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Paolino J, Dimitrov B, Winger BA, Sandoval-Perez A, Rangarajan AV, Ocasio-Martinez N, Tsai HK, Li Y, Robichaud AL, Khalid D, Hatton C, Gillani R, Polonen P, Dilig A, Gotti G, Kavanagh J, Adhav AA, Gow S, Tsai J, Li YD, Ebert BL, Van Allen EM, Bledsoe J, Kim AS, Tasian SK, Cooper SL, Cooper TM, Hijiya N, Sulis ML, Shukla NN, Magee JA, Mullighan CG, Burke MJ, Luskin MR, Mar BG, Jacobson MP, Harris MH, Stegmaier K, Place AE, Pikman Y. Integration of Genomic Sequencing Drives Therapeutic Targeting of PDGFRA in T-Cell Acute Lymphoblastic Leukemia/Lymphoblastic Lymphoma. Clin Cancer Res 2023; 29:4613-4626. [PMID: 37725576 PMCID: PMC10872648 DOI: 10.1158/1078-0432.ccr-22-2562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 05/22/2023] [Accepted: 09/12/2023] [Indexed: 09/21/2023]
Abstract
PURPOSE Patients with relapsed or refractory T-cell acute lymphoblastic leukemia (T-ALL) or lymphoblastic lymphoma (T-LBL) have limited therapeutic options. Clinical use of genomic profiling provides an opportunity to identify targetable alterations to inform therapy. EXPERIMENTAL DESIGN We describe a cohort of 14 pediatric patients with relapsed or refractory T-ALL enrolled on the Leukemia Precision-based Therapy (LEAP) Consortium trial (NCT02670525) and a patient with T-LBL, discovering alterations in platelet-derived growth factor receptor-α (PDGFRA) in 3 of these patients. We identified a novel mutation in PDGFRA, p.D842N, and used an integrated structural modeling and molecular biology approach to characterize mutations at D842 to guide therapeutic targeting. We conducted a preclinical study of avapritinib in a mouse patient-derived xenograft (PDX) model of FIP1L1-PDGFRA and PDGFRA p.D842N leukemia. RESULTS Two patients with T-ALL in the LEAP cohort (14%) had targetable genomic alterations affecting PDGFRA, a FIP1-like 1 protein/PDGFRA (FIP1L1-PDGFRA) fusion and a novel mutation in PDGFRA, p.D842N. The D842N mutation resulted in PDGFRA activation and sensitivity to tested PDGFRA inhibitors. In a T-ALL PDX model, avapritinib treatment led to decreased leukemia burden, significantly prolonged survival, and even cured a subset of mice. Avapritinib treatment was well tolerated and yielded clinical benefit in a patient with refractory T-ALL. CONCLUSIONS Refractory T-ALL has not been fully characterized. Alterations in PDGFRA or other targetable kinases may inform therapy for patients with refractory T-ALL who otherwise have limited treatment options. Clinical genomic profiling, in real time, is needed for fully informed therapeutic decision making.
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Affiliation(s)
- Jonathan Paolino
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA
| | - Boris Dimitrov
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Beth Apsel Winger
- Department of Pediatrics, Division of Hematology/Oncology, Benioff Children’s Hospital and the Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA
| | - Angelica Sandoval-Perez
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA
| | - Amith Vikram Rangarajan
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA
| | | | | | - Yuting Li
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
| | | | - Delan Khalid
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Charlie Hatton
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Riaz Gillani
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA
| | - Petri Polonen
- Department of Pathology, St. Jude Children's Research Hospital, Memphis, TN
| | | | - Giacomo Gotti
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
- Pediatrics, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy
| | - Julia Kavanagh
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Asmani A. Adhav
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Sean Gow
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Jonathan Tsai
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA
| | - Yen Der Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Benjamin L. Ebert
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | | | - Jacob Bledsoe
- Department of Pathology, Boston Children’s Hospital, Boston, MA
| | - Annette S. Kim
- Department of Pathology, Brigham and Women’s Hospital, Boston, MA
| | - Sarah K. Tasian
- Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, and Department of Pediatrics and Abramson Cancer Center at the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Stacy L. Cooper
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD
| | - Todd M. Cooper
- Seattle Children's Hospital, Cancer and Blood Disorders Center, Seattle, WA
| | - Nobuko Hijiya
- Division of Pediatric Hematology/Oncology/Stem Cell Transplantation, Columbia University Irving Medical Center, New York, NY
| | - Maria Luisa Sulis
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Neerav N. Shukla
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Jeffrey A. Magee
- Division of Pediatric Hematology/Oncology, Washington University/St. Louis Children's Hospital, St. Louis, MO
| | | | - Michael J. Burke
- Medical College of Wisconsin, Children’s Hospital of Wisconsin, Milwaukee, WI
| | - Marlise R. Luskin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | | | - Matthew P. Jacobson
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA
| | | | - Kimberly Stegmaier
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA
| | - Andrew E. Place
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA
| | - Yana Pikman
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA
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2
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Kiyomiya M, Fukuda K, Shimazu K, Yoshida T, Taguchi D, Shinozaki H, Nanjyo H, Shibata H. Lymph-node metastasis from gastric adenocarcinoma in a patient bearing a germ line missense variant MSH2 c.1808A > T (Asp603Val) responds to the immune checkpoint inhibitor pembrolizumab. Jpn J Clin Oncol 2023; 53:270-274. [PMID: 36484308 DOI: 10.1093/jjco/hyac183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 11/08/2022] [Indexed: 12/13/2022] Open
Abstract
We report the sensitivity of immune checkpoint inhibitors for tumors developing in a patient bearing the MSH2 c.1808A > T (Asp603Val) variant belonging to a pedigree of Lynch syndrome. This variant was previously thought to be of unknown significance, but we recently found that this missense mutation was likely pathogenic. At that time, there were no active members with malignancies that could be treated with chemotherapy. Thereafter, an 81-year-old woman bearing this variant, who was a cousin of the proband of this family, had multiple lymph node metastases from her resected gastric cancer. An immune checkpoint inhibitor, pembrolizumab, an anti-PD-1 antibody, was used to treat these tumors. After 3 months of treatment, almost all tumors disappeared, and elevated CA19-9 levels normalized. She survives over 15 months safely. It was indicated that the tumors bearing this germline variant were sensitive to pembrolizumab. This observation suggests that an MSH2 c.1808A > T (Asp603Val) variant induces mismatch repair deficiency, resulting in sensitization to immune checkpoint inhibition.
