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Zhou Y, Lauschke VM. Next-generation sequencing in pharmacogenomics - fit for clinical decision support? Expert Rev Clin Pharmacol 2024; 17:213-223. [PMID: 38247431 DOI: 10.1080/17512433.2024.2307418] [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: 10/16/2023] [Accepted: 01/16/2024] [Indexed: 01/23/2024]
Abstract
INTRODUCTION The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial. AREAS COVERED We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing. EXPERT OPINION While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.
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Affiliation(s)
- Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
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2
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Clinical implementation of drug metabolizing gene-based therapeutic interventions worldwide. Hum Genet 2021; 141:1137-1157. [PMID: 34599365 DOI: 10.1007/s00439-021-02369-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/09/2021] [Indexed: 02/05/2023]
Abstract
Over the last few years, the field of pharmacogenomics has gained considerable momentum. The advances of new genomics and bioinformatics technologies propelled pharmacogenomics towards its implementation in the clinical setting. Since 2007, and especially the last-5 years, many studies have focused on the clinical implementation of pharmacogenomics while identifying obstacles and proposed strategies and approaches for overcoming them in the real world of primary care as well as outpatients and inpatients clinics. Here, we outline the recent pharmacogenomics clinical implementation projects and provide details of the study designs, including the most predominant and innovative, as well as clinical studies worldwide that focus on outpatients and inpatient clinics, and primary care. According to these studies, pharmacogenomics holds promise for improving patients' health in terms of efficacy and toxicity, as well as in their overall quality of life, while simultaneously can contribute to the minimization of healthcare expenditure.
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3
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Lo YH, Cheng HC, Hsiung CN, Yang SL, Wang HY, Peng CW, Chen CY, Lin KP, Kang ML, Chen CH, Chu HW, Lin CF, Lee MH, Liu Q, Satta Y, Lin CJ, Lin M, Chaw SM, Loo JH, Shen CY, Ko WY. Detecting Genetic Ancestry and Adaptation in the Taiwanese Han People. Mol Biol Evol 2021; 38:4149-4165. [PMID: 33170928 PMCID: PMC8476137 DOI: 10.1093/molbev/msaa276] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
The Taiwanese people are composed of diverse indigenous populations and the Taiwanese Han. About 95% of the Taiwanese identify themselves as Taiwanese Han, but this may not be a homogeneous population because they migrated to the island from various regions of continental East Asia over a period of 400 years. Little is known about the underlying patterns of genetic ancestry, population admixture, and evolutionary adaptation in the Taiwanese Han people. Here, we analyzed the whole-genome single-nucleotide polymorphism genotyping data from 14,401 individuals of Taiwanese Han collected by the Taiwan Biobank and the whole-genome sequencing data for a subset of 772 people. We detected four major genetic ancestries with distinct geographic distributions (i.e., Northern, Southeastern, Japonic, and Island Southeast Asian ancestries) and signatures of population mixture contributing to the genomes of Taiwanese Han. We further scanned for signatures of positive natural selection that caused unusually long-range haplotypes and elevations of hitchhiked variants. As a result, we identified 16 candidate loci in which selection signals can be unambiguously localized at five single genes: CTNNA2, LRP1B, CSNK1G3, ASTN2, and NEO1. Statistical associations were examined in 16 metabolic-related traits to further elucidate the functional effects of each candidate gene. All five genes appear to have pleiotropic connections to various types of disease susceptibility and significant associations with at least one metabolic-related trait. Together, our results provide critical insights for understanding the evolutionary history and adaption of the Taiwanese Han population.
