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Zhao K, Shen X, Liu H, Lin Z, Li J, Chen S, Liu F, Huang K, Cao J, Liu X, Shen C, Yu L, Zhao Y, Zhao L, Li Y, Hu D, Huang J, Lu X, Gu D. Somatic and Germline Variants and Coronary Heart Disease in a Chinese Population. JAMA Cardiol 2024; 9:233-242. [PMID: 38198131 PMCID: PMC10782380 DOI: 10.1001/jamacardio.2023.5095] [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: 06/30/2023] [Accepted: 10/03/2023] [Indexed: 01/11/2024]
Abstract
Importance The genetic basis of coronary heart disease (CHD) has expanded from a germline to somatic genome, including clonal hematopoiesis of indeterminate potential (CHIP). How CHIP confers CHD risk in East Asian individuals, especially those with small clones (variant allele fraction [VAF] 0.5%-2%) and different genetic backgrounds, was completely unknown. Objective To investigate the CHIP profile in a general Chinese cohort by deep sequencing and further explore the association between CHIP and incident CHD considering germline predisposition. Design, Setting, and Participants This cohort study used data from 3 prospective cohorts in the project Prediction for Atherosclerotic Cardiovascular Disease Risk in China. Participants without cardiovascular disease or cancer at baseline were enrolled in 2001 and 2008 and had a median follow-up of 12.17 years extending into 2021. Exposures CHIP mutations were detected by targeted sequencing (mean depth, 916×). A predefined CHD polygenic risk score (PRS) comprising 531 variants was used to evaluate germline predisposition. Main Outcomes and Measures The main outcome was first incident CHD. Results Among 6181 participants, the median (IQR) age was 53.83 years (45.35-62.39 years); 3082 participants (49.9%) were female, and 3099 (50.1%) were male. A total of 1100 individuals (17.80%) harbored 1372 CHIP mutations at baseline. CHIP was independently associated with incident CHD (hazard ratio [HR], 1.42; 95% CI, 1.18-1.72; P = 2.82 × 10-4) and presented a risk gradient with increasing VAF (P = 3.98 × 10-3 for trend). Notably, individuals with small clones, nearly half of CHIP carriers, also demonstrated a higher CHD risk compared with non-CHIP carriers (HR, 1.33; 95% CI, 1.02-1.74; P = .03) and were 4 years younger than those with VAF of 2% or greater (median age, 58.52 vs 62.70 years). Heightened CHD risk was not observed among CHIP carriers with low PRS (HR, 1.02; 95% CI, 0.64-1.64; P = .92), while high PRS and CHIP jointly contributed a 2.23-fold increase in risk (95% CI, 1.51-3.29; P = 6.29 × 10-5) compared with non-CHIP carriers with low PRS. Interestingly, the diversity in CHIP-related CHD risk within each PRS group was substantially diminished when removing variants in the inflammatory pathway from the PRS. Conclusions This study revealed that elevated CHD risk attributed to CHIP was nonnegligible even for small clones. Inflammation genes involved in CHD could aggravate or abrogate CHIP-related CHD risk.
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Affiliation(s)
- Kun Zhao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xuxiang Shen
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongwei Liu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhennan Lin
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianxin Li
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shufeng Chen
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fangchao Liu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Keyong Huang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie Cao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaoqing Liu
- Division of Epidemiology, Guangdong Provincial People’s Hospital and Cardiovascular Institute, Guangzhou, China
| | - Chong Shen
- Department of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ling Yu
- Department of Cardiology, Fujian Provincial Hospital, Fuzhou, China
| | - Yingxin Zhao
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China
| | - Liancheng Zhao
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ying Li
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongsheng Hu
- Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, China
| | - Jiangfeng Huang
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiangfeng Lu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dongfeng Gu
- Key Laboratory of Cardiovascular Epidemiology & Department of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- School of Public Health and Emergency Management, School of Medicine, Southern University of Science and Technology, Shenzhen, China
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Bridgers J, Alexander K, Karsan A. Operationalizing Quality Assurance for Clinical Illumina Somatic Next-Generation Sequencing Pipelines. J Mol Diagn 2024; 26:96-105. [PMID: 38086510 DOI: 10.1016/j.jmoldx.2023.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 09/01/2023] [Accepted: 11/07/2023] [Indexed: 01/26/2024] Open
Abstract
Quality assurance (QA) is essential for precision oncology workflows, in particular in the clinical setting. However, because of numerous variations in laboratory and bioinformatics pipelines, QA practices remain non-standardized, are often ad hoc, and are lacking longitudinal tracking. A selected review of existing software was performed for quality control of Illumina next-generation sequencing data, focusing specifically on generalizable tools that can be integrated into any bioinformatics workflow to easily develop a QA workflow with longitudinal tracking. Although all implementations need to be integrated, validated, and iterated upon to suit individual operations, providing a base suite of options will enable better validation and use of QA in clinical somatic mutation testing for workflows using Illumina next-generation sequencing and beyond.