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Affiliation(s)
- Miki Kiyomiya
- Department of Clinical Oncology, Graduate School of Medicine, Akita University, Akita, Japan
| | - Koji Fukuda
- Department of Clinical Oncology, Graduate School of Medicine, Akita University, Akita, Japan
| | - Kazuhiro Shimazu
- Department of Clinical Oncology, Graduate School of Medicine, Akita University, Akita, Japan
| | - Taichi Yoshida
- Department of Clinical Oncology, Graduate School of Medicine, Akita University, Akita, Japan
| | - Daiki Taguchi
- Department of Clinical Oncology, Graduate School of Medicine, Akita University, Akita, Japan
| | - Hanae Shinozaki
- Department of Clinical Oncology, Graduate School of Medicine, Akita University, Akita, Japan
| | - Hiroshi Nanjyo
- Department of Pathology, Akita University Hospital, Akita, Japan
| | - Hiroyuki Shibata
- Department of Clinical Oncology, Graduate School of Medicine, Akita University, Akita, Japan
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3
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Lampson BL, Gupta A, Tyekucheva S, Mashima K, Petráčková A, Wang Z, Wojciechowska N, Shaughnessy CJ, Baker PO, Fernandes SM, Shupe S, Machado JH, Fardoun R, Kim AS, Brown JR. Rare Germline ATM Variants Influence the Development of Chronic Lymphocytic Leukemia. J Clin Oncol 2023; 41:1116-1128. [PMID: 36315919 PMCID: PMC9928739 DOI: 10.1200/jco.22.00269] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 09/08/2022] [Accepted: 09/09/2022] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Germline missense variants of unknown significance in cancer-related genes are increasingly being identified with the expanding use of next-generation sequencing. The ataxia telangiectasia-mutated (ATM) gene on chromosome 11 has more than 1,000 germline missense variants of unknown significance and is a tumor suppressor. We aimed to determine if rare germline ATM variants are more frequent in chronic lymphocytic leukemia (CLL) compared with other hematologic malignancies and if they influence the clinical characteristics of CLL. METHODS We identified 3,128 patients (including 825 patients with CLL) in our hematologic malignancy clinic who had received clinical-grade sequencing of the entire coding region of ATM. We ascertained the comparative frequencies of germline ATM variants in categories of hematologic neoplasms, and, in patients with CLL, we determined whether these variants affected CLL-associated characteristics such as somatic 11q deletion. RESULTS Rare germline ATM variants are present in 24% of patients with CLL, significantly greater than that in patients with other lymphoid malignancies (16% prevalence), myeloid disease (15%), or no hematologic neoplasm (14%). Patients with CLL with germline ATM variants are younger at diagnosis and twice as likely to have 11q deletion. The ATM variant p.L2307F is present in 3% of patients with CLL, is associated with a three-fold increase in rates of somatic 11q deletion, and is a hypomorph in cell-based assays. CONCLUSION Germline ATM variants cluster within CLL and affect the phenotype of CLL that develops, implying that some of these variants (such as ATM p.L2307F) have functional significance and should not be ignored. Further studies are needed to determine whether these variants affect the response to therapy or account for some of the inherited risk of CLL.
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Affiliation(s)
- Benjamin L. Lampson
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Aditi Gupta
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | | | - Kiyomi Mashima
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Anna Petráčková
- Department of Immunology, Palacký University, Olomouc, Czech Republic
| | - Zixu Wang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA
| | - Natalia Wojciechowska
- Department of Pathology, Brigham and Women's Hospital, Boston, MA
- Current Address: Wrocław Medical University, Wrocław, Poland
| | - Conner J. Shaughnessy
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Peter O. Baker
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Stacey M. Fernandes
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Samantha Shupe
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - John-Hanson Machado
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Rayan Fardoun
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Annette S. Kim
- Department of Pathology, Brigham and Women's Hospital, Boston, MA
| | - Jennifer R. Brown
- Division of Hematologic Malignancies and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
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4
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Zografos E, Andrikopoulou A, Papatheodoridi AM, Kaparelou M, Bletsa G, Liontos M, Dimopoulos MA, Zagouri F. Multi-Gene Mutation Profiling by Targeted Next-Generation Sequencing in Premenopausal Breast Cancer. Genes (Basel) 2022; 13:genes13081362. [PMID: 36011273 PMCID: PMC9407588 DOI: 10.3390/genes13081362] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 07/25/2022] [Accepted: 07/26/2022] [Indexed: 02/04/2023] Open
Abstract
Breast cancer has distinct etiology, prognoses, and clinical outcomes at premenopausal ages. Determination of the frequency of germline and somatic mutations will refine our understanding of the genetic contribution to premenopausal breast cancer susceptibility. We applied a comprehensive next generation sequencing-based approach to analyze blood and/or tissue samples of 54 premenopausal breast cancer patients treated in our clinic. Genetic testing results were descriptively analyzed in correlation with clinicopathological data. In the present study, 42.5% of premenopausal breast cancer patients tested carried pathogenic mutations in cancer predisposition genes (CHEK2, BRCA1, TP53, and MUTYH). Germline variants of unknown/uncertain significance (VUSs) in eight different cancer susceptibility genes, namely BRCA1, BRCA2, CHEK2, RAD51C, RAD51D, ATM, BRIP1, and PMS2, were also identified in 14 premenopausal patients (35%). Of the breast tumors tested, 61.8% harbored pathogenic somatic variants in tumor suppressor genes (TP53, NF1, RB), genes involved in DNA repair (BRCA1, BRCA2, ATM, RAD50), cell proliferation (PTEN, PIK3C FGFR3, AKT1, ROS1, ERBB2, NOTCH1), and cell adhesion (CTNNB1). This descriptive study employs the powerful NGS technology to highlight the high frequency of premenopausal cases attributable to genetic predisposition. Mutation identification in a larger cohort may further ensure that these patients receive tailored treatment according to their menopausal status.
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Affiliation(s)
- Eleni Zografos
- Department of Clinical Therapeutics, Alexandra Hospital, School of Medicine, National and Kapodistrian University of Athens, 80 Vasilissis Sofias Avenue, 11528 Athens, Greece; (E.Z.); (A.A.); (A.M.P.); (M.K.); (M.L.); (M.-A.D.)
| | - Angeliki Andrikopoulou
- Department of Clinical Therapeutics, Alexandra Hospital, School of Medicine, National and Kapodistrian University of Athens, 80 Vasilissis Sofias Avenue, 11528 Athens, Greece; (E.Z.); (A.A.); (A.M.P.); (M.K.); (M.L.); (M.-A.D.)
| | - Alkistis Maria Papatheodoridi
- Department of Clinical Therapeutics, Alexandra Hospital, School of Medicine, National and Kapodistrian University of Athens, 80 Vasilissis Sofias Avenue, 11528 Athens, Greece; (E.Z.); (A.A.); (A.M.P.); (M.K.); (M.L.); (M.-A.D.)
| | - Maria Kaparelou
- Department of Clinical Therapeutics, Alexandra Hospital, School of Medicine, National and Kapodistrian University of Athens, 80 Vasilissis Sofias Avenue, 11528 Athens, Greece; (E.Z.); (A.A.); (A.M.P.); (M.K.); (M.L.); (M.-A.D.)
| | | | - Michalis Liontos
- Department of Clinical Therapeutics, Alexandra Hospital, School of Medicine, National and Kapodistrian University of Athens, 80 Vasilissis Sofias Avenue, 11528 Athens, Greece; (E.Z.); (A.A.); (A.M.P.); (M.K.); (M.L.); (M.-A.D.)
| | - Meletios-Athanasios Dimopoulos
- Department of Clinical Therapeutics, Alexandra Hospital, School of Medicine, National and Kapodistrian University of Athens, 80 Vasilissis Sofias Avenue, 11528 Athens, Greece; (E.Z.); (A.A.); (A.M.P.); (M.K.); (M.L.); (M.-A.D.)
| | - Flora Zagouri
- Department of Clinical Therapeutics, Alexandra Hospital, School of Medicine, National and Kapodistrian University of Athens, 80 Vasilissis Sofias Avenue, 11528 Athens, Greece; (E.Z.); (A.A.); (A.M.P.); (M.K.); (M.L.); (M.-A.D.)
