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Genomic Classification and Prognosis in Acute Myeloid Leukemia
Open accessAbstract
BACKGROUND: Recent studies have provided a detailed census of genes that are mutated in acute myeloid leukemia (AML). Our next challenge is to understand how this genetic diversity defines the pathophysiology of AML and informs clinical practice. METHODS: We enrolled a total of 1540 patients in three prospective trials of intensive therapy. Combining driver mutations in 111 cancer genes with cytogenetic and clinical data, we defined AML genomic subgroups and their relevance to clinical outcomes. RESULTS: We identified 5234 driver mutations across 76 genes or genomic regions, with 2 or more drivers identified in 86% of the patients. Patterns of co-mutation compartmentalized the cohort into 11 classes, each with distinct diagnostic features and clinical outcomes. In addition to currently defined AML subgroups, three heterogeneous genomic categories emerged: AML with mutations in genes encoding chromatin, RNA-splicing regulators, or both (in 18% of patients); AML with TP53 mutations, chromosomal aneuploidies, or both (in 13%); and, provisionally, AML with IDH2(R172) mutations (in 1%). Patients with chromatin-spliceosome and TP53-aneuploidy AML had poor outcomes, with the various class-defining mutations contributing independently and additively to the outcome. In addition to class-defining lesions, other co-occurring driver mutations also had a substantial effect on overall survival. The prognostic effects of individual mutations were often significantly altered by the presence or absence of other driver mutations. Such gene-gene interactions were especially pronounced for NPM1-mutated AML, in which patterns of co-mutation identified groups with a favorable or adverse prognosis. These predictions require validation in prospective clinical trials. CONCLUSIONS: The driver landscape in AML reveals distinct molecular subgroups that reflect discrete paths in the evolution of AML, informing disease classification and prognostic stratification. (Funded by the Wellcome Trust and others; ClinicalTrials.gov number, NCT00146120.).
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“We identified 391 out of the 622 curated COSMIC cancer-related and AML-related genes located inside the altered TADs in at least one sample, and more than 100 are recurrent across multiple samples (Extended Data Fig. 3b)4,24,25.”
From Subtype-specific 3D genome alteration in acute myeloid leukaemia (2022) · cites this paper as [4]
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“Splicing factor mutations are common in AMl and other blood malignancies and are often mutually exclusive (Haferlach et al. 2014;Papaemmanuil et al. 2016), indicating that cancers harboring such mutations may rely on an intact splicing machinery for survival (lee et al. 2018).”
From From serendipity to strategy: molecular glue degraders in cancer therapeutics (2025) · cites this paper as Papaemmanuil et al. 2016
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“Leukemia is frequently driven by mutations in epigenetic modifiers or signaling master regulators58 that lead to gross alterations of the epigenetic landscape59 and an epigenetic environment widely permissive of activation.”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [58]
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“Particularly in acute myeloid leukemia (AML), a prominent component of the disease is recurrent mutations in spliceosome machinery and genome-wide aberrant splicing events (14)(15)(16)(17).”
