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Villamor-Payà M, Sanchiz-Calvo M, Smak J, Pais L, Sud M, Shankavaram U, Lovgren AK, Austin-Tse C, Ganesh VS, Gay M, Vilaseca M, Arauz-Garofalo G, Palenzuela L, VanNoy G, O’Donnell-Luria A, Stracker TH. De novo TLK1 and MDM1 mutations in a patient with a neurodevelopmental disorder and immunodeficiency. iScience 2024; 27:109984. [PMID: 38868186 PMCID: PMC11166698 DOI: 10.1016/j.isci.2024.109984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 04/08/2024] [Accepted: 05/13/2024] [Indexed: 06/14/2024] Open
Abstract
The Tousled-like kinases 1 and 2 (TLK1/TLK2) regulate DNA replication, repair and chromatin maintenance. TLK2 variants underlie the neurodevelopmental disorder (NDD) 'Intellectual Disability, Autosomal Dominant 57' (MRD57), characterized by intellectual disability and microcephaly. Several TLK1 variants have been reported in NDDs but their functional significance is unknown. A male patient presenting with ID, seizures, global developmental delay, hypothyroidism, and primary immunodeficiency was determined to have a heterozygous TLK1 variant (c.1435C>G, p.Q479E), as well as a mutation in MDM1 (c.1197dupT, p.K400∗). Cells expressing TLK1 p.Q479E exhibited reduced cytokine responses and elevated DNA damage, but not increased radiation sensitivity or DNA repair defects. The TLK1 p.Q479E variant impaired kinase activity but not proximal protein interactions. Our study provides the first functional characterization of NDD-associated TLK1 variants and suggests that, such as TLK2, TLK1 variants may impact development in multiple tissues and should be considered in the diagnosis of rare NDDs.
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Affiliation(s)
- Marina Villamor-Payà
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
- National Cancer Institute, Center for Cancer Research, Radiation Oncology Branch, Bethesda, MD 20892, USA
| | - María Sanchiz-Calvo
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
| | - Jordann Smak
- National Cancer Institute, Center for Cancer Research, Radiation Oncology Branch, Bethesda, MD 20892, USA
| | - Lynn Pais
- Division of Genetics & Genomics, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Malika Sud
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Uma Shankavaram
- National Cancer Institute, Center for Cancer Research, Radiation Oncology Branch, Bethesda, MD 20892, USA
| | - Alysia Kern Lovgren
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Christina Austin-Tse
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Vijay S. Ganesh
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Marina Gay
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
| | - Marta Vilaseca
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
| | - Gianluca Arauz-Garofalo
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
| | - Lluís Palenzuela
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
| | - Grace VanNoy
- Division of Genetics & Genomics, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Anne O’Donnell-Luria
- Division of Genetics & Genomics, Department of Pediatrics, Boston Children’s Hospital, Boston, MA 02115, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Travis H. Stracker
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, 08028 Barcelona, Spain
- National Cancer Institute, Center for Cancer Research, Radiation Oncology Branch, Bethesda, MD 20892, USA
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2
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Wang YH, Orgueira AM, Lin CC, Yao CY, Lo MY, Tsai CH, de la Fuente Burguera A, Hou HA, Chou WC, Tien HF. Stellae-123 gene expression signature improved risk stratification in taiwanese acute myeloid leukemia patients. Sci Rep 2024; 14:11064. [PMID: 38744924 PMCID: PMC11094146 DOI: 10.1038/s41598-024-61022-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 04/30/2024] [Indexed: 05/16/2024] Open
Abstract
The European Leukemia Net recommendations provide valuable guidance in treatment decisions of patients with acute myeloid leukemia (AML). However, the genetic complexity and heterogeneity of AML are not fully covered, notwithstanding that gene expression analysis is crucial in the risk stratification of AML. The Stellae-123 score, an AI-based model that captures gene expression patterns, has demonstrated robust survival predictions in AML patients across four western-population cohorts. This study aims to evaluate the applicability of Stellae-123 in a Taiwanese cohort. The Stellae-123 model was applied to 304 de novo AML patients diagnosed and treated at the National Taiwan University Hospital. We find that the pretrained (BeatAML-based) model achieved c-indexes of 0.631 and 0.632 for the prediction of overall survival (OS) and relapse-free survival (RFS), respectively. Model retraining within our cohort further improve the cross-validated c-indexes to 0.667 and 0.667 for OS and RFS prediction, respectively. Multivariable analysis identify both pretrained and retrained models as independent prognostic biomarkers. We further show that incorporating age, Stellae-123, and ELN classification remarkably improves risk stratification, revealing c-indices of 0.73 and 0.728 for OS and RFS, respectively. In summary, the Stellae-123 gene expression signature is a valuable prognostic tool for AML patients and model retraining can improve the accuracy and applicability of the model in different populations.