- Correspondence:
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5
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Morton SU, Christodoulou J, Costain G, Muntoni F, Wakeling E, Wojcik MH, French CE, Szuto A, Dowling JJ, Cohn RD, Raymond FL, Darras BT, Williams DA, Lunke S, Stark Z, Rowitch DH, Agrawal PB. Multicenter Consensus Approach to Evaluation of Neonatal Hypotonia in the Genomic Era: A Review. JAMA Neurol 2022; 79:405-413. [PMID: 35254387 PMCID: PMC10134401 DOI: 10.1001/jamaneurol.2022.0067] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Importance Infants with hypotonia can present with a variety of potentially severe clinical signs and symptoms and often require invasive testing and multiple procedures. The wide range of clinical presentations and potential etiologies leaves diagnosis and prognosis uncertain, underscoring the need for rapid elucidation of the underlying genetic cause of disease. Observations The clinical application of exome sequencing or genome sequencing has dramatically improved the timely yield of diagnostic testing for neonatal hypotonia, with diagnostic rates of greater than 50% in academic neonatal intensive care units (NICUs) across Australia, Canada, the UK, and the US, which compose the International Precision Child Health Partnership (IPCHiP). A total of 74% (17 of 23) of patients had a change in clinical care in response to genetic diagnosis, including 2 patients who received targeted therapy. This narrative review discusses the common causes of neonatal hypotonia, the relative benefits and limitations of available testing modalities used in NICUs, and hypotonia management recommendations. Conclusions and Relevance This narrative review summarizes the causes of neonatal hypotonia and the benefits of prompt genetic diagnosis, including improved prognostication and identification of targeted treatments which can improve the short-term and long-term outcomes. Institutional resources can vary among different NICUs; as a result, consideration should be given to rule out a small number of relatively unique conditions for which rapid targeted genetic testing is available. Nevertheless, the consensus recommendation is to use rapid genome or exome sequencing as a first-line testing option for NICU patients with unexplained hypotonia. As part of the IPCHiP, this diagnostic experience will be collected in a central database with the goal of advancing knowledge of neonatal hypotonia and improving evidence-based practice.
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Affiliation(s)
- Sarah U Morton
- Division of Newborn Medicine, Boston Children's Hospital, Boston, Massachusetts.,Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
| | - John Christodoulou
- Murdoch Children's Research Institute, Department of Paediatrics, University of Melbourne, Melbourne, Australia.,Discipline of Child and Adolescent Health, Sydney Medical School, University of Sydney, Sydney, Australia
| | - Gregory Costain
- Division of Clinical & Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada.,Program for Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.,Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Francesco Muntoni
- National Institute for Health Research Great Ormond Street Hospital Biomedical Research Centre, Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.,North East Thames Regional Genetic Service, Great Ormond Street Hospital Trust, London, United Kingdom
| | - Emma Wakeling
- North East Thames Regional Genetic Service, Great Ormond Street Hospital Trust, London, United Kingdom
| | - Monica H Wojcik
- Division of Newborn Medicine, Boston Children's Hospital, Boston, Massachusetts.,Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, Massachusetts.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts
| | - Courtney E French
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts
| | - Anna Szuto
- Department of Genetic Counselling, The Hospital for Sick Children, Toronto, Ontario, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - James J Dowling
- Program for Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.,Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.,Division of Neurology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Ronald D Cohn
- Division of Clinical & Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada.,Program for Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.,Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - F Lucy Raymond
- Department of Medical Genetics, University of Cambridge, Cambridge, United Kingdom
| | - Basil T Darras
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts
| | - David A Williams
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,Division of Hematology/Oncology, Boston Children's Hospital, Boston, Massachusetts.,Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Sebastian Lunke
- Murdoch Children's Research Institute, Department of Paediatrics, University of Melbourne, Melbourne, Australia.,Department of Pathology, University of Melbourne, Melbourne, Australia
| | - Zornitza Stark
- Murdoch Children's Research Institute, Department of Paediatrics, University of Melbourne, Melbourne, Australia.,Australian Genomics Health Alliance, Melbourne, Australia
| | - David H Rowitch
- Department of Medical Genetics, University of Cambridge, Cambridge, United Kingdom.,Division of Neonatology, Department of Pediatrics, University of California, San Francisco
| | - Pankaj B Agrawal
- Division of Newborn Medicine, Boston Children's Hospital, Boston, Massachusetts.,Department of Pediatrics, Harvard Medical School, Boston, Massachusetts.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, Massachusetts.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts
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6
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Herman DS, Rhoads DD, Schulz WL, Durant TJS. Artificial Intelligence and Mapping a New Direction in Laboratory Medicine: A Review. Clin Chem 2021; 67:1466-1482. [PMID: 34557917 DOI: 10.1093/clinchem/hvab165] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 07/26/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND Modern artificial intelligence (AI) and machine learning (ML) methods are now capable of completing tasks with performance characteristics that are comparable to those of expert human operators. As a result, many areas throughout healthcare are incorporating these technologies, including in vitro diagnostics and, more broadly, laboratory medicine. However, there are limited literature reviews of the landscape, likely future, and challenges of the application of AI/ML in laboratory medicine. CONTENT In this review, we begin with a brief introduction to AI and its subfield of ML. The ensuing sections describe ML systems that are currently in clinical laboratory practice or are being proposed for such use in recent literature, ML systems that use laboratory data outside the clinical laboratory, challenges to the adoption of ML, and future opportunities for ML in laboratory medicine. SUMMARY AI and ML have and will continue to influence the practice and scope of laboratory medicine dramatically. This has been made possible by advancements in modern computing and the widespread digitization of health information. These technologies are being rapidly developed and described, but in comparison, their implementation thus far has been modest. To spur the implementation of reliable and sophisticated ML-based technologies, we need to establish best practices further and improve our information system and communication infrastructure. The participation of the clinical laboratory community is essential to ensure that laboratory data are sufficiently available and incorporated conscientiously into robust, safe, and clinically effective ML-supported clinical diagnostics.
