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Krueger KE. Neo-Darwinian Principles Exemplified in Cancer Genomics. Mol Cancer Res 2023; 21:1251-1260. [PMID: 37721477 DOI: 10.1158/1541-7786.mcr-23-0247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 06/13/2023] [Accepted: 09/14/2023] [Indexed: 09/19/2023]
Abstract
Within the last two decades, the advent of next-generation sequencing accompanied by single-cell technologies has enabled cancer researchers to study in detail mutations and other genetic aberrations that transpire during transformation of cells to a neoplastic state. This article covers the insights gained through these extensive studies where neo-Darwinian principles can be inferred to play roles throughout neoplastic transformation. The cells promoted during cancer development exhibit cancer hallmarks combined with the related enabling characteristics as outlined by Hanahan and Weinberg, analogous to natural selection and survival of the fittest. Selection of driver mutations that inactivate proteins encoded by tumor suppressor genes differs in profound ways from mutations that activate tumor promoter proteins. In most cases, the later stages of cancer development are characterized by sudden, extensive damage to chromosomes in a process that is not Darwinian in nature. Nevertheless, cells that survive these cataclysmic events remain subject to Darwinian selection promoting clones exhibiting the greatest rates of progression. Duplications of chromosomal segments containing oncogenes, deletions of segments harboring tumor suppressor genes, or distinctive chromosomal rearrangements are often found in cells progressing into later stages of cancer. In summary, the technological developments in genome sequencing since the start of the century have given us clear insights into genomic alterations promoting tumor progression where neo-Darwinian mechanisms of clonal selection can be inferred to play a primary role.
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Clark KA, Paquette A, Tao K, Bell R, Boyle JL, Rosenthal J, Snow AK, Stark AW, Thompson BA, Unger J, Gertz J, Varley KE, Boucher KM, Goldgar DE, Foulkes WD, Thomas A, Tavtigian SV. Comprehensive evaluation and efficient classification of BRCA1 RING domain missense substitutions. Am J Hum Genet 2022; 109:1153-1174. [PMID: 35659930 PMCID: PMC9247830 DOI: 10.1016/j.ajhg.2022.05.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 05/09/2022] [Indexed: 11/21/2022] Open
Abstract
BRCA1 is a high-risk susceptibility gene for breast and ovarian cancer. Pathogenic protein-truncating variants are scattered across the open reading frame, but all known missense substitutions that are pathogenic because of missense dysfunction are located in either the amino-terminal RING domain or the carboxy-terminal BRCT domain. Heterodimerization of the BRCA1 and BARD1 RING domains is a molecularly defined obligate activity. Hence, we tested every BRCA1 RING domain missense substitution that can be created by a single nucleotide change for heterodimerization with BARD1 in a mammalian two-hybrid assay. Downstream of the laboratory assay, we addressed three additional challenges: assay calibration, validation thereof, and integration of the calibrated results with other available data, such as computational evidence and patient/population observational data to achieve clinically applicable classification. Overall, we found that 15%-20% of BRCA1 RING domain missense substitutions are pathogenic. Using a Bayesian point system for data integration and variant classification, we achieved clinical classification of 89% of observed missense substitutions. Moreover, among missense substitutions not present in the human observational data used here, we find an additional 45 with concordant computational and functional assay evidence in favor of pathogenicity plus 223 with concordant evidence in favor of benignity; these are particularly likely to be classified as likely pathogenic and likely benign, respectively, once human observational data become available.
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Affiliation(s)
- Kathleen A Clark
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA
| | - Andrew Paquette
- Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Kayoko Tao
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA
| | - Russell Bell
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA
| | - Julie L Boyle
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA
| | - Judith Rosenthal
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA
| | - Angela K Snow
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA
| | - Alex W Stark
- Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Bryony A Thompson
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA
| | - Joshua Unger
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA
| | - Jason Gertz
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Katherine E Varley
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Kenneth M Boucher
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA; Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT 84108, USA
| | - David E Goldgar
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA; Department of Dermatology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - William D Foulkes
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC H3T 1E2, Canada; Research Institute McGill University Health Center, Montreal, QC H3T 1E2, Canada; Departments of Medicine, Human Genetics, and Oncology, McGill University, Montreal, QC H3T 1E2, Canada
| | - Alun Thomas
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT 84108, USA
| | - Sean V Tavtigian
- Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT 84112, USA; Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84112, USA.