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Affiliation(s)
- Yu-Hung Wang
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
| | - Adrián Mosquera Orgueira
- Department of Hematology, University Hospital of Santiago de Compostela, Santiago de Compostela, Spain
- Group of Computational Hematology and Genomics (GrHeCo-Xen), Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Chien-Chin Lin
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan.
- Department of Laboratory Medicine, National Taiwan University Hospital, No. 7, Chung-Shan S. Rd., Taipei City, 10002, Taiwan.
| | - Chi-Yuan Yao
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Laboratory Medicine, National Taiwan University Hospital, No. 7, Chung-Shan S. Rd., Taipei City, 10002, Taiwan
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Min-Yen Lo
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
- Division of Hematology, Department of Internal Medicine, National Taiwan University Hospital Yunlin Branch, Yunlin, Taiwan
| | - Cheng-Hong Tsai
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Medical Education and Research, National Taiwan University Hospital Yunlin Branch, Yunlin, Taiwan
| | | | - Hsin-An Hou
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
| | - Wen-Chien Chou
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Laboratory Medicine, National Taiwan University Hospital, No. 7, Chung-Shan S. Rd., Taipei City, 10002, Taiwan
| | - Hwei-Fang Tien
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan.
- Department of Internal Medicine, Far-Eastern Memorial Hospital, No. 7, Chung-Shan S. Rd., Taipei City, 10002, Taiwan.
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3
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Wang M, Brandt LTL, Wang X, Russell H, Mitchell E, Kamimae-Lanning AN, Brown JM, Dingler FA, Garaycoechea JI, Isobe T, Kinston SJ, Gu M, Vassiliou GS, Wilson NK, Göttgens B, Patel KJ. Genotoxic aldehyde stress prematurely ages hematopoietic stem cells in a p53-driven manner. Mol Cell 2023; 83:2417-2433.e7. [PMID: 37348497 PMCID: PMC7614878 DOI: 10.1016/j.molcel.2023.05.035] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 04/18/2023] [Accepted: 05/25/2023] [Indexed: 06/24/2023]
Abstract
Aged hematopoietic stem cells (HSCs) display diminished self-renewal and a myeloid differentiation bias. However, the drivers and mechanisms that underpin this fundamental switch are not understood. HSCs produce genotoxic formaldehyde that requires protection by the detoxification enzymes ALDH2 and ADH5 and the Fanconi anemia (FA) DNA repair pathway. We find that the HSCs in young Aldh2-/-Fancd2-/- mice harbor a transcriptomic signature equivalent to aged wild-type HSCs, along with increased epigenetic age, telomere attrition, and myeloid-biased differentiation quantified by single HSC transplantation. In addition, the p53 response is vigorously activated in Aldh2-/-Fancd2-/- HSCs, while p53 deletion rescued this aged HSC phenotype. To further define the origins of the myeloid differentiation bias, we use a GFP genetic reporter to find a striking enrichment of Vwf+ myeloid and megakaryocyte-lineage-biased HSCs. These results indicate that metabolism-derived formaldehyde-DNA damage stimulates the p53 response in HSCs to drive accelerated aging.
