient with no family history, and 71% were unsure about the clinical implications of the test reports.[24]

References

  1. ^ a b c d Richards S, Aziz N, Bale S, Bick D, Das S, Gastier-Foster J, Grody WW, Hegde M, Lyon E, Spector E, Voelkerding K, Rehm HL (May 2015). "Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology". guideline. Genetics in Medicine. 17 (5): 405–24. doi:10.1038/gim.2015.30. PMC 4544753. PMID 25741868.
  2. ^ Reinberg, S. "Angelina Jolie's Mastectomy and Gene Testing Rise". WebMD. WebMD. Retrieved 20 January 2017.
  3. ^ a b c d Mucaki EJ, Caminsky NG, Perri AM, Lu R, Laederach A, Halvorsen M, Knoll JH, Rogan PK (2016). "A unified analytic framework for prioritization of non-coding variants of uncertain significance in heritable breast and ovarian cancer". primary. BMC Medical Genomics. 9: 19. doi:10.1186/s12920-016-0178-5. PMC 4828881. PMID 27067391.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  4. ^ Serjeant GR (2001). "The emerging understanding of sickle cell disease". British Journal of Haematology. 112 (1): 3–18. doi:10.1046/j.1365-2141.2001.02557.x. PMID 11167776.
  5. ^ Marotta CA, Wilson JT, Forget BG, Weissman SM (1977). "Human beta-globin messenger RNA. III. Nucleotide sequences derived from complementary DNA". primary. The Journal of Biological Chemistry. 252 (14): 5040–53. PMID 68958.
  6. ^ a b International Human Genome Sequencing Consortium (February 2001). "Initial sequencing and analysis of the human genome" (PDF). Nature. 409 (6822): 860–921. Bibcode:2001Natur.409..860L. doi:10.1038/35057062. PMID 11237011.
  7. ^ "Next Generation Sequencing Market Size, Share, Analysis Report". Grand View Research, Inc. Retrieved 26 July 2015.
  8. ^ Kühnemund M, Wei Q, Darai E, Wang Y, Hernández-Neuta I, Yang Z, Tseng D, Ahlford A, Mathot L, Sjöblom T, Ozcan A, Nilsson M (2017). "Targeted DNA sequencing and in situ mutation analysis using mobile phone microscopy". primary. Nature Communications. 8: 13913. Bibcode:2017NatCo...813913K. doi:10.1038/ncomms13913. PMC 5247573. PMID 28094784.
  9. ^ "Medical Genetics Practice Resources". www.acmg.net. Retrieved 23 November 2020.
  10. ^ a b Kim, Young-Eun; Ki, Chang-Seok; Jang, Mi-Ae (September 2019). "Challenges and Considerations in Sequence Variant Interpretation for Mendelian Disorders". Annals of Laboratory Medicine. 39 (5): 421–429. doi:10.3343/alm.2019.39.5.421. ISSN 2234-3806. PMC 6502951. PMID 31037860.
  11. ^ a b c Amendola, Laura; Jarvik, Gail; Leo, Michael; McLaughlin, Heather; Akkari, Yassmine; Amaral, Michelle; Berg, Jonathan; Biswas, Sawona; Bowling, Kevin; Conlin, Laura; Cooper, Greg (June 2016). "Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium". American Journal of Human Genetics. 98 (6): 1067–1076. doi:10.1016/j.ajhg.2016.03.024. ISSN 0002-9297. PMC 4908185. PMID 27181684.
  12. ^ Riggs, Erin Rooney; Andersen, Erica F.; Cherry, Athena M.; Kantarci, Sibel; Kearney, Hutton; Patel, Ankita; Raca, Gordana; Ritter, Deborah I.; South, Sarah T.; Thorland, Erik C.; Pineda-Alvarez, Daniel (February 2020). "Technical standards for the interpretation and reporting of constitutional copy number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen)". Genetics in medicine : official journal of the American College of Medical Genetics. 22 (2): 245–257. doi:10.1038/s41436-019-0686-8. ISSN 1098-3600. PMC 7313390. PMID 31690835.
  13. ^ "Regulation of Genetic Tests". NIH. National Human Genome Research Institute. Retrieved 20 January 2017.{{cite web}}: CS1 maint: url-status (link)
  14. ^ Burke, Wylie (24 April 2014). "Genetic Tests:Clinical Validity and Clinical Utility". Current protocols in human genetics / editorial board, Jonathan L. Haines ... [et al.] 81: 9.15.1–9.15.8. doi:10.1002/0471142905.hg0915s81. ISSN 1934-8266. PMC 4084965. PMID 24763995.
