The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing
Open accessAbstract
The sequencing of AML genomes of eight patients before and after relapse reveals two major patterns of clonal evolution, with chemotherapy appearing to have a role in both patterns. Many patients with acute myeloid leukaemia (AML) achieve remission, but it is often short-lived and the returned disease is usually refractory to therapy. Genome sequencing of eight patients with AML before and after relapse reveals two major patterns of tumour cell evolution. The founding clone survives chemotherapy in all patients, and, in one clonal pattern, it acquires new mutations and expands at relapse. In the other, a subclone surviving from the original tumour expands and then acquires new mutations. Comparisons of relapse-specific and primary tumour mutations point to an increase in transversions, implying DNA damage caused by cytotoxic chemotherapy. This work demonstrates that the AML genome in an individual patient presents a moving target, and highlights the importance of striving to eradicate both the founding clone and all of its subclones. Most patients with acute myeloid leukaemia (AML) die from progressive disease after relapse, which is associated with clonal evolution at the cytogenetic level1,2 . To determine the mutational spectrum associated with relapse, we sequenced the primary tumour and relapse genomes from eight AML patients, and validated hundreds of somatic mutations using deep sequencing; this allowed us to define clonality and clonal evolution patterns precisely at relapse. In addition to discovering novel, recurrently mutated genes (for example, WAC, SMC3, DIS3, DDX41 and DAXX) in AML, we also found two major clonal evolution patterns during AML relapse: (1) the founding clone in the primary tumour gained mutations and evolved into the relapse clone, or (2) a subclone of the founding clone survived initial therapy, gained additional mutations and expanded at relapse. In all cases, chemotherapy failed to eradicate the founding clone. The comparison of relapse-specific versus primary tumour mutations in all eight cases revealed an increase in transversions, probably due to DNA damage caused by cytotoxic chemotherapy. These data demonstrate that AML relapse is associated with the addition of new mutations and clonal evolution, which is shaped, in part, by the chemotherapy that the patients receive to establish and maintain remissions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Indeed, several recent studies have shown a similar spectrum of genetic alterations to those observed here during the somatic evolution of cancers in patients undergoing chemotherapy (Podlaha et al., 2012; Landau et al., 2013) or treated with specific inhibitors (Ding et al., 2012) to those observed here.”
From The evolution of drug resistance in clinical isolates of Candida albicans. (2015) · cites this paper as Ding et al., 2012
In the citing paper
“For example, the clonal architecture of de novo AML is dynamic, with certain (often minor) subclones becoming dominant at relapse following chemotherapy 9.”
From Role of TP53 mutations in the origin and evolution of therapy-related acute myeloid leukaemia (2015) · cites this paper as [9]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Somatic mutations affect key pathways in lung adenocarcinoma
Ding, L., Getz, G., Wheeler, D. A., Mardis, E. R., McLellan, M. D., Cibulskis, K., Sougnez, C., Greulich, H., Muzny, D. M., Morgan, M. B., et al. (2008) · Nature · doi:10.1038/nature07423 · Cited by 2,681
Self-citationTumour evolution inferred by single-cell sequencing
Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., Cook, K., Stepansky, A., Levy, D., Esposito, D., et al. (2011) · Nature · doi:10.1038/nature09807 · Cited by 2,598
Distant metastasis occurs late during the genetic evolution of pancreatic cancer
Yachida, S., Jones, S., Bozic, I., Antal, T., Leary, R., Fu, B., Kamiyama, M., Hruban, R. H., Eshleman, J. R., Nowak, M. A., et al. (2010) · Nature · doi:10.1038/nature09515 · Cited by 2,502
Recurring mutations found by sequencing an acute myeloid leukemia genome
Mardis, E. R., Ding, L., Dooling, D. J., Larson, D. E., McLellan, M. D., Chen, K., Koboldt, D. C., Fulton, R. S., Delehaunty, K. D., McGrath, S. D., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0903840 · Cited by 2,219