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Affiliation(s)
- Daniel S Herman
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel D Rhoads
- Department of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA.,Department of Pathology, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Wade L Schulz
- Department of Laboratory Medicine, Yale University, New Haven, CT, USA
| | - Thomas J S Durant
- Department of Laboratory Medicine, Yale University, New Haven, CT, USA
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7
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Ganguly P, Madonsela L, Chao JT, Loewen CJR, O’Connor TP, Verheyen EM, Allan DW. A scalable Drosophila assay for clinical interpretation of human PTEN variants in suppression of PI3K/AKT induced cellular proliferation. PLoS Genet 2021; 17:e1009774. [PMID: 34492006 PMCID: PMC8448351 DOI: 10.1371/journal.pgen.1009774] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 09/17/2021] [Accepted: 08/10/2021] [Indexed: 12/28/2022] Open
Abstract
Gene variant discovery is becoming routine, but it remains difficult to usefully interpret the functional consequence or disease relevance of most variants. To fill this interpretation gap, experimental assays of variant function are becoming common place. Yet, it remains challenging to make these assays reproducible, scalable to high numbers of variants, and capable of assessing defined gene-disease mechanism for clinical interpretation aligned to the ClinGen Sequence Variant Interpretation (SVI) Working Group guidelines for 'well-established assays'. Drosophila melanogaster offers great potential as an assay platform, but was untested for high numbers of human variants adherent to these guidelines. Here, we wished to test the utility of Drosophila as a platform for scalable well-established assays. We took a genetic interaction approach to test the function of ~100 human PTEN variants in cancer-relevant suppression of PI3K/AKT signaling in cellular growth and proliferation. We validated the assay using biochemically characterized PTEN mutants as well as 23 total known pathogenic and benign PTEN variants, all of which the assay correctly assigned into predicted functional categories. Additionally, function calls for these variants correlated very well with our recent published data from a human cell line. Finally, using these pathogenic and benign variants to calibrate the assay, we could set readout thresholds for clinical interpretation of the pathogenicity of 70 other PTEN variants. Overall, we demonstrate that Drosophila offers a powerful assay platform for clinical variant interpretation, that can be used in conjunction with other well-established assays, to increase confidence in the accurate assessment of variant function and pathogenicity.
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Affiliation(s)
- Payel Ganguly
- Department of Cellular and Physiological Sciences, Life Sciences Institute, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Landiso Madonsela
- Department of Molecular Biology and Biochemistry, Centre for Cell Biology, Development and Disease, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Jesse T. Chao
- Department of Cellular and Physiological Sciences, Life Sciences Institute, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Christopher J. R. Loewen
- Department of Cellular and Physiological Sciences, Life Sciences Institute, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Timothy P. O’Connor
- Department of Cellular and Physiological Sciences, Life Sciences Institute, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Esther M. Verheyen
- Department of Molecular Biology and Biochemistry, Centre for Cell Biology, Development and Disease, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Douglas W. Allan
- Department of Cellular and Physiological Sciences, Life Sciences Institute, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
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8
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Mohammed Y, Michaud SA, Pětrošová H, Yang J, Ganguly M, Schibli D, Flenniken AM, Nutter LMJ, Adissu HA, Lloyd KCK, McKerlie C, Borchers CH. Proteotyping of knockout mouse strains reveals sex- and strain-specific signatures in blood plasma. NPJ Syst Biol Appl 2021; 7:25. [PMID: 34050187 PMCID: PMC8163790 DOI: 10.1038/s41540-021-00184-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 04/25/2021] [Indexed: 11/24/2022] Open
Abstract
We proteotyped blood plasma from 30 mouse knockout strains and corresponding wild-type mice from the International Mouse Phenotyping Consortium. We used targeted proteomics with internal standards to quantify 375 proteins in 218 samples. Our results provide insights into the manifested effects of each gene knockout at the plasma proteome level. We first investigated possible contamination by erythrocytes during sample preparation and labeled, in one case, up to 11 differential proteins as erythrocyte originated. Second, we showed that differences in baseline protein abundance between female and male mice were evident in all mice, emphasizing the necessity to include both sexes in basic research, target discovery, and preclinical effect and safety studies. Next, we identified the protein signature of each gene knockout and performed functional analyses for all knockout strains. Further, to demonstrate how proteome analysis identifies the effect of gene deficiency beyond traditional phenotyping tests, we provide in-depth analysis of two strains, C8a-/- and Npc2+/-. The proteins encoded by these genes are well-characterized providing good validation of our method in homozygous and heterozygous knockout mice. Ig alpha chain C region, a poorly characterized protein, was among the differentiating proteins in C8a-/-. In Npc2+/- mice, where histopathology and traditional tests failed to differentiate heterozygous from wild-type mice, our data showed significant difference in various lysosomal storage disease-related proteins. Our results demonstrate how to combine absolute quantitative proteomics with mouse gene knockout strategies to systematically study the effect of protein absence. The approach used here for blood plasma is applicable to all tissue protein extracts.
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Affiliation(s)
- Yassene Mohammed
- University of Victoria-Genome BC Proteomics Centre, Victoria, BC, Canada.
- Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands.
| | - Sarah A Michaud
- University of Victoria-Genome BC Proteomics Centre, Victoria, BC, Canada.
| | - Helena Pětrošová
- University of Victoria-Genome BC Proteomics Centre, Victoria, BC, Canada
| | - Juncong Yang
- University of Victoria-Genome BC Proteomics Centre, Victoria, BC, Canada
| | - Milan Ganguly
- The Center for Phenogenomics, Toronto, ON, Canada
- The Hospital for Sick Children, Toronto, ON, Canada
| | - David Schibli
- University of Victoria-Genome BC Proteomics Centre, Victoria, BC, Canada
| | - Ann M Flenniken
- The Center for Phenogenomics, Toronto, ON, Canada
- Sinai Health Lunenfeld-Tanenbaum Research Institute, Toronto, ON, Canada
| | - Lauryl M J Nutter
- The Center for Phenogenomics, Toronto, ON, Canada
- The Hospital for Sick Children, Toronto, ON, Canada
| | | | - K C Kent Lloyd
- Department of Surgery, School of Medicine, and Mouse Biology Program, University of California, Davis, CA, USA
| | | | - Christoph H Borchers
- Proteomics Centre, Segal Cancer Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, QC, Canada.
- Gerald Bronfman Department of Oncology, Jewish General Hospital, Montreal, QC, Canada.
- Department of Data Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Moscow, Russia.
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9
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Del Re M, Cucchiara F, Rofi E, Fontanelli L, Petrini I, Gri N, Pasquini G, Rizzo M, Gabelloni M, Belluomini L, Crucitta S, Ciampi R, Frassoldati A, Neri E, Porta C, Danesi R. A multiparametric approach to improve the prediction of response to immunotherapy in patients with metastatic NSCLC. Cancer Immunol Immunother 2021; 70:1667-1678. [PMID: 33315149 PMCID: PMC8139911 DOI: 10.1007/s00262-020-02810-6] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 11/23/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND It is still unclear how to combine biomarkers to identify patients who will truly benefit from anti-PD-1 agents in NSCLC. This study investigates exosomal mRNA expression of PD-L1 and IFN-γ, PD-L1 polymorphisms, tumor mutational load (TML) in circulating cell-free DNA (cfDNA) and radiomic features as possible predictive markers of response to nivolumab and pembrolizumab in metastatic NSCLC patients. METHODS Patients were enrolled and blood (12 ml) was collected at baseline before receiving anti-PD-1 therapy. Exosome-derived mRNA and cfDNA were extracted to analyse PD-L1 and IFN-γ expression and tumor mutational load (TML) by digital droplet PCR (ddPCR) and next-generation sequencing (NGS), respectively. The PD-L1 single nucleotide polymorphisms (SNPs) c.-14-368 T > C and c.*395G > C, were analysed on genomic DNA by Real-Time PCR. A radiomic analysis was performed on the QUIBIM Precision® V3.0 platform. RESULTS Thirty-eight patients were enrolled. High baseline IFN-γ was independently associated with shorter median PFS (5.6 months vs. not reached p = 0.0057), and levels of PD-L1 showed an increase at 3 months vs. baseline in patients who progressed (p = 0.01). PD-L1 baseline levels showed significant direct and inverse relationships with radiomic features. Radiomic features also inversely correlated with PD-L1 expression in tumor tissue. In subjects receiving nivolumab, median PFS was shorter in carriers of c.*395GG vs. c.*395GC/CC genotype (2.3 months vs. not reached, p = 0.041). Lastly, responders had higher non-synonymous mutations and more links between co-occurring genetic somatic mutations and ARID1A alterations as well. CONCLUSIONS A combined multiparametric approach may provide a better understanding of the molecular determinants of response to immunotherapy.