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Thompson BA, Walters R, Parsons MT, Dumenil T, Drost M, Tiersma Y, Lindor NM, Tavtigian SV, de Wind N, Spurdle AB. Contribution of mRNA Splicing to Mismatch Repair Gene Sequence Variant Interpretation. Front Genet 2020; 11:798. [PMID: 32849802 PMCID: PMC7398121 DOI: 10.3389/fgene.2020.00798] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 07/03/2020] [Indexed: 12/25/2022] Open
Abstract
Functional assays that assess mRNA splicing can be used in interpretation of the clinical significance of sequence variants, including the Lynch syndrome-associated mismatch repair (MMR) genes. The purpose of this study was to investigate the contribution of splicing assay data to the classification of MMR gene sequence variants. We assayed mRNA splicing for 24 sequence variants in MLH1, MSH2, and MSH6, including 12 missense variants that were also assessed using a cell-free in vitro MMR activity (CIMRA) assay. Multifactorial likelihood analysis was conducted for each variant, combining CIMRA outputs and clinical data where available. We collated these results with existing public data to provide a dataset of splicing assay results for a total of 671 MMR gene sequence variants (328 missense/in-frame indel), and published and unpublished repair activity measurements for 154 of these variants. There were 241 variants for which a splicing aberration was detected: 92 complete impact, 33 incomplete impact, and 116 where it was not possible to determine complete versus incomplete splicing impact. Splicing results mostly aided in the interpretation of intronic (72%) and silent (92%) variants and were the least useful for missense substitutions/in-frame indels (10%). MMR protein functional activity assays were more useful in the analysis of these exonic variants but by design they were not able to detect clinically important splicing aberrations identified by parallel mRNA assays. The development of high throughput assays that can quantitatively assess impact on mRNA transcript expression and protein function in parallel will streamline classification of MMR gene sequence variants.
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Affiliation(s)
- Bryony A Thompson
- Department of Pathology, The Royal Melbourne Hospital, Melbourne, VIC, Australia.,Department of Clinical Pathology, The University of Melbourne, Melbourne, VIC, Australia
| | - Rhiannon Walters
- Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Michael T Parsons
- Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Troy Dumenil
- Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Mark Drost
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Yvonne Tiersma
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Noralane M Lindor
- Department of Health Sciences Research, Mayo Clinic, Scottsdale, AZ, United States
| | - Sean V Tavtigian
- Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT, United States
| | - Niels de Wind
- Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands
| | - Amanda B Spurdle
- Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
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Systematic misclassification of missense variants in BRCA1 and BRCA2 "coldspots". Genet Med 2020; 22:825-830. [PMID: 31911673 PMCID: PMC7200594 DOI: 10.1038/s41436-019-0740-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 12/19/2019] [Indexed: 12/15/2022] Open
Abstract
Purpose Guidelines for variant interpretation incorporate variant hotspots in critical functional domains as evidence for pathogenicity (e.g., PM1 and PP2), but do not use “coldspots,” that is, regions without essential functions that tolerate variation, as evidence a variant is benign. To improve variant classification we evaluated BRCA1 and BRCA2 missense variants reported in ClinVar to identify regions where pathogenic missenses are extremely infrequent, defined as coldspots. Methods We used Bayesian approaches to model variant classification in these regions. Results BRCA1 exon 11 (~60% of the coding sequence), and BRCA2 exons 10 and 11 (~65% of the coding sequence), are coldspots. Of 89 pathogenic (P) or likely pathogenic (LP) missense variants in BRCA1, none are in exon 11 (odds <0.01, 95% confidence interval [CI] 0.0–0.01). Of 34 P or LP missense variants in BRCA2, none are in exons 10–11 (odds <0.01, 95% CI 0.0–0.01). More than half of reported missense variants of uncertain significance (VUS) in BRCA1 and BRCA2 are in coldspots (3115/5301 = 58.8%). Reclassifying these 3115 VUS as likely benign would substantially improve variant classification. Conclusion In BRCA1 and BRCA2 coldspots, missense variants are very unlikely to be pathogenic. Classification schemes that incorporate coldspots can reduce the number of VUS and mitigate risks from reporting benign variation as VUS.