From Discovery of a Novel CIP2A Variant (NOCIVA) with Clinical Relevance in Predicting TKI Resistance in Myeloid Leukemias (2021) · cites this paper as [16]
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Cites
Mutational heterogeneity in cancer and the search for new cancer-associated genes
Lawrence, M. S., Stojanov, P., Polak, P., Kryukov, G. V., Cibulskis, K., Sivachenko, A., Carter, S. L., Stewart, C., Mermel, C. H., Roberts, S. A., et al. (2013) · Nature · doi:10.1038/nature12213 · Cited by 5,461
Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia
The Cancer Genome Atlas Research Network (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1301689 · Cited by 5,078
Age-related clonal hematopoiesis associated with adverse outcomes
Jaiswal, S., Fontanillas, P., Flannick, J., Manning, A., Grauman, P. V., Mar, B. G., Lindsley, R. C., Mermel, C. H., Burtt, N., Chavez, A., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1408617 · Cited by 4,841
Vardiman, J. W., Thiele, J., Arber, D. A., Brunning, R. D., Borowitz, M. J., Porwit‐MacDonald, A., Harris, N. L., Beau, M. M. L., Hellström‐Lindberg, E., Tefferi, A., et al. (2009) · Blood · doi:10.1182/blood-2009-03-209262 · Cited by 4,532
Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence
Genovese, G., Kähler, A. K., Handsaker, R. E., Lindberg, J., Rose, S. A., Bakhoum, S. F., Chambert, K., Mick, E., Neale, B. M., Fromer, M., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1409405 · Cited by 3,531
Döhner, H., Weisdorf, D. J., & Bloomfield, C. D. (2015) · New England Journal of Medicine · doi:10.1056/nejmra1406184 · Cited by 3,468
Self-citationDöhner, H., Estey, E. H., Amadori, S., Appelbaum, F. R., Büchner, T., Burnett, A. K., Dombret, H., Fenaux, P., Grimwade, D. J., Larson, R. A., et al. (2009) · Blood · doi:10.1182/blood-2009-07-235358 · Cited by 3,438
Self-citationGrimwade, D. J., Walker, H., Oliver, F., Wheatley, K., Harrison, C. J., Harrison, G., Rees, J., Hann, I. M., Stevens, R., Burnett, A. K., et al. (1998) · Blood · doi:10.1182/blood.v92.7.2322 · Cited by 2,649
Absolute quantification of somatic DNA alterations in human cancer
Carter, S. L., Cibulskis, K., Helman, E., McKenna, A., Shen, H., Zack, T. I., Laird, P. W., Onofrio, R. C., Winckler, W., Weir, B. A., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2203 · Cited by 2,031
Prognostic Relevance of Integrated Genetic Profiling in Acute Myeloid Leukemia
Patel, J. P., Gönen, M., Figueroa, M. E., Fernandez, H. F., Sun, Z., Racevskis, J., Vlierberghe, P. V., Dolgalev, I., Thomas, S., Aminova, O., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1112304 · Cited by 1,990
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Döhner, H., Estey, E. H., Grimwade, D. J., Amadori, S., Appelbaum, F. R., Büchner, T., Dombret, H., Ebert, B. L., Fenaux, P., Larson, R. A., et al. (2016) · Blood · doi:10.1182/blood-2016-08-733196 · Cited by 5,938
Self-citationDöhner, H., Wei, A. H., Appelbaum, F. R., Craddock, C., Dinardo, C. D., Dombret, H., Ebert, B. L., Fenaux, P., Godley, L. A., Hasserjian, R. P., et al. (2022) · Blood · doi:10.1182/blood.2022016867 · Cited by 3,633
Self-citationArber, D. A., Orazi, A., Hasserjian, R. P., Borowitz, M. J., Calvo, K. R., Kvasnicka, H.-M., Wang, S. A., Bagg, A., Barbui, T., Branford, S., et al. (2022) · Blood · doi:10.1182/blood.2022015850 · Cited by 2,945