Self-citationWard, P. S., Patel, J., Wise, D. R., Abdel-Wahab, O., Bennett, B. D., Coller, H. A., Cross, J. R., Fantin, V. R., Hedvat, C. V., Perl, A. E., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.01.020 · Cited by 2,020
DNMT3A Mutations in Acute Myeloid Leukemia
Ley, T. J., Ding, L., Walter, M. J., McLellan, M. D., Lamprecht, T., Larson, D. E., Kandoth, C., Payton, J. E., Baty, J., Welch, J., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1005143 · Cited by 1,983
Self-citationCytoplasmic Nucleophosmin in Acute Myelogenous Leukemia with a Normal Karyotype
Falini, B., Mecucci, C., Tiacci, E., Alcalay, M., Rosati, R., Pasqualucci, L., La Starza, R., Diverio, D., Colombo, E., Santucci, A., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa041974 · Cited by 1,892
Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia
Puente, X. S., Pinyol, M., Quesada, V., Conde, L., Ordóñez, G. R., Villamor, N., Escaramís, G., Jares, P., Beà, S., González, M., et al. (2011) · Nature · doi:10.1038/nature10113 · Cited by 1,529
BreakDancer: an algorithm for high-resolution mapping of genomic structural variation
Chen, K., Wallis, J. W., McLellan, M. D., Larson, D. E., Kalicki, J. M., Pohl, C. S., McGrath, S. D., Wendl, M. C., Zhang, Q., Locke, D. P., et al. (2009) · Nature Methods · doi:10.1038/nmeth.1363 · Cited by 1,489
Flagged first, then by citations
Cited by
Sorted by citations
Items 101–200 of 999
Mutational and structural analysis of diffuse large B-cell lymphoma using whole-genome sequencing
Morin, R. D., Mungall, K., Pleasance, E., Mungall, A. J. J., Goya, R., Huff, R. D., Scott, D. W., Ding, J., Roth, A. J. L., Chiu, R., et al. (2013) · Blood · doi:10.1182/blood-2013-02-483727 · Cited by 407
Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia
Li, S., Garrett-Bakelman, F. E., Chung, S. S., Sanders, M. A., Hricik, T., Rapaport, F., Patel, J. L., Dillon, R. J., Vijay, P., Brown, A. L., et al. (2016) · Nature Medicine · doi:10.1038/nm.4125 · Cited by 396
Taxanes in cancer treatment: Activity, chemoresistance and its overcoming
Mosca, L., Ilari, A., Fazi, F., Assaraf, Y. G., & Colotti, G. (2021) · Drug Resistance Updates · doi:10.1016/j.drup.2020.100742 · Cited by 406
Single Cell Isolation and Analysis
Hu, P., Zhang, W., Xin, H., & Deng, G. Y. (2016) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2016.00116 · Cited by 401
Recurrent mutations in multiple components of the cohesin complex in myeloid neoplasms
Kon, A., Shih, L., Minamino, M., Sanada, M., Shiraishi, Y., Nagata, Y., Yoshida, K., Okuno, Y., Bando, M., Nakato, R., et al. (2013) · Nature Genetics · doi:10.1038/ng.2731 · Cited by 396
Heterogeneity of epidermal growth factor receptor signalling networks in glioblastoma
Furnari, F. B., Cloughesy, T. F., Cavenee, W. K., & Mischel, P. S. (2015) · Nature reviews. Cancer · doi:10.1038/nrc3918 · Cited by 389
The landscape of somatic mutations in Down syndrome–related myeloid disorders
Yoshida, K., Toki, T., Okuno, Y., Kanezaki, R., Shiraishi, Y., Sato‐Otsubo, A., Sanada, M., Park, M.-J., Terui, K., Suzuki, H., et al. (2013) · Nature Genetics · doi:10.1038/ng.2759 · Cited by 393
Ha, G., Roth, A. J. L., Khattra, J. S., Ho, J., Yap, D., Prentice, L., Melnyk, N., McPherson, A., Bashashati, A., Laks, E., et al. (2014) · Genome Research · doi:10.1101/gr.180281.114 · Cited by 372
Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor
Islam, S. M. A., Díaz‐Gay, M., Wu, Y., Barnes, M. D., Vangara, R., Bergstrom, E. N., He, Y., Vella, M., Wang, J., Teague, J. W., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100179 · Cited by 364
Germline ETV6 mutations in familial thrombocytopenia and hematologic malignancy
Zhang, M. Y., Churpek, J. E., Keel, S., Walsh, T., Lee, M. K., Loeb, K. R., Gülsüner, S., Pritchard, C. C., Sánchez-Bonilla, M., Delrow, J. J., et al. (2015) · Nature Genetics · doi:10.1038/ng.3177 · Cited by 376
Rise and fall of subclones from diagnosis to relapse in pediatric B-acute lymphoblastic leukaemia
Ma, X., Edmonson, M. N., Yergeau, D. A., Muzny, D. M., Hampton, O. A., Rusch, M., Song, G., Easton, J. B., Harvey, R. C., Wheeler, D. A., et al. (2015) · Nature Communications · doi:10.1038/ncomms7604 · Cited by 353
Distribution and levels of cell surface expression of CD33 and CD123 in acute myeloid leukemia
Ehninger, A., Krämer, M., Röllig, C., Thiede, C., Bornhäuser, M., Bonin, M. V., Wermke, M., Feldmann, A., Bachmann, M. P., Ehninger, G., et al. (2014) · Blood Cancer Journal · doi:10.1038/bcj.2014.39 · Cited by 352
The evolution of drug resistance in clinical isolates of Candida albicans.