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Affiliation(s)
- Marzia Del Re
- grid.5395.a0000 0004 1757 3729Unit of Clinical Pharmacology and Pharmacogenetics, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Federico Cucchiara
- grid.5395.a0000 0004 1757 3729Unit of Clinical Pharmacology and Pharmacogenetics, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Eleonora Rofi
- grid.5395.a0000 0004 1757 3729Unit of Clinical Pharmacology and Pharmacogenetics, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Lorenzo Fontanelli
- grid.5395.a0000 0004 1757 3729Unit of Clinical Pharmacology and Pharmacogenetics, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Iacopo Petrini
- grid.5395.a0000 0004 1757 3729General Pathology, Department of Translational Research and New Technologies in Medicine, University of Pisa, Pisa, Italy
| | - Nicole Gri
- Division of Translational Oncology, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy
| | - Giulia Pasquini
- grid.5395.a0000 0004 1757 3729General Pathology, Department of Translational Research and New Technologies in Medicine, University of Pisa, Pisa, Italy
| | - Mimma Rizzo
- Division of Translational Oncology, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy
| | - Michela Gabelloni
- grid.5395.a0000 0004 1757 3729Diagnostic and Interventional Radiology, Department of Translational Research and New Technologies in Medicine, University of Pisa, Pisa, Italy
| | - Lorenzo Belluomini
- grid.416315.4Unit of Clinical Oncology, Specialist Medical Department, S. Anna University Hospital, Ferrara, Italy
| | - Stefania Crucitta
- grid.5395.a0000 0004 1757 3729Unit of Clinical Pharmacology and Pharmacogenetics, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Raffaele Ciampi
- grid.5395.a0000 0004 1757 3729Endocrinology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Antonio Frassoldati
- grid.416315.4Unit of Clinical Oncology, Specialist Medical Department, S. Anna University Hospital, Ferrara, Italy
| | - Emanuele Neri
- grid.5395.a0000 0004 1757 3729Diagnostic and Interventional Radiology, Department of Translational Research and New Technologies in Medicine, University of Pisa, Pisa, Italy
| | - Camillo Porta
- Division of Translational Oncology, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy ,grid.8982.b0000 0004 1762 5736Department of Internal Medicine and Therapeutics, University of Pavia, Pavia, Italy ,grid.7644.10000 0001 0120 3326Present Address: Unit of Medical Oncology, Department of Biomedical Sciences and Human Oncology, University of Bari ‘A. Moro’, Bari, Italy
| | - Romano Danesi
- Unit of Clinical Pharmacology and Pharmacogenetics, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
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10
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Velázquez C, Lastra E, Avila Cobos F, Abella L, de la Cruz V, Hernando BA, Hernández L, Martínez N, Infante M, Durán M. A comprehensive custom panel evaluation for routine hereditary cancer testing: improving the yield of germline mutation detection. J Transl Med 2020; 18:232. [PMID: 32522261 PMCID: PMC7288470 DOI: 10.1186/s12967-020-02391-z] [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: 01/24/2020] [Accepted: 05/28/2020] [Indexed: 12/12/2022] Open
Abstract
Background In the context of our Regional Program of Hereditary Cancer, individuals fulfilling the criteria are tested for germline mutations to subsequently establish the clinical management. Our standard diagnostic approach focuses on sequencing a few classic high-risk genes, a method that frequently renders uninformative genetic results. This study aims to examine the improved yield offered by an On-Demand panel. Methods We designed an On-Demand panel for the analysis of 35-genes associated with inherited cancer susceptibility in a total of 128 cases of Hereditary Breast and Ovarian Cancer (HBOC) and Hereditary Nonpolyposis Colorectal Cancer (HNPCC). Results Eighteen deleterious mutations were detected, in both routinely (BRCA2, MLH1, MSH2, PMS2) and non-routinely (ATM, BLM, BRIP1, CHEK2, MUTYH) tested genes. The screening extended to 35 genes rendered by patients carrying several- up to 6-Variants of Unknown Significance (VUS). Moreover, we confirmed the splicing disruption at RNA level for a not previously reported BRIP1 splicing mutation. Using an On-Demand panel, we identified 18 pathogenic mutation carriers, seven of which would have gone unnoticed with traditional analysis. Conclusions Our results reinforce the utility of NGS gene panels in the diagnostic routine to increase the performance of genetic testing, especially in individuals from families with overlapping cancer phenotypes.
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Affiliation(s)
- Carolina Velázquez
- Cancer Genetics Group, Institute of Genetics and Molecular Biology (UVa-CSIC), Sanz y Forés 3, 47003, Valladolid, Spain. .,IRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Université de Montpellier, Montpellier, France.
| | - Enrique Lastra
- Unit of Genetic Counseling in Cancer, Complejo Hospitalario de Burgos, Burgos, Spain
| | | | - Luis Abella
- Unit of Genetic Counseling in Cancer, Hospital Universitario Rio Hortega, Valladolid, Spain
| | - Virginia de la Cruz
- Unit of Genetic Counseling in Cancer, Hospital Universitario Rio Hortega, Valladolid, Spain
| | | | - Lara Hernández
- Cancer Genetics Group, Institute of Genetics and Molecular Biology (UVa-CSIC), Sanz y Forés 3, 47003, Valladolid, Spain
| | - Noemí Martínez
- Cancer Genetics Group, Institute of Genetics and Molecular Biology (UVa-CSIC), Sanz y Forés 3, 47003, Valladolid, Spain
| | - Mar Infante
- Cancer Genetics Group, Institute of Genetics and Molecular Biology (UVa-CSIC), Sanz y Forés 3, 47003, Valladolid, Spain
| | - Mercedes Durán
- Cancer Genetics Group, Institute of Genetics and Molecular Biology (UVa-CSIC), Sanz y Forés 3, 47003, Valladolid, Spain
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11
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Chao JT, Hollman R, Meyers WM, Meili F, Matreyek KA, Dean P, Fowler DM, Haas K, Roskelley CD, Loewen CJR. A Premalignant Cell-Based Model for Functionalization and Classification of PTEN Variants. Cancer Res 2020; 80:2775-2789. [PMID: 32366478 DOI: 10.1158/0008-5472.can-19-3278] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 12/16/2019] [Accepted: 04/23/2020] [Indexed: 11/16/2022]
Abstract
As sequencing becomes more economical, we are identifying sequence variations in the population faster than ever. For disease-associated genes, it is imperative that we differentiate a sequence variant as either benign or pathogenic, such that the appropriate therapeutic interventions or surveillance can be implemented. PTEN is a frequently mutated tumor suppressor that has been linked to the PTEN hamartoma tumor syndrome. Although the domain structure of PTEN and the functional impact of a number of its most common tumor-linked mutations have been characterized, there is a lack of information about many recently identified clinical variants. To address this challenge, we developed a cell-based assay that utilizes a premalignant phenotype of normal mammary epithelial cells lacking PTEN. We measured the ability of PTEN variants to rescue the spheroid formation phenotype of PTEN-/- MCF10A cells maintained in suspension. As proof of concept, we functionalized 47 missense variants using this assay, only 19 of which have clear classifications in ClinVar. We utilized a machine learning model trained with annotated genotypic data to classify variants as benign or pathogenic based on our functional scores. Our model predicted with high accuracy that loss of PTEN function was indicative of pathogenicity. We also determined that the pathogenicity of certain variants may have arisen from reduced stability of the protein product. Overall, this assay outperformed computational predictions, was scalable, and had a short run time, serving as an ideal alternative for annotating the clinical significance of cancer-associated PTEN variants. SIGNIFICANCE: Combined three-dimensional tumor spheroid modeling and machine learning classifies PTEN missense variants, over 70% of which are currently listed as variants of uncertain significance. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/13/2775/F1.large.jpg.