Self-citationMidostaurin plus Chemotherapy for Acute Myeloid Leukemia with a FLT3 Mutation
Stone, R. M., Mandrekar, S. J., Sanford, B. L., Laumann, K., Geyer, S., Bloomfield, C. D., Thiede, C., Prior, T. W., Döhner, K., Marcucci, G., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1614359 · Cited by 2,250
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Tyner, J. W., Tognon, C. E., Bottomly, D., Wilmot, B., Kurtz, S. E., Savage, S. L., Long, N., Schultz, A. R., Traer, E. A., Abel, M. L., et al. (2018) · Nature · doi:10.1038/s41586-018-0623-z · Cited by 1,359
Gilteritinib or Chemotherapy for Relapsed or Refractory FLT3 -Mutated AML
Perl, A. E., Martinelli, G., Cortes, J. E., Neubauer, A., Berman, E., Paolini, S., Montesinos, P., Baer, M. R., Larson, R. A., Ustun, C., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1902688 · Cited by 1,287
R-2HG Exhibits Anti-tumor Activity by Targeting FTO/m6A/MYC/CEBPA Signaling
Su, R., Dong, L., Li, C., Nachtergaele, S., Wunderlich, M., Qing, Y., Deng, X., Wang, Y., Weng, X., Hu, C., et al. (2018) · Cell · doi:10.1016/j.cell.2017.11.031 · Cited by 1,137
“80% of grade II-III gliomas and secondary glioblastoma (GBM), 10%–20% of acute myeloid leukemia (AML) patients, and at a lower rate in other cancers; most of these lesions involve mutations of arginine (R) residues in codon 132 for IDH1 (IDH1R132) and residues 140 and 172 for IDH2 (IDH2R140 and IDH2R172) (Brat et al.,…”
BackgroundInfluentialTargeting FLT3 mutations in AML: review of current knowledge and evidence
Daver, N. G., Schlenk, R. F., Russell, N. H., & Levis, M. J. (2019) · Leukemia · doi:10.1038/s41375-018-0357-9 · Cited by 1,106
Self-citationGenetic 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
Schuurhuis, G. J., Heuser, M., Freeman, S. D., Béné, M. C., Buccisano, F., Cloos, J. J., Grimwade, D. J., Haferlach, T., Hills, R. K., Hourigan, C. S., et al. (2018) · Blood · doi:10.1182/blood-2017-09-801498 · Cited by 1,072
Self-citationA 17-gene stemness score for rapid determination of risk in acute leukaemia
Ng, S. W. K., Mitchell, A., Kennedy, J. A., Chen, W. C., McLeod, J., Ibrahimova, N., Arruda, A., Popescu, A., Gupta, V., Schimmer, A. D., et al. (2016) · Nature · doi:10.1038/nature20598 · Cited by 912
Self-citationCoombs, C. C., Zehir, A., Devlin, S. M., Kishtagari, A., Syed, A., Jonsson, P., Hyman, D. M., Solit, D. B., Robson, M. E., Baselga, J., et al. (2017) · Cell stem cell · doi:10.1016/j.stem.2017.07.010 · Cited by 866
Prediction of acute myeloid leukaemia risk in healthy individuals
Abelson, S., Collord, G., Ng, S. W. K., Weissbrod, O., Mendelson Cohen, N., Niemeyer, E., Barda, N., Zuzarte, P. C., Heisler, L., Sundaravadanam, Y., et al. (2018) · Nature · doi:10.1038/s41586-018-0317-6 · Cited by 850
Self-citationBolouri, H., Farrar, J. E., Triche, T. J., Ries, R. E., Lim, E. L., Alonzo, T. A., Ma, Y. P., Moore, R. A., Mungall, A. J. J., Marra, M. A., et al. (2017) · Nature Medicine · doi:10.1038/nm.4439 · Cited by 869
Short, N. J., Rytting, M., & Cortes, J. E. (2018) · The Lancet · doi:10.1016/s0140-6736(18)31041-9 · Cited by 862
Acute myeloid leukemia: current progress and future directions
Kantarjian, H. M., Kadia, T. M., Dinardo, C. D., Daver, N. G., Borthakur, G. M., Jabbour, E., Garcia‐Manero, G., Konopleva, M. Y., & Ravandi, F. (2021) · Blood Cancer Journal · doi:10.1038/s41408-021-00425-3 · Cited by 823
