The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Targeted sequencing in DLBCL, molecular subtypes, and outcomes: a Haematological Malignancy Research Network report
Abstract
Based on the profile of genetic alterations occurring in tumor samples from selected diffuse large B-cell lymphoma (DLBCL) patients, 2 recent whole-exome sequencing studies proposed partially overlapping classification systems. Using clustering techniques applied to targeted sequencing data derived from a large unselected population-based patient cohort with full clinical follow-up (n = 928), we investigated whether molecular subtypes can be robustly identified using methods potentially applicable in routine clinical practice. DNA extracted from DLBCL tumors diagnosed in patients residing in a catchment population of ∼4 million (14 centers) were sequenced with a targeted 293-gene hematological-malignancy panel. Bernoulli mixture-model clustering was applied and the resulting subtypes analyzed in relation to their clinical characteristics and outcomes. Five molecular subtypes were resolved, termed MYD88, BCL2, SOCS1/SGK1, TET2/SGK1, and NOTCH2, along with an unclassified group. The subtypes characterized by genetic alterations of BCL2, NOTCH2, and MYD88 recapitulated recent studies showing good, intermediate, and poor prognosis, respectively. The SOCS1/SGK1 subtype showed biological overlap with primary mediastinal B-cell lymphoma and conferred excellent prognosis. Although not identified as a distinct cluster, NOTCH1 mutation was associated with poor prognosis. The impact of TP53 mutation varied with genomic subtypes, conferring no effect in the NOTCH2 subtype and poor prognosis in the MYD88 subtype. Our findings confirm the existence of molecular subtypes of DLBCL, providing evidence that genomic tests have prognostic significance in non-selected DLBCL patients. The identification of both good and poor risk subtypes in patients treated with R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) clearly show the clinical value of the approach, confirming the need for a consensus classification.
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“Lastly, our interesting case of an AITL patient with CH and subsequent development of DLBCL and the sharing of the same TET2 mutation among all three lesions suggest that a subset of DLBCL, possibly the molecular subtype characterized by mutated TET2 (Lacy et al., 2020), may originate from mutated HSC.”
From Mutation analysis links angioimmunoblastic T-cell lymphoma to clonal hematopoiesis and smoking (2021) · cites this paper as Lacy et al., 2020
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Modeling Survival Data: Extending the Cox Model
Therneau, T. M., & Grambsch, P. M. (2000) · Statistics for Biology and Health · doi:10.1007/978-1-4757-3294-8 · Cited by 8,674
Monti, S., Tamayo, P., Mesirov, J., & Golub, T. (2003) · Machine Learning · doi:10.1023/a:1023949509487 · Cited by 2,116
Chapuy, B., Stewart, C., Dunford, A. J., Kim, J., Kamburov, A., Redd, R. A., Lawrence, M. S., Roemer, M. G. M., Li, A. J., Ziepert, M., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0016-8 · Cited by 1,941
Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma
Morin, R. D., Mendez-Lago, M., Mungall, A. J., Goya, R., Mungall, K. L., Corbett, R. D., Johnson, N. A., Severson, T. M., Chiu, R., Field, M., et al. (2011) · Nature · doi:10.1038/nature10351 · Cited by 1,614
Genetic and functional drivers of diffuse large B cell lymphoma
Reddy, A., Zhang, J., Davis, N. S., Moffitt, A. B., Love, C. L., Waldrop, A., Leppa, S., Pasanen, A., Meriranta, L., Karjalainen-Lindsberg, M.-L., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.027 · Cited by 1,104
Research works printed but not linked: 25
- Smith, 2015, Lymphoma incidence, survival and prevalence 2004-2014: sub-type analyses from the UK’s Haematological Malignancy Research Network, Br J Cancer, 112, 1575, 10.1038/bjc.2015.94 · DOI
- Swerdlow, 2017, WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues
- Teras, 2016, 2016 US lymphoid malignancy statistics by World Health Organization subtypes, CA Cancer J Clin, 66, 443, 10.3322/caac.21357 · DOI · Paper page
- Coiffier, 2002, CHOP chemotherapy plus rituximab compared with CHOP alone in elderly patients with diffuse large-B-cell lymphoma, N Engl J Med, 346, 235, 10.1056/NEJMoa011795 · DOI · Paper page
- Alizadeh, 2000, Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling, Nature, 403, 503, 10.1038/35000501 · DOI · Paper page
- Wright, 2003, A gene expression-based method to diagnose clinically distinct subgroups of diffuse large B cell lymphoma, Proc Natl Acad Sci U S A, 100, 9991, 10.1073/pnas.1732008100 · DOI
