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Lin L, Zhang Y, Pan H, Wang J, Qi Y, Ma Y. Inconsistencies between prenatal diagnostic and genetic testing laboratories on variant validation of rare monogenic diseases. Prenat Diagn 2024; 44:1053-1061. [PMID: 38898598 DOI: 10.1002/pd.6628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 05/14/2024] [Accepted: 06/10/2024] [Indexed: 06/21/2024]
Abstract
BACKGROUND The advent of next-generation sequencing (NGS) has enhanced the diagnostic efficacy for monogenic diseases, while presenting challenges in achieving consistent diagnoses. METHOD We retrospectively analyzed the concordance rate and reasons for the inconsistency between the original diagnostic result from the genetic testing laboratory and the variant validation result from the prenatal diagnostic center. The validation procedure comprised three stages: validation of variant detection, reevaluation of variant classification, and assessment of recurrence risk, which involved verifying the mode of inheritance and parental carriage. RESULT In total, 17 (6%) of the 286 families affected by rare monogenic diseases showed different results during the variant validation procedure. These cases comprised four (23.5%) with variant detection errors, 12 (70.5%) with inconsistent interpretation, and one (6%) with non-Mendelian inheritance patterns. False-positive NGS results confirmed by Sanger sequencing were related to pseudogenes and GC-rich regions. The classification of the 17 variants was altered in the 12 cases owing to various factors. The case with an atypical inheritance pattern was originally considered autosomal recessive inheritance, but was diagnosed as maternal uniparental disomy after additional genetic analysis. CONCLUSION We underscored the significance of variant validation by prenatal diagnostic centers. Families affected by monogenic diseases with reproductive plans should be referred to prenatal genetic centers as early as possible to avoid different results that may postpone subsequent prenatal diagnosis.
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Affiliation(s)
- Liling Lin
- Department of Central Laboratory, Peking University First Hospital, Beijing, China
- Department of Clinical Laboratory, Peking Union Medical College Hospital, Beijing, China
| | - Ying Zhang
- Department of Central Laboratory, Peking University First Hospital, Beijing, China
| | - Hong Pan
- Department of Central Laboratory, Peking University First Hospital, Beijing, China
| | - Jingmin Wang
- Department of Pediatrics, Peking University First Hospital, Beijing, China
| | - Yu Qi
- Department of Central Laboratory, Peking University First Hospital, Beijing, China
| | - Yinan Ma
- Department of Central Laboratory, Peking University First Hospital, Beijing, China
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2
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Kraemer D, Terumalai D, Famiglietti ML, Filges I, Joset P, Koller S, Maurer F, Meier S, Nouspikel T, Sanz J, Zweier C, Abramowicz M, Berger W, Cichon S, Schaller A, Superti-Furga A, Barbié V, Rauch A. SwissGenVar: A Platform for Clinical-Grade Interpretation of Genetic Variants to Foster Personalized Healthcare in Switzerland. J Pers Med 2024; 14:648. [PMID: 38929869 PMCID: PMC11204794 DOI: 10.3390/jpm14060648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/28/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024] Open
Abstract
Large-scale next-generation sequencing (NGS) germline testing is technically feasible today, but variant interpretation represents a major bottleneck in analysis workflows. This includes extensive variant prioritization, annotation, and time-consuming evidence curation. The scale of the interpretation problem is massive, and variants of uncertain significance (VUSs) are a challenge to personalized medicine. This challenge is further compounded by the complexity and heterogeneity of the standards used to describe genetic variants and the associated phenotypes when searching for relevant information to support clinical decision making. To address this, all five Swiss academic institutions for Medical Genetics joined forces with the Swiss Institute of Bioinformatics (SIB) to create SwissGenVar as a user-friendly nationwide repository and sharing platform for genetic variant data generated during routine diagnostic procedures and research sequencing projects. Its aim is to provide a protected environment for expert evidence sharing about individual variants to harmonize and upscale their significance interpretation at the clinical grade according to international standards. To corroborate the clinical assessment, the variant-related data will be combined with consented high-quality clinical information. Broader visibility will be achieved by interfacing with international databases, thus supporting global initiatives in personalized healthcare.
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Affiliation(s)
- Dennis Kraemer
- Institute of Medical Genetics (IMG), University of Zurich (UZH), Wagistrasse 12, CH-8952 Zurich, Switzerland;
| | - Dillenn Terumalai
- Swiss Institute of Bioinformatics (SIB), Clinical Bioinformatics, CH-1202 Geneva, Switzerland; (D.T.); (V.B.)
| | | | - Isabel Filges
- Medical Genetics, Institute of Medical Genetics and Pathology, University Hospital Basel and University of Basel, CH-4031 Basel, Switzerland; (I.F.); (P.J.); (S.M.); (S.C.)
| | - Pascal Joset
- Medical Genetics, Institute of Medical Genetics and Pathology, University Hospital Basel and University of Basel, CH-4031 Basel, Switzerland; (I.F.); (P.J.); (S.M.); (S.C.)
| | - Samuel Koller
- Institute of Medical Molecular Genetics (IMMG), University of Zurich (UZH), Wagistrasse 12, CH-8952 Zurich, Switzerland; (S.K.); (W.B.)
| | - Fabienne Maurer
- Division of Genetic Medicine, Lausanne University Hospital (CHUV), CH-1011 Lausanne, Switzerland; (F.M.); (A.S.-F.)
| | - Stéphanie Meier
- Medical Genetics, Institute of Medical Genetics and Pathology, University Hospital Basel and University of Basel, CH-4031 Basel, Switzerland; (I.F.); (P.J.); (S.M.); (S.C.)
| | - Thierry Nouspikel
- Genetic Medicine Division, Diagnostics Department/Center for Genomic Medicine, Geneva University Hospitals (HUG), 1206 Geneva, Switzerland; (T.N.); (M.A.)
| | - Javier Sanz
- Department of Human Genetics, Inselspital, Bern University Hospital, CH-3010 Bern, Switzerland; (J.S.); (C.Z.); (A.S.)
| | - Christiane Zweier
- Department of Human Genetics, Inselspital, Bern University Hospital, CH-3010 Bern, Switzerland; (J.S.); (C.Z.); (A.S.)
| | - Marc Abramowicz
- Genetic Medicine Division, Diagnostics Department/Center for Genomic Medicine, Geneva University Hospitals (HUG), 1206 Geneva, Switzerland; (T.N.); (M.A.)
| | - Wolfgang Berger
- Institute of Medical Molecular Genetics (IMMG), University of Zurich (UZH), Wagistrasse 12, CH-8952 Zurich, Switzerland; (S.K.); (W.B.)
- Neuroscience Center Zurich (ZNZ), University and ETH Zurich, CH-8057 Zurich, Switzerland
- Zurich Center for Integrative Human Physiology (ZIHP), University of Zurich, CH-8057 Zurich, Switzerland
| | - Sven Cichon
- Medical Genetics, Institute of Medical Genetics and Pathology, University Hospital Basel and University of Basel, CH-4031 Basel, Switzerland; (I.F.); (P.J.); (S.M.); (S.C.)
| | - André Schaller
- Department of Human Genetics, Inselspital, Bern University Hospital, CH-3010 Bern, Switzerland; (J.S.); (C.Z.); (A.S.)
| | - Andrea Superti-Furga
- Division of Genetic Medicine, Lausanne University Hospital (CHUV), CH-1011 Lausanne, Switzerland; (F.M.); (A.S.-F.)
| | - Valérie Barbié
- Swiss Institute of Bioinformatics (SIB), Clinical Bioinformatics, CH-1202 Geneva, Switzerland; (D.T.); (V.B.)
| | - Anita Rauch
- Institute of Medical Genetics (IMG), University of Zurich (UZH), Wagistrasse 12, CH-8952 Zurich, Switzerland;
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Garza D, Hildebrand MS, Penington AJ, Brown N, de Silva MG. Australian healthcare professionals' perspectives on genetic counseling and genetic diagnosis in vascular anomalies. J Genet Couns 2024; 33:677-688. [PMID: 37632295 DOI: 10.1002/jgc4.1776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 08/13/2023] [Accepted: 08/17/2023] [Indexed: 08/27/2023]
Abstract
Genomic technologies are now utilized for the genetic diagnosis of vascular anomalies. This provides the opportunity for genetic counselors to make a significant contribution to patient care for this complex disease. The aim of this study was to explore Australian healthcare professionals' perspectives on the relatively recent integration of molecular diagnostic testing for vascular anomalies, with or without genetic counseling support. Nine semi-structured interviews were conducted with Australian healthcare professionals involved in the provision of care for individuals with vascular anomalies. Thematic analysis identified six themes: (1) Molecular diagnosis is beneficial; (2) psychosocial needs can motivate families to pursue a molecular diagnosis; (3) molecular genetic testing for vascular anomalies is complex; (4) genetic service provision is not a one size fits all; (5) a client-centered approach for genetic service provision can go a long way; and (6) the value of genetic counselors. Based on our findings, implementation of a vascular anomalies genetic diagnostic program inclusive of genetic counseling may be challenging, yet such programs are likely to benefit both patients and their families, as well as healthcare professionals. As this paradigm shift unfolds, genetic counselors have an opportunity to contribute to the vascular anomaly field by educating healthcare professionals and patients, by participating in multidisciplinary clinics to support complex cases and by raising awareness regarding their practice and potential contributions.
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Affiliation(s)
- Denisse Garza
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Tasmanian Clinical Genetics Service, Hobart, Tasmania, Australia
- School of Medicine and Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Michael S Hildebrand
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Epilepsy Research Centre, Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia
| | - Anthony J Penington
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Plastic and Maxillofacial Surgery, Royal Children's Hospital, Parkville, Victoria, Australia
| | - Natasha Brown
- Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Michelle G de Silva
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
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4
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Rizzo AD, Sanz M, Roffe G, Sajaroff EO, Prado DA, Prieto E, Goris V, Rossi JG, Bernasconi AR. CD62-L down-regulation after L18-MDP stimulation as a complementary flow cytometry functional assay for the diagnosis of XIAP deficiency. CYTOMETRY. PART B, CLINICAL CYTOMETRY 2024. [PMID: 38770762 DOI: 10.1002/cyto.b.22181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 04/26/2024] [Accepted: 05/06/2024] [Indexed: 05/22/2024]
Abstract
X-linked inhibitor of apoptosis (XIAP) deficiency is an infrequent inborn error of immunity caused by mutations in XIAP gene. Most cases present with absence of XIAP protein which can be detected by flow cytometry (FC), representing a rapid diagnostic method. However, since some genetic defects may not preclude protein expression, it is important to include a complementary functional test in the laboratory workup of these patients. L-selectin (CD62-L) is a molecule that is cleaved from the surface membrane of leukocytes upon stimulation of different receptors such as toll like receptors (TLRs) and nucleotide-binding oligomerization domain-like receptors (NLRs), including NOD2. Considering that XIAP deficiency impairs NOD2 signaling, we decided to assess CD62-L down-regulation by FC post-stimulation of neutrophils and monocytes with L18-muramyl Di-Peptide (L18-MDP), a NOD2 specific agonist, in order to develop a novel assay for the functional evaluation of patients with suspicion of XIAP defects. Whole blood samples from 20 healthy controls (HC) and four patients with confirmed molecular diagnosis of XIAP deficiency were stimulated with 200 ng/mL of L18-MDP for 2 h. Stimulation with 100 ng/mL of lipopolysaccharide (LPS) was carried out in parallel as a positive control of CD62-L shedding. CD62-L expression was evaluated by FC using an anti CD62-L- antibody and down-regulation was assessed by calculating the difference in CD62-L expression before and after stimulation, both in terms of percentage of CD62-L expressing cells (Δ%CD62-L) and median fluorescence intensity (ΔMFI%). Neutrophils and monocytes from XIAP deficient patients displayed a significantly diminished response to L18-MDP stimulation compared with HC (p < 0.0001), indicating a severely altered mechanism of CD62-L down-regulation following activation of NOD2-XIAP axis. On the other hand, the response to LPS stimulation was comparable between patients and heathy controls, suggesting preserved CD62-L shedding with a different stimulus. FC detection of CD62-L down-regulation in monocytes and neutrophils after whole blood stimulation with L18-MDP results in an effective and rapid functional test for the identification of XIAP deficient patients.
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Affiliation(s)
- Agustín D Rizzo
- Laboratory Division, Cellular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Marianela Sanz
- Laboratory Division, Cellular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Georgina Roffe
- Laboratory Division, Cellular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Elisa O Sajaroff
- Laboratory Division, Cellular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Damian A Prado
- Laboratory Division, Cellular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Emma Prieto
- Immunology and Rheumatology Division, Molecular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Verónica Goris
- Immunology and Rheumatology Division, Molecular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Jorge G Rossi
- Laboratory Division, Cellular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
| | - Andrea R Bernasconi
- Laboratory Division, Cellular Immunology Laboratory, Hospital de Pediatría S.A.M.I.C. Prof. Dr. Juan P. Garrahan, Buenos Aires, Argentina
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5
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Mao D, Liu C, Wang L, Ai-Ouran R, Deisseroth C, Pasupuleti S, Kim SY, Li L, Rosenfeld JA, Meng L, Burrage LC, Wangler MF, Yamamoto S, Santana M, Perez V, Shukla P, Eng CM, Lee B, Yuan B, Xia F, Bellen HJ, Liu P, Liu Z. AI-MARRVEL - A Knowledge-Driven AI System for Diagnosing Mendelian Disorders. NEJM AI 2024; 1:10.1056/aioa2300009. [PMID: 38962029 PMCID: PMC11221788 DOI: 10.1056/aioa2300009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/05/2024]
Abstract
BACKGROUND Diagnosing genetic disorders requires extensive manual curation and interpretation of candidate variants, a labor-intensive task even for trained geneticists. Although artificial intelligence (AI) shows promise in aiding these diagnoses, existing AI tools have only achieved moderate success for primary diagnosis. METHODS AI-MARRVEL (AIM) uses a random-forest machine-learning classifier trained on over 3.5 million variants from thousands of diagnosed cases. AIM additionally incorporates expert-engineered features into training to recapitulate the intricate decision-making processes in molecular diagnosis. The online version of AIM is available at https://ai.marrvel.org. To evaluate AIM, we benchmarked it with diagnosed patients from three independent cohorts. RESULTS AIM improved the rate of accurate genetic diagnosis, doubling the number of solved cases as compared with benchmarked methods, across three distinct real-world cohorts. To better identify diagnosable cases from the unsolved pools accumulated over time, we designed a confidence metric on which AIM achieved a precision rate of 98% and identified 57% of diagnosable cases out of a collection of 871 cases. Furthermore, AIM's performance improved after being fine-tuned for targeted settings including recessive disorders and trio analysis. Finally, AIM demonstrated potential for novel disease gene discovery by correctly predicting two newly reported disease genes from the Undiagnosed Diseases Network. CONCLUSIONS AIM achieved superior accuracy compared with existing methods for genetic diagnosis. We anticipate that this tool may aid in primary diagnosis, reanalysis of unsolved cases, and the discovery of novel disease genes. (Funded by the NIH Common Fund and others.).
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Affiliation(s)
- Dongxue Mao
- Department of Pediatrics, Baylor College of Medicine, Houston
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
| | - Chaozhong Liu
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
- Graduate School of Biomedical Sciences, Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston
| | - Linhua Wang
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
- Graduate School of Biomedical Sciences, Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston
| | - Rami Ai-Ouran
- Department of Pediatrics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
- Department of Data Science and AI, Al Hussein Technical University, Amman, Jordan
| | - Cole Deisseroth
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
| | - Sasidhar Pasupuleti
- Department of Pediatrics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
| | - Seon Young Kim
- Department of Pediatrics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
| | - Lucian Li
- Department of Pediatrics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
| | - Jill A Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
| | - Linyan Meng
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Baylor Genetics, Houston7
| | - Lindsay C Burrage
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
| | - Michael F Wangler
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
| | - Shinya Yamamoto
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
| | | | | | | | - Christine M Eng
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Baylor Genetics, Houston7
| | - Brendan Lee
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
| | - Bo Yuan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Human Genome Sequencing Center, Baylor College of Medicine, Houston
| | - Fan Xia
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Baylor Genetics, Houston7
| | - Hugo J Bellen
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
- Department of Neuroscience, Baylor College of Medicine, Houston
| | - Pengfei Liu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston
- Baylor Genetics, Houston7
| | - Zhandong Liu
- Department of Pediatrics, Baylor College of Medicine, Houston
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston
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6
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Koike Y, Osakabe M, Sugimoto R, Uesugi N, Matsumoto T, Suzuki H, Yanagawa N, Sugai T. A genome-wide study of gastric intramucosal neoplasia based on somatic copy number alterations, gene mutations, and mRNA expression patterns. J Pathol Clin Res 2024; 10:e12368. [PMID: 38454538 PMCID: PMC10920940 DOI: 10.1002/2056-4538.12368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/20/2024] [Accepted: 02/21/2024] [Indexed: 03/09/2024]
Abstract
We performed comprehensive analyses of somatic copy number alterations (SCNAs) and gene expression profiles of gastric intramucosal neoplasia (IMN) using array-based methods in 97 intestinal-type IMNs, including 39 low-grade dysplasias (LGDs), 37 high-grade dysplasias (HGDs), and 26 intramucosal carcinomas (IMCs) with stromal invasion of the lamina propria to identify the molecular mechanism of IMN. In addition, we examined gene mutations using gene panel analyses. We used cluster analyses for exclusion of arbitrariness to identify SCNA patterns and expression profiles. IMNs were classified into two distinct subgroups (subgroups 1 and 2) based on SCNA patterns. Subgroup 1 showed a genomic stable pattern due to the low frequency of SCNAs, whereas subgroup 2 exhibited a chromosomal instability pattern due to the high frequencies of SCNAs and TP53 mutations. Interestingly, although the frequencies of LGD and HGD were significantly higher in subgroup 1 than in subgroup 2, IMC was commonly found in both types. Although the expression profiles of specific mRNAs could be used to categorise subgroups 1 and 2, no clinicopathological findings correlated with either subgroup. We examined signalling pathways specific to subgroups 1 and 2 to identify the association of each subgroup with signalling pathways based on gene ontology tree visualisation: subgroups 1 and 2 were associated with haem metabolism and chromosomal instability, respectively. These findings reveal a comprehensive genomic landscape that highlights the molecular complexity of IMNs and provide a road map to facilitate our understanding of gastric IMNs.