Molecular Minimal Residual Disease in Acute Myeloid Leukemia
Jongen‐Lavrencic, M., Grob, T., Hanekamp, D., Kavelaars, F. G., Hinai, A. S. A. A., Zeilemaker, A., Erpelinck-Verschueren, C. A. J., Gradowska, P. L., Meijer, R. J., Cloos, J. J., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1716863 · Cited by 804
Cancer therapy shapes the fitness landscape of clonal hematopoiesis
Bolton, K. L., Ptashkin, R. N., Gao, T., Braunstein, L., Devlin, S. M., Kelly, D., Patel, M., Berthon, A., Syed, A., Yabe, M., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00710-0 · Cited by 751
Self-citationRestoration of TET2 Function Blocks Aberrant Self-Renewal and Leukemia Progression
Cimmino, L., Dolgalev, I., Wang, Y., Yoshimi, A., Martin, G. H., Wang, J., Ng, V., Xia, B., Witkowski, M. T., Mitchell-Flack, M., et al. (2017) · Cell · doi:10.1016/j.cell.2017.07.032 · Cited by 707
Wei, A. H., Strickland, S. A., Hou, J.-Z., Fiedler, W., Lin, T. L., Walter, R. B., Enjeti, A., Tiong, I. S., Savona, M., Lee, S., et al. (2019) · Journal of Clinical Oncology · doi:10.1200/jco.18.01600 · Cited by 692
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Sperling, A. S., Gibson, C. J., & Ebert, B. L. (2016) · Nature reviews. Cancer · doi:10.1038/nrc.2016.112 · Cited by 706
Bernard, E., Nannya, Y., Hasserjian, R. P., Devlin, S. M., Tuechler, H., Medina-Martinez, J. S., Yoshizato, T., Shiozawa, Y., Saiki, R., Malcovati, L., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1008-z · Cited by 648
Self-citationAcute Myeloid Leukemia, Version 3.2017, NCCN Clinical Practice Guidelines in Oncology
O'Donnell, M. R., Tallman, M. S., Abboud, C. N., Altman, J. K., Appelbaum, F. R., Arber, D. A., Bhatt, V. R., Bixby, D. L., Blum, W. G., Coutre, S. E., et al. (2017) · Journal of the National Comprehensive Cancer Network · doi:10.6004/jnccn.2017.0116 · Cited by 648
Classification and Personalized Prognosis in Myeloproliferative Neoplasms
Grinfeld, J., Nangalia, J., Baxter, E. J., Wedge, D. C., Angelopoulos, N., Cantrill, R., Godfrey, A. L., Papaemmanuil, E., Gundem, G., MacLean, C., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1716614 · Cited by 655
Self-citationSomatic mutations precede acute myeloid leukemia years before diagnosis
Desai, P., Mencia-Trinchant, N., Savenkov, O., Simon, M. S., Cheang, G., Lee, S., Samuel, M., Ritchie, E. K., Guzman, M. L., Ballman, K. V., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0081-z · Cited by 619
Burchert, A., Bug, G., Fritz, L. V., Finke, J., Stelljes, M., Röllig, C., Wollmer, E., Wäsch, R., Bornhäuser, M., Berg, T., et al. (2020) · Journal of Clinical Oncology · doi:10.1200/jco.19.03345 · Cited by 576
Genomics of Acute Myeloid Leukemia Diagnosis and Pathways
Bullinger, L., Döhner, K., & Döhner, H. (2017) · Journal of Clinical Oncology · doi:10.1200/jco.2016.71.2208 · Cited by 570
Self-citationThe menin inhibitor revumenib in KMT2A-rearranged or NPM1-mutant leukaemia
Issa, G. C., Aldoss, I. T., DiPersio, J. F., Cuglievan, B., Stone, R. M., Arellano, M. L., Thirman, M. J., Patel, M. R., Dickens, D. S., Shenoy, S. M., et al. (2023) · Nature · doi:10.1038/s41586-023-05812-3 · Cited by 531
Spectrum and prognostic relevance of driver gene mutations in acute myeloid leukemia