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Affiliation(s)
- Jesse T Chao
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Rocio Hollman
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Warren M Meyers
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Fabian Meili
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Kenneth A Matreyek
- Department of Pathology, Case Western Reserve University School of Medicine, Cleveland, Ohio.,Department of Genome Sciences, University of Washington, Seattle, Washington
| | - Pamela Dean
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Douglas M Fowler
- Department of Genome Sciences, University of Washington, Seattle, Washington.,Department of Bioengineering, University of Washington, Seattle, Washington
| | - Kurt Haas
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Calvin D Roskelley
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Christopher J R Loewen
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, Canada.
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12
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Leonard RJ, Preston CC, Gucwa ME, Afeworki Y, Selya AS, Faustino RS. Protein Subdomain Enrichment of NUP155 Variants Identify a Novel Predicted Pathogenic Hotspot. Front Cardiovasc Med 2020; 7:8. [PMID: 32118046 PMCID: PMC7019101 DOI: 10.3389/fcvm.2020.00008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 01/17/2020] [Indexed: 01/05/2023] Open
Abstract
Functional variants in nuclear envelope genes are implicated as underlying causes of cardiopathology. To examine the potential association of single nucleotide variants of nucleoporin genes with cardiac disease, we employed a prognostic scoring approach to investigate variants of NUP155, a nucleoporin gene clinically linked with atrial fibrillation. Here we implemented bioinformatic profiling and predictive scoring, based on the gnomAD, National Heart Lung and Blood Institute-Exome Sequencing Project (NHLBI-ESP) Exome Variant Server, and dbNSFP databases to identify rare single nucleotide variants (SNVs) of NUP155 potentially associated with cardiopathology. This predictive scoring revealed 24 SNVs of NUP155 as potentially cardiopathogenic variants located primarily in the N-terminal crescent-shaped domain of NUP155. In addition, a predicted NUP155 R672G variant prioritized in our study was mapped to a region within the alpha helical stack of the crescent domain of NUP155. Bioinformatic analysis of inferred protein-protein interactions of NUP155 revealed over representation of top functions related to molecular transport, RNA trafficking, and RNA post-transcriptional modification. Topology analysis revealed prioritized hubs critical for maintaining network integrity and informational flow that included FN1, SIRT7, and CUL7 with nodal enrichment of RNA helicases in the topmost enriched subnetwork. Furthermore, integration of the top 5 subnetworks to capture network topology of an expanded framework revealed that FN1 maintained its hub status, with elevation of EED, CUL3, and EFTUD2. This is the first study to report novel discovery of a NUP155 subdomain hotspot that enriches for allelic variants of NUP155 predicted to be clinically damaging, and supports a role for RNA metabolism in cardiac disease and development.
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Affiliation(s)
- Riley J. Leonard
- Genetics and Genomics Group, Sanford Research, Sioux Falls, SD, United States
- Department of Biology, College of St. Benedict/St. John's University, Collegeville, MN, United States
| | - Claudia C. Preston
- Genetics and Genomics Group, Sanford Research, Sioux Falls, SD, United States
| | - Melanie E. Gucwa
- Genetics and Genomics Group, Sanford Research, Sioux Falls, SD, United States
- Department of Biology, Carthage College, Kenosha, WI, United States
| | - Yohannes Afeworki
- Functional Genomics & Bioinformatics Core Facility, Sanford Research, Sioux Falls, SD, United States
| | - Arielle S. Selya
- Behavioral Sciences Group, Sanford Research, Sioux Falls, SD, United States
| | - Randolph S. Faustino
- Genetics and Genomics Group, Sanford Research, Sioux Falls, SD, United States
- Department of Pediatrics, Sanford School of Medicine of the University of South Dakota, Sioux Falls, SD, United States
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13
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Selecting variants of unknown significance through network-based gene-association significantly improves risk prediction for disease-control cohorts. Sci Rep 2019; 9:3266. [PMID: 30824863 PMCID: PMC6397233 DOI: 10.1038/s41598-019-39796-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Accepted: 01/31/2019] [Indexed: 12/12/2022] Open
Abstract
Variants of unknown/uncertain significance (VUS) pose a huge dilemma in current genetic variation screening methods and genetic counselling. Driven by methods of next generation sequencing (NGS) such as whole exome sequencing (WES), a plethora of VUS are being detected in research laboratories as well as in the health sector. Motivated by this overabundance of VUS, we propose a novel computational methodology, termed VariantClassifier (VarClass), which utilizes gene-association networks and polygenic risk prediction models to shed light into this grey area of genetic variation in association with disease. VarClass has been evaluated using numerous validation steps and proves to be very successful in assigning significance to VUS in association with specific diseases of interest. Notably, using VUS that are deemed significant by VarClass, we improved risk prediction accuracy in four large case-studies involving disease-control cohorts from GWAS as well as WES, when compared to traditional odds ratio analysis. Biological interpretation of selected high scoring VUS revealed interesting biological themes relevant to the diseases under investigation. VarClass is available as a standalone tool for large-scale data analyses, as well as a web-server with additional functionalities through a user-friendly graphical interface.