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Affiliation(s)
- Joshua Bridgers
- Genome Sciences Centre, Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
| | - Kenyon Alexander
- Genome Sciences Centre, Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Aly Karsan
- Genome Sciences Centre, Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
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3
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Wang H, Zhao L, Yang L, Ge M, Yang X, Gao Z, Cun Y, Xiao F, Kong Q. Scrutiny of genome-wide somatic mutation profiles in centenarians identifies the key genomic regions for human longevity. Aging Cell 2024; 23:e13916. [PMID: 37400997 PMCID: PMC10776117 DOI: 10.1111/acel.13916] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 06/14/2023] [Accepted: 06/14/2023] [Indexed: 07/05/2023] Open
Abstract
Somatic mutations accumulate with age and are associated closely with human health, their characterization in longevity cohorts remains largely unknown. Here, by analyzing whole genome somatic mutation profiles in 73 centenarians and 51 younger controls in China, we found that centenarian genomes are characterized by a markedly skewed distribution of somatic mutations, with many genomic regions being specifically conserved but displaying a high function potential. This, together with the observed more efficient DNA repair ability in the long-lived individuals, supports the existence of key genomic regions for human survival during aging, with their integrity being of essential to human longevity.
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Affiliation(s)
- Hao‐Tian Wang
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesKunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Long Zhao
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesKunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
- Kunming College of Life ScienceUniversity of Chinese Academy of SciencesKunmingChina
| | - Li‐Qin Yang
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesKunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Ming‐Xia Ge
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesKunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
- Kunming College of Life ScienceUniversity of Chinese Academy of SciencesKunmingChina
| | - Xing‐Li Yang
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesKunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
- Kunming College of Life ScienceUniversity of Chinese Academy of SciencesKunmingChina
| | - Zong‐Liang Gao
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesKunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
- Kunming College of Life ScienceUniversity of Chinese Academy of SciencesKunmingChina
| | - Yu‐Peng Cun
- Pediatric Research Institute/Ministry of Education Key Laboratory of Child Development and Disorders/National Clinical Research Center for Child Health and DisordersChildren's Hospital of Chongqing Medical UniversityChongqingChina
| | - Fu‐Hui Xiao
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesKunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
| | - Qing‐Peng Kong
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common DiseasesKunming Institute of Zoology, Chinese Academy of SciencesKunmingChina
- CAS Center for Excellence in Animal Evolution and GeneticsChinese Academy of SciencesKunmingChina
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O’Sullivan B, Seoighe C. Comprehensive and realistic simulation of tumour genomic sequencing data. NAR Cancer 2023; 5:zcad051. [PMID: 37746635 PMCID: PMC10516706 DOI: 10.1093/narcan/zcad051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 08/25/2023] [Accepted: 09/08/2023] [Indexed: 09/26/2023] Open
Abstract
Accurate identification of somatic mutations and allele frequencies in cancer has critical research and clinical applications. Several computational tools have been developed for this purpose but, in the absence of comprehensive 'ground truth' data, assessing the accuracy of these methods is challenging. We created a computational framework to simulate tumour and matched normal sequencing data for which the source of all loci that contain non-reference bases is known, based on a phased, personalized genome. Unlike existing methods, we account for sampling errors inherent in the sequencing process. Using this framework, we assess accuracy and biases in inferred mutations and their frequencies in an established somatic mutation calling pipeline. We demonstrate bias in existing methods of mutant allele frequency estimation and show, for the first time, the observed mutation frequency spectrum corresponding to a theoretical model of tumour evolution. We highlight the impact of quality filters on detection sensitivity of clinically actionable variants and provide definitive assessment of false positive and false negative mutation calls. Our simulation framework provides an improved means to assess the accuracy of somatic mutation calling pipelines and a detailed picture of the effects of technical parameters and experimental factors on somatic mutation calling in cancer samples.