Metzeler, K. H., Herold, T., Rothenberg-Thurley, M., Amler, S., Sauerland, M. C., Görlich, D., Schneider, S., Konstandin, N. P., Dufour, A., Bräundl, K., et al. (2016) · Blood · doi:10.1182/blood-2016-01-693879 · Cited by 529
Single-cell mutation analysis of clonal evolution in myeloid malignancies
Miles, L. A., Bowman, R. L., Merlinsky, T. R., Csete, I., Ooi, A. T., Durruthy-Durruthy, R., Bowman, M., Famulare, C. A., Patel, M. A., Méndez, P., et al. (2020) · Nature · doi:10.1038/s41586-020-2864-x · Cited by 522
Biology and relevance of human acute myeloid leukemia stem cells
Thomas, D., & Majeti, R. (2017) · Blood · doi:10.1182/blood-2016-10-696054 · Cited by 517
Acute myeloid leukemia: 2023 update on diagnosis, risk‐stratification, and management
Shimony, S. O., Stahl, M. F., & Stone, R. M. (2023) · American Journal of Hematology · doi:10.1002/ajh.26822 · Cited by 494
Advances in acute myeloid leukemia
Newell, L. F., & Cook, R. J. (2021) · BMJ · doi:10.1136/bmj.n2026 · Cited by 461
Erba, H. P., Montesinos, P., Kim, H., Patkowska, E., Vrḫovac, R., Žák, P., Wang, P., Mitov, T., HANYOK, J. J., Kamel, Y. M., et al. (2023) · The Lancet · doi:10.1016/s0140-6736(23)00464-6 · Cited by 449
Self-citationClonal Hematopoiesis and Evolution to Hematopoietic Malignancies
Bowman, R. L., Busque, L., & Levine, R. L. (2018) · Cell stem cell · doi:10.1016/j.stem.2018.01.011 · Cited by 448
The IBD interactome: an integrated view of aetiology, pathogenesis and therapy
de Souza, H. S. P., Fiocchi, C., & Iliopoulos, D. (2017) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/nrgastro.2017.110 · Cited by 447
McMahon, C. M., Ferng, T., Canaani, J., Wang, E. S., Morrissette, J. J. D., Eastburn, D. J., Pellegrino, M., Durruthy-Durruthy, R., Watt, C. D., Asthana, S., et al. (2019) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-1453 · Cited by 446
Hourigan, C. S., Dillon, L. W., Gui, G., Logan, B. R., Fei, M., Ghannam, J. Y., Li, Y., Licon, A., Alyea, E. P., Bashey, A., et al. (2019) · Journal of Clinical Oncology · doi:10.1200/jco.19.03011 · Cited by 445
Acute Myeloid Leukemia, Version 3.2019, NCCN Clinical Practice Guidelines in Oncology
Tallman, M. S., Wang, E. S., Altman, J. K., Appelbaum, F. R., Bhatt, V. R., Bixby, D. L., Coutre, S. E., Lima, M. J. G. D., Fathi, A. T., Fiorella, M., et al. (2019) · Journal of the National Comprehensive Cancer Network · doi:10.6004/jnccn.2019.0028 · Cited by 423
Integrative Analysis of Drug Response and Clinical Outcome in Acute Myeloid Leukemia
Bottomly, D., Long, N., Schultz, A. R., Kurtz, S. E., Tognon, C. E., Johnson, K., Abel, M., Agarwal, A., Avaylon, S., Benton, E., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.07.002 · Cited by 403
The implications of IDH mutations for cancer development and therapy
Pirozzi, C. J., & Yan, H. (2021) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-021-00521-0 · Cited by 417
Short, N. J., Zhou, S., Fu, C., Berry, D. A., Walter, R. B., Freeman, S. D., Hourigan, C. S., Huang, X., González, G. N., Hwang, H., et al. (2020) · JAMA Oncology · doi:10.1001/jamaoncol.2020.4600 · Cited by 398
γδ T cells: origin and fate, subsets, diseases and immunotherapy
Hu, Y., Hu, Q., Li, Y., Lu, L., Xiang, Z., Yin, Z., Kabelitz, D., & Wu, Y. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01653-8 · Cited by 418
Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics
Morita, K., Wang, F., Jahn, K., Hu, T., Tanaka, T. N., Sasaki, Y., Kuipers, J., Loghavi, S., Wang, S. A., Yan, Y., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19119-8 · Cited by 411
Snowden, J. A., Sánchez‐Ortega, I., Corbacioglu, S., Basak, G. W., Chabannon, C., de la Cámara, R., Dolstra, H., Duarte, R. F., Glaß, B., Greco, R., et al. (2022) · Bone Marrow Transplantation · doi:10.1038/s41409-022-01691-w · Cited by 400
Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics
Nam, A. S., Chaligné, R., & Landau, D. A. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0265-5 · Cited by 399
Acute myeloid leukemia: 2019 update on risk‐stratification and management
Estey, E. H. (2018) · American Journal of Hematology · doi:10.1002/ajh.25214 · Cited by 374
The longitudinal dynamics and natural history of clonal haematopoiesis
Fabre, M. A., de Almeida, J. G., Fiorillo, E., Mitchell, E., Damaskou, A., Rak, J., Orrù, V., Marongiu, M., Chapman, M. S., Vijayabaskar, M. S., et al. (2022) · Nature · doi:10.1038/s41586-022-04785-z · Cited by 374
Self-citationAdvances in the Treatment of Acute Myeloid Leukemia: New Drugs and New Challenges
Short, N. J., Konopleva, M. Y., Kadia, T. M., Borthakur, G. M., Ravandi, F., Dinardo, C. D., & Daver, N. G. (2020) · Cancer Discovery · doi:10.1158/2159-8290.cd-19-1011 · Cited by 382
Ogawa, S. (2019) · Blood · doi:10.1182/blood-2018-10-844621 · Cited by 382
The genetic basis and cell of origin of mixed phenotype acute leukaemia
Alexander, T., Gu, Z., Iacobucci, I., Dickerson, K. M., Choi, J. K., Xu, B., Payne-Turner, D., Yoshihara, H., Loh, M. L., Horan, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0436-0 · Cited by 369
Enasidenib induces acute myeloid leukemia cell differentiation to promote clinical response
Amatangelo, M. D., Quek, L. S., Shih, A. H., Stein, E. M., Roshal, M., David, M. D., Marteyn, B., Farnoud, N. R., de Botton, S., Bernard, O., et al. (2017) · Blood · doi:10.1182/blood-2017-04-779447 · Cited by 358
Self-citationThe leukaemia stem cell: similarities, differences and clinical prospects in CML and AML
Vetrie, D. L. P., Helgason, G. V., & Copland, M. (2020) · Nature reviews. Cancer · doi:10.1038/s41568-019-0230-9 · Cited by 365
The PI3K-Akt-mTOR Signaling Pathway in Human Acute Myeloid Leukemia (AML) Cells
Nepstad, I., Hatfield, K. J., Grønningsæter, I. S., & Reikvam, H. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21082907 · Cited by 365
Isocitrate dehydrogenase mutations in myeloid malignancies
Medeiros, B. C., Fathi, A. T., Dinardo, C. D., Pollyea, D. A., Chan, S. M., & Swords, R. T. (2016) · Leukemia · doi:10.1038/leu.2016.275 · Cited by 348
NPM1-mutated acute myeloid leukemia: from bench to bedside
Falini, B., Brunetti, L., Sportoletti, P., & Martelli, M. P. (2020) · Blood · doi:10.1182/blood.2019004226 · Cited by 355
Zeng, A. G. X., Bansal, S., Jin, L., Mitchell, A., Chen, W. C., Abbas, H. A., Chan‐Seng‐Yue, M., Voisin, V., van Galen, P., Tierens, A. M., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01819-x · Cited by 353
Stein, E. M., Dinardo, C. D., Fathi, A. T., Pollyea, D. A., Stone, R. M., Altman, J. K., Roboz, G. J., Patel, M. R., Collins, R. H., Flinn, I. W., et al. (2018) · Blood · doi:10.1182/blood-2018-08-869008 · Cited by 330
Xuan, L., Wang, Y., Huang, F., Fan, Z., Xu, Y., Sun, J., Xu, N., Deng, L., Li, X., Liang, X., et al. (2020) · The Lancet Oncology · doi:10.1016/s1470-2045(20)30455-1 · Cited by 330