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14
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Todd JJ, Sagar V, Lawal TA, Allen C, Razaqyar MS, Shelton MS, Chrismer IC, Zhang X, Cosgrove MM, Kuo A, Vasavada R, Jain MS, Waite M, Rajapakse D, Witherspoon JW, Wistow G, Meilleur KG. Correlation of phenotype with genotype and protein structure in RYR1-related disorders. J Neurol 2018; 265:2506-2524. [PMID: 30155738 PMCID: PMC6182665 DOI: 10.1007/s00415-018-9033-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 08/17/2018] [Accepted: 08/18/2018] [Indexed: 01/01/2023]
Abstract
Variants in the skeletal muscle ryanodine receptor 1 gene (RYR1) result in a spectrum of RYR1-related disorders. Presentation during infancy is typical and ranges from delayed motor milestones and proximal muscle weakness to severe respiratory impairment and ophthalmoplegia. We aimed to elucidate correlations between genotype, protein structure and clinical phenotype in this rare disease population. Genetic and clinical data from 47 affected individuals were analyzed and variants mapped to the cryo-EM RyR1 structure. Comparisons of clinical severity, motor and respiratory function and symptomatology were made according to the mode of inheritance and affected RyR1 structural domain(s). Overall, 49 RYR1 variants were identified in 47 cases (dominant/de novo, n = 35; recessive, n = 12). Three variants were previously unreported. In recessive cases, facial weakness, neonatal hypotonia, ophthalmoplegia/paresis, ptosis, and scapular winging were more frequently observed than in dominant/de novo cases (all, p < 0.05). Both dominant/de novo and recessive cases exhibited core myopathy histopathology. Clinically severe cases were typically recessive or had variants localized to the RyR1 cytosolic shell domain. Motor deficits were most apparent in the MFM-32 standing and transfers dimension, [median (IQR) 85.4 (18.8)% of maximum score] and recessive cases exhibited significantly greater overall motor function impairment compared to dominant/de novo cases [79.7 (18.8)% vs. 87.5 (17.7)% of maximum score, p = 0.03]. Variant mapping revealed patterns of clinical severity across RyR1 domains, including a structural plane of interest within the RyR1 cytosolic shell, in which 84% of variants affected the bridging solenoid. We have corroborated genotype-phenotype correlations and identified RyR1 regions that may be especially sensitive to structural modification.
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Affiliation(s)
- Joshua J Todd
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA.
| | - Vatsala Sagar
- Section on Molecular Structure and Functional Genomics, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Tokunbor A Lawal
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Carolyn Allen
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Muslima S Razaqyar
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Monique S Shelton
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Irene C Chrismer
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Xuemin Zhang
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Mary M Cosgrove
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Anna Kuo
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Ruhi Vasavada
- Mark O. Hatfield Clinical Research Center, Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, USA
| | - Minal S Jain
- Mark O. Hatfield Clinical Research Center, Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, USA
| | - Melissa Waite
- Mark O. Hatfield Clinical Research Center, Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, USA
| | - Dinusha Rajapakse
- Section on Molecular Structure and Functional Genomics, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jessica W Witherspoon
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
| | - Graeme Wistow
- Section on Molecular Structure and Functional Genomics, National Eye Institute, National Institutes of Health, Bethesda, MD, USA
| | - Katherine G Meilleur
- Neuromuscular Symptoms Unit, Tissue Injury Branch, National Institute of Nursing Research, National Institutes of Health, 10 Center Drive, Room 2A07, Bethesda, MD, 20892, USA
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15
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Musunuru K, Sheikh F, Gupta RM, Houser SR, Maher KO, Milan DJ, Terzic A, Wu JC. Induced Pluripotent Stem Cells for Cardiovascular Disease Modeling and Precision Medicine: A Scientific Statement From the American Heart Association. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2018; 11:e000043. [PMID: 29874173 PMCID: PMC6708586 DOI: 10.1161/hcg.0000000000000043] [Citation(s) in RCA: 125] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Induced pluripotent stem cells (iPSCs) offer an unprece-dented opportunity to study human physiology and disease at the cellular level. They also have the potential to be leveraged in the practice of precision medicine, for example, personalized drug testing. This statement comprehensively describes the provenance of iPSC lines, their use for cardiovascular disease modeling, their use for precision medicine, and strategies through which to promote their wider use for biomedical applications. Human iPSCs exhibit properties that render them uniquely qualified as model systems for studying human diseases: they are of human origin, which means they carry human genomes; they are pluripotent, which means that in principle, they can be differentiated into any of the human body's somatic cell types; and they are stem cells, which means they can be expanded from a single cell into millions or even billions of cell progeny. iPSCs offer the opportunity to study cells that are genetically matched to individual patients, and genome-editing tools allow introduction or correction of genetic variants. Initial progress has been made in using iPSCs to better understand cardiomyopathies, rhythm disorders, valvular and vascular disorders, and metabolic risk factors for ischemic heart disease. This promising work is still in its infancy. Similarly, iPSCs are only just starting to be used to identify the optimal medications to be used in patients from whom the cells were derived. This statement is intended to (1) summarize the state of the science with respect to the use of iPSCs for modeling of cardiovascular traits and disorders and for therapeutic screening; (2) identify opportunities and challenges in the use of iPSCs for disease modeling and precision medicine; and (3) outline strategies that will facilitate the use of iPSCs for biomedical applications. This statement is not intended to address the use of stem cells as regenerative therapy, such as transplantation into the body to treat ischemic heart disease or heart failure.
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16
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Phan HTN, Sjögren B, Neubig RR. Human Missense Mutations in Regulator of G Protein Signaling 2 Affect the Protein Function Through Multiple Mechanisms. Mol Pharmacol 2017; 92:451-458. [PMID: 28784619 DOI: 10.1124/mol.117.109215] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Accepted: 08/02/2017] [Indexed: 01/11/2023] Open
Abstract
Regulator of G protein signaling 2 (RGS2) plays a significant role in alleviating vascular contraction and promoting vascular relaxation due to its GTPase accelerating protein activity toward Gαq. Mice lacking RGS2 display a hypertensive phenotype, and several RGS2 missense mutations have been found predominantly in hypertensive human subjects. However, the mechanisms whereby these mutations could impact blood pressure is unknown. Here, we selected 16 rare, missense mutations in RGS2 identified in various human exome sequencing projects and evaluated their ability to inhibit intracellular calcium release mediated by angiotensin II receptor type 1 (AT1R). Four of them had reduced function and were further investigated to elucidate underlying mechanisms. Low protein expression, protein mislocalization, and reduced G protein binding were identified as likely mechanisms of the malfunctioning mutants. The Q2L mutant had 50% lower RGS2 than wild-type (WT) protein detected by Western blot. Confocal microscopy demonstrated that R44H and D40Y had impaired plasma membrane targeting; only 46% and 35% of those proteins translocated to the plasma membrane when coexpressed with Gαq Q209L compared with 67% for WT RGS2. The R188H mutant had a significant reduction in Gαq binding affinity (10-fold increase in Ki compared with WT RGS2 in a flow cytometry competition binding assay). This study provides functional data for 16 human RGS2 missense variants on their effects on AT1R-mediated calcium mobilization and provides molecular understanding of those variants with functional loss in vitro. These molecular behaviors can provide insight to inform antihypertensive therapeutics in individuals with variants having reduced function.