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Lessons learned from two decades of BRCA1 and BRCA2 genetic testing: the evolution of data sharing and variant classification. Genet Med 2019; 21:1476-1480. [PMID: 30474649 PMCID: PMC9936330 DOI: 10.1038/s41436-018-0370-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Accepted: 11/06/2018] [Indexed: 02/02/2023] Open
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Nones K, Johnson J, Newell F, Patch AM, Thorne H, Kazakoff SH, de Luca XM, Parsons MT, Ferguson K, Reid LE, McCart Reed AE, Srihari S, Lakis V, Davidson AL, Mukhopadhyay P, Holmes O, Xu Q, Wood S, Leonard C, Beesley J, Harris JM, Barnes D, Degasperi A, Ragan MA, Spurdle AB, Khanna KK, Lakhani SR, Pearson JV, Nik-Zainal S, Chenevix-Trench G, Waddell N, Simpson PT. Whole-genome sequencing reveals clinically relevant insights into the aetiology of familial breast cancers. Ann Oncol 2019; 30:1071-1079. [PMID: 31090900 PMCID: PMC6637375 DOI: 10.1093/annonc/mdz132] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Whole-genome sequencing (WGS) is a powerful method for revealing the diversity and complexity of the somatic mutation burden of tumours. Here, we investigated the utility of tumour and matched germline WGS for understanding aetiology and treatment opportunities for high-risk individuals with familial breast cancer. PATIENTS AND METHODS We carried out WGS on 78 paired germline and tumour DNA samples from individuals carrying pathogenic variants in BRCA1 (n = 26) or BRCA2 (n = 22) or from non-carriers (non-BRCA1/2; n = 30). RESULTS Matched germline/tumour WGS and somatic mutational signature analysis revealed patients with unreported, dual pathogenic germline variants in cancer risk genes (BRCA1/BRCA2; BRCA1/MUTYH). The strategy identified that 100% of tumours from BRCA1 carriers and 91% of tumours from BRCA2 carriers exhibited biallelic inactivation of the respective gene, together with somatic mutational signatures suggestive of a functional deficiency in homologous recombination. A set of non-BRCA1/2 tumours also had somatic signatures indicative of BRCA-deficiency, including tumours with BRCA1 promoter methylation, and tumours from carriers of a PALB2 pathogenic germline variant and a BRCA2 variant of uncertain significance. A subset of 13 non-BRCA1/2 tumours from early onset cases were BRCA-proficient, yet displayed complex clustered structural rearrangements associated with the amplification of oncogenes and pathogenic germline variants in TP53, ATM and CHEK2. CONCLUSIONS Our study highlights the role that WGS of matched germline/tumour DNA and the somatic mutational signatures can play in the discovery of pathogenic germline variants and for providing supporting evidence for variant pathogenicity. WGS-derived signatures were more robust than germline status and other genomic predictors of homologous recombination deficiency, thus impacting the selection of platinum-based or PARP inhibitor therapy. In this first examination of non-BRCA1/2 tumours by WGS, we illustrate the considerable heterogeneity of these tumour genomes and highlight that complex genomic rearrangements may drive tumourigenesis in a subset of cases.