Ford, C. B., Funt, J. M., Abbey, D., Issi, L., Guiducci, C., Martinez, D. A., Delorey, T., Li, B. Y., White, T. C., Cuomo, C., et al. (2015) · eLife · doi:10.7554/elife.00662 · Cited by 348
The Implications of Clonal Genome Evolution for Cancer Medicine
Aparicio, S. A. J. R., & Caldas, C. (2013) · New England Journal of Medicine · doi:10.1056/nejmra1204892 · Cited by 361
Tumor evolution: Linear, branching, neutral or punctuated?
Davis, A., Gao, R., & Navin, N. E. (2017) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2017.01.003 · Cited by 371
The 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
Maze, I. S., Noh, K., Soshnev, A. A., & Allis, C. D. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3673 · Cited by 376
Acute Myeloid Leukemia: A Concise Review
Saultz, J. N., & Garzon, R. (2016) · Journal of Clinical Medicine · doi:10.3390/jcm5030033 · Cited by 363
Role of integrated cancer nanomedicine in overcoming drug resistance
Iyer, A. K., Singh, A., Ganta, S., & Amiji, M. M. (2013) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2013.07.012 · Cited by 343
Klco, J. M., Miller, C. A., Griffith, M., Petti, A. A., Spencer, D. H., Ketkar-Kulkarni, S., Wartman, L. D., Christopher, M. J., Westover, T., Helton, N. M., et al. (2015) · JAMA · doi:10.1001/jama.2015.9643 · Cited by 341
Divergent clonal selection dominates medulloblastoma at recurrence
Morrissy, A. S., Garzia, L., Shih, D. J. H., Zuyderduyn, S., Huang, X., Skowron, P., Remke, M., Cavalli, F. M. G., Ramaswamy, V., Lindsay, P. E., et al. (2016) · Nature · doi:10.1038/nature16478 · Cited by 336
Next-generation sequencing and its clinical application
Dahui, Q. (2019) · Cancer Biology and Medicine · doi:10.20892/j.issn.2095-3941.2018.0055 · Cited by 334
Insights into new mechanisms and models of cancer stem cell multidrug resistance
Garcia‐Mayea, Y., Mir, C., Masson, F., Paciucci, R., & LLeonart, M. E. (2019) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2019.07.022 · Cited by 332
Schuh, A., Becq, J., Humphray, S., Alexa, A., Burns, A., Clifford, R. M., Feller, S. M., Grocock, R., Henderson, S. J., Khrebtukova, I., et al. (2012) · Blood · doi:10.1182/blood-2012-05-433540 · Cited by 321
Cancer genomics: one cell at a time
Navin, N. E. (2014) · Genome biology · doi:10.1186/s13059-014-0452-9 · Cited by 318
The evolution of tumour phylogenetics: principles and practice
Schwartz, R. S., & Schäffer, A. A. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.170 · Cited by 329
Spatiotemporal Evolution of the Primary Glioblastoma Genome
Kim, J., Lee, I., Cho, H. J., Park, C., Jung, Y.-S., Kim, Y., Nam, S. H., Kim, B. S., Johnson, M. D., Kong, D., et al. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.07.013 · Cited by 328
Hu, Q., Sun, W., Wang, J., Ruan, H., Zhang, X., Ye, Y., Shen, S., Wang, C., Lu, W., Cheng, K., et al. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0310-2 · Cited by 315
Tree inference for single-cell data
Jahn, K., Kuipers, J., & Beerenwinkel, N. (2016) · Genome biology · doi:10.1186/s13059-016-0936-x · Cited by 307
Molecular biomarkers in acute myeloid leukemia
Prada‐Arismendy, J., Arroyave-Ospina, J. C., & Röthlisberger, S. (2016) · Blood Reviews · doi:10.1016/j.blre.2016.08.005 · Cited by 317
Mutant Cohesin in Premature Ovarian Failure
Caburet, S., Arboleda, V. A., Llano, E., Overbeek, P. A., Barbero, J. L., Oka, K., Harrison, W. R., Vaiman, D., Ben‐Neriah, Z., García‐Tuñón, I., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1309635 · Cited by 303