- Sha, 2019, Molecular high-grade B-cell lymphoma: defining a poor-risk group that requires different approaches to therapy, J Clin Oncol, 37, 202, 10.1200/JCO.18.01314 · DOI
- Painter, 2019, Cell-of-origin in diffuse large B-cell lymphoma: findings from the UK’s population-based Haematological Malignancy Research Network, Br J Haematol, 185, 781, 10.1111/bjh.15619 · DOI
- Pasqualucci, 2011, Analysis of the coding genome of diffuse large B-cell lymphoma, Nat Genet, 43, 830, 10.1038/ng.892 · DOI
- Lohr, 2012, Discovery and prioritization of somatic mutations in diffuse large B-cell lymphoma (DLBCL) by whole-exome sequencing, Proc Natl Acad Sci U S A, 109, 3879, 10.1073/pnas.1121343109 · DOI
- Monti, 2012, Integrative analysis reveals an outcome-associated and targetable pattern of p53 and cell cycle deregulation in diffuse large B cell lymphoma, Cancer Cell, 22, 359, 10.1016/j.ccr.2012.07.014 · DOI
- Morin, 2013, Mutational and structural analysis of diffuse large B-cell lymphoma using whole-genome sequencing, Blood, 122, 1256, 10.1182/blood-2013-02-483727 · DOI
- de Miranda, 2014, Exome sequencing reveals novel mutation targets in diffuse large B-cell lymphomas derived from Chinese patients, Blood, 124, 2544, 10.1182/blood-2013-12-546309 · DOI
- Karube, 2018, Integrating genomic alterations in diffuse large B-cell lymphoma identifies new relevant pathways and potential therapeutic targets, Leukemia, 32, 675, 10.1038/leu.2017.251 · DOI
- Schmitz, 2018, Genetics and pathogenesis of diffuse large B-cell lymphoma, N Engl J Med, 378, 1396, 10.1056/NEJMoa1801445 · DOI · Paper page
- Smith, 2018, Cohort profile: the Haematological Malignancy Research Network (HMRN): a UK population-based patient cohort, Int J Epidemiol, 47, 700, 10.1093/ije/dyy044 · DOI
- Smith, 2010, The Haematological Malignancy Research Network (HMRN): a new information strategy for population based epidemiology and health service research, Br J Haematol, 148, 739, 10.1111/j.1365-2141.2009.08010.x · DOI
- Leisch, 2004, FlexMix: a general framework for finite mixture models and latent class regression in R, J Stat Softw, 11, 1
- Biernacki, 2000, Assessing a mixture model for clustering with the integrated completed likelihood, IEEE Trans Pattern Anal Mach Intell, 22, 719, 10.1109/34.865189 · DOI
- Stata Corp, 2017, Stata Statistical Software: Release 15
- R Core Team, 2019, R: A language and environment for statistical computing
- Yuan, 2015, Identification of primary mediastinal large B-cell lymphoma at nonmediastinal sites by gene expression profiling, Am J Surg Pathol, 39, 1322, 10.1097/PAS.0000000000000473 · DOI
- Mottok, 2019, Integrative genomic analysis identifies key pathogenic mechanisms in primary mediastinal large B-cell lymphoma, Blood, 134, 802, 10.1182/blood.2019001126 · DOI
- Wright, 2018, Genetics of diffuse large B-cell lymphoma, N Engl J Med, 379, 493, 10.1056/NEJMc1806191 · DOI
- Wang, 2019, Impact of concurrent indolent lymphoma on the clinical outcome of newly diagnosed diffuse large B-cell lymphoma, Blood, 134, 1289, 10.1182/blood.2019000858 · DOI
Cited by
Clonal haematopoiesis and dysregulation of the immune system
Belizaire, R., Wong, W. J., Robinette, M. L., & Ebert, B. L. (2023) · Nature Reviews Immunology · doi:10.1038/s41577-023-00843-3 · Cited by 161
Mutation analysis links angioimmunoblastic T-cell lymphoma to clonal hematopoiesis and smoking
Cheng, S., Zhang, W., Inghirami, G., & Tam, W. (2021) · eLife · doi:10.7554/elife.66395 · Cited by 37
Metadata
- Authors
- Lacy, S. E., Barrans, S. L., Beer, P. A., Painter, D., Smith, A. G., Roman, E., Cooke, S. L., Ruiz, C., Glover, P., Van Hoppe, S. J. L., Webster, N., Campbell, P. J., Tooze, R. M., Patmore, R., Burton, C., Crouch, S., & Hodson, D. J.
- Affiliations
- Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, United Kingdom;
- Haematological Malignancy Diagnostic Service, St. James’s Institute of Oncology, Leeds, United Kingdom;
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom;
- Institute of Cancer Sciences, University of Glasgow, Glasgow, United Kingdom;
- Section of Experimental Haematology, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, United Kingdom;
- Queen’s Centre for Oncology and Haematology, Castle Hill Hospital, Cottingham, United Kingdom; and
- Wellcome–MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
- Venue
- Blood
- Publisher
- American Society of Hematology
- Published
- 2020-05-14
- Volume
- 135
- Issue
- 20
- Pages
- 1759-1771
- ISSN
- 0006-4971
- 1528-0020
- Cited by
- 506
- References
- 7
- Language
- en
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