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Affiliation(s)
- K Nones
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - J Johnson
- Faculty of Medicine, Centre for Clinical Research, The University of Queensland, Brisbane, QLD
| | - F Newell
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - A M Patch
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - H Thorne
- kConFab Investigators, The Peter MacCallum Cancer Centre, Melbourne, VIC; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC
| | - S H Kazakoff
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - X M de Luca
- Faculty of Medicine, Centre for Clinical Research, The University of Queensland, Brisbane, QLD
| | - M T Parsons
- Molecular Cancer Epidemiology Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - K Ferguson
- Faculty of Medicine, Centre for Clinical Research, The University of Queensland, Brisbane, QLD
| | - L E Reid
- Faculty of Medicine, Centre for Clinical Research, The University of Queensland, Brisbane, QLD
| | - A E McCart Reed
- Faculty of Medicine, Centre for Clinical Research, The University of Queensland, Brisbane, QLD
| | - S Srihari
- Faculty of Medicine, Centre for Clinical Research, The University of Queensland, Brisbane, QLD; Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD
| | - V Lakis
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - A L Davidson
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD; Faculty of Medicine, The University of Queensland, Brisbane, QLD
| | - P Mukhopadhyay
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - O Holmes
- Genome Informatics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - Q Xu
- Genome Informatics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - S Wood
- Genome Informatics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - C Leonard
- Genome Informatics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - J Beesley
- Cancer Genetics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - J M Harris
- Faculty of Health, School Biomedical Science - Queensland University of Technology, Brisbane, QLD, Australia
| | - D Barnes
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge
| | - A Degasperi
- MRC Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge; Department of Medical Genetics, The Clinical School, University of Cambridge, Cambridge, UK
| | - M A Ragan
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD
| | - A B Spurdle
- Molecular Cancer Epidemiology Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - K K Khanna
- Signal Transduction Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - S R Lakhani
- Faculty of Medicine, Centre for Clinical Research, The University of Queensland, Brisbane, QLD; Royal Brisbane & Women's Hospital, Pathology Queensland, Brisbane, QLD, Australia
| | - J V Pearson
- Genome Informatics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - S Nik-Zainal
- MRC Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge; Department of Medical Genetics, The Clinical School, University of Cambridge, Cambridge, UK
| | - G Chenevix-Trench
- Cancer Genetics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD
| | - N Waddell
- Medical Genomics Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD.
| | - P T Simpson
- Faculty of Medicine, Centre for Clinical Research, The University of Queensland, Brisbane, QLD.
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7
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Caleca L, Colombo M, van Overeem Hansen T, Lázaro C, Manoukian S, Parsons MT, Spurdle AB, Radice P. GFP-Fragment Reassembly Screens for the Functional Characterization of Variants of Uncertain Significance in Protein Interaction Domains of the BRCA1 and BRCA2 Genes. Cancers (Basel) 2019; 11:E151. [PMID: 30696104 PMCID: PMC6406614 DOI: 10.3390/cancers11020151] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 01/22/2019] [Indexed: 01/14/2023] Open
Abstract
Genetic testing for BRCA1 and BRCA2 genes has led to the identification of many unique variants of uncertain significance (VUS). Multifactorial likelihood models that predict the odds ratio for VUS in favor or against cancer causality, have been developed, but their use is conditioned by the amount of necessary data, which are difficult to obtain if a variant is rare. As an alternative, variants mapping to the coding regions can be examined using in vitro functional assays. BRCA1 and BRCA2 proteins promote genome protection by interacting with different proteins. In this study, we assessed the functional effect of two sets of variants in BRCA genes by exploiting the green fluorescent protein (GFP)-reassembly in vitro assay, which was set-up to test the BRCA1/BARD1, BRCA1/UbcH5a, and BRCA2/DSS1 interactions. Based on the findings observed for the validation panels of previously classified variants, BRCA1/UbcH5a and BRCA2/DSS1 binding assays showed 100% sensitivity and specificity in identifying pathogenic and non-pathogenic variants. While the actual efficiency of these assays in assessing the clinical significance of BRCA VUS has to be verified using larger validation panels, our results suggest that the GFP-reassembly assay is a robust method to identify variants affecting normal protein functioning and contributes to the classification of VUS.
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Affiliation(s)
- Laura Caleca
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
| | - Mara Colombo
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
| | - Thomas van Overeem Hansen
- Center for Genomic Medicine, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark.
- Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, 2100 Copenhagen, Denmark.
| | - Conxi Lázaro
- Hereditary Cancer Program, Catalan Institute of Oncology. Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Hospitalet de Llobregat, 08900 Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain.
| | - Siranoush Manoukian
- Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
| | - Michael T Parsons
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane 4029, Australia.
| | - Amanda B Spurdle
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane 4029, Australia.
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy.
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Lee JS, Oh S, Park SK, Lee MH, Lee JW, Kim SW, Son BH, Noh DY, Lee JE, Park HL, Kim MJ, Cho SI, Lee YK, Park SS, Seong MW. Reclassification of BRCA1 and BRCA2 variants of uncertain significance: a multifactorial analysis of multicentre prospective cohort. J Med Genet 2018; 55:794-802. [PMID: 30415210 DOI: 10.1136/jmedgenet-2018-105565] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 08/27/2018] [Accepted: 08/29/2018] [Indexed: 11/03/2022]
Abstract
BACKGROUND BRCA1 and BRCA2 (BRCA1/2) variants classified ambiguously as variants of uncertain significance (VUS) are a major challenge for clinical genetic testing in breast cancer; their relevance to the cancer risk is unclear and the association with the response to specific BRCA1/2-targeted agents is uncertain. To minimise the proportion of VUS in BRCA1/2, we performed the multifactorial likelihood analysis and validated this method using an independent cohort of patients with breast cancer. METHODS We used a data set of 2115 patients with breast cancer from the nationwide multicentre prospective Korean Hereditary Breast Cancer study. In total, 83 BRCA1/2 VUSs (BRCA1, n=26; BRCA2, n=57) were analysed. The multifactorial probability was estimated by combining the prior probability with the overall likelihood ratio derived from co-occurrence of each VUS with pathogenic variants, personal and family history, and tumour characteristics. The classification was compared with the interpretation according to the American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG/AMP) guidelines. An external validation was conducted using independent data set of 810 patients. RESULTS We were able to redefine 38 VUSs (BRCA1, n=10; BRCA2, n=28). The revised classification was highly correlated with the ACMG/AMP guideline-based interpretation (BRCA1, p for trend=0.015; BRCA2, p=0.001). Our approach reduced the proportion of VUS from 19% (154/810) to 8.9% (72/810) in the retrospective validation data set. CONCLUSION The classification in this study would minimise the 'uncertainty' in clinical interpretation, and this validated multifactorial model can be used for the reliable annotation of BRCA1/2 VUSs.
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Affiliation(s)
- Jee-Soo Lee
- Department of Laboratory Medicine, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea.,Department of Laboratory Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sohee Oh
- Department of Biostatistics SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Sue Kyung Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Min-Hyuk Lee
- Department of Surgery, College of Medicine, Soonchunhyang University, Seoul, Republic of Korea
| | - Jong Won Lee
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seongnam, Republic of Korea
| | - Sung-Won Kim
- Department of Surgery, Seoul National University Bundang Hospital, Seoul, Republic of Korea
| | - Byung Ho Son
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seongnam, Republic of Korea
| | - Dong-Young Noh
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jeong Eon Lee
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hai-Lin Park
- Department of Surgery, Kangnam CHA Hospital, Seoul, Republic of Korea
| | - Man Jin Kim
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sung Im Cho
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Young Kyung Lee
- Department of Laboratory Medicine, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea.,Department of Laboratory Medicine, Hallym University College of Medicine, Anyang, Republic of Korea
| | - Sung Sup Park
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Moon-Woo Seong
- Department of Laboratory Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.,Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea
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9