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Affiliation(s)
- Meng Wang
- Division of Nutritional Sciences, Cornell University, Ithaca, NY, USA; Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK; MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, UK.
| | - Laura T L Brandt
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, UK
| | - Xiaonan Wang
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK; School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Holly Russell
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Emily Mitchell
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK; Wellcome Sanger Institute, Hinxton, UK
| | - Ashley N Kamimae-Lanning
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Jill M Brown
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Felix A Dingler
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Juan I Garaycoechea
- Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center, Utrecht, the Netherlands
| | - Tomoya Isobe
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Sarah J Kinston
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Muxin Gu
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - George S Vassiliou
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Nicola K Wilson
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Berthold Göttgens
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Ketan J Patel
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK.
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4
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Transcriptome-based molecular subtypes and differentiation hierarchies improve the classification framework of acute myeloid leukemia. Proc Natl Acad Sci U S A 2022; 119:e2211429119. [PMID: 36442087 PMCID: PMC9894241 DOI: 10.1073/pnas.2211429119] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
The current classification of acute myeloid leukemia (AML) relies largely on genomic alterations. Robust identification of clinically and biologically relevant molecular subtypes from nongenomic high-throughput sequencing data remains challenging. We established the largest multicenter AML cohort (n = 655) in China, with all patients subjected to RNA sequencing (RNA-Seq) and 619 (94.5%) to targeted or whole-exome sequencing (TES/WES). Based on an enhanced consensus clustering, eight stable gene expression subgroups (G1-G8) with unique clinical and biological significance were identified, including two unreported (G5 and G8) and three redefined ones (G4, G6, and G7). Apart from four well-known low-risk subgroups including PML::RARA (G1), CBFB::MYH11 (G2), RUNX1::RUNX1T1 (G3), biallelic CEBPA mutations or -like (G4), four meta-subgroups with poor outcomes were recognized. The G5 (myelodysplasia-related/-like) subgroup enriched clinical, cytogenetic and genetic features mimicking secondary AML, and hotspot mutations of IKZF1 (p.N159S) (n = 7). In contrast, most NPM1 mutations and KMT2A and NUP98 fusions clustered into G6-G8, showing high expression of HOXA/B genes and diverse differentiation stages, from hematopoietic stem/progenitor cell down to monocyte, namely HOX-primitive (G7), HOX-mixed (G8), and HOX-committed (G6). Through constructing prediction models, the eight gene expression subgroups could be reproduced in the Cancer Genome Atlas (TCGA) and Beat AML cohorts. Each subgroup was associated with distinct prognosis and drug sensitivities, supporting the clinical applicability of this transcriptome-based classification of AML. These molecular subgroups illuminate the complex molecular network of AML, which may promote systematic studies of disease pathogenesis and foster the screening of targeted agents based on omics.
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5
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Yasuda T, Sanada M, Tsuzuki S, Hayakawa F. Oncogenic lesions and molecular subtypes in adults with B-cell acute lymphoblastic leukemia. Cancer Sci 2022; 114:8-15. [PMID: 36106363 PMCID: PMC9807527 DOI: 10.1111/cas.15583] [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: 06/14/2022] [Revised: 08/12/2022] [Accepted: 09/04/2022] [Indexed: 01/07/2023] Open
Abstract
B-cell acute lymphoblastic leukemia (B-ALL), a genetically heterogeneous disease, is classified into different molecular subtypes that are defined by recurrent gene rearrangements, gross chromosomal abnormalities, or specific gene mutations. Cells with these genetic alterations acquire a leukemia-initiating ability and show unique expression profiles. The distribution of B-ALL molecular subtypes is greatly dependent on age, which also affects treatment responsiveness and long-term survival, partly accounting for the inferior outcome in adolescents and young adults (AYA) and (older) adults with B-ALL. Recent advances in sequencing technology, especially RNA sequencing and the application of these technologies in large B-ALL cohorts have uncovered B-ALL molecular subtypes prevalent in AYA and adults. These new insights supply more precise estimations of prognoses and targeted therapies informed by sequencing results, as well as a deeper understanding of the genetic basis of AYA/adult B-ALL. This article provides an account of these technological advances and an overview of the recent major findings of B-ALL molecular subtypes in adults.