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Affiliation(s)
- Yoshihiko Koike
- Department of Molecular Diagnostic Pathology, School of MedicineIwate Medical UniversityShiwagun'yahabachouJapan
| | - Mitsumasa Osakabe
- Department of Molecular Diagnostic Pathology, School of MedicineIwate Medical UniversityShiwagun'yahabachouJapan
| | - Ryo Sugimoto
- Department of Molecular Diagnostic Pathology, School of MedicineIwate Medical UniversityShiwagun'yahabachouJapan
| | - Noriyuku Uesugi
- Department of Molecular Diagnostic Pathology, School of MedicineIwate Medical UniversityShiwagun'yahabachouJapan
- Diagnostic Pathology CenterSouthern Tohoku General HospitalKooriyamaJapan
| | - Takayuki Matsumoto
- Division of GastroenterologyDepartment of Internal MedicineShiwagun'yahabachouJapan
| | - Hiromu Suzuki
- Department of Molecular BiologySapporo Medical University, School of MedicineSapporoJapan
| | - Naoki Yanagawa
- Department of Molecular Diagnostic Pathology, School of MedicineIwate Medical UniversityShiwagun'yahabachouJapan
| | - Tamotsu Sugai
- Department of Molecular Diagnostic Pathology, School of MedicineIwate Medical UniversityShiwagun'yahabachouJapan
- Diagnostic Pathology CenterSouthern Tohoku General HospitalKooriyamaJapan
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7
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Sugai T, Uesugi N, Osakabe M, Yao T, Yanagawa N, Ajioka Y. Characterization of sessile serrated adenomas with dysplasia including intramucosal adenocarcinoma and colorectal carcinoma with a microsatellite instability phenotype. Hum Pathol 2024; 145:9-15. [PMID: 38218351 DOI: 10.1016/j.humpath.2023.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 12/03/2023] [Accepted: 12/19/2023] [Indexed: 01/15/2024]
Abstract
Recent studies have shown that sessile serrated lesions (SSLs) lead to the development of colorectal cancer (CRC) with a microsatellite instability (MSI) phenotype via a dysplasia-carcinoma sequence. However, the pathological and molecular mechanisms of SSL with dysplasia (SSLD) are unclear. Here, we aimed to examine the clinicopathological and molecular alterations in SSLD and to evaluate the significance of such alterations with regard to lesion progression. Fifty-four SSLDs (20 serrated dysplasia cases and 17 intestinal dysplasia cases, including 30 low-grade dysplasia [LGD] cases, 7 high-grade dysplasia [HGD] cases, and 17 intramucosal adenocarcinomas [IMAs]) were evaluated. Molecular alterations, including immunohistochemical expression of various markers, DNA methylation status, and multiple genetic mutations (using next-generation sequencing), were assessed. Additionally, such alterations were also investigated in 41 CRCs with an MSI phenotype (invasion beyond submucosa). The frequency of mismatch repair (MMR) deficiency in SSLD was 12 of 39 cases (32.4 %), whereas the MMR proficient type was observed in 17 of 39 SSLD cases. SSLD with serrated dysplasia showed a significantly higher frequency of loss of MMR protein expression and methylation status. Moreover, loss of MMR protein expression differed significantly between LGD and IMA. Furthermore, the frequency of TP53 mutation was significantly higher in IMA than in LGD. The current findings demonstrated that SSL with serrated dysplasia may be associated with an increased risk of malignant transformation compared with intestinal dysplasia. Loss of MMR proteins and mutation of TP53 may play important roles in tumor progression from dysplasia to carcinomatous lesions.
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Affiliation(s)
- Tamotsu Sugai
- Department of Molecular Diagnostic Pathology, School of Medicine, Iwate Medical University, 2-1-1, Shiwagun'yahabachou, 028-3695, Japan; Diagnostic Pathology Center, Southern Tohoku General Hospital, 7-115, Yatsuyamada, Kooriyama City, Fukushima, 963-8563, Japan.
| | - Noriyuki Uesugi
- Department of Molecular Diagnostic Pathology, School of Medicine, Iwate Medical University, 2-1-1, Shiwagun'yahabachou, 028-3695, Japan; Diagnostic Pathology Center, Southern Tohoku General Hospital, 7-115, Yatsuyamada, Kooriyama City, Fukushima, 963-8563, Japan
| | - Mistumasa Osakabe
- Department of Molecular Diagnostic Pathology, School of Medicine, Iwate Medical University, 2-1-1, Shiwagun'yahabachou, 028-3695, Japan
| | - Takashi Yao
- Department of Diagnostic Pathology, Juntendo University, Tokyo, Japan
| | - Naoki Yanagawa
- Department of Molecular Diagnostic Pathology, School of Medicine, Iwate Medical University, 2-1-1, Shiwagun'yahabachou, 028-3695, Japan
| | - Yoichi Ajioka
- Division of Molecular and Diagnostic Pathology, Graduate School of Medical and Dental Sciences, Niigata University, 757, Cyuo-Asahi, 951-8510, Niigata, Japan
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8
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Aggarwal A, Sharma S, Brar Z, Kumar V, Kumar A, Katara R, Mohanty SK. Comprehensive molecular analysis of driver mutations in non-small cell lung carcinomas and its correlation with PD-L1 expression, An Indian perspective. Pathol Res Pract 2024; 253:155013. [PMID: 38096714 DOI: 10.1016/j.prp.2023.155013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 12/01/2023] [Accepted: 12/02/2023] [Indexed: 01/24/2024]
Abstract
BACKGROUND The understanding of molecular mechanisms involved in non-small cell lung carcinoma (NSCLC) has revolutionized significantly in the recent years. These have helped to develop personalized management strategies by identifying specific molecular alterations such as mutations in EGFR, ROS1, BRAF, ERBB2, MET, ALK, and KRAS genes. These mutations are targetable ensuring a better clinical outcome. Next-generation sequencing (NGS) methodology is the recommended technique for the identification of driver mutations in the five hot-spot genes (EGFR, ALK, ROS1, MET, and BRAF) involved in the NSCLC. NGS has numerous advantages including multiplexing, tissue conservation, identification of rare and novel variants, and reduced cost over the sequential single gene testing. Herein, we sought to demonstrate the mutational profile in NSCLC and their clinicopathologic correlation in a contemporary cohort of Indian NSCLC patients. Additionally, we studied the correlation of oncogenic driver mutations with PD-L1 status in these patients. MATERIALS AND METHODS Five fifty-two stage IV NSCLC patients (adenocarcinoma=490; squamous cell carcinoma=51; adenosquamous carcinoma=5; large cell carcinoma=2; sarcomatoid carcinoma=3; spindle cell carcinoma=1) underwent broad molecular profiling by a custom-made, targeted DNA- and RNA-based five hot-spot genes lung cancer panel (EGFR, ALK, ROS1, BRAF, and MET), compatible with the NGS Ion S5 system. The mutations were correlated with the clinicopathologic characteristics. Additionally, PD-L1 expression status, available on 252 tumors, was correlated with the oncogenic drivers. RESULTS Validation of the 5 gene panel yielded the following results: a) specificity of 99.74%; b) sensitivity of 100% for single nucleotide variants (SNVs) (>5% variant allele frequency, VAF), indels (>10% VAF) and fusions; c) 100% intra- and inter-run reproducibility; d) 88% inter-laboratory agreement. Validated panel was then used to analyze clinical samples. Sixty percentage tumors harbored either one (54.71%) or multiple (3.26%) mutations. EGFR and BRAF V600E mutations, ALK and ROS1 rearrangements, and MET exon 14 skipping mutation were observed in 38.41% (n = 212) and 2.72% (n = 15) patients, 12.14% (n = 67) and 3.62% (n = 20) patients, and 1.09% (n = 6) patients, respectively. EGFR exon 19 deletion accounted for 52.83% of all mutations, followed by L858R (35.85%), T790M (5.19%), exon 20 insertions (6.6%), and other rare mutations (G719X, L861Q, S768I) (9.91%). Concurrent EGFR with ALK, EGFR with ROS1, EGFR with MET, and EGFR with BRAF were observed in 10, 4, 1, and 3 patients, respectively. PD-L1 was expressed in 134 patients (53.2%). Exon 19 deletion was more prevalent in PD-L1 negative tumors whereas exon 21 substitution (L858R) was seen more in PD-L1 positive tumors. CONCLUSIONS This is one of the largest cohorts of NSCLC for comprehensive targeted mutational profiling and correlation with the PD-L1 expression. The mutations are more prevalent in non-smoker females for all genes, except ALK (non-smoker males). MET and BRAF mutations are more common in elderly population whereas EGFR mutations, and ALK and ROS1 genes rearrangements are more prevalent in younger population. The most common histopathologic subtype/feature associated with various mutations was as follows: acinar with EGFR, solid with ALK, macronucleoli with ROS1, signet ring with MET, and micropapillary with BRAF.
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Affiliation(s)
- Aditi Aggarwal
- Department of Molecular Pathology, CORE Diagnostics, Gurugram, Haryana, India
| | - Shivani Sharma
- Department of Molecular Pathology, CORE Diagnostics, Gurugram, Haryana, India
| | - Zoya Brar
- Department of Molecular Pathology, CORE Diagnostics, Gurugram, Haryana, India
| | - Vipin Kumar
- Department of Molecular Pathology, CORE Diagnostics, Gurugram, Haryana, India
| | - Akash Kumar
- Department of Molecular Pathology, CORE Diagnostics, Gurugram, Haryana, India
| | - Rahul Katara
- Department of Molecular Pathology, CORE Diagnostics, Gurugram, Haryana, India
| | - Sambit K Mohanty
- Department of Molecular Pathology, CORE Diagnostics, Gurugram, Haryana, India.
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9
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Flowers M, Dickson A, Miller MJ, Spector E, Enns GM, Baudet H, Pasquali M, Racacho L, Sadre-Bazzaz K, Wen T, Fogarty M, Fernandez R, Weaver MA, Feigenbaum A, Graham BH, Mao R. Specifications of the ACMG/AMP guidelines for ACADVL variant interpretation. Mol Genet Metab 2023; 140:107668. [PMID: 37549443 PMCID: PMC10811274 DOI: 10.1016/j.ymgme.2023.107668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/09/2023]
Abstract
Very long-chain acyl-CoA dehydrogenase (VLCAD) deficiency (VLCADD) is a relatively common inborn error of metabolism, but due to difficulty in accurately predicting affected status through newborn screening, molecular confirmation of the causative variants by sequencing of the ACADVL gene is necessary. Although the ACMG/AMP guidelines have helped standardize variant classification, ACADVL variant classification remains disparate due to a phenotype that can be nonspecific, the possibility of variants that produce late-onset disease, and relatively high carrier frequency, amongst other challenges. Therefore, an ACADVL-specific variant curation expert panel (VCEP) was created to facilitate the specification of the ACMG/AMP guidelines for VLCADD. We expect these guidelines to help streamline, increase concordance, and expedite the classification of ACADVL variants.
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Affiliation(s)
- May Flowers
- Invitae Corporation, San Francisco, CA 94103, USA
| | - Alexa Dickson
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO 63110, USA
| | - Marcus J Miller
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Elaine Spector
- Department of Pathology, University of Colorado School of Medicine, Aurora, CO 80045, USA; Section of Clinical Genetics and Metabolism, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Gregory Mark Enns
- Division of Medical Genetics, Department of Pediatrics, Lucile Packard Children's Hospital, Stanford University, Stanford, CA 94304, USA
| | - Heather Baudet
- Department of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | - Marzia Pasquali
- Department of Pathology, University of Utah, Salt Lake City, UT 84112, USA; ARUP Laboratories, Salt Lake City, UT 84108, USA
| | - Lemuel Racacho
- Department of Medical Genetics, Alberta Children's Hospital, Calgary, Alberta T3B6A8, Canada
| | | | - Ting Wen
- ARUP Laboratories, Salt Lake City, UT 84108, USA
| | | | - Raquel Fernandez
- American College of Medical Genetics and Genomics, Bethesda, MD 20814, USA
| | - Meredith A Weaver
- American College of Medical Genetics and Genomics, Bethesda, MD 20814, USA
| | - Annette Feigenbaum
- Department of Pediatrics, Division of Genetics, Rady Children's Hospital and The University of California, San Diego, CA 92123, USA
| | - Brett H Graham
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Rong Mao
- Department of Pathology, University of Utah, Salt Lake City, UT 84112, USA; ARUP Laboratories, Salt Lake City, UT 84108, USA.
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10
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Schlottmann PG, Luna JD, Labat N, Yadarola MB, Bainttein S, Esposito E, Ibañez A, Barbaro EI, Álvarez Mendiara A, Picotti CP, Chirino Misisian A, Andreussi L, Gras J, Capalbo L, Visotto M, Dipierri JE, Alcoba E, Fernández Gabrielli L, Ávila S, Aucar ME, Martin DM, Ormaechea GJ, Inga ME, Francone AA, Charles M, Zompa T, Pérez PJ, Lotersztein V, Nuova PJ, Canonero IB, Mahroo OA, Michaelides M, Arno G, Daich Varela M. Nationwide genetic analysis of more than 600 families with inherited eye diseases in Argentina. NPJ Genom Med 2023; 8:8. [PMID: 37217489 DOI: 10.1038/s41525-023-00352-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 04/05/2023] [Indexed: 05/24/2023] Open
Abstract
This study corresponds to the first large-scale genetic analysis of inherited eye diseases (IED) in Argentina and describes the comprehensive genetic profile of a large cohort of patients. Medical records of 22 ophthalmology and genetics services throughout 13 Argentinian provinces were analyzed retrospectively. Patients with a clinical diagnosis of an ophthalmic genetic disease and a history of genetic testing were included. Medical, ophthalmological and family history was collected. A total of 773 patients from 637 families were included, with 98% having inherited retinal disease. The most common phenotype was retinitis pigmentosa (RP, 62%). Causative variants were detected in 379 (59%) patients. USH2A, RPGR, and ABCA4 were the most common disease-associated genes. USH2A was the most frequent gene associated with RP, RDH12 early-onset severe retinal dystrophy, ABCA4 Stargardt disease, PROM1 cone-rod dystrophy, and BEST1 macular dystrophy. The most frequent variants were RPGR c.1345 C > T, p.(Arg449*) and USH2A c.15089 C > A, p.(Ser5030*). The study revealed 156/448 (35%) previously unreported pathogenic/likely pathogenic variants and 8 possible founder mutations. We present the genetic landscape of IED in Argentina and the largest cohort in South America. This data will serve as a reference for future genetic studies, aid diagnosis, inform counseling, and assist in addressing the largely unmet need for clinical trials to be conducted in the region.
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Affiliation(s)
| | - José D Luna
- Centro Privado de Ojos Romagosa SA, Córdoba, Argentina
| | - Natalia Labat
- Centro Privado de Ojos Romagosa SA, Córdoba, Argentina
| | | | | | - Evangelina Esposito
- University Clinic Reina Fabiola, Córdoba, Córdoba, Argentina
- Catholic University of Cordoba, Cordoba, Argentina
| | - Agustina Ibañez
- University Clinic Reina Fabiola, Córdoba, Córdoba, Argentina
- Catholic University of Cordoba, Cordoba, Argentina
| | | | | | | | | | | | | | | | - Mauro Visotto
- Instituto Oftalmológico Trelew, Trelew, Chubut, Argentina
| | | | - Emilio Alcoba
- Hospital Materno Infantil Dr Héctor Quintana, Jujuy, Argentina
| | | | - Silvia Ávila
- Facultad de Ciencias Médicas, Universidad Nacional del Comahue, Río Negro, Argentina
| | | | | | | | - M Eugenia Inga
- Organización Medica de Investigación, Buenos Aires, Argentina
| | | | | | - Tamara Zompa
- Charles Centro Oftalmológico, Buenos Aires, Argentina
| | | | | | - Pedro J Nuova
- Ocularyb Oftalmoclinica, Yerba Buena, Tucumán, Argentina
| | | | - Omar A Mahroo
- Moorfields Eye Hospital, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Michel Michaelides
- Moorfields Eye Hospital, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Gavin Arno
- Moorfields Eye Hospital, London, UK
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Malena Daich Varela
- Moorfields Eye Hospital, London, UK.