Poised epigenetic states and acquired drug resistance in cancer
Brown, R., Curry, E., Magnani, L., Wilhelm-Benartzi, C. S., & Borley, J. (2014) · Nature Reviews Cancer · doi:10.1038/nrc3819 · Cited by 301
Implementing personalized cancer genomics in clinical trials
Simon, R. M., & Roychowdhury, S. (2013) · Nature Reviews Drug Discovery · doi:10.1038/nrd3979 · Cited by 309
Pan-cancer analysis of intratumor heterogeneity as a prognostic determinant of survival
Morris, L. G. T., Riaz, N., Desrichard, A., Şenbabaoğlu, Y., Hakimi, A. A., Makarov, V., Reis-Filho, J. S., & Chan, T. A.-T. (2016) · Oncotarget · doi:10.18632/oncotarget.7067 · Cited by 307
Thol, F. R., Gabdoulline, R. R., Liebich, A., Klement, P., Schiller, J., Kandziora, C., Hambach, L., Stadler, M., Koenecke, C., Flintrop, M., et al. (2018) · Blood · doi:10.1182/blood-2018-02-829911 · Cited by 301
Midostaurin approved for FLT3-mutated AML
Levis, M. J. (2017) · Blood · doi:10.1182/blood-2017-05-782292 · Cited by 300
EGFR Variant Heterogeneity in Glioblastoma Resolved through Single-Nucleus Sequencing
Francis, J. M., Zhang, C.-Z., Maire, C. L., Jung, J., Manzo, V. E., Adalsteinsson, V. A., Homer, H., Haidar, S., Blumenstiel, B., Pedamallu, C. S., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0879 · Cited by 287
Johanns, T. M., Miller, C. A., Dorward, I. G., Tsien, C. I., Chang, E. F., Perry, A., Uppaluri, R., Ferguson, C., Schmidt, R. E., Dahiya, S. M., et al. (2016) · Cancer Discovery · doi:10.1158/2159-8290.cd-16-0575 · Cited by 297
Preclinical studies of gilteritinib, a next-generation FLT3 inhibitor
Lee, L. Y., Hernandez, D., Rajkhowa, T., Smith, S. C. L., Raman, J., Nguyen, B., Small, D., & Levis, M. J. (2016) · Blood · doi:10.1182/blood-2016-10-745133 · Cited by 286
Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics
Gawad, C., Koh, W. L. C., & Quake, S. R. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1420822111 · Cited by 283
Almendro, V., Cheng, Y.-K., Randles, A. P., Itzkovitz, S., Marusyk, A., Ametller, E., González, X., Muñoz-Mateu, M., Russnes, H. G., Helland, Å., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2013.12.041 · Cited by 274
Polytherapy and Targeted Cancer Drug Resistance
Chatterjee, N., & Bivona, T. G. (2019) · Trends in cancer · doi:10.1016/j.trecan.2019.02.003 · Cited by 277
Clonal evolution in relapsed NPM1-mutated acute myeloid leukemia
Krönke, J., Bullinger, L., Teleanu, V., Tschürtz, F., Gaidzik, V. I., Kühn, M. W. M., Rücker, F. G., Holzmann, K., Paschka, P., Kapp‐Schwoerer, S., et al. (2013) · Blood · doi:10.1182/blood-2013-01-479188 · Cited by 286
The genomic landscape of core-binding factor acute myeloid leukemias
Faber, Z. J., Chen, X. '., Gedman, A. L., Boggs, K., Cheng, J., Ma, J., Radtke, I., Chao, J.-R., Walsh, M. P., Song, G., et al. (2016) · Nature Genetics · doi:10.1038/ng.3709 · Cited by 276
Building a lineage from single cells: genetic techniques for cell lineage tracking
Woodworth, M. B., Girskis, K. M., & Walsh, C. A. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.159 · Cited by 236
Current therapy and drug resistance in metastatic castration-resistant prostate cancer
Cai, M., Song, X., Li, X., Chen, M., Guo, J., Yang, D., Chen, Z., & Zhao, S. (2023) · Drug Resistance Updates · doi:10.1016/j.drup.2023.100962 · Cited by 278
Oncogene addiction: pathways of therapeutic response, resistance, and road maps toward a cure
Pagliarini, R. A., Shao, W., & Sellers, W. R. (2015) · EMBO Reports · doi:10.15252/embr.201439949 · Cited by 264
Leukemic stem cells and therapy resistance in acute myeloid leukemia