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Affiliation(s)
- Yun-Hua Lo
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Hsueh-Chien Cheng
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chia-Ni Hsiung
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Show-Ling Yang
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Han-Yu Wang
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chia-Wei Peng
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chun-Yu Chen
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Kung-Ping Lin
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Mei-Ling Kang
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Hou-Wei Chu
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | | | - Mei-Hsuan Lee
- Institute of Clinical Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Quintin Liu
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan
| | - Yoko Satta
- Department of Evolutionary Studies of Biosystems, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan
| | - Cheng-Jui Lin
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Marie Lin
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Shu-Miaw Chaw
- Biodiversity Research Center, Academia Sinica, Taipei City, Taiwan
| | - Jun-Hun Loo
- Molecular Anthropology and Transfusion Medicine Research Laboratory, Mackay Memorial Hospital, Taipei, Taiwan
| | - Chen-Yang Shen
- Institute of Biomedical Sciences, Academia Sinica, Taipei City, Taiwan
| | - Wen-Ya Ko
- Faculty of Life Sciences and Institute of Genome Sciences, National Yang-Ming University, Taipei, Taiwan
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4
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Tafazoli A, Guchelaar HJ, Miltyk W, Kretowski AJ, Swen JJ. Applying Next-Generation Sequencing Platforms for Pharmacogenomic Testing in Clinical Practice. Front Pharmacol 2021; 12:693453. [PMID: 34512329 PMCID: PMC8424415 DOI: 10.3389/fphar.2021.693453] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 07/26/2021] [Indexed: 11/13/2022] Open
Abstract
Pharmacogenomics (PGx) studies the use of genetic data to optimize drug therapy. Numerous clinical centers have commenced implementing pharmacogenetic tests in clinical routines. Next-generation sequencing (NGS) technologies are emerging as a more comprehensive and time- and cost-effective approach in PGx. This review presents the main considerations for applying NGS in guiding drug treatment in clinical practice. It discusses both the advantages and the challenges of implementing NGS-based tests in PGx. Moreover, the limitations of each NGS platform are revealed, and the solutions for setting up and management of these technologies in clinical practice are addressed.
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Affiliation(s)
- Alireza Tafazoli
- Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy with the Division of Laboratory Medicine, Medical University of Bialystok, Bialystok, Poland
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
- Leiden Network of Personalized Therapeutics, Leiden, Netherlands
| | - Wojciech Miltyk
- Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy with the Division of Laboratory Medicine, Medical University of Bialystok, Bialystok, Poland
| | - Adam J. Kretowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok, Poland
| | - Jesse J. Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
- Leiden Network of Personalized Therapeutics, Leiden, Netherlands
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6
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Technologies for Pharmacogenomics: A Review. Genes (Basel) 2020; 11:genes11121456. [PMID: 33291630 PMCID: PMC7761897 DOI: 10.3390/genes11121456] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 11/30/2020] [Accepted: 12/02/2020] [Indexed: 12/11/2022] Open
Abstract
The continuous development of new genotyping technologies requires awareness of their potential advantages and limitations concerning utility for pharmacogenomics (PGx). In this review, we provide an overview of technologies that can be applied in PGx research and clinical practice. Most commonly used are single nucleotide variant (SNV) panels which contain a pre-selected panel of genetic variants. SNV panels offer a short turnaround time and straightforward interpretation, making them suitable for clinical practice. However, they are limited in their ability to assess rare and structural variants. Next-generation sequencing (NGS) and long-read sequencing are promising technologies for the field of PGx research. Both NGS and long-read sequencing often provide more data and more options with regard to deciphering structural and rare variants compared to SNV panels-in particular, in regard to the number of variants that can be identified, as well as the option for haplotype phasing. Nonetheless, while useful for research, not all sequencing data can be applied to clinical practice yet. Ultimately, selecting the right technology is not a matter of fact but a matter of choosing the right technique for the right problem.