- UCL Institute of Ophthalmology, University College London, London, UK.
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11
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Margraf RL, Alexander RZ, Fulmer ML, Miller CE, Coupal E, Mao R. Multiple endocrine neoplasia type 2 (MEN2) and RET specific modifications of the ACMG/AMP variant classification guidelines and impact on the MEN2 RET database. Hum Mutat 2022; 43:1780-1794. [PMID: 36251279 DOI: 10.1002/humu.24486] [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: 04/20/2022] [Revised: 09/20/2022] [Accepted: 10/04/2022] [Indexed: 01/24/2023]
Abstract
The Multiple Endocrine Neoplasia type 2 (MEN2) RET proto-oncogene database, originally published in 2008, is a comprehensive repository of all publicly available RET gene variations associated with MEN2 syndromes. The variant-specific genotype/phenotype information, age of earliest reported medullary thyroid carcinoma (MTC) onset, and relevant references with a brief summary of findings are cataloged. The ACMG/AMP 2015 consensus statement on variant classification was modified specifically for MEN2 syndromes and RET variants using ClinGen sequence variant interpretation working group recommendations and ClinGen expert panel manuscripts, as well as manuscripts from the American Thyroid Association Guidelines Task Force on Medullary Thyroid Carcinoma and other MEN2 RET literature. The classifications for the 166 single unique variants in the MEN2 RET database were reanalyzed using the MEN2 RET specifically modified ACMG/AMP classification guidelines (version 1). Applying these guidelines added two new variant classifications to the database (likely benign and likely pathogenic) and resulted in clinically significant classification changes (e.g., from pathogenic to uncertain) in 15.7% (26/166) of the original variants. Of those clinically significant changes, the highest percentage of changes, 46.2% (12/26), were changes from uncertain to benign or likely benign. The modified ACMG/AMP criteria with MEN2 RET specifications will optimize and standardize RET variant classifications.
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Affiliation(s)
- Rebecca L Margraf
- ARUP Institute for Clinical and Experimental Pathology®, Salt Lake City, Utah, USA
| | | | - Makenzie L Fulmer
- ARUP Institute for Clinical and Experimental Pathology®, Salt Lake City, Utah, USA.,Department of Pathology, School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Christine E Miller
- ARUP Institute for Clinical and Experimental Pathology®, Salt Lake City, Utah, USA
| | - Elena Coupal
- ARUP Institute for Clinical and Experimental Pathology®, Salt Lake City, Utah, USA
| | - Rong Mao
- ARUP Institute for Clinical and Experimental Pathology®, Salt Lake City, Utah, USA.,Department of Pathology, School of Medicine, University of Utah, Salt Lake City, Utah, USA
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12
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Evaluating use of changing technologies for rapid next-generation sequencing in pediatrics. Pediatr Res 2022; 92:1364-1369. [PMID: 35115709 PMCID: PMC10024604 DOI: 10.1038/s41390-022-01965-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 01/17/2022] [Accepted: 01/20/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND Rapid next-generation sequencing (NGS) offers the potential to shorten the diagnostic process and improve the care of acutely ill children. The goal of this study was to report our findings, including benefits and limitations, of a targeted NGS panel and rapid genome sequencing (rGS) in neonatal and pediatric acute clinical care settings. METHODS Retrospective analysis of patient characteristics, diagnostic yields, turnaround time, and changes in management for infants and children receiving either RapSeq, a targeted NGS panel for 4500+ genes, or rGS, at the University of Utah Hospital and Primary Children's Hospital, from 2015 to 2020. RESULTS Over a 5-year period, 142 probands underwent rapid NGS: 66 received RapSeq and 76 rGS. Overall diagnostic yield was 39%. In the majority of diagnostic cases, there were one or more changes in clinical care management. Of note, 7% of diagnoses identified by rGS would not have been identified by RapSeq. CONCLUSIONS Our results indicate that rapid NGS impacts acute pediatric care in real-life clinical settings. Although affected by patient selection criteria, diagnostic yields were similar to those from clinical trial settings. Future studies are needed to determine relative advantages, including cost, turnaround time, and benefits for patients, of each approach in specific clinical circumstances. IMPACT The use of comprehensive Mendelian gene panels and genome sequencing in the clinical setting allows for early diagnosis of patients in neonatal, pediatric, and cardiac intensive care units and impactful change in management. Diagnoses led to significant changes in management for several patients in lower acuity inpatient units supporting further exploration of the utility of rapid sequencing in these settings. This study reviews the limitations of comparing sequencing platforms in the clinical setting and the variables that should be considered in evaluating diagnostic rates across studies.
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13
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New Developments and Possibilities in Reanalysis and Reinterpretation of Whole Exome Sequencing Datasets for Unsolved Rare Diseases Using Machine Learning Approaches. Int J Mol Sci 2022; 23:ijms23126792. [PMID: 35743235 PMCID: PMC9224427 DOI: 10.3390/ijms23126792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 06/13/2022] [Accepted: 06/15/2022] [Indexed: 11/21/2022] Open
Abstract
Rare diseases impact the lives of 300 million people in the world. Rapid advances in bioinformatics and genomic technologies have enabled the discovery of causes of 20–30% of rare diseases. However, most rare diseases have remained as unsolved enigmas to date. Newer tools and availability of high throughput sequencing data have enabled the reanalysis of previously undiagnosed patients. In this review, we have systematically compiled the latest developments in the discovery of the genetic causes of rare diseases using machine learning methods. Importantly, we have detailed methods available to reanalyze existing whole exome sequencing data of unsolved rare diseases. We have identified different reanalysis methodologies to solve problems associated with sequence alterations/mutations, variation re-annotation, protein stability, splice isoform malfunctions and oligogenic analysis. In addition, we give an overview of new developments in the field of rare disease research using whole genome sequencing data and other omics.
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14
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Doig KD, Love CG, Conway T, Seleznev A, Ma D, Fellowes A, Blombery P, Fox SB. Findings from precision oncology in the clinic: rare, novel variants are a significant contributor to scaling molecular diagnostics. BMC Med Genomics 2022; 15:70. [PMID: 35346197 PMCID: PMC8962530 DOI: 10.1186/s12920-022-01214-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 03/15/2022] [Indexed: 11/24/2022] Open
Abstract
Background Next generation sequencing for oncology patient management is now routine in clinical pathology laboratories. Although wet lab, sequencing and pipeline tasks are largely automated, the analysis of variants for clinical reporting remains largely a manual task. The increasing volume of sequencing data and the limited availability of genetic experts to analyse and report on variants in the data is a key scalability limit for molecular diagnostics. Method To determine the impact and size of the issue, we examined the longitudinally compiled genetic variants from 48,036 cancer patients over a six year period in a large cancer hospital from ten targeted cancer panel tests in germline, solid tumour and haematology contexts using hybridization capture and amplicon assays. This testing generated 24,168,398 sequenced variants of which 23,255 (8214 unique) were clinically reported. Results Of the reported variants, 17,240 (74.1%) were identified in more than one assay which allowed curated variant data to be reused in later reports. The remainder, 6015 (25.9%) were not subsequently seen in later assays and did not provide any reuse benefit. The number of new variants requiring curation has significantly increased over time from 1.72 to 3.73 variants per sample (292 curated variants per month). Analysis of the 23,255 variants reported, showed 28.6% (n = 2356) were not present in common public variant resources and therefore required de novo curation. These in-house only variants were enriched for indels, tumour suppressor genes and from solid tumour assays. Conclusion This analysis highlights the significant percentage of variants not present within common public variant resources and the level of non-recurrent variants that consequently require greater curation effort. Many of these variants are unique to a single patient and unlikely to appear in other patients reflecting the personalised nature of cancer genomics. This study depicts the real-world situation for pathology laboratories faced with curating increasing numbers of low-recurrence variants while needing to expedite the process of manual variant curation. In the absence of suitably accurate automated methods, new approaches are needed to scale oncology diagnostics for future genetic testing volumes. Supplementary Information The online version contains supplementary material available at 10.1186/s12920-022-01214-y.
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15
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Bruehl FK, Kim AS, Li MM, Lindeman NI, Moncur JT, Souers RJ, Vasalos P, Voelkerding KV, Xian RR, Surrey LF. Tiered Somatic Variant Classification Adoption Has Increased Worldwide With Some Practice Differences Based on Location and Institutional Setting. Arch Pathol Lab Med 2022; 146:822-832. [PMID: 34979564 DOI: 10.5858/arpa.2021-0179-cp] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/27/2021] [Indexed: 11/06/2022]
Abstract
CONTEXT.— The 2017 Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists (CAP) tier classification guideline provides a framework to standardize interpretation and reporting of somatic variants. OBJECTIVE.— To evaluate the adoption and performance of the 2017 guideline among laboratories performing somatic next-generation sequencing (NGS). DESIGN.— A survey was distributed to laboratories participating in NGS CAP proficiency testing for solid tumors (NGSST) and hematologic malignancies (NGSHM). RESULTS.— Worldwide, 64.4% (152 of 236) of NGSST and 66.4% (87 of 131) of NGSHM participants used tier classification systems, of which the 2017 guideline was used by 84.9% (129 of 152) of NGSST and 73.6% (64 of 87) of NGSHM participants. The 2017 guideline was modified by 24.4% (30 of 123) of NGSST and 21.7% (13 of 60) of NGSHM laboratories. Laboratories implementing the 2017 guideline were satisfied or very satisfied (74.2% [89 of 120] NGSST and 69.5% [41 of 59] NGSHM), and the impression of tier classification reproducibility was high (mean of 3.9 [NGSST] and 3.6 [NGSHM] on a 5-point scale). Of nonusers, 35.2% (38 of 108) of NGSST and 39.4% (26 of 66) of NGSHM laboratories were planning implementation. For future guideline revisions, respondents favored including variants to monitor disease (63.9% [78 of 122] NGSST, 80.0% [48 of 60] NGSHM) and germline variants (55.3% [63 of 114] NGSST, 75.0% [45 of 60] NGSHM). Additional subtiers were not favored by academic laboratories compared to nonacademic laboratories (P < .001 NGSST and P = .02 NGSHM). CONCLUSIONS.— The 2017 guideline has been implemented by more than 50.0% of CAP laboratories. While most laboratories using the 2017 guideline report satisfaction, thoughtful guideline modifications may further enhance the quality, reproducibility, and clinical utility of the 2017 guideline for tiered somatic variant classification.
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Affiliation(s)
- Frido K Bruehl
- From Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio (Bruehl)
| | - Annette S Kim
- The Departments of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts (Kim, Lindeman)
| | - Marilyn M Li
- The Department of Pathology and Laboratory Medicine, Perelman School of Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania (Li, Surrey)
| | - Neal I Lindeman
- The Departments of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts (Kim, Lindeman)
| | - Joel T Moncur
- The Joint Pathology Center, Office of the Director, Silver Spring, Maryland (Moncur), College of American Pathologists, Northfield, Illinois
| | - Rhona J Souers
- Biostatistics Department (Souers), College of American Pathologists, Northfield, Illinois
| | - Patricia Vasalos
- Proficiency Testing (Vasalos), College of American Pathologists, Northfield, Illinois
| | | | - Rena R Xian
- The Department of Pathology and Oncology, School of Medicine, Johns Hopkins University, Baltimore, Maryland (Xian)
| | - Lea F Surrey
- The Department of Pathology and Laboratory Medicine, Perelman School of Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania (Li, Surrey)
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16
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Vesteghem C, Brøndum RF, Sønderkær M, Sommer M, Schmitz A, Bødker JS, Dybkær K, El-Galaly TC, Bøgsted M. Implementing the FAIR Data Principles in precision oncology: review of supporting initiatives. Brief Bioinform 2021; 21:936-945. [PMID: 31263868 PMCID: PMC7299292 DOI: 10.1093/bib/bbz044] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Revised: 03/13/2019] [Accepted: 03/21/2019] [Indexed: 12/26/2022] Open
Abstract
Compelling research has recently shown that cancer is so heterogeneous that single research centres cannot produce enough data to fit prognostic and predictive models of sufficient accuracy. Data sharing in precision oncology is therefore of utmost importance. The Findable, Accessible, Interoperable and Reusable (FAIR) Data Principles have been developed to define good practices in data sharing. Motivated by the ambition of applying the FAIR Data Principles to our own clinical precision oncology implementations and research, we have performed a systematic literature review of potentially relevant initiatives. For clinical data, we suggest using the Genomic Data Commons model as a reference as it provides a field-tested and well-documented solution. Regarding classification of diagnosis, morphology and topography and drugs, we chose to follow the World Health Organization standards, i.e. ICD10, ICD-O-3 and Anatomical Therapeutic Chemical classifications, respectively. For the bioinformatics pipeline, the Genome Analysis ToolKit Best Practices using Docker containers offer a coherent solution and have therefore been selected. Regarding the naming of variants, we follow the Human Genome Variation Society's standard. For the IT infrastructure, we have built a centralized solution to participate in data sharing through federated solutions such as the Beacon Networks.
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Affiliation(s)
- Charles Vesteghem
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark
| | | | - Mads Sønderkær
- Department of Haematology, Aalborg University Hospital, Denmark
| | - Mia Sommer
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark
| | | | | | - Karen Dybkær
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark.,Clinical Cancer Research Center, Aalborg University Hospital, Denmark
| | - Tarec Christoffer El-Galaly
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark.,Clinical Cancer Research Center, Aalborg University Hospital, Denmark
| | - Martin Bøgsted
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark.,Clinical Cancer Research Center, Aalborg University Hospital, Denmark
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17
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Bruzas S, Kuemmel S, Harrach H, Breit E, Ataseven B, Traut A, Rüland A, Kostara A, Chiari O, Dittmer-Grabowski C, Reinisch M. Next-Generation Sequencing-Directed Therapy in Patients with Metastatic Breast Cancer in Routine Clinical Practice. Cancers (Basel) 2021; 13:4564. [PMID: 34572791 PMCID: PMC8468801 DOI: 10.3390/cancers13184564] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 09/02/2021] [Accepted: 09/06/2021] [Indexed: 11/20/2022] Open
Abstract
Next-generation sequencing (NGS) followed by matched therapy has opened up new therapeutic options to patients with metastatic breast cancer (mBC). Here we report our experience with this approach in everyday clinical practice. This retrospective study included 95 patients with mBC who were genotyped with the FoundationOne® (CDx) assay in a commercial molecular pathology laboratory. Genetic alterations were identified in all tumor specimens, and 83 patients (87.4%) had a median of 2 (range, 1-6) potentially actionable alterations. A multidisciplinary tumor board recommended genomically guided therapy to 63 patients, 30 of whom received such treatment. Everolimus (n = 15) and anti-human epidermal growth factor receptor 2 (HER2) therapy (n = 6) were most frequently administered. The ratio of progression-free survival (PFS) under NGS-based therapy to PFS under the last line of standard therapy prior to NGS was >1.3 in 13 (43.3%) patients, indicative of a clinical benefit to NGS-directed therapy. One-year overall survival rates were 22.7% (95% CI, 6.5-44.4) in 65 patients allocated to the standard therapy versus 62.9% (95% CI, 41.6-78.2) in 30 patients receiving the matched therapy. In conclusion, NGS-matched treatment improved the clinical outcomes in a subgroup of mBC patients.
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Affiliation(s)
- Simona Bruzas
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
| | - Sherko Kuemmel
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
- Department of Gynecology with Breast Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Hakima Harrach
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
| | - Elisabeth Breit
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
| | - Beyhan Ataseven
- Department of Gynecology and Gynecologic Oncology, Kliniken Essen-Mitte, 45136 Essen, Germany; (B.A.); (A.T.)
- Department of Obstetrics and Gynecology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Alexander Traut
- Department of Gynecology and Gynecologic Oncology, Kliniken Essen-Mitte, 45136 Essen, Germany; (B.A.); (A.T.)
| | - Anna Rüland
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
- Brustzentrum, St. Marienhospital, 52353 Düren, Germany
| | - Athina Kostara
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
| | - Ouafaa Chiari
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
| | - Christine Dittmer-Grabowski
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
| | - Mattea Reinisch
- Interdisciplinary Breast Unit, Kliniken Essen-Mitte, 45136 Essen, Germany; (S.B.); (S.K.); (H.H.); (E.B.); (A.R.); (A.K.); (O.C.); (C.D.-G.)
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Applying Bioinformatic Platforms, In Vitro, and In Vivo Functional Assays in the Characterization of Genetic Variants in the GH/IGF Pathway Affecting Growth and Development. Cells 2021; 10:cells10082063. [PMID: 34440832 PMCID: PMC8392544 DOI: 10.3390/cells10082063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 08/06/2021] [Accepted: 08/09/2021] [Indexed: 02/07/2023] Open
Abstract
Heritability accounts for over 80% of adult human height, indicating that genetic variability is the main determinant of stature. The rapid technological development of Next-Generation Sequencing (NGS), particularly Whole Exome Sequencing (WES), has resulted in the characterization of several genetic conditions affecting growth and development. The greatest challenge of NGS remains the high number of candidate variants identified. In silico bioinformatic tools represent the first approach for classifying these variants. However, solving the complicated problem of variant interpretation requires the use of experimental approaches such as in vitro and, when needed, in vivo functional assays. In this review, we will discuss a rational approach to apply to the gene variants identified in children with growth and developmental defects including: (i) bioinformatic tools; (ii) in silico modeling tools; (iii) in vitro functional assays; and (iv) the development of in vivo models. While bioinformatic tools are useful for a preliminary selection of potentially pathogenic variants, in vitro—and sometimes also in vivo—functional assays are further required to unequivocally determine the pathogenicity of a novel genetic variant. This long, time-consuming, and expensive process is the only scientifically proven method to determine causality between a genetic variant and a human genetic disease.