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Affiliation(s)
- Takahiko Yasuda
- Clinical Research CenterNational Hospital Organization Nagoya Medical CenterNagoyaJapan
| | - Masashi Sanada
- Clinical Research CenterNational Hospital Organization Nagoya Medical CenterNagoyaJapan
| | - Shinobu Tsuzuki
- Department of BiochemistryAichi Medical University School of MedicineNagakuteJapan
| | - Fumihiko Hayakawa
- Division of Cellular and Genetic Sciences, Department of Integrated Health SciencesNagoya University Graduate School of MedicineNagoyaJapan
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6
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FVC as an adaptive and accurate method for filtering variants from popular NGS analysis pipelines. Commun Biol 2022; 5:975. [PMID: 36114280 PMCID: PMC9481582 DOI: 10.1038/s42003-022-03397-7] [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: 07/09/2021] [Accepted: 04/22/2022] [Indexed: 11/08/2022] Open
Abstract
The quality control of variants from whole-genome sequencing data is vital in clinical diagnosis and human genetics research. However, current filtering methods (Frequency, Hard-Filter, VQSR, GARFIELD, and VEF) were developed to be utilized on particular variant callers and have certain limitations. Especially, the number of eliminated true variants far exceeds the number of removed false variants using these methods. Here, we present an adaptive method for quality control on genetic variants from different analysis pipelines, and validate it on the variants generated from four popular variant callers (GATK HaplotypeCaller, Mutect2, Varscan2, and DeepVariant). FVC consistently exhibited the best performance. It removed far more false variants than the current state-of-the-art filtering methods and recalled ~51-99% true variants filtered out by the other methods. Once trained, FVC can be conveniently integrated into a user-specific variant calling pipeline. FVC is a method for calling specific gene variants from whole genome data, for potential use in clinical diagnosis and human genetics research.
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7
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Quiros PM, Gu M, Barcena C, Iyer V, Vassiliou GS. NPM1 gene mutations can be confidently identified in blood DNA months before de novo AML onset. Blood Adv 2022; 6:2409-2413. [PMID: 34920452 PMCID: PMC9006299 DOI: 10.1182/bloodadvances.2021005927] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 11/10/2021] [Indexed: 11/20/2022] Open
Affiliation(s)
- Pedro M. Quiros
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Department of Haematology, University of Cambridge, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, United Kingdom
- Instituto de Investigación Sanitaria del Principado de Asturias, Oviedo, Spain; and
| | - Muxin Gu
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Department of Haematology, University of Cambridge, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Clea Barcena
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Department of Haematology, University of Cambridge, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Vivek Iyer
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - George S. Vassiliou
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, Department of Haematology, University of Cambridge, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, United Kingdom
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, United Kingdom
- Department of Haematology, Cambridge University Hospitals National Health Service Trust, Cambridge, United Kingdom
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8
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Wei S, Kutikov A, Patchefsky AS, Flieder DB, Talarchek JN, Al-Saleem T, Dulaimi E, Uzzo RG, Testa JR, Pei J. Papillary Renal Neoplasm With Reverse Polarity Is Often Cystic: Report of 7 Cases and Review of 93 Cases in the Literature. Am J Surg Pathol 2022; 46:336-343. [PMID: 34352808 DOI: 10.1097/pas.0000000000001773] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Papillary renal neoplasm with reverse polarity (PRNRP) is a newly proposed entity with distinct histology and frequent KRAS mutations. To date, 93 cases of PRNRPs have been reported. In this study, we present 7 new cases of PRNRP and review the literature. Most of the pathologic features in our 7 cases are similar to those previously reported cases. However, all 7 of our cases showed at least partial cystic changes, which was not stressed in prior studies. Single-nucleotide polymorphism-microarray based chromosomal analysis demonstrated no trisomy or other alteration of chromosomes 7 or 17; and no loss or other alteration of chromosome Y was detected in all 7 cases. Next-generation sequencing detected KRAS missense mutations in 4 of 7 cases. No fusion genes were detected. In summary, PRNRP is a small, well-circumscribed often encapsulated and cystic neoplasm with loose papillary formations. Cuboidal tumor cells always have eosinophilic cytoplasm and nuclei located at the pole opposite the basement membrane with a low World Health Organization (WHO)/International Society of Urologic Pathologists (ISUP) nuclear grade. The fibrovascular cores can be hyalinized or edematous. Macrophage aggregates and intracellular hemosiderin are uncommon, and no psammoma bodies or necrosis should be seen. Immunophenotypically, this tumor is always positive for CK7 and GATA3, and negative for CD117 and vimentin. CD10 and AMACR can be positive, but often weakly and focally. PRNRP often has KRAS mutations, however, only 32% of cases have chromosomal abnormalities in chromosomes 7, 17, and Y. No recurrences, metastases, or tumor-related deaths have been reported following complete resection.