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Ernst C, Hahnen E, Engel C, Nothnagel M, Weber J, Schmutzler RK, Hauke J. Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics. BMC Med Genomics 2018; 11:35. [PMID: 29580235 PMCID: PMC5870501 DOI: 10.1186/s12920-018-0353-y] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Accepted: 03/19/2018] [Indexed: 01/10/2023] Open
Abstract
Background The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. Methods We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. Results PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. Conclusion We show that due to low specificities state-of-the-art in silico prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2. Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis. Electronic supplementary material The online version of this article (10.1186/s12920-018-0353-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Corinna Ernst
- Center for Familial Breast and Ovarian Cancer, Center for Integated Oncology (CIO), Medical Faculty, University Hospital Cologne, Kerpener Straße 34, Cologne, 50931, Germany
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Center for Integated Oncology (CIO), Medical Faculty, University Hospital Cologne, Kerpener Straße 34, Cologne, 50931, Germany
| | - Christoph Engel
- Institute of Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig, Germany
| | - Michael Nothnagel
- Cologne Center for Genomics, University of Cologne, Cologne, Germany
| | - Jonas Weber
- Center for Familial Breast and Ovarian Cancer, Center for Integated Oncology (CIO), Medical Faculty, University Hospital Cologne, Kerpener Straße 34, Cologne, 50931, Germany
| | - Rita K Schmutzler
- Center for Familial Breast and Ovarian Cancer, Center for Integated Oncology (CIO), Medical Faculty, University Hospital Cologne, Kerpener Straße 34, Cologne, 50931, Germany
| | - Jan Hauke
- Center for Familial Breast and Ovarian Cancer, Center for Integated Oncology (CIO), Medical Faculty, University Hospital Cologne, Kerpener Straße 34, Cologne, 50931, Germany.
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10
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Gradishar W, Johnson K, Brown K, Mundt E, Manley S. Clinical Variant Classification: A Comparison of Public Databases and a Commercial Testing Laboratory. Oncologist 2017; 22:797-803. [PMID: 28408614 PMCID: PMC5507641 DOI: 10.1634/theoncologist.2016-0431] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 01/05/2017] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, the well-documented limitations of these databases call into question how often clinicians will encounter discordant variant classifications that may introduce uncertainty into patient management. Here, we evaluate discordance in BRCA1 and BRCA2 variant classifications between a single commercial testing laboratory and a public database commonly consulted in clinical practice. MATERIALS AND METHODS BRCA1 and BRCA2 variant classifications were obtained from ClinVar and compared with the classifications from a reference laboratory. Full concordance and discordance were determined for variants whose ClinVar entries were of the same pathogenicity (pathogenic, benign, or uncertain). Variants with conflicting ClinVar classifications were considered partially concordant if ≥1 of the listed classifications agreed with the reference laboratory classification. RESULTS Four thousand two hundred and fifty unique BRCA1 and BRCA2 variants were available for analysis. Overall, 73.2% of classifications were fully concordant and 12.3% were partially concordant. The remaining 14.5% of variants had discordant classifications, most of which had a definitive classification (pathogenic or benign) from the reference laboratory compared with an uncertain classification in ClinVar (14.0%). CONCLUSION Here, we show that discrepant classifications between a public database and single reference laboratory potentially account for 26.7% of variants in BRCA1 and BRCA2. The time and expertise required of clinicians to research these discordant classifications call into question the practicality of checking all test results against a database and suggest that discordant classifications should be interpreted with these limitations in mind. IMPLICATIONS FOR PRACTICE With the increasing use of clinical genetic testing for hereditary cancer risk, accurate variant classification is vital to ensuring appropriate medical management. There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, we show that up to 26.7% of variants in BRCA1 and BRCA2 have discordant classifications between ClinVar and a reference laboratory. The findings presented in this paper serve as a note of caution regarding the utility of database consultation.