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19
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Chang I, Park S, Lee HJ, Kim I, Park S, Ahn MK, Lee J, Kang M, Baek IJ, Sung YH, Pack CG, Kang HJ, Lee K, Im HJ, Seo EJ, Kim KM, Yang SK, Song K, Oh SH. Interpretation of XIAP Variants of Uncertain Significance in Paediatric Patients with Refractory Crohn's Disease. J Crohns Colitis 2021; 15:1291-1304. [PMID: 33460440 DOI: 10.1093/ecco-jcc/jjab013] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND AND AIMS Mutations in XIAP can lead to the development of treatment-refractory severe paediatric Crohn's disease [CD], for which haematopoietic stem cell transplantation is the primary therapeutic option. The interpretation of variants of uncertain significance [VUSs] in XIAP needs to be scrutinized. METHODS Targeted next-generation sequencing was performed for 33 male paediatric patients with refractory CD admitted at a tertiary referral hospital. To obtain functional data, biomolecular cell assays and supercomputing molecular dynamics simulations were performed. RESULTS Nine unrelated male patients harboured hemizygous XIAP variants. Four known pathogenic variants and one novel pathogenic variant [p.Lys168Serfs*12] were identified in five patients, and two novel VUSs [p.Gly205del and p.Pro260Ser] and one known VUS [p.Glu350del] were identified in the remaining four. Among children with VUSs, only the subject with p.Gly205del exhibited defective NOD2 signalling. Using molecular dynamics simulation, we determined that the altered backbone torsional energy of C203 in XIAP of p.G205del was ~2 kcal/mol, suggesting loss of zinc binding in the mutant XIAP protein and poor coordination between the mutant XIAP and RIP2 proteins. Elevated auto-ubiquitination of zinc-depleted p.G205del XIAP protein resulted in XIAP protein deficiency. CONCLUSION A high prevalence of XIAP deficiency was noted among children with refractory CD. Advanced functional studies decreased the subjectivity in the case-level interpretation of XIAP VUSs and directed consideration of haematopoietic stem cell transplantation.
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Affiliation(s)
- Iksoo Chang
- Supercomputing & Big Data Center, DGIST, Daegu, Korea.,Department of Brain and Cognitive Sciences, DGIST, Daegu, Korea
| | - Seongjun Park
- Department of Emerging Materials Science, DGIST, Daegu, Korea
| | - Hye-Jin Lee
- Department of Pediatrics, Asan Medical Center Children's Hospital, University of Ulsan College of Medicine, Seoul, Korea
| | - Inki Kim
- Department of Convergence Medicine, Asan Institutes for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sojung Park
- Department of Convergence Medicine, Asan Institutes for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Mi Kyoung Ahn
- Department of Pediatrics, Asan Medical Center Children's Hospital, University of Ulsan College of Medicine, Seoul, Korea
| | - Juhwan Lee
- Supercomputing & Big Data Center, DGIST, Daegu, Korea
| | - Mooseok Kang
- Department of Brain and Cognitive Sciences, DGIST, Daegu, Korea
| | - In-Jeoung Baek
- Department of Convergence Medicine, Asan Institutes for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Young Hoon Sung
- Department of Convergence Medicine, Asan Institutes for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Chan-Gi Pack
- Department of Convergence Medicine, Asan Institutes for Life Sciences, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Hyo-Jeong Kang
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Kunsong Lee
- Department of Pediatrics, Dankook University College of Medicine, Dankook University Hospital, Chungnam, Korea
| | - Ho Joon Im
- Department of Pediatrics, Asan Medical Center Children's Hospital, University of Ulsan College of Medicine, Seoul, Korea
| | - Eul Ju Seo
- Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Kyung Mo Kim
- Department of Pediatrics, Asan Medical Center Children's Hospital, University of Ulsan College of Medicine, Seoul, Korea
| | - Suk-Kyun Yang
- Department of Gastroenterology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Kyuyoung Song
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul, Korea
| | - Seak Hee Oh
- Department of Pediatrics, Asan Medical Center Children's Hospital, University of Ulsan College of Medicine, Seoul, Korea
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20
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Fabiani M, Cogo F, Poli M, Capalbo A. Technical factors to consider when developing an Expanded Carrier Screening platform. Curr Opin Obstet Gynecol 2021; 33:178-183. [PMID: 33741771 DOI: 10.1097/gco.0000000000000706] [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
PURPOSE OF REVIEW Expanded Carrier Screening (ECS) is a genetic test able to detect carriers for a large number of autosomal recessive and X-linked diseases. Its clinical utilization is increasing but some technical aspects for its implementation are still controversial. RECENT FINDINGS In the current literature, several aspects of ECS panel implementation have been addressed. One of the most relevant topics involves which genes/pathologies should be included in an optimized ECS panel and which variants should be reported. SUMMARY Here, we review the best practice criteria to refine and improve clinical utility and validity of an ECS panel. The criteria for optimal ECS panel implementation include the severity of pathologies, the prevalence of diseases in general population and a definitive or strong gene/disease association. Moreover, we discuss the main complications associated with the reporting of Variant of Uncertain Significance and the need for periodic reassessment.
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Affiliation(s)
| | | | | | - Antonio Capalbo
- Igenomix Italia, Marostica, Vicenza, Italy.,Igenomix Foundation, Valencia, Spain
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21
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Jain E, Sharma S, Aggarwal A, Bhardwaj N, Dewan A, Kumar A, Jain D, Bhattacharya M, Saurav GK, Kini L, Mohanty SK. PD-L1 expression and its clinicopathologic and genomic correlation in the non-small cell lung carcinoma patients: An Indian perspective. Pathol Res Pract 2021; 228:153497. [PMID: 34053784 DOI: 10.1016/j.prp.2021.153497] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 05/18/2021] [Accepted: 05/20/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Immunotherapy with checkpoint inhibitor programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) antibodies targeting the cellular immune checkpoints is the present area of interest showing promising results in patients with advanced non-small cell lung cancer (NSCLC). As there is paucity of PD-L1 expression data from the Indian perspective, we studied the correlation of clinicopathologic profile and oncogenic driver mutations in these patients. MATERIALS AND METHODS Samples from 252 advanced NSCLCs patients were studied for PD-L1 expression through immunohistochemistry using rabbit anti-human PD-L1 monoclonal antibody (clone SP263) on Ventana BenchMark ULTRA autostainer. Simultaneously, genetic mutations were studied by next generation sequencing (for EGFR, ALK, ROS, MET, and BRAF). PD-L1 expression was analyzed for association with clinicopathologic features and various mutations. RESULTS PD-L1 positivity was seen in 134 patients (53.2 %). It was twice more prevalent in males than females. No significant correlation was observed between PD-L1 expression with age, gender, site of testing (primary vs. metastatic tumors), smoking status, tumor laterality, stage, or histologic type; however, there was significant difference among solid and acinar types of adenocarcinoma combined together vs. other adenocarcinoma subtypes (p = 0.013), and well and moderately differentiated vs. poorly differentiated tumors (p = 0.022). When types/extent of PD-L1 positivity (≥25 %) were compared with demographics, clinical, and pathologic variables, significant differences were observed across the tumor grades (high-grade vs. low-grade) (p = 0.009) and stages (p = 0.039). The PD-L1 expression failed to demonstrate any statistical significance with oncogenic drivers. High PD-L1 expression (TPS ≥ 50) was observed in 27.6 % patients, and it was more prevalent in female patients (32.4 %), aged ≥60 years (33.8 %), smokers (27.3 %), poorly differentiated (36.8 %) and stage IV tumors (28.2 %). Exon 19 deletion was more prevalent in PD-L1 negative tumors whereas exon 21 substitution (L858R) was seen more in PD-L1 positive tumors. CONCLUSIONS This is the largest Indian study demonstrating PD-L1 expression in NSCLC patients comparing with clinicopathologic and genomic parameters. PD-L1 expression was significantly associated with high-grade, solid, and acinar types of adenocarcinoma and advanced tumors. High PD-L1 expression was more prevalent in female patients, aged ≥60 years, smokers, and poorly differentiated and stage IV tumors (28.2 %). Exon 19 deletion was more in PD-L1 negative tumors whereas exon 21 substitution (L858R) was more in PD-L1 positive tumors. PD-L1 is a potential predictive marker stratifying patients who benefit from PD-1 pathway-targeted therapy.
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Affiliation(s)
- Ekta Jain
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Shivani Sharma
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Aditi Aggarwal
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Nitin Bhardwaj
- Indian Council of Medical Research and National Institute of Malaria Research, New Delhi, 110029, India.
| | - Aditi Dewan
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Abhishek Kumar
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Deepika Jain
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Munmun Bhattacharya
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Gauraw Kumar Saurav
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Lata Kini
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
| | - Sambit Kumar Mohanty
- Department of Pathology, CORE Diagnostics, 406, Udyog Vihar III, Gurgaon, Haryana 122001, India.
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Specifications of the variant curation guidelines for ITGA2B/ITGB3: ClinGen Platelet Disorder Variant Curation Panel. Blood Adv 2021; 5:414-431. [PMID: 33496739 PMCID: PMC7839359 DOI: 10.1182/bloodadvances.2020003712] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Accepted: 12/08/2020] [Indexed: 12/17/2022] Open
Abstract
Accurate and consistent sequence variant interpretation is critical to the correct diagnosis and appropriate clinical management and counseling of patients with inherited genetic disorders. To minimize discrepancies in variant curation and classification among different clinical laboratories, the American College of Medical Genetics and Genomics (ACMG), along with the Association for Molecular Pathology (AMP), published standards and guidelines for the interpretation of sequence variants in 2015. Because the rules are not universally applicable to different genes or disorders, the Clinical Genome Resource (ClinGen) Platelet Disorder Expert Panel (PD-EP) has been tasked to make ACMG/AMP rule specifications for inherited platelet disorders. ITGA2B and ITGB3, the genes underlying autosomal recessive Glanzmann thrombasthenia (GT), were selected as the pilot genes for specification. Eight types of evidence covering clinical phenotype, functional data, and computational/population data were evaluated in the context of GT by the ClinGen PD-EP. The preliminary specifications were validated with 70 pilot ITGA2B/ITGB3 variants and further refined. In the final adapted criteria, gene- or disease-based specifications were made to 16 rules, including 7 with adjustable strength; no modification was made to 5 rules; and 7 rules were deemed not applicable to GT. Employing the GT-specific ACMG/AMP criteria to the pilot variants resulted in a reduction of variants classified with unknown significance from 29% to 20%. The overall concordance with the initial expert assertions was 71%. These adapted criteria will serve as guidelines for GT-related variant interpretation to increase specificity and consistency across laboratories and allow for better clinical integration of genetic knowledge into patient care.
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23
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Maron JL, Kingsmore SF, Wigby K, Chowdhury S, Dimmock D, Poindexter B, Suhrie K, Vockley J, Diacovo T, Gelb BD, Stroustrup A, Powell CM, Trembath A, Gallen M, Mullen TE, Tanpaiboon P, Reed D, Kurfiss A, Davis JM. Novel Variant Findings and Challenges Associated With the Clinical Integration of Genomic Testing: An Interim Report of the Genomic Medicine for Ill Neonates and Infants (GEMINI) Study. JAMA Pediatr 2021; 175:e205906. [PMID: 33587123 PMCID: PMC7885094 DOI: 10.1001/jamapediatrics.2020.5906] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 09/30/2020] [Indexed: 12/18/2022]
Abstract
Importance A targeted genomic sequencing platform focused on diseases presenting in the first year of life may minimize financial and ethical challenges associated with rapid whole-genomic sequencing. Objective To report interim variants and associated interpretations of an ongoing study comparing rapid whole-genomic sequencing with a novel targeted genomic platform composed of 1722 actionable genes targeting disorders presenting in infancy. Design, Setting, and Participants The Genomic Medicine in Ill Neonates and Infants (GEMINI) study is a prospective, multicenter clinical trial with projected enrollment of 400 patients. The study is being conducted at 6 US hospitals. Hospitalized infants younger than 1 year of age suspected of having a genetic disorder are eligible. Results of the first 113 patients enrolled are reported here. Patient recruitment began in July 2019, and the interim analysis of enrolled patients occurred from March to June 2020. Interventions Patient (proband) and parents (trios, when available) were tested simultaneously on both genomic platforms. Each laboratory performed its own phenotypically driven interpretation and was blinded to other results. Main Outcomes and Measures Variants were classified according to the American College of Medical Genetics and Genomics standards of pathogenic (P), likely pathogenic (LP), or variants of unknown significance (VUS). Chromosomal and structural variations were reported by rapid whole-genomic sequencing. Results Gestational age of 113 patients ranged from 23 to 40 weeks and postmenstrual age from 27 to 83 weeks. Sixty-seven patients (59%) were male. Diagnostic and/or VUS were returned for 51 patients (45%), while 62 (55%) had negative results. Results were concordant between platforms in 83 patients (73%). Thirty-seven patients (33%) were found to have a P/LP variant by 2 or both platforms and 14 (12%) had a VUS possibly related to phenotype. The median day of life at diagnosis was 22 days (range, 3-313 days). Significant alterations in clinical care occurred in 29 infants (78%) with a P/LP variant. Incidental findings were reported in 7 trios. Of 51 positive cases, 34 (67%) differed in the reported result because of technical limitations of the targeted platform, interpretation of the variant, filtering discrepancies, or multiple causes. Conclusions and Relevance As comprehensive genetic testing becomes more routine, these data highlight the critically important variant detection capabilities of existing genomic sequencing technologies and the significant limitations that must be better understood.
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Affiliation(s)
- Jill L. Maron
- Mother Infant Research Institute, Tufts Medical Center, Boston, Massachusetts
| | | | - Kristen Wigby
- Rady Children’s Institute for Genomic Medicine, San Diego, California
- Department of Pediatrics, University of California, San Diego, San Diego
| | - Shimul Chowdhury
- Rady Children’s Institute for Genomic Medicine, San Diego, California
| | - David Dimmock
- Rady Children’s Institute for Genomic Medicine, San Diego, California
| | - Brenda Poindexter
- Children’s Healthcare of Atlanta, Department of Pediatrics, Emory University, Atlanta, Georgia
| | - Kristen Suhrie
- Perinatal Institute, Cincinnati Children’s Hospital, Cincinnati, Ohio
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Jerry Vockley
- UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Thomas Diacovo
- UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Bruce D. Gelb
- Mindich Child Health and Development Institute and Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Annemarie Stroustrup
- Department of Pediatrics, Cohen Children’s Medical Center, New Hyde Park, New York, New York
| | - Cynthia M. Powell
- University of North Carolina Children’s Research Institute, University of North Carolina Health Children’s Hospital, Chapel Hill
| | - Andrea Trembath
- University of North Carolina Children’s Research Institute, University of North Carolina Health Children’s Hospital, Chapel Hill
| | - Matthew Gallen
- Athena Diagnostics/Quest Diagnostics, Marlborough, Massachusetts
| | - Thomas E. Mullen
- Athena Diagnostics/Quest Diagnostics, Marlborough, Massachusetts
| | | | - Dallas Reed
- Department of Obstetrics and Gynecology, Tufts Medical Center Boston, Boston, Massachusetts
- Department of Pediatrics, The Floating Hospital for Children at Tufts Medical Center, Boston, Massachusetts
| | - Anne Kurfiss
- Department of Pediatrics, The Floating Hospital for Children at Tufts Medical Center, Boston, Massachusetts
| | - Jonathan M. Davis
- Department of Pediatrics, The Floating Hospital for Children at Tufts Medical Center, Boston, Massachusetts
- The Tufts Clinical and Translation Science Institute, Tufts University School of Medicine, Boston, Massachusetts
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24
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Li H, Liu S, Wang S, Zeng Q, Chen Y, Fang T, Zhang Y, Zhou Y, Zhang Y, Wang K, Yan Z, Qiang C, Xu M, Chai X, Yuan Y, Huang M, Zhang H, Xiong Y. Cancer SIGVAR: A semiautomated interpretation tool for germline variants of hereditary cancer-related genes. Hum Mutat 2021; 42:359-372. [PMID: 33565189 DOI: 10.1002/humu.24177] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 12/27/2020] [Accepted: 02/05/2021] [Indexed: 01/21/2023]
Abstract
Cancer is one of the most important health issues globally and the accuracy of interpretation of cancer-related variants is critical for the clinical management of hereditary cancer. ClinGen Sequence Variant Interpretation Working Groups have developed many adaptations of American College of Medical Genetics and Genomics and the Association of Molecular Pathologists guidelines to improve the consistency of interpretation. We combined the most recent adaptations to expand the number of the criteria from 28 to 48 and developed a tool called Cancer SIGVAR to help genetic counselors interpret the clinical significance of cancer germline variants. Our tool can accept VCF files as input and realize fully automated interpretation based on 21 criteria and semiautomated interpretation based on 48 criteria. We validated the performance of our tool with the ClinVar and CLINVITAE benchmark databases, achieving an average consistency for pathogenic and benign assessment up to 93.71% and 79.38%, respectively. We compared Cancer SIGVAR with two similar tools, InterVar and PathoMAN, and analyzed the main differences in criteria and implementation. Furthermore, we selected 911 variants from another two in-house benchmark databases, and semiautomated interpretation reached an average classification consistency of 98.35%. Our findings highlight the need to optimize automated interpretation tools based on constantly updated guidelines. Cancer SIGVAR is publicly available at http://cancersigvar.bgi.com/.