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MESH Headings
- Adult
- Aged
- Aged, 80 and over
- Biomarkers, Tumor/genetics
- Biomarkers, Tumor/metabolism
- Carcinoma, Papillary/diagnosis
- Carcinoma, Papillary/genetics
- Carcinoma, Papillary/metabolism
- Carcinoma, Papillary/pathology
- Carcinoma, Renal Cell/diagnosis
- Carcinoma, Renal Cell/genetics
- Carcinoma, Renal Cell/metabolism
- Carcinoma, Renal Cell/pathology
- Cysts/diagnosis
- Cysts/genetics
- Cysts/metabolism
- Cysts/pathology
- Female
- Humans
- Kidney Neoplasms/diagnosis
- Kidney Neoplasms/genetics
- Kidney Neoplasms/metabolism
- Kidney Neoplasms/pathology
- Male
- Middle Aged
- Prognosis
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Affiliation(s)
| | | | | | | | | | | | | | | | - Joseph R Testa
- Cancer Signaling and Epigenetics Program, Fox Chase Cancer Center, Philadelphia, PA
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9
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Dunn WG, Gu MS, Fabre MA, Cooper J, Nomdedeu JF, Koumas L, Nicolaou K, Chi J, Costeas P, Vassiliou GS. The PML-RARA fusion is not detectable in historical blood samples of acute promyelocytic leukaemia patients. Ann Hematol 2022; 101:443-445. [PMID: 33650061 PMCID: PMC8742812 DOI: 10.1007/s00277-021-04472-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 02/18/2021] [Indexed: 10/28/2022]
Affiliation(s)
- William G Dunn
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK
- Department of Haematology, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Muxin S Gu
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Margarete A Fabre
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK
- Department of Haematology, Cambridge University Hospitals NHS Trust, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Jonathan Cooper
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Josep F Nomdedeu
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
- Department of Haematology, Hospital de la Santa Creu I Sant Pau, Barcelona, Spain
| | - Laura Koumas
- Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicosia, Cyprus
| | - Katerina Nicolaou
- Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicosia, Cyprus
| | - Jiangxiang Chi
- Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicosia, Cyprus
| | - Paul Costeas
- Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicosia, Cyprus.
- Cyprus Cancer Research Institute, Nicosia, Cyprus.
| | - George S Vassiliou
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge, CB2 0AW, UK.
- Department of Haematology, Cambridge University Hospitals NHS Trust, Cambridge, UK.
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.
- Center for the Study of Haematological Malignancies, Karaiskakio Foundation, Nicosia, Cyprus.
- Cyprus Cancer Research Institute, Nicosia, Cyprus.