Stelmach, P., & Trumpp, A. (2023) · Haematologica · doi:10.3324/haematol.2022.280800 · Cited by 273
Drug repositioning for personalized medicine
Li, Y. Y., & Jones, S. J. M. (2012) · Genome Medicine · doi:10.1186/gm326 · Cited by 264
Accuracy of Next Generation Sequencing Platforms
Fox, E., & Reid-Bayliss, K. S. (2014) · Journal of Next Generation Sequencing & Applications · doi:10.4172/2469-9853.1000106 · Cited by 271
Role of intratumoural heterogeneity in cancer drug resistance: molecular and clinical perspectives
Saunders, N. A., Simpson, F., Thompson, E. W., Hill, M. M. C., Endo‐Munoz, L., Leggatt, G. R., Minchin, R. F., & Guminski, A. D. (2012) · EMBO Molecular Medicine · doi:10.1002/emmm.201101131 · Cited by 252
Histological Transformation and Progression in Follicular Lymphoma: A Clonal Evolution Study
Kridel, R., Chan, F. C., Mottok, A., Boyle, M., Farinha, P., Tan, K. L., Meissner, B., Bashashati, A., McPherson, A., Roth, A. J. L., et al. (2016) · PLoS Medicine · doi:10.1371/journal.pmed.1002197 · Cited by 245
Clonality inference in multiple tumor samples using phylogeny
Malikić, S., McPherson, A., Donmez, N., & Şahinalp, S. C. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv003 · Cited by 248
Tracking Genomic Cancer Evolution for Precision Medicine: The Lung TRACERx Study
Jamal‐Hanjani, M., Hackshaw, A., Ngai, Y., Shaw, J., Dive, C., Quezada, S. A., Middleton, G., de Bruin, E. C., Quesne, J. P. C. L., Shafi, S., et al. (2014) · PLoS Biology · doi:10.1371/journal.pbio.1001906 · Cited by 247
Walker, B. A., Wardell, C. P., Melchor, L., Wilson, S. H., Potter, N. E., Johnson, D. C., Fenwick, K., Kozarewa, I., Gonzalez, D., Lord, C. J., et al. (2012) · Blood · doi:10.1182/blood-2012-03-412981 · Cited by 246
Genomic Instability in Cancer: Teetering on the Limit of Tolerance
Andor, N., Maley, C. C., & Ji, H. P. (2017) · Cancer Research · doi:10.1158/0008-5472.can-16-1553 · Cited by 246
Chronic lymphocytic leukaemia: from genetics to treatment
Bosch, F., & Dalla‐Favera, R. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0239-8 · Cited by 259
Evolutionary biology of high-risk multiple myeloma
Pawlyn, C., & Morgan, G. J. (2017) · Nature reviews. Cancer · doi:10.1038/nrc.2017.63 · Cited by 242
Fan, J., Lee, H., Lee, S., Ryu, D., Lee, S., Xue, C., Kim, S. J., Kım, K., Barkas, N., Park, P. J., et al. (2018) · Genome Research · doi:10.1101/gr.228080.117 · Cited by 228
Measurable residual disease testing in acute myeloid leukaemia
Hourigan, C. S., Gale, R. P., Gormley, N. J., Ossenkoppele, G. J., & Walter, R. B. (2017) · Leukemia · doi:10.1038/leu.2017.113 · Cited by 239
Epigenetic Memory Underlies Cell-Autonomous Heterogeneous Behavior of Hematopoietic Stem Cells
Yu, V. W. C., Yusuf, R. Z., Oki, T., Wu, J. W., Sáez, B., Wang, X., Cook, C., Baryawno, N., Ziller, M. J., Lee, E., et al. (2017) · Cell · doi:10.1016/j.cell.2017.02.010 · Cited by 239
Dnmt3a loss predisposes murine hematopoietic stem cells to malignant transformation
Mayle, A., Yang, L., Rodriguez, B., Zhou, T., Chang, E., Curry, C. V., Challen, G. A., Li, W., Wheeler, D., Rebel, V. I., et al. (2015) · Blood · doi:10.1182/blood-2014-08-594648 · Cited by 235
Melchor, L., Brioli, A., Wardell, C. P., Murison, A., Potter, N. E., Kaiser, M., Fryer, R. A., Johnson, D. C., Begum, D. B., Wilson, S. H., et al. (2014) · Leukemia · doi:10.1038/leu.2014.13 · Cited by 237
Evolution of acute myelogenous leukemia stem cell properties after treatment and progression