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Affiliation(s)
- Hong Li
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Shuixia Liu
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | | | - Quanlei Zeng
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Yulan Chen
- BGI Genomics, BGI-Shenzhen, ShenZhen, China
| | - Ting Fang
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Yi Zhang
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Ying Zhou
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Yu Zhang
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Kaiyue Wang
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Zhangwei Yan
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Cuicui Qiang
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | - Meng Xu
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | | | | | - Ming Huang
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
| | | | - Yun Xiong
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China
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25
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Frühwald MC, Nemes K, Boztug H, Cornips MCA, Evans DG, Farah R, Glentis S, Jorgensen M, Katsibardi K, Hirsch S, Jahnukainen K, Kventsel I, Kerl K, Kratz CP, Pajtler KW, Kordes U, Ridola V, Stutz E, Bourdeaut F. Current recommendations for clinical surveillance and genetic testing in rhabdoid tumor predisposition: a report from the SIOPE Host Genome Working Group. Fam Cancer 2021; 20:305-316. [PMID: 33532948 PMCID: PMC8484234 DOI: 10.1007/s10689-021-00229-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Accepted: 01/06/2021] [Indexed: 12/28/2022]
Abstract
The rhabdoid tumor (RT) predisposition syndromes 1 and 2 (RTPS1 and 2) are rare genetic conditions rendering young children vulnerable to an increased risk of RT, malignant neoplasms affecting the kidney, miscellaneous soft-part tissues, the liver and the central nervous system (Atypical Teratoid Rhabdoid Tumors, ATRT). Both, RTPS1&2 are due to pathogenic variants (PV) in genes encoding constituents of the BAF chromatin remodeling complex, i.e. SMARCB1 (RTPS1) and SMARCA4 (RTPS2). In contrast to other genetic disorders related to PVs in SMARCB1 and SMARCA4 such as Coffin-Siris Syndrome, RTPS1&2 are characterized by a predominance of truncating PVs, terminating transcription thus explaining a specific cancer risk. The penetrance of RTPS1 early in life is high and associated with a poor survival. However, few unaffected carriers may be encountered. Beyond RT, the tumor spectrum may be larger than initially suspected, and cancer surveillance offered to unaffected carriers (siblings or parents) and long-term survivors of RT is still a matter of discussion. RTPS2 exposes female carriers to an ill-defined risk of small cell carcinoma of the ovaries, hypercalcemic type (SCCOHT), which may appear in prepubertal females. RT surveillance protocols for these rare families have not been established. To address unresolved issues in the care of individuals with RTPS and to propose appropriate surveillance guidelines in childhood, the SIOPe Host Genome working group invited pediatric oncologists and geneticists to contribute to an expert meeting. The current manuscript summarizes conclusions of the panel discussion, including consented statements as well as non-evidence-based proposals for validation in the future.
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Affiliation(s)
- M C Frühwald
- Paediatric and Adolescent Medicine, Swabian Children's Cancer Center, University Medical Center Augsburg, Stenglinstraße 2, 86156, Augsburg, Germany.
| | - K Nemes
- Paediatric and Adolescent Medicine, Swabian Children's Cancer Center, University Medical Center Augsburg, Stenglinstraße 2, 86156, Augsburg, Germany
| | - H Boztug
- St. Anna Children's Hospital and Children's Cancer Research Institute, Department of Pediatrics, Medical University of Vienna, Vienna, Austria
| | - M C A Cornips
- Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - D G Evans
- Manchester Centre for Genomic Medicine, Division of Evolution and Genomic Sciences, MAHSC, St Mary's Hospital, Manchester University Hospitals NHS Foundation Trust, University of Manchester, Manchester, UK
| | - R Farah
- Department of Pediatrics, Division of Hematology/Oncology, LAU Medical Center-Rizk Hospital, Ashrafieh, Beirut, Lebanon
| | - S Glentis
- Pediatric Hematology-Oncology Unit, First Department of Pediatrics, National and Kapodistrian University of Athens, "Aghia Sofia" Children's Hospital, Athens, Greece
| | - M Jorgensen
- Great Ormond Street Hospital for Children, NHS Foundation Trust, London, WC1N 3JH, UK
| | - K Katsibardi
- Pediatric Hematology-Oncology Unit, First Department of Pediatrics, National and Kapodistrian University of Athens, "Aghia Sofia" Children's Hospital, Athens, Greece
| | - S Hirsch
- Institute of Human Genetics, Heidelberg University Hospital, Heidelberg, Germany.,Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany
| | - K Jahnukainen
- Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - I Kventsel
- Department of Pediatric Hematology-Oncology, The Edmond and Lily Safra Children's Hospital, Chaim Sheba Medical Center, 52621, Tel-Hashomer, Israel
| | - K Kerl
- Department of Pediatric Hematology and Oncology, University Children's Hospital Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany
| | - C P Kratz
- Pediatric Hematology and Oncology, Hannover Medical School, Hannover, Germany
| | - K W Pajtler
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.,Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,Department of Pediatric Oncology, Hematology, and Immunology, University Hospital Heidelberg, Heidelberg, Germany
| | - U Kordes
- Department of Pediatric Hematology and Oncology, University Medical Center Hamburg Eppendorf, Hamburg, Germany
| | - V Ridola
- Department of Pediatric Oncology and Haematology, Mitera Children's Hospital, Athens, Greece
| | - E Stutz
- Department of Oncology, University Children's Hospital, Zurich, Switzerland
| | - F Bourdeaut
- Institut Curie, SIREDO Pediatric Cancer Center, INSERM U830, Laboratory of Translational Research in Pediatric Oncology, Paris Sciences Lettres Research University, Paris, France.
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Pauly R, Ziats CA, Abenavoli L, Schwartz CE, Boccuto L. New Strategies for Clinical Trials in Autism Spectrum Disorder. Rev Recent Clin Trials 2020; 16:131-137. [PMID: 33222679 DOI: 10.2174/1574887115666201120093634] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 10/10/2020] [Accepted: 10/22/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that poses several challenges in terms of clinical diagnosis and investigation of molecular etiology. The lack of knowledge on the pathogenic mechanisms underlying ASD has hampered the clinical trials that so far have tried to target ASD behavioral symptoms. In order to improve our understanding of the molecular abnormalities associated with ASD, a deeper and more extensive genetic profiling of targeted individuals with ASD was needed. METHODS The recent availability of new and more powerful sequencing technologies (third-generation sequencing) has allowed to develop novel strategies for the characterization of comprehensive genetic profiles of individuals with ASD. In particular, this review will describe integrated approaches based on the combination of various omics technologies that will lead to a better stratification of targeted cohorts for the design of clinical trials in ASD. RESULTS In order to analyze the big data collected by assays such as the whole genome, epigenome, transcriptome, and proteome, it is critical to develop an efficient computational infrastructure. Machine learning models are instrumental to identify non-linear relationships between the omics technologies and, therefore, establish a functional informative network among the different data sources. CONCLUSION The potential advantage provided by these new integrated omics-based strategies is better characterization of the genetic background of ASD cohorts, to identify novel molecular targets for drug development, and ultimately offer a more personalized approach in the design of clinical trials for ASD.
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Affiliation(s)
- Rini Pauly
- Greenwood Genetic Center, Greenwood, SC, United States
| | | | - Ludovico Abenavoli
- Department of Health Sciences, University "Magna Graecia", Catanzaro, Italy
| | | | - Luigi Boccuto
- Greenwood Genetic Center, Greenwood, SC, United States
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27
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Chunn LM, Nefcy DC, Scouten RW, Tarpey RP, Chauhan G, Lim MS, Elenitoba-Johnson KSJ, Schwartz SA, Kiel MJ. Mastermind: A Comprehensive Genomic Association Search Engine for Empirical Evidence Curation and Genetic Variant Interpretation. Front Genet 2020; 11:577152. [PMID: 33281875 PMCID: PMC7691534 DOI: 10.3389/fgene.2020.577152] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 10/19/2020] [Indexed: 12/21/2022] Open
Abstract
Design and interpretation of genome sequencing assays in clinical diagnostics and research labs is complicated by an inability to identify information from the medical literature and related databases quickly, comprehensively and reproducibly. This challenge is compounded by the complexity and heterogeneity of nomenclatures used to describe diseases, genes and genetic variants. Mastermind is a widely-used bioinformatic platform of genomic associations that has indexed more than 7.5 M full-text articles and 2.5 M supplemental datasets. It has automatically identified, disambiguated and annotated >6.1 M genetic variants and identified >50 K disease-gene associations. Here, we describe how Mastermind improves the sensitivity and reproducibility of clinical variant interpretation and produces comprehensive genomic landscapes of genetic variants driving pharmaceutical research. We demonstrate an alarmingly high degree of heterogeneity across commercially available panels for hereditary cancer that is resolved by evidence from Mastermind. We further examined the sensitivity of Mastermind for variant interpretation by examining 108 clinically-encountered variants and comparing the results to alternate methods. Mastermind demonstrated a sensitivity of 98.4% compared to 4.4, 45.6, and 37.4% for alternatives PubMed, Google Scholar, and ClinVar, respectively, and a specificity of 98.5% compared to 45.1, 57.6, and 68.8% as well as an increase in content yield of 22.6-, 2.2-, and 2.6-fold. When curated for clinical significance, Mastermind identified more than 4.9-fold more pathogenic variants than ClinVar for representative genes. For structural variants, we compared Mastermind's ability to sensitively identify evidence for 10 representative disease-causing CNVs versus results identified in PubMed, as well as its ability to identify evidence for fusion events compared to COSMIC. Mastermind demonstrated a 4.0- to 43.9-fold increase in references for specific CNVs compared to PubMed, as well as 5.4-fold more fusion genes when compared with COSMIC's curated database. Additionally, Mastermind produced an 8.0-fold increase in reference citations for fusion events common to Mastermind and outside databases. Taken together, these results demonstrate the utility and superiority of Mastermind in terms of both sensitivity and specificity of automated results for clinical diagnostic variant interpretation for multiple genetic variant types and highlight the potential benefit in informing pharmaceutical research.
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Affiliation(s)
| | | | | | - Ryan P. Tarpey
- The Johns Hopkins Hospital, Department of Pharmacy, Baltimore, MD, United States
| | | | - Megan S. Lim
- Division of Hematopathology, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Kojo S. J. Elenitoba-Johnson
- Division of Precision and Computational Diagnostics, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
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28
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Wong M, Mayoh C, Lau LMS, Khuong-Quang DA, Pinese M, Kumar A, Barahona P, Wilkie EE, Sullivan P, Bowen-James R, Syed M, Martincorena I, Abascal F, Sherstyuk A, Bolanos NA, Baber J, Priestley P, Dolman MEM, Fleuren EDG, Gauthier ME, Mould EVA, Gayevskiy V, Gifford AJ, Grebert-Wade D, Strong PA, Manouvrier E, Warby M, Thomas DM, Kirk J, Tucker K, O'Brien T, Alvaro F, McCowage GB, Dalla-Pozza L, Gottardo NG, Tapp H, Wood P, Khaw SL, Hansford JR, Moore AS, Norris MD, Trahair TN, Lock RB, Tyrrell V, Haber M, Marshall GM, Ziegler DS, Ekert PG, Cowley MJ. Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk pediatric cancer. Nat Med 2020; 26:1742-1753. [PMID: 33020650 DOI: 10.1038/s41591-020-1072-4] [Citation(s) in RCA: 201] [Impact Index Per Article: 50.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 08/20/2020] [Indexed: 02/08/2023]
Abstract
The Zero Childhood Cancer Program is a precision medicine program to benefit children with poor-outcome, rare, relapsed or refractory cancer. Using tumor and germline whole genome sequencing (WGS) and RNA sequencing (RNAseq) across 252 tumors from high-risk pediatric patients with cancer, we identified 968 reportable molecular aberrations (39.9% in WGS and RNAseq, 35.1% in WGS only and 25.0% in RNAseq only). Of these patients, 93.7% had at least one germline or somatic aberration, 71.4% had therapeutic targets and 5.2% had a change in diagnosis. WGS identified pathogenic cancer-predisposing variants in 16.2% of patients. In 76 central nervous system tumors, methylome analysis confirmed diagnosis in 71.1% of patients and contributed to a change of diagnosis in two patients (2.6%). To date, 43 patients have received a recommended therapy, 38 of whom could be evaluated, with 31% showing objective evidence of clinical benefit. Comprehensive molecular profiling resolved the molecular basis of virtually all high-risk cancers, leading to clinical benefit in some patients.
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Affiliation(s)
- Marie Wong
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Chelsea Mayoh
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
| | - Loretta M S Lau
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, NSW, Australia
| | - Dong-Anh Khuong-Quang
- Children's Cancer Centre, Royal Children's Hospital, Parkville, VIC, Australia
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, VIC, Australia
| | - Mark Pinese
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Amit Kumar
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Paulette Barahona
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Emilie E Wilkie
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
| | - Patricia Sullivan
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Rachel Bowen-James
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Mustafa Syed
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | | | | | - Alexandra Sherstyuk
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Noemi A Bolanos
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, NSW, Australia
| | - Jonathan Baber
- Hartwig Medical Foundation, Amsterdam, The Netherlands
- Hartwig Medical Foundation Australia, Sydney, NSW, Australia
| | - Peter Priestley
- Hartwig Medical Foundation, Amsterdam, The Netherlands
- Hartwig Medical Foundation Australia, Sydney, NSW, Australia
| | - M Emmy M Dolman
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Emmy D G Fleuren
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
| | - Marie-Emilie Gauthier
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Emily V A Mould
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Velimir Gayevskiy
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Andrew J Gifford
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- Department of Anatomical Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Dylan Grebert-Wade
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Patrick A Strong
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Elodie Manouvrier
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Meera Warby
- Cancer Centre for Children, The Children's Hospital Westmead, Westmead, NSW, Australia
| | - David M Thomas
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Judy Kirk
- Familial Cancer Service, Crown Princess Mary Cancer Centre, Westmead Hospital, Westmead, NSW, Australia
- Sydney Medical School, University of Sydney Centre for Cancer Research, The Westmead Institute for Medical Research, Westmead, NSW, Australia
| | - Katherine Tucker
- Hereditary Cancer Centre, Prince of Wales Hospital, Randwick, NSW, Australia
- Prince of Wales Hospital Clinical School, University of New South Wales, Randwick, NSW, Australia
| | - Tracey O'Brien
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, NSW, Australia
| | - Frank Alvaro
- John Hunter Children's Hospital, New Lambton Heights, NSW, Australia
| | - Geoffry B McCowage
- Cancer Centre for Children, The Children's Hospital Westmead, Westmead, NSW, Australia
| | - Luciano Dalla-Pozza
- Cancer Centre for Children, The Children's Hospital Westmead, Westmead, NSW, Australia
| | - Nicholas G Gottardo
- Department of Paediatric and Adolescent Oncology/Haematology, Perth Children's Hospital, Nedlands, WA, Australia
- Brain Tumour Research Program, Telethon Kids Institute, Nedlands, WA, Australia
| | - Heather Tapp
- Women's and Children's Hospital, Adelaide, SA, Australia
| | - Paul Wood
- Monash Children's Hospital, Melbourne, VIC, Australia
| | - Seong-Lin Khaw
- Children's Cancer Centre, Royal Children's Hospital, Parkville, VIC, Australia
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, VIC, Australia
| | - Jordan R Hansford
- Children's Cancer Centre, Royal Children's Hospital, Parkville, VIC, Australia
| | - Andrew S Moore
- Oncology Service, Oncology Service, Queensland Children's Hospital, Brisbane, QLD, Australia
- Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia
| | - Murray D Norris
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- University of New South Wales Centre for Childhood Cancer Research, UNSW Sydney, Kensington, NSW, Australia
| | - Toby N Trahair
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, NSW, Australia
| | - Richard B Lock
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
| | - Vanessa Tyrrell
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
| | - Michelle Haber
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
| | - Glenn M Marshall
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, NSW, Australia
| | - David S Ziegler
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia.
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia.
- Kids Cancer Centre, Sydney Children's Hospital, Randwick, NSW, Australia.
| | - Paul G Ekert
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia.
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia.
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, VIC, Australia.
- Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.
| | - Mark J Cowley
- Children's Cancer Institute, Lowy Cancer Centre, UNSW Sydney, Kensington, NSW, Australia.
- School of Women's and Children's Health, UNSW Sydney, Kensington, NSW, Australia.
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia.