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Affiliation(s)
- Brian O’Sullivan
- School of Mathematical and Statistical Sciences, University of Galway, University Road, Galway H91 TK33, Ireland
| | - Cathal Seoighe
- School of Mathematical and Statistical Sciences, University of Galway, University Road, Galway H91 TK33, Ireland
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Wienert B, Cromer MK. CRISPR nuclease off-target activity and mitigation strategies. Front Genome Ed 2022; 4:1050507. [PMID: 36439866 PMCID: PMC9685173 DOI: 10.3389/fgeed.2022.1050507] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 10/26/2022] [Indexed: 11/11/2022] Open
Abstract
The discovery of CRISPR has allowed site-specific genomic modification to become a reality and this technology is now being applied in a number of human clinical trials. While this technology has demonstrated impressive efficacy in the clinic to date, there remains the potential for unintended on- and off-target effects of CRISPR nuclease activity. A variety of in silico-based prediction tools and empirically derived experimental methods have been developed to identify the most common unintended effect-small insertions and deletions at genomic sites with homology to the guide RNA. However, large-scale aberrations have recently been reported such as translocations, inversions, deletions, and even chromothripsis. These are more difficult to detect using current workflows indicating a major unmet need in the field. In this review we summarize potential sequencing-based solutions that may be able to detect these large-scale effects even at low frequencies of occurrence. In addition, many of the current clinical trials using CRISPR involve ex vivo isolation of a patient's own stem cells, modification, and re-transplantation. However, there is growing interest in direct, in vivo delivery of genome editing tools. While this strategy has the potential to address disease in cell types that are not amenable to ex vivo manipulation, in vivo editing has only one desired outcome-on-target editing in the cell type of interest. CRISPR activity in unintended cell types (both on- and off-target) is therefore a major safety as well as ethical concern in tissues that could enable germline transmission. In this review, we have summarized the strengths and weaknesses of current editing and delivery tools and potential improvements to off-target and off-tissue CRISPR activity detection. We have also outlined potential mitigation strategies that will ensure that the safety of CRISPR keeps pace with efficacy, a necessary requirement if this technology is to realize its full translational potential.
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Affiliation(s)
- Beeke Wienert
- Graphite Bio, Inc., South San Francisco, CA, United States
| | - M. Kyle Cromer
- Department of Surgery, University of California, San Francisco, San Francisco, CA, United States
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States
- Eli and Edythe Broad Center for Regeneration Medicine, University of California, San Francisco, San Francisco, CA, United States
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Mavridis K, Papapostolou KM, Ilias A, Michaelidou K, Stavrakaki M, Roditakis E, Tsagkarakou A, Bass C, Vontas J. Next-generation molecular diagnostics (TaqMan qPCR and ddPCR) for monitoring insecticide resistance in Bemisia tabaci. PEST MANAGEMENT SCIENCE 2022; 78:4994-5001. [PMID: 36054028 DOI: 10.1002/ps.7122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/12/2022] [Accepted: 08/10/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Insecticide resistance has developed in several populations of the whitefly Bemisia tabaci worldwide and threatens to compromise the efficacy of chemical control. The molecular mechanisms underpinning resistance have been characterized and markers associated with the trait have been identified, allowing the development of diagnostics for individual insects. RESULTS TaqMan and Droplet Digital PCR (ddPCR) assays were developed and validated, in individual and pooled whitefly samples, respectively, for the following target-site mutations: the acetylcholinesterase (ace1) F331W mutation conferring organophosphate-resistance; the voltage-gated sodium channel (vgsc) mutations L925I and T929V conferring pyrethroid-resistance; and the acetyl-CoA carboxylase (acc) A2083V mutation conferring ketoenol-resistance. The ddPCR's limit of detection (LoD) was <0.2% (i.e. detection of one heterozygote whitefly in a pool of 249 wild-type individuals). The assays were applied in 11 B. tabaci field populations from four locations in Crete, Greece. The F331W mutation was detected to be fixed or close to fixation in eight of 11 B. tabaci populations, and at lower frequency in the remaining ones. The pyrethroid-resistance mutations were detected at very high frequencies. The A2083V spiromesifen resistance mutation was detected in eight of 11 populations (frequencies = 6.16-89.56%). Spiromesifen phenotypic resistance monitoring showed that the populations tested had variable levels of resistance, ranging from full susceptibility to high resistance. A strong spiromesifen-resistance phenotype-genotype (A2083V) correlation (rs = -0.839, P = 0.002) was observed confirming the ddPCR diagnostic value. CONCLUSION The ddPCR diagnostics developed in this study are a valuable tool to support evidence-based rational use of insecticides and resistance management strategies. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Konstantinos Mavridis