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Scott SA, Scott ER, Seki Y, Chen AJ, Wallsten R, Owusu Obeng A, Botton MR, Cody N, Shi H, Zhao G, Brake P, Nicoletti P, Yang Y, Delio M, Shi L, Kornreich R, Schadt EE, Edelmann L. Development and Analytical Validation of a 29 Gene Clinical Pharmacogenetic Genotyping Panel: Multi-Ethnic Allele and Copy Number Variant Detection. Clin Transl Sci 2020; 14:204-213. [PMID: 32931151 PMCID: PMC7877843 DOI: 10.1111/cts.12844] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 06/16/2020] [Indexed: 12/12/2022] Open
Abstract
To develop a novel pharmacogenetic genotyping panel, a multidisciplinary team evaluated available evidence and selected 29 genes implicated in interindividual drug response variability, including 130 sequence variants and additional copy number variants (CNVs). Of the 29 genes, 11 had guidelines published by the Clinical Pharmacogenetics Implementation Consortium. Targeted genotyping and CNV interrogation were accomplished by multiplex single‐base extension using the MassARRAY platform (Agena Biosciences) and multiplex ligation‐dependent probe amplification (MRC Holland), respectively. Analytical validation of the panel was accomplished by a strategic combination of > 500 independent tests performed on 170 unique reference material DNA samples, which included sequence variant and CNV accuracy, reproducibility, and specimen (blood, saliva, and buccal swab) controls. Among the accuracy controls were 32 samples from the 1000 Genomes Project that were selected based on their enrichment of sequence variants included in the pharmacogenetic panel (VarCover.org). Coupled with publicly available samples from the Genetic Testing Reference Materials Coordination Program (GeT‐RM), accuracy validation material was available for the majority (77%) of interrogated sequence variants (100% with average allele frequencies > 0.1%), as well as additional structural alleles with unique copy number signatures (e.g., CYP2D6*5, *13, *36, *68; CYP2B6*29; and CYP2C19*36). Accuracy and reproducibility for both genotyping and copy number were > 99.9%, indicating that the optimized panel platforms were precise and robust. Importantly, multi‐ethnic allele frequencies of the interrogated variants indicate that the vast majority of the general population carries at least one of these clinically relevant pharmacogenetic variants, supporting the implementation of this panel for pharmacogenetic research and/or clinical implementation programs.
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Affiliation(s)
- Stuart A Scott
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Erick R Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | | | | | - Aniwaa Owusu Obeng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mariana R Botton
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Neal Cody
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | | | | | - Paola Nicoletti
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Yao Yang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Lisong Shi
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ruth Kornreich
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Eric E Schadt
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Lisa Edelmann
- Sema4, Stamford, Connecticut, USA.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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8
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Hippman C, Nislow C. Pharmacogenomic Testing: Clinical Evidence and Implementation Challenges. J Pers Med 2019; 9:jpm9030040. [PMID: 31394823 PMCID: PMC6789586 DOI: 10.3390/jpm9030040] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 07/23/2019] [Accepted: 08/02/2019] [Indexed: 12/25/2022] Open
Abstract
Pharmacogenomics can enhance patient care by enabling treatments tailored to genetic make-up and lowering risk of serious adverse events. As of June 2019, there are 132 pharmacogenomic dosing guidelines for 99 drugs and pharmacogenomic information is included in 309 medication labels. Recently, the technology for identifying individual-specific genetic variants (genotyping) has become more accessible. Next generation sequencing (NGS) is a cost-effective option for genotyping patients at many pharmacogenomic loci simultaneously, and guidelines for implementation of these data are available from organizations such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG). NGS and related technologies are increasing knowledge in the research sphere, yet rates of genomic literacy remain low, resulting in a widening gap in knowledge translation to the patient. Multidisciplinary teams—including physicians, nurses, genetic counsellors, and pharmacists—will need to combine their expertise to deliver optimal pharmacogenomically-informed care.
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Affiliation(s)
- Catriona Hippman
- Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, BC, V6T 2A1, Canada.
- BC Mental Health and Addictions Research Institute, 3rd Floor - 938 West 28th Avenue, Vancouver, BC, V5Z 4H4, Canada.
| | - Corey Nislow
- Faculty of Pharmaceutical Sciences, University of British Columbia, 6619-2405 Wesbrook Mall, Vancouver, BC, V6T 1Z3, Canada.
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Schwarz UI, Gulilat M, Kim RB. The Role of Next-Generation Sequencing in Pharmacogenetics and Pharmacogenomics. Cold Spring Harb Perspect Med 2019; 9:cshperspect.a033027. [PMID: 29844222 DOI: 10.1101/cshperspect.a033027] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Inherited genetic variations in pharmacogenetic loci are widely acknowledged as important determinants of phenotypic differences in drug response, and may be actionable in the clinic. However, recent studies suggest that a considerable number of novel rare variants in pharmacogenes likely contribute to a still unexplained fraction of the observed interindividual variability. Next-generation sequencing (NGS) represents a rapid, relatively inexpensive, large-scale DNA sequencing technology with potential relevance as a comprehensive pharmacogenetic genotyping platform to identify genetic variation related to drug therapy. However, many obstacles remain before the clinical use of NGS-based test results, including technical challenges, functional interpretation, and strict requirements for diagnostic tests. Advanced computational analyses, high-throughput screening methodologies, and generation of shared resources with cell-based and clinical information will facilitate the integration of NGS data into candidate genotyping approaches, likely enhancing future drug phenotype predictions in patients.