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Affiliation(s)
- William Gradishar
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Myriad Genetic Laboratories, Inc., Salt Lake City, Utah, USA
| | - KariAnne Johnson
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Myriad Genetic Laboratories, Inc., Salt Lake City, Utah, USA
| | - Krystal Brown
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Myriad Genetic Laboratories, Inc., Salt Lake City, Utah, USA
| | - Erin Mundt
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Myriad Genetic Laboratories, Inc., Salt Lake City, Utah, USA
| | - Susan Manley
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- Myriad Genetic Laboratories, Inc., Salt Lake City, Utah, USA
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11
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Flower KJ, Shenker NS, El-Bahrawy M, Goldgar DE, Parsons MT, Spurdle AB, Morris JR, Brown R, Flanagan JM. DNA methylation profiling to assess pathogenicity of BRCA1 unclassified variants in breast cancer. Epigenetics 2016; 10:1121-32. [PMID: 26727311 PMCID: PMC4844213 DOI: 10.1080/15592294.2015.1111504] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Germline pathogenic mutations in BRCA1 increase risk of developing breast cancer. Screening for mutations in BRCA1 frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate BRCA1-mutated from BRCA1-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 BRCA1 pathogenic mutation carriers, 65 BRCAx (BRCA1-wild type), 38 BRCA1 test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (BACH2, C8orf31, and LOC654342) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set). Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G>A (IVS 19-12 G>A) (P>0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of BRCA1 variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity.
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Affiliation(s)
- Kirsty J Flower
- a Epigenetics Unit; Department of Surgery and Cancer; Imperial College London ; UK
| | - Natalie S Shenker
- a Epigenetics Unit; Department of Surgery and Cancer; Imperial College London ; UK
| | - Mona El-Bahrawy
- b Department of Histopathology ; Hammersmith Hospital; Imperial College London ; UK
| | - David E Goldgar
- c Huntsman Cancer Institute; University of Utah ; Salt Lake City , UT , USA
| | - Michael T Parsons
- d QIMR Berghofer Medical Research Institute ; Brisbane , QLD , Australia
| | | | | | - Amanda B Spurdle
- d QIMR Berghofer Medical Research Institute ; Brisbane , QLD , Australia
| | - Joanna R Morris
- f Genome Stability Unit; School of Cancer Sciences; University of Birmingham ; UK
| | - Robert Brown
- a Epigenetics Unit; Department of Surgery and Cancer; Imperial College London ; UK.,g Section of Molecular Pathology; Institute for Cancer Research ; Sutton , UK
| | - James M Flanagan
- a Epigenetics Unit; Department of Surgery and Cancer; Imperial College London ; UK
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12
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Implementation of next-generation sequencing for molecular diagnosis of hereditary breast and ovarian cancer highlights its genetic heterogeneity. Breast Cancer Res Treat 2016; 159:245-56. [PMID: 27553368 DOI: 10.1007/s10549-016-3948-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Accepted: 08/16/2016] [Indexed: 01/13/2023]
Abstract
Molecular diagnosis of hereditary breast and ovarian cancer (HBOC) by standard methodologies has been limited to the BRCA1 and BRCA2 genes. With the recent development of new sequencing methodologies, the speed and efficiency of DNA testing have dramatically improved. The aim of this work was to validate the use of next-generation sequencing (NGS) for the detection of BRCA1/BRCA2 point mutations in a diagnostic setting and to study the role of other genes associated with HBOC in Portuguese families. A cohort of 94 high-risk families was included in the study, and they were initially screened for the two common founder mutations with variant-specific methods. Fourteen index patients were shown to carry the Portuguese founder mutation BRCA2 c.156_157insAlu, and the remaining 80 were analyzed in parallel by Sanger sequencing for the BRCA1/BRCA2 genes and by NGS for a panel of 17 genes that have been described as involved in predisposition to breast and/or ovarian cancer. A total of 506 variants in the BRCA1/BRCA2 genes were detected by both methodologies, with a 100 % concordance between them. This strategy allowed the detection of a total of 39 deleterious mutations in the 94 index patients, namely 10 in BRCA1 (25.6 %), 21 in BRCA2 (53.8 %), four in PALB2 (10.3 %), two in ATM (5.1 %), one in CHEK2 (2.6 %), and one in TP53 (2.6 %), with 20.5 % of the deleterious mutations being found in genes other than BRCA1/BRCA2. These results demonstrate the efficiency of NGS for the detection of BRCA1/BRCA2 point mutations and highlight the genetic heterogeneity of HBOC.