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Affiliation(s)
- Hoa T N Phan
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, Michigan
| | - Benita Sjögren
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, Michigan
| | - Richard R Neubig
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, Michigan
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17
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Chandonia JM, Adhikari A, Carraro M, Chhibber A, Cutting GR, Fu Y, Gasparini A, Jones DT, Kramer A, Kundu K, Lam HYK, Leonardi E, Moult J, Pal LR, Searls DB, Shah S, Sunyaev S, Tosatto SCE, Yin Y, Buckley BA. Lessons from the CAGI-4 Hopkins clinical panel challenge. Hum Mutat 2017; 38:1155-1168. [PMID: 28397312 DOI: 10.1002/humu.23225] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 03/24/2017] [Accepted: 03/29/2017] [Indexed: 12/17/2022]
Abstract
The CAGI-4 Hopkins clinical panel challenge was an attempt to assess state-of-the-art methods for clinical phenotype prediction from DNA sequence. Participants were provided with exonic sequences of 83 genes for 106 patients from the Johns Hopkins DNA Diagnostic Laboratory. Five groups participated in the challenge, predicting both the probability that each patient had each of the 14 possible classes of disease, as well as one or more causal variants. In cases where the Hopkins laboratory reported a variant, at least one predictor correctly identified the disease class in 36 of the 43 patients (84%). Even in cases where the Hopkins laboratory did not find a variant, at least one predictor correctly identified the class in 39 of the 63 patients (62%). Each prediction group correctly diagnosed at least one patient that was not successfully diagnosed by any other group. We discuss the causal variant predictions by different groups and their implications for further development of methods to assess variants of unknown significance. Our results suggest that clinically relevant variants may be missed when physicians order small panels targeted on a specific phenotype. We also quantify the false-positive rate of DNA-guided analysis in the absence of prior phenotypic indication.
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Affiliation(s)
- John-Marc Chandonia
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California
| | - Aashish Adhikari
- Department of Plant and Microbial Biology, University of California, Berkeley, California
| | - Marco Carraro
- Department of Biomedical Sciences, University of Padova, Padova, Italy
| | | | - Garry R Cutting
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Yao Fu
- Roche Sequencing Solutions, Belmont, California
| | - Alessandra Gasparini
- Department of Biomedical Sciences, University of Padova, Padova, Italy.,Department of Women's and Children's Health, University of Padova, Padova, Italy
| | - David T Jones
- Department of Computer Science, University College London, London, United Kingdom
| | | | - Kunal Kundu
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.,Computational Biology, Bioinformatics and Genomics, Biological Sciences Graduate Program, University of Maryland, College Park, Maryland
| | | | - Emanuela Leonardi
- Department of Women's and Children's Health, University of Padova, Padova, Italy
| | - John Moult
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.,Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland
| | - Lipika R Pal
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland
| | | | - Sohela Shah
- Qiagen Bioinformatics, Redwood City, California
| | - Shamil Sunyaev
- Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts.,Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Silvio C E Tosatto
- Department of Biomedical Sciences, University of Padova, Padova, Italy.,CNR Institute of Neuroscience, Padova, Italy
| | - Yizhou Yin
- Institute for Bioscience and Biotechnology Research, University of Maryland, Rockville, Maryland.,Computational Biology, Bioinformatics and Genomics, Biological Sciences Graduate Program, University of Maryland, College Park, Maryland
| | - Bethany A Buckley
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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18
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Factor VIII mutation spectrum in haemophilia A patients in the population of Henan, China. Blood Coagul Fibrinolysis 2017; 28:509-513. [PMID: 28252515 DOI: 10.1097/mbc.0000000000000628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
: Defects in the coagulation factor VIII gene cause haemophilia A, which is the most common X-linked recessive bleeding disorder. In total, 45 affected families were investigated to elucidate the factor VIII gene mutation spectrum. The families were subjected to clinical, biochemical, and molecular analyses. Inverse-shifting PCR was first applied to severe haemophilia A patients to identify inversions in introns 22 and 1. Then, next-generation sequencing was performed to detect mutations in inversion-negative patients with severe haemophilia A and moderate-mild haemophilia A patients. Finally, multiplex ligation-dependent probe amplification was utilized to identify rare cases with large fragment duplications or deletions in the factor VIII gene. In total, 41 mutations were identified, 19 of which (c.24C>A, c.49T>C, c.170_171delTT, c.533T>C, c.1126delG, c.1495delA, c.1660A>C, c.1736A>G, c.2711-2712insAATCT, c.3077C>G, c.3846delA, c.4238C>G, c.4349delG, c.4828G>C, c.5821A>C, c.6190C>T, c.6656T>C, c.6902T>G, and c.1904-2A>T) were novel and 80% (44/55) of the pathogenic mutations fell into the categories of missense (43.6%), nonsense (16.36%), frameshift (14.55%), and splice (5.45%) mutations. Additionally, 10 (18.18%) patients displayed inversions in intron 22 or 1 and one case (1.82%) exhibited a 3059-bp large fragment deletion in factor VIII. This study aimed to provide insight contributing to the genetic diagnosis of haemophilia A and to fill gaps in the factor VIII mutation spectrum in northern China.
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19
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Cayer DM, Nazor KL, Schork NJ. Mission critical: the need for proteomics in the era of next-generation sequencing and precision medicine. Hum Mol Genet 2016; 25:R182-R189. [DOI: 10.1093/hmg/ddw214] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Accepted: 06/29/2016] [Indexed: 12/14/2022] Open
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20
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Garrett LT, Hickman N, Jacobson A, Bennett RL, Amendola LM, Rosenthal EA, Shirts BH. Family Studies for Classification of Variants of Uncertain Classification: Current Laboratory Clinical Practice and a New Web-Based Educational Tool. J Genet Couns 2016; 25:1146-1156. [PMID: 27422780 PMCID: PMC5114323 DOI: 10.1007/s10897-016-9993-2] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2016] [Accepted: 06/30/2016] [Indexed: 01/28/2023]
Abstract
Multi-gene cancer panels often identify variants of uncertain clinical significance (VUS) that pose a challenge to health care providers in managing a patient's cancer risk. Family segregation analysis can yield powerful data to re-classify a VUS (as either benign or pathogenic). However, financial and personnel resources to coordinate these studies are limited. In an informal assessment we found that family studies for variant classification are done by most clinical genetics laboratories that offer hereditary cancer panel testing. The process for family studies differs substantially across laboratories. One near universal limitation is that families usually have too few individuals for an informative co-segregation analysis. A unique and potential resource-saving approach is to engage patients and their families in expanding their own pedigrees for segregation analysis of their VUS. We describe a novel public educational tool ( FindMyVariant.org ) designed to inform patients and genetic counselors about strategies to improve the probability of variant classification using familial segregation. While the web tool is designed to be useful for any gene, the project was primarily focused on VUS's returned in cancer risk genes. FindMyVariant.org is a resource for genetic providers to offer motivated families who are willing to gather information about their family relationships and history. Working alongside clinical or research genetic laboratories, the information they collect may help reclassify their VUS using segregation analysis.
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Affiliation(s)
- Lauren T Garrett
- Department of Laboratory Medicine, University of Washington, Rm NW120, Box 357110, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Nathan Hickman
- Department of Laboratory Medicine, University of Washington, Rm NW120, Box 357110, 1959 NE Pacific Street, Seattle, WA, 98195, USA
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA
| | - Angela Jacobson
- Department of Laboratory Medicine, University of Washington, Rm NW120, Box 357110, 1959 NE Pacific Street, Seattle, WA, 98195, USA
| | - Robin L Bennett
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA
| | - Laura M Amendola
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA
| | - Elisabeth A Rosenthal
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA
| | - Brian H Shirts
- Department of Laboratory Medicine, University of Washington, Rm NW120, Box 357110, 1959 NE Pacific Street, Seattle, WA, 98195, USA.
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