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10
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Lee J, Cho S, Hong SE, Kang D, Choi H, Lee JM, Yoon JH, Cho BS, Lee S, Kim HJ, Kim M, Kim Y. Integrative Analysis of Gene Expression Data by RNA Sequencing for Differential Diagnosis of Acute Leukemia: Potential Application of Machine Learning. Front Oncol 2021; 11:717616. [PMID: 34497767 PMCID: PMC8419339 DOI: 10.3389/fonc.2021.717616] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 07/21/2021] [Indexed: 11/24/2022] Open
Abstract
BCR-ABL1–positive acute leukemia can be classified into three disease categories: B-lymphoblastic leukemia (B-ALL), acute myeloid leukemia (AML), and mixed-phenotype acute leukemia (MPAL). We conducted an integrative analysis of RNA sequencing (RNA-seq) data obtained from 12 BCR-ABL1–positive B-ALL, AML, and MPAL samples to evaluate its diagnostic utility. RNA-seq facilitated the identification of all p190 BCR-ABL1 with accurate splicing sites and a new gene fusion involving MAP2K2. Most of the clinically significant mutations were also identified including single-nucleotide variations, insertions, and deletions. In addition, RNA-seq yielded differential gene expression profile according to the disease category. Therefore, we selected 368 genes differentially expressed between AML and B-ALL and developed two differential diagnosis models based on the gene expression data using 1) scoring algorithm and 2) machine learning. Both models showed an excellent diagnostic accuracy not only for our 12 BCR-ABL1–positive cases but also for 427 public gene expression datasets from acute leukemias regardless of specific genetic aberration. This is the first trial to develop models of differential diagnosis using RNA-seq, especially to evaluate the potential role of machine learning in identifying the disease category of acute leukemia. The integrative analysis of gene expression data by RNA-seq facilitates the accurate differential diagnosis of acute leukemia with successful detection of significant gene fusion and/or mutations, which warrants further investigation.
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Affiliation(s)
- Jaewoong Lee
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.,Catholic Genetic Laboratory Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | | | - Seong-Eui Hong
- Next Generation Sequencing (NGS) Division, Theragen Bio Co. Ltd., Seongnam-si, South Korea
| | - Dain Kang
- Catholic Genetic Laboratory Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Hayoung Choi
- Catholic Genetic Laboratory Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Jong-Mi Lee
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.,Catholic Genetic Laboratory Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Jae-Ho Yoon
- Department of Hematology, Catholic Hematology Hospital and Leukemia Research Institute, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Byung-Sik Cho
- Department of Hematology, Catholic Hematology Hospital and Leukemia Research Institute, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Seok Lee
- Department of Hematology, Catholic Hematology Hospital and Leukemia Research Institute, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Hee-Je Kim
- Department of Hematology, Catholic Hematology Hospital and Leukemia Research Institute, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Myungshin Kim
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.,Catholic Genetic Laboratory Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Yonggoo Kim
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.,Catholic Genetic Laboratory Center, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
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11
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Dai B, Yu H, Ma T, Lei Y, Wang J, Zhang Y, Lu J, Yan H, Jiang L, Chen B. The Application of Targeted RNA Sequencing for KMT2A-Partial Tandem Duplication Identification and Integrated Analysis of Molecular Characterization in Acute Myeloid Leukemia. J Mol Diagn 2021; 23:1478-1490. [PMID: 34384895 DOI: 10.1016/j.jmoldx.2021.07.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 07/12/2021] [Accepted: 07/26/2021] [Indexed: 12/25/2022] Open
Abstract
The partial tandem duplication of histone-lysine N-methyltransferase 2A (KMT2A-PTD) is an important genetic alteration in acute myeloid leukemia (AML) and is associated with poor clinical outcome. Accurate and rapid detection of KMT2A-PTD is important for outcome prediction and clinical management, but next-generation sequencing-based quantitative research is still lacking. In this study, we developed a targeted RNA-based next-generation sequencing panel, together with single primer enrichment and unique molecular identifiers, to identify KMT2A-PTD as well as AML-related gene fusions and other driver mutations. Our panel showed high sensitivity, accuracy, and reproducibility in detecting the fusion ratio of KMT2A-PTD. We characterized the mutation profile of KMT2A-PTD-positive patients with AML and found different distribution patterns of driver mutations according to KMT2A-PTD fusion ratio level. Survival analyses revealed that the fusion ratio of KMT2A-PTD did not affect clinical outcome, but a novel molecular combination, namely, KMT2A-PTD/DNMT3A/FMS-like tyrosine kinase 3-internal tandem duplication, was associated with poor prognosis. Finally, we proved that the dynamic changes in the KMT2A-PTD fusion ratio were consistent with the overall process of disease progression. In summary, we applied the unique molecular identifier-based RNA panel to quantitatively detect KMT2A-PTD and elucidate its clinical relevance, which complemented the integrative network of various genetic alterations in AML.