Qing, Y., Dong, L., Gao, L., Li, C., Li, Y., Han, L., Prince, E. A., Tan, B., Deng, X., Wetzel, C., et al. (2021) · Molecular Cell · doi:10.1016/j.molcel.2020.12.026 · Cited by 328
Mutant NPM1 Maintains the Leukemic State through HOX Expression
Brunetti, L., Gundry, M. C., Sorcini, D., Guzman, A. G., Huang, Y., Ramabadran, R., Gionfriddo, I., Mezzasoma, F., Milano, F., Nabet, B., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.08.005 · Cited by 331
FLT3 mutations in acute myeloid leukemia: Therapeutic paradigm beyond inhibitor development
Kiyoi, H., Kawashima, N., & Ishikawa, Y. (2019) · Cancer Science · doi:10.1111/cas.14274 · Cited by 325
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Sciarrillo, R., Wojtuszkiewicz, A., Assaraf, Y. G., Jansen, G., Kaspers, G. J. L., Giovannetti, E., & Cloos, J. J. (2020) · Drug Resistance Updates · doi:10.1016/j.drup.2020.100728 · Cited by 317
Grob, T., Al Hinai, A. S. A., Sanders, M. A., Kavelaars, F. G., Rijken, M., Gradowska, P. L., Biemond, B. J., Breems, D. A., Maertens, J., van Marwijk Kooy, M., et al. (2022) · Blood · doi:10.1182/blood.2021014472 · Cited by 305
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Prada‐Arismendy, J., Arroyave-Ospina, J. C., & Röthlisberger, S. (2016) · Blood Reviews · doi:10.1016/j.blre.2016.08.005 · Cited by 317
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Metadata
- Authors
- Papaemmanuil, E., Gerstung, M., Bullinger, L., Gaidzik, V. I., Paschka, P., Roberts, N. D., Potter, N. E., Heuser, M., Thol, F., Bolli, N., Gundem, G., Van Loo, P., Martincorena, I., Ganly, P., Mudie, L., McLaren, S., O’Meara, S., Raine, K., Jones, D. R., Teague, J. W., Butler, A. P., Greaves, M. F., Ganser, A., Döhner, K., Schlenk, R. F., Döhner, H., & Campbell, P. J.
- Affiliations
- European Bioinformatics Institute (GB)
- Wellcome Sanger Institute (GB)
- ORCID
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2016-06-09
- Volume
- 374
- Issue
- 23
- Pages
- 2209-2221
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- PMC
- PMC4979995
- OpenAlex
- W2419140434
- Cited by
- 4,350
- References
- 40
- Citations by year
- 2026: 345 · 2025: 403 · 2024: 468 · 2023: 460 · 2022: 551 · 2021: 583 · 2020: 481 · 2019: 415 · 2018: 286 · 2017: 282 · 2016: 63
- FWCI
- 331.83
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion)
- Lirias (KU Leuven) (submittedVersion)
- Funders
- Wellcome Trust (103858/Z/14/Z, 105104, 077012/Z/05/Z, 077012, 103858, 105104/Z/14/Z, WT088340MA)
- Francis Crick Institute (10202)
- Topics
- Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Retinoids in leukemia and cellular processes
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- acute myeloid leukemia, driver mutations, genomic subgroups, prognostic stratification, TP53 mutation, aneuploidy, NPM1 mutation, IDH2 mutation, gene-gene interaction, co-mutation patterns, overall survival, intensive treatment
- MeSH terms
- DNA Methyltransferase 3A, Nucleophosmin, Adult, DNA (Cytosine-5-)-Methyltransferases, DNA Mutational Analysis, Epistasis, Genetic, Genotype, Humans, Middle Aged, Mutation, Nuclear Proteins, Prognosis, Prospective Studies, RNA Splicing, Leukemia, Myeloid, Acute, Proportional Hazards Models, Survival Analysis, Intracellular Signaling Peptides and Proteins, Gene Fusion
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