Ho, T., LaMere, M. W., Stevens, B. M., Ashton, J. M., Myers, J. R., O’Dwyer, K. M., Liesveld, J. L., Mendler, J. H., Guzmán, M. L., Morrissette, J. D., et al. (2016) · Blood · doi:10.1182/blood-2016-02-695312 · Cited by 241
Fast and scalable inference of multi-sample cancer lineages
Popic, V., Salari, R., Hajirasouliha, I., Kashef-Haghighi, D., West, R. B., & Batzoglou, S. (2015) · Genome biology · doi:10.1186/s13059-015-0647-8 · Cited by 231
THetA: inferring intra-tumor heterogeneity from high-throughput DNA sequencing data
Oesper, L., Mahmoody, A., & Raphael, B. J. (2013) · Genome biology · doi:10.1186/gb-2013-14-7-r80 · Cited by 229
The influence of subclonal resistance mutations on targeted cancer therapy
Schmitt, M. W., Loeb, L. A., & Salk, J. J. (2015) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2015.175 · Cited by 234
Cancer stem cells: In the line of fire
Alison, M. R., Lin, W., Lim, S. M. L., & Nicholson, L. J. (2012) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2012.03.003 · Cited by 228
Targeting multiple signaling pathways: the new approach to acute myeloid leukemia therapy
Carter, J. L., Hege-Hurrish, K., Yang, J., Kalpage, H. A., Su, Y., Edwards, H. J., Hüttemann, M., Taub, J. W., & Ge, Y. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-00361-x · Cited by 230
From single cells to deep phenotypes in cancer
Bendall, S. C., & Nolan, G. P. (2012) · Nature Biotechnology · doi:10.1038/nbt.2283 · Cited by 225
Fujimoto, A., Furuta, M., Shiraishi, Y., Gotoh, K., Kawakami, Y., Arihiro, K., Nakamura, T., Ueno, M., Ariizumi, S.-I., Hà, N. H., et al. (2015) · Nature Communications · doi:10.1038/ncomms7120 · Cited by 223
Reconstruction of clonal trees and tumor composition from multi-sample sequencing data
El-Kebir, M., Oesper, L., Acheson-Field, H., & Raphael, B. J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv261 · Cited by 219
Jiang, Y., Qiu, Y. L., Minn, A. J., & Zhang, N. R. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1522203113 · Cited by 216
Raphael, B. J., Dobson, J. R., Oesper, L., & Vandin, F. (2014) · Genome Medicine · doi:10.1186/gm524 · Cited by 226
Cancer pharmacogenomics: strategies and challenges
Wheeler, H. E., Maitland, M. L., Dolan, M. E., Cox, N. J., & Ratain, M. J. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3352 · Cited by 221
Mechanisms of drug resistance in acute myeloid leukemia
Zhang, J., Gu, Y., & Chen, B. (2019) · OncoTargets and Therapy · doi:10.2147/ott.s191621 · Cited by 221
PLCG1 mutations in cutaneous T-cell lymphomas
Vaqué, J. P., Gómez-López, G., Monsálvez, V., Varela, I., Martínez, N., Pérez, C., Domínguez, O., Graña, O., Rodríguez-Peralto, J. L., Rodríguez-Pinilla, S. M., et al. (2014) · Blood · doi:10.1182/blood-2013-05-504308 · Cited by 229
Intratumoral Heterogeneity of the Epigenome
Mazor, T., Pankov, A., Song, J. S., & Costello, J. (2016) · Cancer Cell · doi:10.1016/j.ccell.2016.03.009 · Cited by 217
Rusch, M., Nakitandwe, J., Shurtleff, S. A., Newman, S., Zhang, Z., Edmonson, M. N., Parker, M. D., Jiao, Y., Ma, X., Liu, Y., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06485-7 · Cited by 219
CD34+CD38− leukemic stem cell frequency to predict outcome in acute myeloid leukemia
Zeijlemaker, W., Grob, T., Meijer, R. J., Hanekamp, D., Kelder, A., Carbaat-Ham, J. C., Oussoren-Brockhoff, Y. J. M., Snel, A. N., Veldhuizen, D., Scholten, W. J., et al. (2018) · Leukemia · doi:10.1038/s41375-018-0326-3 · Cited by 228
Emergence of New ALK Mutations at Relapse of Neuroblastoma