  15. ^ a b Evans, Barbara J.; Javitt, Gail; Hall, Ralph; Robertson, Megan; Ossorio, Pilar; Wolf, Susan M.; Morgan, Thomas; Clayton, Ellen Wright (1 March 2020). "How Can Law and Policy Advance Quality in Genomic Analysis and Interpretation for Clinical Care?". The Journal of Law, Medicine & Ethics. 48 (1): 44–68. doi:10.1177/1073110520916995. ISSN 1073-1105. PMC 7447152. PMID 32342785.{{cite journal}}: CS1 maint: PMC format (link)
  16. ^ Hoskinson, Derick C.; Dubuc, Adrian M.; Mason-Suares, Heather (February 2017). "The Current State of Clinical Interpretation of Sequence Variants". Current opinion in genetics & development. 42: 33–39. doi:10.1016/j.gde.2017.01.001. ISSN 0959-437X. PMC 5446800. PMID 28157586.
  17. ^ Amendola, Laura M.; Dorschner, Michael O.; Robertson, Peggy D.; Salama, Joseph S.; Hart, Ragan; Shirts, Brian H.; Murray, Mitzi L.; Tokita, Mari J.; Gallego, Carlos J.; Kim, Daniel Seung; Bennett, James T. (March 2015). "Actionable exomic incidental findings in 6503 participants: challenges of variant classification". Genome Research. 25 (3): 305–315. doi:10.1101/gr.183483.114. ISSN 1088-9051. PMC 4352885. PMID 25637381.
  18. ^ Hoffman-Andrews, Lily (1 December 2017). "The known unknown: the challenges of genetic variants of uncertain significance in clinical practice". Journal of Law and the Biosciences. 4 (3): 648–657. doi:10.1093/jlb/lsx038.
  19. ^ a b Khurana, E; et al. (2016). "Role of non-coding sequence variants in cancer". Nature Reviews Genetics. 17 (2): 93–108. doi:10.1038/nrg.2015.17. PMID 26781813.
  20. ^ Guenther, CA; et al. (2014). "A molecular basis for classic blond hair color in Europeans". Nature Genetics. 46 (7): 748–752. doi:10.1038/ng.2991. PMC 4704868. PMID 24880339.
  21. ^ Smemo S, Tena JJ, Kim KH, Gamazon ER, Sakabe NJ, Gómez-Marín C, Aneas I, Credidio FL, Sobreira DR, Wasserman NF, Lee JH, Puviindran V, Tam D, Shen M, Son JE, Vakili NA, Sung HK, Naranjo S, Acemel RD, Manzanares M, Nagy A, Cox NJ, Hui CC, Gomez-Skarmeta JL, Nóbrega MA (March 2014). "Obesity-associated variants within FTO form long-range functional connections with IRX3". Nature. 507 (7492): 371–5. Bibcode:2014Natur.507..371S. doi:10.1038/nature13138. PMC 4113484. PMID 24646999.
  22. ^ O'Neill SC, Rini C, Goldsmith RE, Valdimarsdottir H, Cohen LH, Schwartz MD (2009). "Distress among women receiving uninformative BRCA1/2 results: 12-month outcomes". Psycho-oncology. 18 (10): 1088–96. doi:10.1002/pon.1467. PMC 3503506. PMID 19214961.
  23. ^ Vos J, Gómez-García E, Oosterwijk JC, Menko FH, Stoel RD, van Asperen CJ, Jansen AM, Stiggelbout AM, Tibben A (2012). "Opening the psychological black box in genetic counseling. The psychological impact of DNA testing is predicted by the counselees' perception, the medical impact by the pathogenic or uninformative BRCA1/2-result". primary. Psycho-oncology. 21 (1): 29–42. doi:10.1002/pon.1864. PMID 21072753.
  24. ^ Eccles BK, Copson E, Maishman T, Abraham JE, Eccles DM (2015). "Understanding of BRCA VUS genetic results by breast cancer specialists". BMC Cancer. 15: 936. doi:10.1186/s12885-015-1934-1. PMC 4660681. PMID 26608569.{{cite journal}}: CS1 maint: unflagged free DOI (link)

Further reading

  • "Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer" [1]

External links

  1. ^ Li, Marilyn M.; Datto, Michael; Duncavage, Eric J.; Kulkarni, Shashikant; Lindeman, Neal I.; Roy, Somak; Tsimberidou, Apostolia M.; Vnencak-Jones, Cindy L.; Wolff, Daynna J.; Younes, Anas; Nikiforova, Marina N. (January 2017). "Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer". The Journal of Molecular Diagnostics : JMD. 19 (1): 4–23. doi:10.1016/j.jmoldx.2016.10.002. ISSN 1525-1578. PMC 5707196. PMID 27993330.
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