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Prieto-Potin I, Carvajal N, Plaza-Sánchez J, Manso R, Aúz-Alexandre CL, Chamizo C, Zazo S, López-Sánchez A, Rodríguez-Pinilla SM, Camacho L, Longarón R, Bellosillo B, Somoza R, Hernández-Losa J, Fernández-Soria VM, Ramos-Ruiz R, Cristóbal I, García-Foncillas J, Rojo F. Validation and clinical application of a targeted next-generation sequencing gene panel for solid and hematologic malignancies. PeerJ 2020; 8:e10069. [PMID: 33083132 PMCID: PMC7546223 DOI: 10.7717/peerj.10069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 09/09/2020] [Indexed: 01/29/2023] Open
Abstract
Background Next-generation sequencing (NGS) is a high-throughput technology that has become widely integrated in molecular diagnostics laboratories. Among the large diversity of NGS-based panels, the Trusight Tumor 26 (TsT26) enables the detection of low-frequency variants across 26 genes using the MiSeq platform. Methods We describe the inter-laboratory validation and subsequent clinical application of the panel in 399 patients presenting a range of tumor types, including gastrointestinal (GI, 29%), hematologic (18%), lung (13%), gynecological and breast (8% each), among others. Results The panel is highly accurate with a test sensitivity of 92%, and demonstrated high specificity and positive predictive values (95% and 96%, respectively). Sequencing testing was successful in two-thirds of patients, while the remaining third failed due to unsuccessful quality-control filtering. Most detected variants were observed in the TP53 (28%), KRAS (16%), APC (10%) and PIK3CA (8%) genes. Overall, 372 variants were identified, primarily distributed as missense (81%), stop gain (9%) and frameshift (7%) altered sequences and mostly reported as pathogenic (78%) and variants of uncertain significance (19%). Only 14% of patients received targeted treatment based on the variant determined by the panel. The variants most frequently observed in GI and lung tumors were: KRAS c.35G > A (p.G12D), c.35G > T (p.G12V) and c.34G > T (p.G12C). Conclusions Prior panel validation allowed its use in the laboratory daily practice by providing several relevant and potentially targetable variants across multiple tumors. However, this study is limited by high sample inadequacy rate, raising doubts as to continuity in the clinical setting.
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Affiliation(s)
- Iván Prieto-Potin
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Nerea Carvajal
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Jenifer Plaza-Sánchez
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Rebeca Manso
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Carmen Laura Aúz-Alexandre
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Cristina Chamizo
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Sandra Zazo
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Almudena López-Sánchez
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | | | - Laura Camacho
- Department of Pathology, Hospital Del Mar Medical Research Institute, Barcelona, Spain
| | - Raquel Longarón
- Department of Pathology, Hospital Del Mar Medical Research Institute, Barcelona, Spain
| | - Beatriz Bellosillo
- Department of Pathology, Hospital Del Mar Medical Research Institute, Barcelona, Spain
| | - Rosa Somoza
- Department of Pathology, Vall d'Hebron University Hospital, Barcelona, Spain
| | | | | | | | - Ion Cristóbal
- Translational Oncology Division, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Jesús García-Foncillas
- Translational Oncology Division, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
| | - Federico Rojo
- Department of Pathology, CIBERONC, UAM, Fundación Jiménez Díaz University Hospital Health Research Institute, Madrid, Spain
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Jaravine V, Balmford J, Metzger P, Boerries M, Binder H, Boeker M. Annotation of Human Exome Gene Variants with Consensus Pathogenicity. Genes (Basel) 2020; 11:E1076. [PMID: 32938008 PMCID: PMC7563776 DOI: 10.3390/genes11091076] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/10/2020] [Accepted: 09/11/2020] [Indexed: 11/16/2022] Open
Abstract
A novel approach is developed to address the challenge of annotating with phenotypic effects those exome variants for which relevant empirical data are lacking or minimal. The predictive annotation method is implemented as a stacked ensemble of supervised base-learners, including distributed random forest and gradient boosting machines. Ensemble models were trained and cross-validated on evidence-based categorical variant effect annotations from the ClinVar database, and were applied to 84 million non-synonymous single nucleotide variants (SNVs). The consensus model combined 39 functional mutation impacts, cross-species conservation score, and gene indispensability score. The indispensability score, accounting for differences in variant pathogenicities including in essential and mutation-tolerant genes, considerably improved the predictions. The consensus combination is consistent with as many input scores as possible while minimizing false predictions. The input scores are ranked based on their ability to predict effects. The score rankings and categorical phenotypic variant effect predictions are aimed for direct use in clinical and biological applications to prioritize human exome variants and mutations.
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Affiliation(s)
- Victor Jaravine
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, 79104 Freiburg im Breisgau, Germany; (J.B.); (H.B.); (M.B.)
| | - James Balmford
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, 79104 Freiburg im Breisgau, Germany; (J.B.); (H.B.); (M.B.)
| | - Patrick Metzger
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79110 Freiburg im Breisgau, Germany; (P.M.); (M.B.)
| | - Melanie Boerries
- Institute of Medical Bioinformatics and Systems Medicine, Medical Center—University of Freiburg, Faculty of Medicine, University of Freiburg, 79110 Freiburg im Breisgau, Germany; (P.M.); (M.B.)
| | - Harald Binder
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, 79104 Freiburg im Breisgau, Germany; (J.B.); (H.B.); (M.B.)
| | - Martin Boeker
- Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, 79104 Freiburg im Breisgau, Germany; (J.B.); (H.B.); (M.B.)
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Reassessment of causality of ABCC6 missense variants associated with pseudoxanthoma elasticum based on Sherloc. Genet Med 2020; 23:131-139. [PMID: 32873932 DOI: 10.1038/s41436-020-00945-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 08/10/2020] [Accepted: 08/11/2020] [Indexed: 01/25/2023] Open
Abstract
PURPOSE Pseudoxanthoma elasticum (PXE) is a heritable disorder affecting elastic fibers in the skin, eyes, and cardiovascular system. It is caused by biallelic pathogenic variants in the ABCC6 gene. To date, over 300 ABCC6 variants are associated with PXE, more than half being missense variants. Correct variant interpretation is essential for establishing a direct link between the variant and the patient's phenotype and has important implications for diagnosis and treatment. METHODS We used a systematic approach for interpretation of 271 previously reported and 15 novel ABCC6 missense variants, based on the semiquantitative classification system Sherloc. RESULTS Only 35% of variants were very likely to contribute directly to disease, in contrast to reported interpretations in ClinVar, while 59% of variants are currently of uncertain significance (VUS). Subclasses were created to distinguish VUS that are leaning toward likely benign or pathogenic, increasing the number of (likely) pathogenic ABCC6 missense variants to 47%. CONCLUSION Besides highlighting discrepancies between the Sherloc, American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP), ClinVar, and Leiden Open Variation Database (LOVD) classification, our results emphasize the need for segregation analysis, functional assays, and detailed evidence sharing in variant databases to reach a confident interpretation of ABCC6 missense variants and subsequent appropriate genetic and preconceptual counseling.
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Pauly R, Schwartz CE. The Future of Clinical Diagnosis: Moving Functional Genomics Approaches to the Bedside. Clin Lab Med 2020; 40:221-230. [PMID: 32439070 DOI: 10.1016/j.cll.2020.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Rini Pauly
- Greenwood Genetic Center, JC Self Research Institute, 113 Gregor Mendel Circle, Greenwood, SC 29646, USA.
| | - Charles E Schwartz
- Greenwood Genetic Center, JC Self Research Institute, 113 Gregor Mendel Circle, Greenwood, SC 29646, USA
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Gorcenco S, Ilinca A, Almasoudi W, Kafantari E, Lindgren AG, Puschmann A. New generation genetic testing entering the clinic. Parkinsonism Relat Disord 2020; 73:72-84. [DOI: 10.1016/j.parkreldis.2020.02.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 02/24/2020] [Accepted: 02/24/2020] [Indexed: 12/18/2022]
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34
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Abolhassani H, Marcotte H, Fang M, Hammarström L. Clinical implications of experimental analyses of AID function on predictive computational tools: Challenge of missense variants. Clin Genet 2020; 97:844-856. [PMID: 32162335 DOI: 10.1111/cge.13737] [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: 01/07/2020] [Revised: 02/27/2020] [Accepted: 03/03/2020] [Indexed: 11/30/2022]
Abstract
Due to the increased usage of high throughput sequencing for the diagnosis of genetically inherited disorders, it is vital to evaluate the risk of new variants and novel genes before accepting them in clinical practice. However, discordant in silico and in vitro results, challenge estimations of the effect of an identified genetic variant. We aimed to comprehensively evaluate pathogenic and polymorphic variants using the activation-induced-cytidine-deaminase (AICDA) gene as a model. We systematically searched and identified patients with confirmed AICDA-mutations. Population-based-databases were screened for germline-polymorphic-AICDA-variants. Activity of AICDA-mutant and severity of the clinical and immunologic-phenotype were showed comparing 108 population-based-variants with 48 pathogenic mutations (12 overlapping-variants). Discordant predictions of different algorithms were observed on average in 38% of the population-database variants, mainly for missense mutations. Functional activity in mutations observed only in patients was significantly lower than variants in the population databases and overlapping-variants between patients and the general-population. Surprisingly, overlapping-variants had an even higher functional activity than the most common polymorphic-variants; however, their pathogenicity was still distinguishable when their function was compared with wild-type AICDA. Classifications of genetic variants cannot readily be translated into a clinical implication. Combined databases of functional and computational assays should therefore be developed for each specific gene.
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Affiliation(s)
- Hassan Abolhassani
- Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Harold Marcotte
- Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Mingyan Fang
- Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, Stockholm, Sweden.,BGI-Shenzhen, Shenzhen, China.,China National GeneBank, Shenzhen, China
| | - Lennart Hammarström
- Division of Clinical Immunology, Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, Stockholm, Sweden.,BGI-Shenzhen, Shenzhen, China.,China National GeneBank, Shenzhen, China
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Abstract
Artificial intelligence (AI) has contributed substantially to the resolution of a variety of biomedical problems, including cancer, over the past decade. Deep learning, a subfield of AI that is highly flexible and supports automatic feature extraction, is increasingly being applied in various areas of both basic and clinical cancer research. In this review, we describe numerous recent examples of the application of AI in oncology, including cases in which deep learning has efficiently solved problems that were previously thought to be unsolvable, and we address obstacles that must be overcome before such application can become more widespread. We also highlight resources and datasets that can help harness the power of AI for cancer research. The development of innovative approaches to and applications of AI will yield important insights in oncology in the coming decade.
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Affiliation(s)
- Hideyuki Shimizu
- Department of Molecular and Cellular BiologyMedical Institute of BioregulationKyushu UniversityFukuokaJapan
| | - Keiichi I. Nakayama
- Department of Molecular and Cellular BiologyMedical Institute of BioregulationKyushu UniversityFukuokaJapan
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36
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Farré X, Spataro N, Haziza F, Rambla J, Navarro A. Genome-phenome explorer (GePhEx): a tool for the visualization and interpretation of phenotypic relationships supported by genetic evidence. Bioinformatics 2020; 36:890-896. [PMID: 31393550 DOI: 10.1093/bioinformatics/btz622] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 07/05/2019] [Accepted: 08/07/2019] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Association studies based on SNP arrays and Next Generation Sequencing technologies have enabled the discovery of thousands of genetic loci related to human diseases. Nevertheless, their biological interpretation is still elusive, and their medical applications limited. Recently, various tools have been developed to help bridging the gap between genomes and phenomes. To our knowledge, however none of these tools allows users to retrieve the phenotype-wide list of genetic variants that may be linked to a given disease or to visually explore the joint genetic architecture of different pathologies. RESULTS We present the Genome-Phenome Explorer (GePhEx), a web-tool easing the visual exploration of phenotypic relationships supported by genetic evidences. GePhEx is primarily based on the thorough analysis of linkage disequilibrium between disease-associated variants and also considers relationships based on genes, pathways or drug-targets, leveraging on publicly available variant-disease associations to detect potential relationships between diseases. We demonstrate that GePhEx does retrieve well-known relationships as well as novel ones, and that, thus, it might help shedding light on the patho-physiological mechanisms underlying complex diseases. To this end, we investigate the potential relationship between schizophrenia and lung cancer, first detected using GePhEx and provide further evidence supporting a functional link between them. AVAILABILITY AND IMPLEMENTATION GePhEx is available at: https://gephex.ega-archive.org/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Xavier Farré
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain
| | - Nino Spataro
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain.,Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain
| | - Frederic Haziza
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain
| | - Jordi Rambla
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain
| | - Arcadi Navarro
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Catalonia 08003, Spain.,Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona 08003, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), PRBB, Barcelona, Catalonia 08003, Spain
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Development of a Precision Medicine Workflow in Hematological Cancers, Aalborg University Hospital, Denmark. Cancers (Basel) 2020; 12:cancers12020312. [PMID: 32013121 PMCID: PMC7073219 DOI: 10.3390/cancers12020312] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 01/10/2020] [Accepted: 01/27/2020] [Indexed: 12/17/2022] Open
Abstract
Within recent years, many precision cancer medicine initiatives have been developed. Most of these have focused on solid cancers, while the potential of precision medicine for patients with hematological malignancies, especially in the relapse situation, are less elucidated. Here, we present a demographic unbiased and observational prospective study at Aalborg University Hospital Denmark, referral site for 10% of the Danish population. We developed a hematological precision medicine workflow based on sequencing analysis of whole exome tumor DNA and RNA. All steps involved are outlined in detail, illustrating how the developed workflow can provide relevant molecular information to multidisciplinary teams. A group of 174 hematological patients with progressive disease or relapse was included in a non-interventional and population-based study, of which 92 patient samples were sequenced. Based on analysis of small nucleotide variants, copy number variants, and fusion transcripts, we found variants with potential and strong clinical relevance in 62% and 9.5% of the patients, respectively. The most frequently mutated genes in individual disease entities were in concordance with previous studies. We did not find tumor mutational burden or micro satellite instability to be informative in our hematologic patient cohort.
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Impact of proactive high-throughput functional assay data on BRCA1 variant interpretation in 3684 patients with breast or ovarian cancer. J Hum Genet 2020; 65:209-220. [PMID: 31907386 DOI: 10.1038/s10038-019-0713-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 12/12/2019] [Accepted: 12/16/2019] [Indexed: 11/08/2022]
Abstract
The clinical utility of BRCA1/2 genotyping was recently extended from the selection of subjects at high risk for hereditary breast and ovary cancer to the identification of candidates for poly (ADP-ribose) polymerase (PARP) inhibitor treatment. This underscores the importance of accurate interpretation of BRCA1/2 genetic variants and of reducing the number of variants of uncertain significance (VUSs). Two recent studies by Findlay et al. and Starita et al. introduced high-throughput functional assays, and proactively analyzed variants in specific regions regardless of whether they had been previously observed. We retrospectively reviewed all BRCA1 and BRCA2 germline genetic test reports from patients with breast or ovarian cancer examined at Asan Medical Center (Seoul, Korea) between September 2011 and December 2018. Variants were assigned pathogenic or benign strong evidence codes according to the functional classification and were reclassified according to the ACMG/AMP 2015 guidelines. Among 3684 patients with available BRCA1 and BRCA2 germline genetic test reports, 429 unique variants (181 from BRCA1) were identified. Of 34 BRCA1 variants intersecting with the data reported by Findlay et al., three missense single-nucleotide variants from four patients (0.11%, 4/3684) were reclassified from VUSs to likely pathogenic variants. Four variants scored as functional were reclassified into benign or likely benign variants. Three variants that overlapped with the data reported by Starita et al. could not be reclassified. In conclusion, proactive high-throughput functional study data are useful for the reclassification of clinically observed VUSs. Integrating additional evidence, including functional assay results, may help reduce the number of VUSs.
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González-Acosta M, Hinrichsen I, Fernández A, Lázaro C, Pineda M, Plotz G, Capellá G. Validation of an in Vitro Mismatch Repair Assay Used in the Functional Characterization of Mismatch Repair Variants. J Mol Diagn 2019; 22:376-385. [PMID: 31881334 DOI: 10.1016/j.jmoldx.2019.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 09/27/2019] [Accepted: 12/05/2019] [Indexed: 10/25/2022] Open
Abstract
A significant proportion of DNA-mismatch repair (MMR) variants are classified as of unknown significance, precluding diagnosis. The in vitro MMR assay is used to assess their MMR capability, likely the most important function of an MMR protein. However, the robustness of the assay, crucial for its use in the clinical setting, has been rarely evaluated. The aim of the present work was to validate an in vitro MMR assay approach to the functional characterization of MMR variants, as a first step to meeting quality standards of diagnostic laboratories. The MMR assay was optimized by testing a variety of reagents and experimental conditions. Reference materials and standard operating procedures were established. To determine the intra- and interexperimental variability of the assay and its reproducibility among centers, independent transfections of six previously characterized MLH1 variants were performed in two independent laboratories. Reagents and conditions optimal for performing the in vitro MMR assay were determined. The validated assay demonstrated no significant intra- or interexperimental variability and good reproducibility between centers. We set up a robust in vitro MMR assay that can provide relevant in vitro functional evidence for MMR variant pathogenicity assessment, eventually improving the molecular diagnosis of hereditary cancer syndromes associated with MMR deficiency.