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Affiliation(s)
- Ute I Schwarz
- Division of Clinical Pharmacology, Department of Medicine, Western University, London, Ontario N6A 5A5, Canada.,Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5A5, Canada
| | - Markus Gulilat
- Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5A5, Canada
| | - Richard B Kim
- Division of Clinical Pharmacology, Department of Medicine, Western University, London, Ontario N6A 5A5, Canada.,Department of Physiology and Pharmacology, Western University, London, Ontario N6A 5A5, Canada
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10
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Qiao W, Martis S, Mendiratta G, Shi L, Botton MR, Yang Y, Gaedigk A, Vijzelaar R, Edelmann L, Kornreich R, Desnick RJ, Scott SA. Integrated CYP2D6 interrogation for multiethnic copy number and tandem allele detection. Pharmacogenomics 2018; 20:9-20. [PMID: 30730286 DOI: 10.2217/pgs-2018-0135] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
AIM To comprehensively interrogate CYP2D6 by integrating genotyping, copy number analysis and novel strategies to identify CYP2D6*36 and characterize CYP2D6 duplications. METHODS Genotyping of 16 CYP2D6 alleles, multiplex ligation-dependent probe amplification (MLPA) and CYP2D6*36 and duplication allele-specific genotyping were performed on 427 African-American, Asian, Caucasian, Hispanic, and Ashkenazi Jewish individuals. RESULTS A novel PCR strategy determined that almost half of all CYP2D6*10 (100C>T) alleles are actually *36 (isolated or in tandem with *10) and all identified duplication alleles were characterized. Integrated results from all testing platforms enabled the refinement of genotype frequencies across all studied populations. CONCLUSION The polymorphic CYP2D6 gene requires comprehensive interrogation to characterize allelic variation across ethnicities, which was enabled in this study by integrating multiplexed genotyping, MLPA copy number analysis, novel PCR strategies and duplication allele-specific genotyping.
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Affiliation(s)
- Wanqiong Qiao
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Suparna Martis
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Geetu Mendiratta
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Lisong Shi
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Mariana R Botton
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Yao Yang
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Andrea Gaedigk
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, MO 64108, USA
| | - Raymon Vijzelaar
- MRC-Holland, Willem Schoutenstraat 6, Amsterdam, The Netherlands
| | - Lisa Edelmann
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Ruth Kornreich
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Robert J Desnick
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Stuart A Scott
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
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Haque MM, Kowtal P, Sarin R. Identification and characterization of TP53 gene Allele Dropout in Li-Fraumeni syndrome and Oral cancer cohorts. Sci Rep 2018; 8:11705. [PMID: 30076369 PMCID: PMC6076284 DOI: 10.1038/s41598-018-30238-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 07/21/2018] [Indexed: 12/20/2022] Open
Abstract
Allele Drop out (ADO) arising from non-amplification of one allele may produce false negative result and impact clinical management. In cancer, germline and somatic genetic analysis is being increasingly used but the prevalence, nature and implications of ADO has not been studied in any cohort. In a cohort of 290 Li Fraumeni/Li Fraumeni Like Syndrome cases undergoing TP53 genetic testing, of the 69 pathogenic mutations identified so far, 5 were initially missed and 4 were misgenotyped as homozygous mutation due to germline ADO. Of the 9 germline ADOs, 8 were sequence dependent, arising from a polymorphism (rs12951053) in the primer annealing region of exon 7. Of 35 somatic TP53 variants identified by exome sequencing in 50 oral cancer tissues registered under International Cancer Genome Consortium (ICGC), as a result of ADO, 4 were not detectable and 6 were not called as variant on Sanger Sequencing due to low peak height. High prevalence of germline and somatic ADO in the most frequently mutated cancer gene TP53, highlights the need for systematic evaluation of ADO prevalence and causes in clinically important cancer genes. False negative result for high penetrance germline mutations or actionable somatic mutations in oncogenes could have major clinical implications.