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Affiliation(s)
- Bing Dai
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hao Yu
- Jiangsu Key Laboratory of Zoonosis and Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonose, Yangzhou University, Yangzhou, China
| | - Tingting Ma
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yichen Lei
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiyue Wang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yunxiang Zhang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jing Lu
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Han Yan
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lu Jiang
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Bing Chen
- Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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12
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CLEC12A and CD33 coexpression as a preferential target for pediatric AML combinatorial immunotherapy. Blood 2021; 137:1037-1049. [PMID: 33094319 DOI: 10.1182/blood.2020006921] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 09/30/2020] [Indexed: 12/14/2022] Open
Abstract
Emerging immunotherapies such as chimeric antigen receptor T cells have advanced the treatment of acute lymphoblastic leukemia. In contrast, long-term control of acute myeloid leukemia (AML) cannot be achieved by single lineage-specific targeting while sparing benign hematopoiesis. In addition, heterogeneity of AML warrants combinatorial targeting, and several suitable immunotargets (HAVCR2/CD33 and HAVCR2/CLEC12A) have been identified in adult AML. However, clinical and biologic characteristics of AML differ between children and the elderly. Here, we analyzed 36 bone marrow (BM) samples of pediatric AML patients and 13 age-matched healthy donors using whole RNA sequencing of sorted CD45dim and CD34+CD38-CD45dim BM populations and flow cytometry for surface expression of putative target antigens. Pediatric AML clusters apart from healthy myeloid BM precursors in principal-component analysis. Known immunotargets of adult AML, such as IL3RA, were not overexpressed in pediatric AML compared with healthy precursors by RNA sequencing. CD33 and CLEC12A were the most upregulated immunotargets on the RNA level and showed the highest surface expression on AML detected by flow cytometry. KMT2A-mutated infant AML clusters separately by RNA sequencing and overexpresses FLT3, and hence, CD33/FLT3 cotargeting is an additional specific option for this subgroup. CLEC12A and CD33/CLEC12Adouble-positive expression was absent in CD34+CD38-CD45RA-CD90+ hematopoietic stem cells (HSCs) and nonhematopoietic tissue, while CD33 and FLT3 are expressed on HSCs. In summary, we show that expression of immunotargets in pediatric AML differs from known expression profiles in adult AML. We identify CLEC12A and CD33 as preferential generic combinatorial immunotargets in pediatric AML and CD33 and FLT3 as immunotargets specific for KMT2A-mutated infant AML.
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13
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Ehx G, Larouche JD, Durette C, Laverdure JP, Hesnard L, Vincent K, Hardy MP, Thériault C, Rulleau C, Lanoix J, Bonneil E, Feghaly A, Apavaloaei A, Noronha N, Laumont CM, Delisle JS, Vago L, Hébert J, Sauvageau G, Lemieux S, Thibault P, Perreault C. Atypical acute myeloid leukemia-specific transcripts generate shared and immunogenic MHC class-I-associated epitopes. Immunity 2021; 54:737-752.e10. [PMID: 33740418 DOI: 10.1016/j.immuni.2021.03.001] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Revised: 10/24/2020] [Accepted: 02/26/2021] [Indexed: 12/11/2022]
Abstract
Acute myeloid leukemia (AML) has not benefited from innovative immunotherapies, mainly because of the lack of actionable immune targets. Using an original proteogenomic approach, we analyzed the major histocompatibility complex class I (MHC class I)-associated immunopeptidome of 19 primary AML samples and identified 58 tumor-specific antigens (TSAs). These TSAs bore no mutations and derived mainly (86%) from supposedly non-coding genomic regions. Two AML-specific aberrations were instrumental in the biogenesis of TSAs, intron retention, and epigenetic changes. Indeed, 48% of TSAs resulted from intron retention and translation, and their RNA expression correlated with mutations of epigenetic modifiers (e.g., DNMT3A). AML TSA-coding transcripts were highly shared among patients and were expressed in both blasts and leukemic stem cells. In AML patients, the predicted number of TSAs correlated with spontaneous expansion of cognate T cell receptor clonotypes, accumulation of activated cytotoxic T cells, immunoediting, and improved survival. These TSAs represent attractive targets for AML immunotherapy.