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Affiliation(s)
- Maribel González-Acosta
- Hereditary Cancer Program, the Catalan Institute of Oncology (ICO), Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Ciber Oncología (CIBERONC) Instituto Salud Carlos III, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Inga Hinrichsen
- Biomedical Research Laboratory, Department of Internal Medicine 1, Universitätsklinikum Frankfurt, Frankfurt, Germany
| | - Anna Fernández
- Hereditary Cancer Program, the Catalan Institute of Oncology (ICO), Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Ciber Oncología (CIBERONC) Instituto Salud Carlos III, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Conxi Lázaro
- Hereditary Cancer Program, the Catalan Institute of Oncology (ICO), Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Ciber Oncología (CIBERONC) Instituto Salud Carlos III, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Marta Pineda
- Hereditary Cancer Program, the Catalan Institute of Oncology (ICO), Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Ciber Oncología (CIBERONC) Instituto Salud Carlos III, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Guido Plotz
- Biomedical Research Laboratory, Department of Internal Medicine 1, Universitätsklinikum Frankfurt, Frankfurt, Germany
| | - Gabriel Capellá
- Hereditary Cancer Program, the Catalan Institute of Oncology (ICO), Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Ciber Oncología (CIBERONC) Instituto Salud Carlos III, L'Hospitalet de Llobregat, Barcelona, Spain.
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40
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Standardization of Somatic Variant Classifications in Solid and Haematological Tumours by a Two-Level Approach of Biological and Clinical Classes: An Initiative of the Belgian ComPerMed Expert Panel. Cancers (Basel) 2019; 11:cancers11122030. [PMID: 31888289 PMCID: PMC6966529 DOI: 10.3390/cancers11122030] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 12/03/2019] [Accepted: 12/05/2019] [Indexed: 12/20/2022] Open
Abstract
In most diagnostic laboratories, targeted next-generation sequencing (NGS) is currently the default assay for the detection of somatic variants in solid as well as haematological tumours. Independent of the method, the final outcome is a list of variants that differ from the human genome reference sequence of which some may relate to the establishment of the tumour in the patient. A critical point towards a uniform patient management is the assignment of the biological contribution of each variant to the malignancy and its subsequent clinical impact in a specific malignancy. These so-called biological and clinical classifications of somatic variants are currently not standardized and are vastly dependent on the subjective analysis of each laboratory. This subjectivity can thus result in a different classification and subsequent clinical interpretation of the same variant. Therefore, the ComPerMed panel of Belgian experts in cancer diagnostics set up a working group with the goal to harmonize the biological classification and clinical interpretation of somatic variants detected by NGS. This effort resulted in the establishment of a uniform, two-level classification workflow system that should enable high consistency in diagnosis, prognosis, treatment and follow-up of cancer patients. Variants are first classified into a tumour-independent biological five class system and subsequently in a four tier ACMG clinical classification. Here, we describe the ComPerMed workflow in detail including examples for each step of the pipeline. Moreover, this workflow can be implemented in variant classification software tools enabling automatic reporting of NGS data, independent of panel, method or analysis software.
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41
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Danos AM, Krysiak K, Barnell EK, Coffman AC, McMichael JF, Kiwala S, Spies NC, Sheta LM, Pema SP, Kujan L, Clark KA, Wollam AZ, Rao S, Ritter DI, Sonkin D, Raca G, Lin WH, Grisdale CJ, Kim RH, Wagner AH, Madhavan S, Griffith M, Griffith OL. Standard operating procedure for curation and clinical interpretation of variants in cancer. Genome Med 2019; 11:76. [PMID: 31779674 PMCID: PMC6883603 DOI: 10.1186/s13073-019-0687-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 11/07/2019] [Indexed: 02/04/2023] Open
Abstract
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the complexity of the models used to capture clinical knowledge. CIViC (Clinical Interpretation of Variants in Cancer - www.civicdb.org) is a fully open, free-to-use cancer variant interpretation knowledgebase that incorporates highly detailed curation of evidence obtained from peer-reviewed publications and meeting abstracts, and currently holds over 6300 Evidence Items for over 2300 variants derived from over 400 genes. CIViC has seen increased adoption by, and also undertaken collaboration with, a wide range of users and organizations involved in research. To enhance CIViC’s clinical value, regular submission to the ClinVar database and pursuit of other regulatory approvals is necessary. For this reason, a formal peer reviewed curation guideline and discussion of the underlying principles of curation is needed. We present here the CIViC knowledge model, standard operating procedures (SOP) for variant curation, and detailed examples to support community-driven curation of cancer variants.
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Affiliation(s)
- Arpad M Danos
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Kilannin Krysiak
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.,Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
| | - Erica K Barnell
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Adam C Coffman
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Joshua F McMichael
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Susanna Kiwala
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Nicholas C Spies
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Lana M Sheta
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Shahil P Pema
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Lynzey Kujan
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Kaitlin A Clark
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Amber Z Wollam
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Shruti Rao
- Innovation Center for Biomedical Informatics, Georgetown University, Washington DC, USA
| | - Deborah I Ritter
- Department of Pediatrics, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Dmitriy Sonkin
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, USA
| | - Gordana Raca
- Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Wan-Hsin Lin
- Department of Cancer Biology, Mayo Clinic, Jacksonville, Florida, USA
| | - Cameron J Grisdale
- Canada's Michael Smith Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Raymond H Kim
- Fred A. Litwin Family Center in Genetic Medicine, University Health Network, Toronto, ON, Canada
| | - Alex H Wagner
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Subha Madhavan
- Innovation Center for Biomedical Informatics, Georgetown University, Washington DC, USA.,Georgetown Lombardi Comprehensive Cancer Center, Washington DC, USA
| | - Malachi Griffith
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA. .,Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA.
| | - Obi L Griffith
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA. .,Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA. .,Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA.
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42
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Kumar KR, Davis RL, Tchan MC, Wali GM, Mahant N, Ng K, Kotschet K, Siow SF, Gu J, Walls Z, Kang C, Wali G, Levy S, Phua CS, Yiannikas C, Darveniza P, Chang FCF, Morales-Briceño H, Rowe DB, Drew A, Gayevskiy V, Cowley MJ, Minoche AE, Tisch S, Hayes M, Kummerfeld S, Fung VSC, Sue CM. Whole genome sequencing for the genetic diagnosis of heterogenous dystonia phenotypes. Parkinsonism Relat Disord 2019; 69:111-118. [PMID: 31731261 DOI: 10.1016/j.parkreldis.2019.11.004] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Revised: 10/21/2019] [Accepted: 11/02/2019] [Indexed: 11/17/2022]
Abstract
INTRODUCTION Dystonia is a clinically and genetically heterogeneous disorder and a genetic cause is often difficult to elucidate. This is the first study to use whole genome sequencing (WGS) to investigate dystonia in a large sample of affected individuals. METHODS WGS was performed on 111 probands with heterogenous dystonia phenotypes. We performed analysis for coding and non-coding variants, copy number variants (CNVs), and structural variants (SVs). We assessed for an association between dystonia and 10 known dystonia risk variants. RESULTS A genetic diagnosis was obtained for 11.7% (13/111) of individuals. We found that a genetic diagnosis was more likely in those with an earlier age at onset, younger age at testing, and a combined dystonia phenotype. We identified pathogenic/likely-pathogenic variants in ADCY5 (n = 1), ATM (n = 1), GNAL (n = 2), GLB1 (n = 1), KMT2B (n = 2), PRKN (n = 2), PRRT2 (n = 1), SGCE (n = 2), and THAP1 (n = 1). CNVs were detected in 3 individuals. We found an association between the known risk variant ARSG rs11655081 and dystonia (p = 0.003). CONCLUSION A genetic diagnosis was found in 11.7% of individuals with dystonia. The diagnostic yield was higher in those with an earlier age of onset, younger age at testing, and a combined dystonia phenotype. WGS may be particularly relevant for dystonia given that it allows for the detection of CNVs, which accounted for 23% of the genetically diagnosed cases.
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Affiliation(s)
- Kishore R Kumar
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia; Department of Neurogenetics, Kolling Institute, University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, 2065, Australia; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia; Molecular Medicine Laboratory, Concord Hospital, 2139, Australia; Department of Neurology, Concord Hospital, 2139, Australia.
| | - Ryan L Davis
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia; Department of Neurogenetics, Kolling Institute, University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, 2065, Australia; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia.
| | - Michel C Tchan
- Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia; Department of Genetic Medicine, Westmead Hospital, Westmead, NSW, 2145, Australia.
| | - G M Wali
- Neurospecialities Centre, Jawaharlal Nehru Medical College, Belgaum, India.
| | - Neil Mahant
- Movement Disorders Unit, Department of Neurology, Westmead Hospital, Sydney Medical School, University of Sydney, Sydney, 2145, Australia.
| | - Karl Ng
- Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia; Department of Neurology and Neurophysiology, Royal North Shore Hospital, Reserve Road, St Leonards, New South Wales, 2065, Australia.
| | - Katya Kotschet
- Florey Neuroscience Institute, University of Melbourne, Parkville, 3052, Australia; Department of Neurology, St Vincent's Hospital, Fitzroy, 3065, Australia.
| | - Sue-Faye Siow
- Department of Neurogenetics, Kolling Institute, University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, 2065, Australia; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia; Department of Genetic Medicine, Westmead Hospital, Westmead, NSW, 2145, Australia.
| | - Jason Gu
- Department of Neurology, Wollongong Hospital, Wollongong, New South Wales, 2500, Australia.
| | - Zachary Walls
- Faculty of Engineering and Information Technologies, University of Sydney, Darlington, 2008, Australia.
| | - Ce Kang
- Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia.
| | - Gautam Wali
- Department of Neurogenetics, Kolling Institute, University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, 2065, Australia; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia.
| | - Stan Levy
- Campbelltown Hospital, Campbelltown, 2560, Australia.
| | | | - Con Yiannikas
- Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia; Department of Neurology, Concord Hospital, 2139, Australia; Department of Neurology, Royal North Shore Hospital, St Leonards, New South Wales, 2065, Australia.
| | - Paul Darveniza
- School of Medicine, University of New South Wales, Sydney, Australia; Department of Neurology, St Vincent's Hospital, Darlinghurst, 2010, Australia.
| | - Florence C F Chang
- Movement Disorders Unit, Department of Neurology, Westmead Hospital, Sydney Medical School, University of Sydney, Sydney, 2145, Australia.
| | - Hugo Morales-Briceño
- Movement Disorders Unit, Department of Neurology, Westmead Hospital, Sydney Medical School, University of Sydney, Sydney, 2145, Australia.
| | - Dominic B Rowe
- Department of Clinical Medicine, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, New South Wales, 2109, Australia.
| | - Alex Drew
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia.
| | - Velimir Gayevskiy
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia.
| | - Mark J Cowley
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia; Children's Cancer Institute, Kensington, 2750, Australia; St Vincent's Clinical School, UNSW Sydney, Darlinghurst, 2010, Australia.
| | - Andre E Minoche
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia.
| | - Stephen Tisch
- School of Medicine, University of New South Wales, Sydney, Australia; Department of Neurology, St Vincent's Hospital, Darlinghurst, 2010, Australia.
| | - Michael Hayes
- Department of Neurology, Concord Hospital, 2139, Australia.
| | - Sarah Kummerfeld
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia.
| | - Victor S C Fung
- Movement Disorders Unit, Department of Neurology, Westmead Hospital, Sydney Medical School, University of Sydney, Sydney, 2145, Australia.
| | - Carolyn M Sue
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, NSW, 2010, Australia; Department of Neurogenetics, Kolling Institute, University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, 2065, Australia; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Camperdown, 2050, Australia; Department of Neurology, Royal North Shore Hospital, St Leonards, New South Wales, 2065, Australia.
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Palomo L, Ibáñez M, Abáigar M, Vázquez I, Álvarez S, Cabezón M, Tazón-Vega B, Rapado I, Fuster-Tormo F, Cervera J, Benito R, Larrayoz MJ, Cigudosa JC, Zamora L, Valcárcel D, Cedena MT, Acha P, Hernández-Sánchez JM, Fernández-Mercado M, Sanz G, Hernández-Rivas JM, Calasanz MJ, Solé F, Such E. Spanish Guidelines for the use of targeted deep sequencing in myelodysplastic syndromes and chronic myelomonocytic leukaemia. Br J Haematol 2019; 188:605-622. [PMID: 31621063 PMCID: PMC7064979 DOI: 10.1111/bjh.16175] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 07/04/2019] [Accepted: 07/06/2019] [Indexed: 12/20/2022]
Abstract
The landscape of medical sequencing has rapidly changed with the evolution of next generation sequencing (NGS). These technologies have contributed to the molecular characterization of the myelodysplastic syndromes (MDS) and chronic myelomonocytic leukaemia (CMML), through the identification of recurrent gene mutations, which are present in >80% of patients. These mutations contribute to a better classification and risk stratification of the patients. Currently, clinical laboratories include NGS genomic analyses in their routine clinical practice, in an effort to personalize the diagnosis, prognosis and treatment of MDS and CMML. NGS technologies have reduced the cost of large-scale sequencing, but there are additional challenges involving the clinical validation of these technologies, as continuous advances are constantly being made. In this context, it is of major importance to standardize the generation, analysis, clinical interpretation and reporting of NGS data. To that end, the Spanish MDS Group (GESMD) has expanded the present set of guidelines, aiming to establish common quality standards for the adequate implementation of NGS and clinical interpretation of the results, hoping that this effort will ultimately contribute to the benefit of patients with myeloid malignancies.
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Affiliation(s)
- Laura Palomo
- Josep Carreras Leukaemia Research Institute, ICO Badalona-Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Sadalona, Spain
| | - Mariam Ibáñez
- Department of Haematology, Hospital Universitari i Politècnic La Fe, València, Spain.,Centro de Investigacion Biomédica en Red de Cáncer (CIBERONC), Instituto Carlos III, Madrid, Spain.,Departamento de Ciencias Biomédicas, Facultad de Ciencias de la Salud, Universidad CEU Cardenal Herrera, València, Spain
| | - María Abáigar
- Institute of Biomedical Research of Salamanca (IBSAL), Cancer Research Centre (IBMCC-CIC; Univ. of Salamanca-CSIC), Salamanca, Spain
| | - Iria Vázquez
- Haematological Diseases Laboratory, CIMA LAB Diagnostics, University of Navarra, Pamplona, Spain.,Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Sara Álvarez
- NIMGenetics, Genómica y Medicina, S.L., Madrid, Spain
| | - Marta Cabezón
- Haematology Service, ICO Badalona-Hospital Germans Trias i Pujol, Josep Carreras Leukaemia Research Institute, Badalona, Spain
| | - Bárbara Tazón-Vega
- Department of Haematology, Vall d'Hebron Institute of Oncology, Vall d'Hebron University Hospital, Barcelona, Spain.,Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Inmaculada Rapado
- Haematology Department, Hospital Universitario 12 de Octubre, Madrid, Spain.,Haematological Malignancies Clinical Research Unit, CNIO, Madrid, Spain.,Centro de investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain
| | - Francisco Fuster-Tormo
- Josep Carreras Leukaemia Research Institute, ICO Badalona-Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Sadalona, Spain
| | - José Cervera
- Department of Haematology, Hospital Universitari i Politècnic La Fe, València, Spain.,Centro de Investigacion Biomédica en Red de Cáncer (CIBERONC), Instituto Carlos III, Madrid, Spain.,Genetics Unit, Hospital Universitario y Politécnico La Fe, Valencia, Spain
| | - Rocío Benito
- Institute of Biomedical Research of Salamanca (IBSAL), Cancer Research Centre (IBMCC-CIC; Univ. of Salamanca-CSIC), Salamanca, Spain
| | - María J Larrayoz
- Haematological Diseases Laboratory, CIMA LAB Diagnostics, University of Navarra, Pamplona, Spain.,Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | | | - Lurdes Zamora
- Haematology Service, ICO Badalona-Hospital Germans Trias i Pujol, Josep Carreras Leukaemia Research Institute, Badalona, Spain
| | - David Valcárcel
- Department of Haematology, Vall d'Hebron Institute of Oncology, Vall d'Hebron University Hospital, Barcelona, Spain.,Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - María T Cedena
- Haematology Department, Hospital Universitario 12 de Octubre, Madrid, Spain.,Haematological Malignancies Clinical Research Unit, CNIO, Madrid, Spain.,Centro de investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain
| | - Pamela Acha
- Josep Carreras Leukaemia Research Institute, ICO Badalona-Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Sadalona, Spain
| | - Jesús M Hernández-Sánchez
- Institute of Biomedical Research of Salamanca (IBSAL), Cancer Research Centre (IBMCC-CIC; Univ. of Salamanca-CSIC), Salamanca, Spain.,University of Salamanca (USAL), Salamanca, Spain
| | - Marta Fernández-Mercado
- Haematological Diseases Laboratory, CIMA LAB Diagnostics, University of Navarra, Pamplona, Spain.,Advanced Genomics Laboratory, Centre for Applied Medical Research (CIMA), University of Navarra, Haemato-Oncology, Pamplona, Spain.,Biomedical Engineering Department, School of Engineering, University of Navarra, San Sebastian, Spain
| | - Guillermo Sanz
- Department of Haematology, Hospital Universitari i Politècnic La Fe, València, Spain.,Centro de Investigacion Biomédica en Red de Cáncer (CIBERONC), Instituto Carlos III, Madrid, Spain
| | - Jesús M Hernández-Rivas
- Institute of Biomedical Research of Salamanca (IBSAL), Cancer Research Centre (IBMCC-CIC; Univ. of Salamanca-CSIC), Salamanca, Spain.,University of Salamanca (USAL), Salamanca, Spain.,Hospital Universitario de Salamanca, Salamanca, Spain
| | - María J Calasanz
- Haematological Diseases Laboratory, CIMA LAB Diagnostics, University of Navarra, Pamplona, Spain.,Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Francesc Solé
- Josep Carreras Leukaemia Research Institute, ICO Badalona-Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Sadalona, Spain
| | - Esperanza Such
- Department of Haematology, Hospital Universitari i Politècnic La Fe, València, Spain.,Centro de Investigacion Biomédica en Red de Cáncer (CIBERONC), Instituto Carlos III, Madrid, Spain.,Departamento de Ciencias Biomédicas, Facultad de Ciencias de la Salud, Universidad CEU Cardenal Herrera, València, Spain
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Chinn IK, Chan AY, Chen K, Chou J, Dorsey MJ, Hajjar J, Jongco AM, Keller MD, Kobrynski LJ, Kumanovics A, Lawrence MG, Leiding JW, Lugar PL, Orange JS, Patel K, Platt CD, Puck JM, Raje N, Romberg N, Slack MA, Sullivan KE, Tarrant TK, Torgerson TR, Walter JE. Diagnostic interpretation of genetic studies in patients with primary immunodeficiency diseases: A working group report of the Primary Immunodeficiency Diseases Committee of the American Academy of Allergy, Asthma & Immunology. J Allergy Clin Immunol 2019; 145:46-69. [PMID: 31568798 DOI: 10.1016/j.jaci.2019.09.009] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 09/02/2019] [Accepted: 09/20/2019] [Indexed: 12/19/2022]
Abstract
Genetic testing has become an integral component of the diagnostic evaluation of patients with suspected primary immunodeficiency diseases. Results of genetic testing can have a profound effect on clinical management decisions. Therefore clinical providers must demonstrate proficiency in interpreting genetic data. Because of the need for increased knowledge regarding this practice, the American Academy of Allergy, Asthma & Immunology Primary Immunodeficiency Diseases Committee established a work group that reviewed and summarized information concerning appropriate methods, tools, and resources for evaluating variants identified by genetic testing. Strengths and limitations of tests frequently ordered by clinicians were examined. Summary statements and tables were then developed to guide the interpretation process. Finally, the need for research and collaboration was emphasized. Greater understanding of these important concepts will improve the diagnosis and management of patients with suspected primary immunodeficiency diseases.