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Heraklion, Greece
- Pesticide Science Laboratory, Department of Crop Science, Agricultural University of Athens, Athens, Greece
| | - Kyriaki Maria Papapostolou
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Heraklion, Greece
- Department of Biology, University of Crete, Heraklion, Greece
| | - Aris Ilias
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Heraklion, Greece
| | - Kleita Michaelidou
- Laboratory of Translational Oncology, School of Medicine, University of Crete, Heraklion, Greece
| | - Marianna Stavrakaki
- Pesticide Science Laboratory, Department of Crop Science, Agricultural University of Athens, Athens, Greece
- Institute of Olive Tree, Subtropical Crops and Viticulture, Hellenic Agricultural Organization "DIMITRA", Heraklion, Greece
| | - Emmanouil Roditakis
- Institute of Olive Tree, Subtropical Crops and Viticulture, Hellenic Agricultural Organization "DIMITRA", Heraklion, Greece
- Hellenic Mediterranean University, Department of Agriculture, School of Agricultural Sciences, Heraklion, Greece
| | - Anastasia Tsagkarakou
- Institute of Olive Tree, Subtropical Crops and Viticulture, Hellenic Agricultural Organization "DIMITRA", Heraklion, Greece
| | - Chris Bass
- College of Life and Environmental Sciences, Biosciences, University of Exeter, Penryn Campus, Cornwall, UK
| | - John Vontas
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Heraklion, Greece
- Pesticide Science Laboratory, Department of Crop Science, Agricultural University of Athens, Athens, Greece
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Akkari YM, Baughn LB, Dubuc AM, Smith AC, Mallo M, Dal Cin P, Diez Campelo M, Gallego MS, Granada Font I, Haase DT, Schlegelberger B, Slavutsky I, Mecucci C, Levine RL, Hasserjian RP, Solé F, Levy B, Xu X. Guiding the global evolution of cytogenetic testing for hematologic malignancies. Blood 2022; 139:2273-2284. [PMID: 35167654 PMCID: PMC9710485 DOI: 10.1182/blood.2021014309] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Accepted: 02/03/2022] [Indexed: 12/15/2022] Open
Abstract
Cytogenetics has long represented a critical component in the clinical evaluation of hematologic malignancies. Chromosome banding studies provide a simultaneous snapshot of genome-wide copy number and structural variation, which have been shown to drive tumorigenesis, define diseases, and guide treatment. Technological innovations in sequencing have ushered in our present-day clinical genomics era. With recent publications highlighting novel sequencing technologies as alternatives to conventional cytogenetic approaches, we, an international consortium of laboratory geneticists, pathologists, and oncologists, describe herein the advantages and limitations of both conventional chromosome banding and novel sequencing technologies and share our considerations on crucial next steps to implement these novel technologies in the global clinical setting for a more accurate cytogenetic evaluation, which may provide improved diagnosis and treatment management. Considering the clinical, logistic, technical, and financial implications, we provide points to consider for the global evolution of cytogenetic testing.
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Affiliation(s)
- Yassmine M.N. Akkari
- Departments of Cytogenetics and Molecular Pathology, Legacy Health, Portland, OR
| | - Linda B. Baughn
- Division of Hematopathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Adrian M. Dubuc
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Adam C. Smith
- Laboratory Medicine Program, University Health Network and Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | - Mar Mallo
- MDS Group, Microarrays Unit, Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | - Paola Dal Cin
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Maria Diez Campelo
- Hematology Department University Hospital of Salamanca, IBSAL, Salamanca, Spain
| | - Marta S. Gallego
- Laboratory of Cytogenetics and Molecular Cytogenetics, Department of Clinical Pathology, Italian Hospital, Buenos Aires, Argentina
| | - Isabel Granada Font
- Hematology Laboratory, Germans Trias i Pujol University Hospital–Catalan Institute of Oncology, Josep Carreras Leukemia Research Institute, Barcelona, Spain
| | - Detlef T. Haase
- Clinics of Hematology and Medical Oncology, University Medical Center Göttingen, Göttingen, Germany
| | | | - Irma Slavutsky
- Laboratory Genetics of Lymphoid Malignancies, Institute of Experimental Medicine, Buenos Aires, Argentina
| | - Cristina Mecucci
- Laboratory of Cytogenetics and Molecular Medicine, Hematology University of Perugia, Perugia, Italy
| | - Ross L. Levine
- Department of Medicine, Human Oncology and Pathogenesis Program, Memorial Sloan-Kettering Cancer Center, New York, NY
| | | | - Francesc Solé
- MDS Group, Microarrays Unit, Josep Carreras Leukaemia Research Institute, Barcelona, Spain
| | - Brynn Levy
- College of Physicians and Surgeons, Columbia University Medical Center and the New York Presbyterian Hospital, New York, NY
| | - Xinjie Xu
- Division of Hematopathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
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