Schleiermacher, G., Javanmardi, N., Bernard, V., Leroy, Q., Cappo, J., Frio, T. R., Pierron, G., Lapouble, E., Combaret, V., Speleman, F., et al. (2014) · Journal of Clinical Oncology · doi:10.1200/jco.2013.54.0674 · Cited by 216
Pediatric AML: From Biology to Clinical Management
de Rooij, J. D. E., Zwaan, C. M., & van den Heuvel‐Eibrink, M. M. (2015) · Journal of Clinical Medicine · doi:10.3390/jcm4010127 · Cited by 224
Profiling of somatic mutations in acute myeloid leukemia with FLT3-ITD at diagnosis and relapse
Garg, M., Nagata, Y., Kanojia, D., Mayakonda, A., Yoshida, K., Keloth, S. H., Zang, Z. J., Okuno, Y., Shiraishi, Y., Chiba, K., et al. (2015) · Blood · doi:10.1182/blood-2015-05-646240 · Cited by 212
Recurrent somatic mutations of PTPN1 in primary mediastinal B cell lymphoma and Hodgkin lymphoma
Gunawardana, J., Chan, F. C., Telenius, A., Woolcock, B. W., Kridel, R., Tan, K. L., Ben‐Neriah, S., Mottok, A., Lim, R. S., Boyle, M., et al. (2014) · Nature Genetics · doi:10.1038/ng.2900 · Cited by 216
Cancer: Evolution Within a Lifetime
Gerlinger, M., McGranahan, N., Dewhurst, S. M., Burrell, R. A., Tomlinson, I. P. M., & Swanton, C. (2014) · Annual Review of Genetics · doi:10.1146/annurev-genet-120213-092314 · Cited by 210
Scalable whole-genome single-cell library preparation without preamplification
Zahn, H., Steif, A., Laks, E., Eirew, P. D., VanInsberghe, M. A., Shah, S. P., Aparicio, S. A. J. R., & Hansen, C. L. (2017) · Nature Methods · doi:10.1038/nmeth.4140 · Cited by 199
A review of FLT3 inhibitors in acute myeloid leukemia
Zhao, J. C., Agarwal, S., Ahmad, H., Amin, K., Bewersdorf, J. P., & Zeidan, A. M. (2021) · Blood Reviews · doi:10.1016/j.blre.2021.100905 · Cited by 211
An empirical Bayesian framework for somatic mutation detection from cancer genome sequencing data
Shiraishi, Y., Sato, Y., Chiba, K., Okuno, Y., Nagata, Y., Yoshida, K., Shiba, N., Hayashi, Y., Kume, H., Homma, Y., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt126 · Cited by 202
Genetic landscape of metastatic and recurrent head and neck squamous cell carcinoma
Hedberg, M. L., Goh, G., Chiosea, S. I., Bauman, J. E., Freilino, M. L., Zeng, Y., Wang, L., Diergaarde, B. B., Gooding, W. E., Lui, V. W. Y., et al. (2015) · Journal of Clinical Investigation · doi:10.1172/jci82066 · Cited by 208
Disease evolution and outcomes in familial AML with germline CEBPA mutations
Tawana, K., Wang, J., Renneville, A., Bödör, C., Hills, R. K., Loveday, C., Savić, A., van Delft, F. W., Treleaven, J. G., Georgiades, P., et al. (2015) · Blood · doi:10.1182/blood-2015-05-647172 · Cited by 207
Epigenetic Memory Underlies Cell-Autonomous Heterogeneous Behavior of Hematopoietic Stem Cells
Yu, V. W. C., Yusuf, R. Z., Oki, T., Wu, J. W., Sáez, B., Wang, X., Cook, C., Baryawno, N., Ziller, M. J., Lee, E., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.045 · Cited by 207
Leukemia Propagating Cells Rebuild an Evolving Niche in Response to Therapy
Duan, C.-W., Shi, J., Chen, J., Wang, B., Yu, Y.-H., Qin, X., Zhou, X.-C., Cai, Y.-J., Li, Z.-Q., Zhang, F., et al. (2014) · Cancer Cell · doi:10.1016/j.ccr.2014.04.015 · Cited by 198
Studer, R. A., Dessailly, B. H., & Orengo, C. A. (2013) · Biochemical Journal · doi:10.1042/bj20121221 · Cited by 202
Optimizing Cancer Genome Sequencing and Analysis
Griffith, M., Miller, C. A., Griffith, O. L., Krysiak, K., Skidmore, Z. L., Ramu, A., Walker, J., Dang, H. X., Trani, L., Larson, D. E., et al. (2015) · Cell Systems · doi:10.1016/j.cels.2015.08.015 · Cited by 195
Genetic and epigenetic heterogeneity in acute myeloid leukemia