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13
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Park KS, Cho EY, Nam SJ, Ki CS, Kim JW. Comparative analysis of BRCA1 and BRCA2 variants of uncertain significance in patients with breast cancer: a multifactorial probability-based model versus ACMG standards and guidelines for interpreting sequence variants. Genet Med 2016; 18:1250-1257. [PMID: 27124784 DOI: 10.1038/gim.2016.39] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Accepted: 02/17/2016] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To investigate variants of uncertain significance (VUS) in BRCA1 and BRCA2, we assessed the multifactorial posterior probability of VUS in BRCA1 and BRCA2 and compared these analyses with interpretations according to the recently released American College of Medical Genetics and Genomics (ACMG) standards and guidelines. METHODS The analysis involved 715 Korean patients with breast cancer. The multifactorial probability of a VUS was analyzed using the prior probability and combined likelihoods of personal and family history, the pathologic profile of the breast cancer, and co-occurrence with pathogenic variants. Results were compared with those obtained according to the ACMG standards/guidelines. RESULTS Sixteen VUS from 51 BRCA1 VUS carriers and 28 VUS from 62 BRCA2 VUS carriers were analyzed. There was a slight agreement between the two analyses, with a kappa value of 0.14 (95% confidence interval (CI) = -0.34 to 0.62) for the BRCA1 VUS and a kappa value of 0.17 (95% CI = -0.10 to 0.49) for the BRCA2 VUS. CONCLUSION We propose that genetic counseling should be based on the concordant results between these two analyses. When discrepancies are found, those variants are still considered VUS and careful counseling should be provided.Genet Med 18 12, 1250-1257.
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Affiliation(s)
| | - Eun Yoon Cho
- Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Seok Jin Nam
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Chang-Seok Ki
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jong-Won Kim
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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14
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Vallée MP, Di Sera TL, Nix DA, Paquette AM, Parsons MT, Bell R, Hoffman A, Hogervorst FBL, Goldgar DE, Spurdle AB, Tavtigian SV. Adding In Silico Assessment of Potential Splice Aberration to the Integrated Evaluation of BRCA Gene Unclassified Variants. Hum Mutat 2016; 37:627-39. [PMID: 26913838 PMCID: PMC4907813 DOI: 10.1002/humu.22973] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 01/29/2016] [Indexed: 01/05/2023]
Abstract
Clinical mutation screening of the cancer susceptibility genes BRCA1 and BRCA2 generates many unclassified variants (UVs). Most of these UVs are either rare missense substitutions or nucleotide substitutions near the splice junctions of the protein coding exons. Previously, we developed a quantitative method for evaluation of BRCA gene UVs—the “integrated evaluation”—that combines a sequence analysis‐based prior probability of pathogenicity with patient and/or tumor observational data to arrive at a posterior probability of pathogenicity. One limitation of the sequence analysis‐based prior has been that it evaluates UVs from the perspective of missense substitution severity but not probability to disrupt normal mRNA splicing. Here, we calibrated output from the splice‐site fitness program MaxEntScan to generate spliceogenicity‐based prior probabilities of pathogenicity for BRCA gene variants; these range from 0.97 for variants with high probability to damage a donor or acceptor to 0.02 for exonic variants that do not impact a splice junction and are unlikely to create a de novo donor. We created a database http://priors.hci.utah.edu/PRIORS/ that provides the combined missense substitution severity and spliceogenicity‐based probability of pathogenicity for BRCA gene single‐nucleotide substitutions. We also updated the BRCA gene Ex‐UV LOVD, available at http://hci‐exlovd.hci.utah.edu, with 77 re‐evaluable variants.
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Affiliation(s)
- Maxime P Vallée
- Department of Molecular Medicine, CHUQ Research Center, Quebec City, Canada
| | - Tonya L Di Sera
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah
| | - David A Nix
- ARUP Laboratories, University of Utah School of Medicine, Salt Lake City, Utah
| | - Andrew M Paquette
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah
| | | | - Russel Bell
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah
| | - Andrea Hoffman
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | - David E Goldgar
- Department of Dermatology, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah
| | | | - Sean V Tavtigian
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah
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