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Affiliation(s)
- Grégory Ehx
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Jean-David Larouche
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Chantal Durette
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Jean-Philippe Laverdure
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Leslie Hesnard
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Krystel Vincent
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Marie-Pierre Hardy
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Catherine Thériault
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Caroline Rulleau
- Centre de recherche de l'Hôpital Maisonneuve-Rosemont, Montréal, QC, Canada
| | - Joël Lanoix
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Eric Bonneil
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Albert Feghaly
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Anca Apavaloaei
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Nandita Noronha
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Céline M Laumont
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Jean-Sébastien Delisle
- Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada; Centre de recherche de l'Hôpital Maisonneuve-Rosemont, Montréal, QC, Canada; Division of Hematology, Maisonneuve-Rosemont Hospital, Montreal, QC H1T 2M4, Canada
| | - Luca Vago
- Unit of Immunogenetics, Leukemia Genomics and Immunobiology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Josée Hébert
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada; Division of Hematology, Maisonneuve-Rosemont Hospital, Montreal, QC H1T 2M4, Canada
| | - Guy Sauvageau
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada; Division of Hematology, Maisonneuve-Rosemont Hospital, Montreal, QC H1T 2M4, Canada
| | - Sébastien Lemieux
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Biochemistry and Molecular Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Pierre Thibault
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Chemistry, Université de Montréal, Montreal, QC H3C 3J7, Canada.
| | - Claude Perreault
- Institute for Research in Immunology and Cancer (IRIC), Université de Montréal, Montreal, QC H3C 3J7, Canada; Department of Medicine, Université de Montréal, Montreal, QC H3C 3J7, Canada.
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14
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Emerging molecular subtypes and therapeutic targets in B-cell precursor acute lymphoblastic leukemia. Front Med 2021; 15:347-371. [PMID: 33400146 DOI: 10.1007/s11684-020-0821-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 09/04/2020] [Indexed: 12/13/2022]
Abstract
B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is characterized by genetic alterations with high heterogeneity. Precise subtypes with distinct genomic and/or gene expression patterns have been recently revealed using high-throughput sequencing technology. Most of these profiles are associated with recurrent non-overlapping rearrangements or hotspot point mutations that are analogous to the established subtypes, such as DUX4 rearrangements, MEF2D rearrangements, ZNF384/ZNF362 rearrangements, NUTM1 rearrangements, BCL2/MYC and/or BCL6 rearrangements, ETV6-RUNX1-like gene expression, PAX5alt (diverse PAX5 alterations, including rearrangements, intragenic amplifications, or mutations), and hotspot mutations PAX5 (p.Pro80Arg) with biallelic PAX5 alterations, IKZF1 (p.Asn159Tyr), and ZEB2 (p.His1038Arg). These molecular subtypes could be classified by gene expression patterns with RNA-seq technology. Refined molecular classification greatly improved the treatment strategy. Multiagent therapy regimens, including target inhibitors (e.g., imatinib), immunomodulators, monoclonal antibodies, and chimeric antigen receptor T-cell (CAR-T) therapy, are transforming the clinical practice from chemotherapy drugs to personalized medicine in the field of risk-directed disease management. We provide an update on our knowledge of emerging molecular subtypes and therapeutic targets in BCP-ALL.
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