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Affiliation(s)
- Mohammed Moquitul Haque
- Sarin Lab, Advanced Centre for Treatment Research and Education in Cancer-Tata Memorial Centre, Kharghar, Navi Mumbai, Maharashtra, India.,Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai, 400085, Maharashtra, India
| | - Pradnya Kowtal
- Sarin Lab, Advanced Centre for Treatment Research and Education in Cancer-Tata Memorial Centre, Kharghar, Navi Mumbai, Maharashtra, India.,Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai, 400085, Maharashtra, India
| | - Rajiv Sarin
- Sarin Lab, Advanced Centre for Treatment Research and Education in Cancer-Tata Memorial Centre, Kharghar, Navi Mumbai, Maharashtra, India. .,Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai, 400085, Maharashtra, India. .,Cancer Genetics Clinic, Tata Memorial Hospital, Tata Memorial Centre, Parel, Mumbai, 400012, Maharashtra, India.
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12
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Zhang X, Lin G, Tan L, Li J. Current progress of tacrolimus dosing in solid organ transplant recipients: Pharmacogenetic considerations. Biomed Pharmacother 2018; 102:107-114. [DOI: 10.1016/j.biopha.2018.03.054] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Revised: 02/27/2018] [Accepted: 03/09/2018] [Indexed: 12/11/2022] Open
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13
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Scott SA, Owusu Obeng A, Botton MR, Yang Y, Scott ER, Ellis SB, Wallsten R, Kaszemacher T, Zhou X, Chen R, Nicoletti P, Naik H, Kenny EE, Vega A, Waite E, Diaz GA, Dudley J, Halperin JL, Edelmann L, Kasarskis A, Hulot JS, Peter I, Bottinger EP, Hirschhorn K, Sklar P, Cho JH, Desnick RJ, Schadt EE. Institutional profile: translational pharmacogenomics at the Icahn School of Medicine at Mount Sinai. Pharmacogenomics 2017; 18:1381-1386. [PMID: 28982267 DOI: 10.2217/pgs-2017-0137] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
For almost 50 years, the Icahn School of Medicine at Mount Sinai has continually invested in genetics and genomics, facilitating a healthy ecosystem that provides widespread support for the ongoing programs in translational pharmacogenomics. These programs can be broadly cataloged into discovery, education, clinical implementation and testing, which are collaboratively accomplished by multiple departments, institutes, laboratories, companies and colleagues. Focus areas have included drug response association studies and allele discovery, multiethnic pharmacogenomics, personalized genotyping and survey-based education programs, pre-emptive clinical testing implementation and novel assay development. This overview summarizes the current state of translational pharmacogenomics at Mount Sinai, including a future outlook on the forthcoming expansions in overall support, research and clinical programs, genomic technology infrastructure and the participating faculty.
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Affiliation(s)
- Stuart A Scott
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA.,The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Department of Pharmacy, the Mount Sinai Medical Center, NY 10029, USA
| | - Mariana R Botton
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Yao Yang
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Erick R Scott
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Stephen B Ellis
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | | | - Tom Kaszemacher
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Xiang Zhou
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Rong Chen
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Paola Nicoletti
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Hetanshi Naik
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Eimear E Kenny
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Aida Vega
- Mount Sinai Faculty Practice Associates Primary Care Program, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Eva Waite
- Mount Sinai Faculty Practice Associates Primary Care Program, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - George A Diaz
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Joel Dudley
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Institute for Next Generation Healthcare, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Jonathan L Halperin
- The Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Lisa Edelmann
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Andrew Kasarskis
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Jean-Sébastien Hulot
- Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sorbonne Universités, UPMC Univ Paris 06, Faculty of Medicine, UMRS_1166 ICAN, Institute of Cardiometabolism & Nutrition, AP-HP, Pitié-Salpêtrière Hospital, Institute of Cardiology, Paris, France
| | - Inga Peter
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Erwin P Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Berlin Institute of Health, Berlin, Germany
| | - Kurt Hirschhorn
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Pamela Sklar
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Department of Psychiatry & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, NY 10029, USA
| | - Judy H Cho
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Department of Medicine, Division of Gastroenterology, Icahn School of Medicine at Mount Sinai, NY 10029 USA
| | - Robert J Desnick
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA
| | - Eric E Schadt
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT 06902, USA.,Icahn Institute for Genomics & Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY 10029, USA
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