Li, S., Mason, C. E., & Melnick, A. M. (2016) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2016.03.011 · Cited by 195
Oshima, K., Khiabanian, H., da Silva-Almeida, A. C., Tzoneva, G., Abate, F., Ambesi‐Impiombato, A., Sánchez-Martín, M., Carpenter, Z., Penson, A., Pérez-García, A., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608420113 · Cited by 196
Molecular and cellular heterogeneity: the hallmark of glioblastoma
Aum, D. J., Kim, D. H., Beaumont, T., Leuthardt, E. C., Dunn, G. P., & Kim, A. H. (2014) · Neurosurgical FOCUS · doi:10.3171/2014.9.focus14521 · Cited by 200
Size Does Matter: Why Polyploid Tumor Cells are Critical Drug Targets in the War on Cancer
Coward, J. I. G., & Harding, A. S. (2014) · Frontiers in Oncology · doi:10.3389/fonc.2014.00123 · Cited by 197
Tumour evolution and microenvironment interactions in 2D and 3D space
Mo, C.-K., Liu, J., Chen, S., Storrs, E. P., da Costa, A. L. N. T., Houston, A., Wendl, M. C., Jayasinghe, R. G., Iglesia, M. D., Ma, C., et al. (2024) · Nature · doi:10.1038/s41586-024-08087-4 · Cited by 198
Metadata
- Authors
- Ding, L., Ley, T. J., Larson, D. E., Miller, C. A., Koboldt, D. C., Welch, J. S., Ritchey, J. K., Young, M. A., Lamprecht, T., McLellan, M. D., McMichael, J. F., Wallis, J. W., Lu, C., Shen, D., Harris, C. C., Dooling, D. J., Fulton, R. S., Fulton, L. L., Chen, K., Schmidt, H., Kalicki-Veizer, J., Magrini, V. J., Cook, L., McGrath, S. D., Vickery, T. L., Wendl, M. C., Heath, S., Watson, M. A., Link, D. C., Tomasson, M. H., Shannon, W. D., Payton, J. E., Kulkarni, S., Westervelt, P., Walter, M. J., Graubert, T. A., Mardis, E. R., Wilson, R. K., & DiPersio, J. F.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Ley, Timothy J.
- ORCID
- Ding, Li
- Ley, Timothy J.
- Larson, David E.
- Miller, Christopher A.
- Koboldt, Daniel C.
- Welch, John S.
- Ritchey, Julie K.
- McLellan, Michael D.
- McMichael, Joshua F.
- Lu, Charles
- Shen, Dong
- Fulton, Robert S.
- Fulton, Lucinda L.
- Chen, Ken
- Magrini, Vincent J.
- McGrath, Sean D.
- Vickery, Tammi L.
- Wendl, Michael C.
- Heath, Sharon
- Watson, Mark A.
- Link, Daniel C.
- Tomasson, Michael H.
- Payton, Jacqueline E.
- Kulkarni, Shashikant
- Walter, Matthew J.
- Graubert, Timothy A.
- Mardis, Elaine R.
- Wilson, Richard K.
- DiPersio, John F.
- Venue
- Nature
- Published
- 2012-01
- Volume
- 481
- Issue
- 7382
- Pages
- 506-510
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3267864
- OpenAlex
- W2093144236
- Cited by
- 1,993
- References
- 30
- Citations by year
- 2026: 55 · 2025: 50 · 2024: 61 · 2023: 74 · 2022: 116 · 2021: 138 · 2020: 134 · 2019: 151 · 2018: 155 · 2017: 160 · 2016: 197 · 2015: 192 · 2014: 210 · 2013: 182 · 2012: 118
- FWCI
- 149.48
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Foundation for Barnes-Jewish Hospital (00335-0505-02)
- National Human Genome Research Institute (U54HG003079, HG003079, NHGRI U54 HG003079)
- National Cancer Institute (PO1CA101937, CA101937, P01CA101937)
- Topics
- Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- acute myeloid leukemia, relapse, clonal evolution, somatic mutations, subclones, chemotherapy-induced DNA damage, transversions, recurrently mutated genes, WAC, SMC3, DIS3, DDX41, DAXX, clonality
- MeSH terms
- Antineoplastic Agents, Clone Cells, DNA Damage, DNA Mutational Analysis, Humans, Recurrence, Reproducibility of Results, Leukemia, Myeloid, Acute, Genome, Human, Mutagenesis, Genes, Neoplasm, High-Throughput Nucleotide Sequencing, Clonal Evolution
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