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Affiliation(s)
- Ivan K Chinn
- Department of Pediatrics, Baylor College of Medicine, Houston, Tex; Section of Immunology, Allergy, and Rheumatology, Texas Children's Hospital, Houston, Tex.
| | - Alice Y Chan
- Department of Pediatrics, Division of Allergy, Immunology, and Bone Marrow Transplantation, University of California at San Francisco, San Francisco, Calif
| | - Karin Chen
- Division of Allergy and Immunology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah
| | - Janet Chou
- Department of Pediatrics, Harvard Medical School, Boston, Mass; Division of Allergy and Immunology, Boston Children's Hospital, Boston, Mass
| | - Morna J Dorsey
- Department of Pediatrics, Division of Allergy, Immunology, and Bone Marrow Transplantation, University of California at San Francisco, San Francisco, Calif
| | - Joud Hajjar
- Department of Pediatrics, Baylor College of Medicine, Houston, Tex; Section of Immunology, Allergy, and Rheumatology, Texas Children's Hospital, Houston, Tex
| | - Artemio M Jongco
- Departments of Medicine and Pediatrics, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Great Neck, NY; Center for Health Innovations and Outcomes Research, Feinstein Institute for Medical Research, Great Neck, NY; Division of Allergy & Immunology, Cohen Children's Medical Center of New York, Great Neck, NY
| | - Michael D Keller
- Department of Allergy and Immunology, Children's National Hospital, Washington, DC
| | - Lisa J Kobrynski
- Department of Pediatrics, Division of Allergy and Immunology, Emory University School of Medicine, Atlanta, Ga
| | - Attila Kumanovics
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minn
| | - Monica G Lawrence
- Department of Medicine, Division of Asthma, Allergy and Immunology, University of Virginia Health System, Charlottesville, Va
| | - Jennifer W Leiding
- Departments of Pediatrics and Medicine, University of South Florida, St Petersburg, Fla; Division of Pediatric Allergy/Immunology, Johns Hopkins-All Children's Hospital, St Petersburg, Fla; Cancer and Blood Disorders Institute, Johns Hopkins-All Children's Hospital, St Petersburg, Fla
| | - Patricia L Lugar
- Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University Medical Center, Durham, NC
| | - Jordan S Orange
- Department of Pediatrics, Columbia University College of Physicians and Surgeons, New York, NY; New York Presbyterian Morgan Stanley Children's Hospital, New York, NY
| | - Kiran Patel
- Department of Pediatrics, Division of Allergy and Immunology, Emory University School of Medicine, Atlanta, Ga
| | - Craig D Platt
- Department of Pediatrics, Harvard Medical School, Boston, Mass; Division of Allergy and Immunology, Boston Children's Hospital, Boston, Mass
| | - Jennifer M Puck
- Department of Pediatrics, Division of Allergy, Immunology, and Bone Marrow Transplantation, University of California at San Francisco, San Francisco, Calif
| | - Nikita Raje
- Department of Pediatrics, University of Missouri-Kansas City, Kansas City, Mo; Division of Allergy/Asthma/Immunology, Children's Mercy Hospital, Kansas City, Mo
| | - Neil Romberg
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa; Division of Allergy/Immunology, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Maria A Slack
- Department of Medicine, Division of Allergy, Immunology, and Rheumatology, University of Rochester Medical Center, Rochester, NY; Department of Pediatrics, Division of Pediatric Allergy and Immunology, University of Rochester Medical Center, Rochester, NY
| | - Kathleen E Sullivan
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa; Division of Allergy/Immunology, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Teresa K Tarrant
- Department of Medicine, Division of Rheumatology and Immunology, Duke University Medical Center, Durham, NC
| | - Troy R Torgerson
- Department of Pediatrics, University of Washington School of Medicine, Seattle, Wash; Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, Wash
| | - Jolan E Walter
- Departments of Pediatrics and Medicine, University of South Florida, St Petersburg, Fla; Division of Pediatric Allergy/Immunology, Johns Hopkins-All Children's Hospital, St Petersburg, Fla; Division of Pediatric Allergy Immunology, Massachusetts General Hospital, Boston, Mass
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45
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Elbracht M, Meyer R, Eggermann T, Kurth I. [Rational use of genetic tests in internal medicine : Possibilities and limitations of next generation sequencing diagnostics]. Internist (Berl) 2019; 59:756-765. [PMID: 29946883 DOI: 10.1007/s00108-018-0457-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND New methods of molecular genetic diagnostics enable a more comprehensive genetic analysis of patients. OBJECTIVES Rational use and benefits of molecular genetic testing in patients with various internal diseases. METHOD Evaluation of topic-related literature, discussion of own experiences, as well as consideration of current guidelines. RESULTS New genetic tests, such as next generation sequencing (NGS), improve the diagnosis of hereditary diseases; however, the use of this technology also leads to additional findings, which must be carefully considered. CONCLUSION The rational use of genetic tests is a benefit for patients and can significantly influence the prevention and treatment of a disease. The increasing complexity of genetic findings requires interdisciplinary approaches involving human genetics, internal medicine, and other disciplines.
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Affiliation(s)
- M Elbracht
- Institut für Humangenetik, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Deutschland
| | - R Meyer
- Institut für Humangenetik, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Deutschland
| | - T Eggermann
- Institut für Humangenetik, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Deutschland
| | - I Kurth
- Institut für Humangenetik, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52074, Aachen, Deutschland.
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46
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Mouthon L, Busa T, Bretelle F, Karmous-Benailly H, Missirian C, Philip N, Sigaudy S. Prenatal diagnosis of micrognathia in 41 fetuses: Retrospective analysis of outcome and genetic etiologies. Am J Med Genet A 2019; 179:2365-2373. [PMID: 31509347 DOI: 10.1002/ajmg.a.61359] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 08/20/2019] [Accepted: 08/23/2019] [Indexed: 12/20/2022]
Abstract
Fetal micrognathia can be detected early in pregnancy. Prognosis of micrognathia depends on the risk of respiratory distress at birth and on the long-term risk of intellectual disability. The purpose of this study was to evaluate the long-term prognosis of fetuses with prenatal diagnosis of micrognathia by estimating the prevalence and the severity of confirmed genetic diagnosis in our cohort. Our retrospective study included 41 fetuses with prenatal diagnosis of micrognathia referred to the multidisciplinary centers for prenatal diagnosis in Nice and Marseille, France, between 2006 and 2016. Fetal micrognathia was associated with cleft palate in 27 cases. A genetic cause was confirmed in 21 cases (67%). A chromosomal abnormality was present in 12 cases, including three copy-number variations diagnosed by array CGH. Monogenic disorders were identified in nine cases, most often after birth. Fetuses with family history of micrognathia or Pierre Robin sequence had a favorable outcome. Prognosis was good for the fetuses without associated findings and normal chromosomal analysis, with the exception of one case with a postnatal diagnosis of mandibulofacial dysostosis with microcephaly. Prognostic was poor for the fetuses with additional ultrasound anomalies, as only 5 out of 28 children had a good outcome. Prenatal diagnosis of micrognathia is an indicator of a possible fetal pathology justifying multidisciplinary management. Our study confirms the necessity of performing prenatal array CGH. Use of high-throughput gene sequencing in prenatal period could improve diagnostic performance, prenatal counseling, and adequate postnatal care.
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Affiliation(s)
- Linda Mouthon
- GH La Pitié Salpêtrière-Charles Foix, Medical Genetics, Paris, France
| | - Tiffany Busa
- Hôpital de la Timone, Medical Genetics, Marseille, Provence-Alpes-Côte d'Azur, France
| | - Florence Bretelle
- Hôpital de la Timone, Prenatal diagnosis, Marseille, Provence-Alpes-Côte d'Azur, France
| | | | - Chantal Missirian
- Hôpital de la Timone, Cytogenetics, Marseille, Provence-Alpes-Côte d'Azur, France
| | - Nicole Philip
- Hôpital de la Timone, Medical Genetics, Marseille, Provence-Alpes-Côte d'Azur, France.,Hôpital de la Timone, Prenatal diagnosis, Marseille, Provence-Alpes-Côte d'Azur, France
| | - Sabine Sigaudy
- Hôpital de la Timone, Medical Genetics, Marseille, Provence-Alpes-Côte d'Azur, France.,Hôpital de la Timone, Prenatal diagnosis, Marseille, Provence-Alpes-Côte d'Azur, France
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47
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Kim YE, Ki CS, Jang MA. Challenges and Considerations in Sequence Variant Interpretation for Mendelian Disorders. Ann Lab Med 2019; 39:421-429. [PMID: 31037860 PMCID: PMC6502951 DOI: 10.3343/alm.2019.39.5.421] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 12/28/2018] [Accepted: 04/09/2019] [Indexed: 11/23/2022] Open
Abstract
In 2015, the American College of Medical Genetics and Genomics (ACMG), together with the Association for Molecular Pathology (AMP), published the latest guidelines for the interpretation of sequence variants, which have been widely adopted into clinical practice. Despite these standardized efforts, the degrees of subjectivity and uncertainty allowed by the guidelines can lead to inconsistent variant classification across clinical laboratories, making it difficult to assess the pathogenicity of identified variants. We describe the critical elements of variant interpretation processes and potential pitfalls through practical examples and provide updated information based on a review of recent literature. The variant classification we describe is meant to be applicable to sequence variants for Mendelian disorders, whether identified by single-gene tests, multi-gene panels, exome sequencing, or genome sequencing. Continuing efforts to improve the reproducibility and objectivity of sequence variant interpretation across individuals and laboratories are needed.
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Affiliation(s)
- Young Eun Kim
- Department of Laboratory Medicine, Hanyang University College of Medicine, Seoul, Korea
| | | | - Mi Ae Jang
- Department of Laboratory Medicine and Genetics, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon, Korea.
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48
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Muiño-Mosquera L, Steijns F, Audenaert T, Meerschaut I, De Paepe A, Steyaert W, Symoens S, Coucke P, Callewaert B, Renard M, De Backer J. Tailoring the American College of Medical Genetics and Genomics and the Association for Molecular Pathology Guidelines for the Interpretation of Sequenced Variants in the FBN1 Gene for Marfan Syndrome: Proposal for a Disease- and Gene-Specific Guideline. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2019; 11:e002039. [PMID: 29875124 DOI: 10.1161/circgen.117.002039] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 03/09/2018] [Indexed: 01/08/2023]
Abstract
BACKGROUND The introduction of next-generation sequencing techniques has substantially increased the identification of new genetic variants and hence the necessity of accurate variant interpretation. In 2015, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology proposed new variant interpretation guidelines. Gene-specific characteristics were, however, not considered, sometimes leading to inconsistent variant interpretation. METHODS To allow a more uniform interpretation of variants in the FBN1 (fibrillin-1) gene, causing Marfan syndrome, we tailored these guidelines to this gene and disease. We adapted 15 of the 28 general criteria and classified 713 FBN1 variants previously identified in our laboratory as causal mutation or variant of uncertain significance according to these adapted guidelines. We then compared the agreement between previous methods and the adapted American College of Medical Genetics and Genomics and the Association for Molecular Pathology criteria. RESULTS Agreement between the methods was 86.4% (K-alpha, 0.6). Application of the tailored guidelines resulted in an increased number of variants of uncertain significance (14.5% to 24.2%). Of the 85 variants that were downscaled to likely benign or variant of uncertain significance, 59.7% were missense variants outside a well-established functional site. Available clinical- or segregation data, necessary to further classify these types of variants, were in many cases insufficient to aid the classification. CONCLUSIONS Our study shows that classification of variants remains challenging and may change over time. Currently, a higher level of evidence is necessary to classify a variant as pathogenic. Gene-specific guidelines may be useful to allow a more precise and uniform interpretation of the variants to accurately support clinical decision-making.
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Affiliation(s)
- Laura Muiño-Mosquera
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.) .,Division of Pediatric Cardiology (L.M.-M.)
| | - Felke Steijns
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.)
| | - Tjorven Audenaert
- Department of Cardiology (T.A., J.D.B.), Ghent University Hospital, Belgium
| | - Ilse Meerschaut
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.)
| | - Anne De Paepe
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.)
| | - Wouter Steyaert
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.)
| | - Sofie Symoens
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.)
| | - Paul Coucke
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.)
| | - Bert Callewaert
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.)
| | - Marjolijn Renard
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.)
| | - Julie De Backer
- Center for Medical Genetics (L.M.-M., F.S., I.M., A.D.P., W.S., S.S., P.C., B.C., M.R., J.D.B.).,Department of Cardiology (T.A., J.D.B.), Ghent University Hospital, Belgium
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Abstract
With rapid advances in genetics and genomics, the commercialization and access to new applications has become more widespread and omnipresent throughout biomedical research. Thus, increasingly, more patients will have personal genomic information they may share with primary care providers (PCPs) to better understand the clinical significance of the data. To be able to respond to patient inquiries about genomic data, variant interpretation, disease risk, and other issues, PCPs will need to be able to increase or refresh their awareness about genetics and genomics, and identify reliable resources to use or refer patients. While provider educational efforts have increased, with the rapid advances in the field, ongoing efforts will be needed to prepare PCPs to manage patient needs, integrate results into care, and refer as indicated.
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Affiliation(s)
- Susanne B Haga
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, 27708, USA.
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50
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Ahmad F, McNally EM, Ackerman MJ, Baty LC, Day SM, Kullo IJ, Madueme PC, Maron MS, Martinez MW, Salberg L, Taylor MR, Wilcox JE. Establishment of Specialized Clinical Cardiovascular Genetics Programs: Recognizing the Need and Meeting Standards: A Scientific Statement From the American Heart Association. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2019; 12:e000054. [DOI: 10.1161/hcg.0000000000000054] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Cardiovascular genetics is a rapidly evolving subspecialty within cardiovascular medicine, and its growth is attributed to advances in genome sequencing and genetic testing and the expanding understanding of the genetic basis of multiple cardiac conditions, including arrhythmias (channelopathies), heart failure (cardiomyopathies), lipid disorders, cardiac complications of neuromuscular conditions, and vascular disease, including aortopathies. There have also been great advances in clinical diagnostic methods, as well as in therapies to ameliorate symptoms, slow progression of disease, and mitigate the risk of adverse outcomes. Emerging challenges include interpretation of genetic test results and the evaluation, counseling, and management of genetically at-risk family members who have inherited pathogenic variants but do not yet manifest disease. With these advances and challenges, there is a need for specialized programs combining both cardiovascular medicine and genetics expertise. The integration of clinical cardiovascular findings, including those obtained from physical examination, imaging, and functional assessment, with genetic information allows for improved diagnosis, prognostication, and cascade family testing to identify and to manage risk, and in some cases to provide genotype-specific therapy. This emerging subspecialty may ultimately require a new cardiovascular subspecialist, the genetic cardiologist, equipped with these combined skills, to permit interpretation of genetic variation within the context of phenotype and to extend the utility of genetic testing. This scientific statement outlines current best practices for delivering cardiovascular genetic evaluation and care in both the pediatric and the adult settings, with a focus on team member expertise and conditions that most benefit from genetic evaluation.
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