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SF3B1 and Other Novel Cancer Genes in Chronic Lymphocytic Leukemia
Open accessAbstract
BACKGROUND: The somatic genetic basis of chronic lymphocytic leukemia, a common and clinically heterogeneous leukemia occurring in adults, remains poorly understood. METHODS: We obtained DNA samples from leukemia cells in 91 patients with chronic lymphocytic leukemia and performed massively parallel sequencing of 88 whole exomes and whole genomes, together with sequencing of matched germline DNA, to characterize the spectrum of somatic mutations in this disease. RESULTS: Nine genes that are mutated at significant frequencies were identified, including four with established roles in chronic lymphocytic leukemia (TP53 in 15% of patients, ATM in 9%, MYD88 in 10%, and NOTCH1 in 4%) and five with unestablished roles (SF3B1, ZMYM3, MAPK1, FBXW7, and DDX3X). SF3B1, which functions at the catalytic core of the spliceosome, was the second most frequently mutated gene (with mutations occurring in 15% of patients). SF3B1 mutations occurred primarily in tumors with deletions in chromosome 11q, which are associated with a poor prognosis in patients with chronic lymphocytic leukemia. We further discovered that tumor samples with mutations in SF3B1 had alterations in pre-messenger RNA (mRNA) splicing. CONCLUSIONS: Our study defines the landscape of somatic mutations in chronic lymphocytic leukemia and highlights pre-mRNA splicing as a critical cellular process contributing to chronic lymphocytic leukemia.
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Cites
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
Self-citationComprehensive genomic characterization defines human glioblastoma genes and core pathways
The Cancer Genome Atlas Research Network (2008) · Nature · doi:10.1038/nature07385 · Cited by 7,735
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
Cited by
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
The 2016 revision of the World Health Organization classification of lymphoid neoplasms
Swerdlow, S. H., Campo, E., Pileri, S. A., Harris, N. L., Stein, H., Siebert, R., Advani, R., Ghielmini, M., Salles, G. A., Zelenetz, A. D., et al. (2016) · Blood · doi:10.1182/blood-2016-01-643569 · Cited by 7,831
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
Self-citationThe Somatic Genomic Landscape of Glioblastoma
Brennan, C. W., Verhaak, R. G. W., McKenna, A., Campos, B., Noushmehr, H., Salama, S. R., Zheng, S., Chakravarty, D., Sanborn, J. Z., Berman, S. H., et al. (2013) · Cell · doi:10.1016/j.cell.2013.09.034 · Cited by 5,016
Self-citationEvolution and impact of subclonal mutations in chronic lymphocytic leukemia
Landau, D. A., Carter, S. L., Stojanov, P., McKenna, A., Stevenson, K., Lawrence, M. S., Sougnez, C., Stewart, C., Sivachenko, A., Wang, L., et al. (2013) · Cell · doi:10.1016/j.cell.2013.01.019 · Cited by 1,379
Self-citationResistance Mechanisms for the Bruton's Tyrosine Kinase Inhibitor Ibrutinib
Woyach, J. A., Furman, R. R., Liu, T.-M., Ozer, H. G., Zapatka, M., Ruppert, A. S., Xue, L., Li, D. H.-H., Steggerda, S. M., Versele, M., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1400029 · Cited by 1,275
JAKs and STATs in immunity, immunodeficiency, and cancer
O'Shea, J. J., Holland, S. M., & Staudt, L. M. (2013) · New England Journal of Medicine · doi:10.1056/nejmra1202117 · Cited by 927
Dissecting the genomic complexity underlying medulloblastoma
Jones, D. T. W., Jäger, N., Kool, M., Zichner, T., Hutter, B., Sultan, M., Cho, Y.-J., Pugh, T. J., Hovestadt, V., Stütz, A. M., et al. (2012) · Nature · doi:10.1038/nature11284 · Cited by 839
Self-citationMedulloblastoma exome sequencing uncovers subtype-specific somatic mutations
Pugh, T. J., Weeraratne, S. D., Archer, T. C., Pomeranz Krummel, D. A., Auclair, D., Bochicchio, J., Carneiro, M. O., Carter, S. L., Cibulskis, K., Erlich, R. L., et al. (2012) · Nature · doi:10.1038/nature11329 · Cited by 750
Self-citationRNA splicing dysregulation and the hallmarks of cancer
Bradley, R. K., & Anczuków, O. (2023) · Nature Reviews Cancer · doi:10.1038/s41568-022-00541-7 · Cited by 579
SRSF2 Mutations Contribute to Myelodysplasia by Mutant-Specific Effects on Exon Recognition
Kim, E., Ilagan, J. O., Liang, Y., Daubner, G. M., Lee, S. C.-W., Ramakrishnan, A., Li, Y., Chung, Y. R., Micol, J.-B., Murphy, M. E., et al. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.04.006 · Cited by 575
Obeng, E. A., Chappell, R. J., Seiler, M., Chen, M. C., Campagna, D. R., Schmidt, P. J., Schneider, R. K., Lord, A. M., Wang, L., Gambe, R. G., et al. (2016) · Cancer Cell · doi:10.1016/j.ccell.2016.08.006 · Cited by 380
Mitochondrial Reprogramming Underlies Resistance to BCL-2 Inhibition in Lymphoid Malignancies
Guièze, R., Liu, V. M., Rosebrock, D., Jourdain, A. A., Hernández-Sánchez, M., Martinez Zurita, A., Sun, J., Ten Hacken, E., Baranowski, K., Thompson, P. A., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.08.005 · Cited by 361
Self-citationSynthetic Lethal and Convergent Biological Effects of Cancer-Associated Spliceosomal Gene Mutations
Lee, S. C.-W., North, K., Kim, E., Jang, E., Obeng, E., Lu, S. X., Liu, B., Inoue, D., Yoshimi, A., Ki, M., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.07.003 · Cited by 219
Ferreira, P. G., Jares, P., Rico, D., Gómez-López, G., Martínez-Trillos, A., Villamor, N., Ecker, S., González-Pérez, A., Knowles, D. G., Monlong, J., et al. (2014) · Genome Research · doi:10.1101/gr.152132.112 · Cited by 214
Alternative splicing: decoding an expansive regulatory layer
Irimia, M., & Blencowe, B. J. (2012) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2012.03.005 · Cited by 177
Splicing factor mutations and cancer
Yoshida, K., & Ogawa, S. (2014) · WIREs RNA · doi:10.1002/wrna.1222 · Cited by 155
Mutations in the RNA Splicing Factor SF3B1 Promote Tumorigenesis through MYC Stabilization
Liu, Z., Yoshimi, A., Wang, J., Cho, H., Chun-Wei Lee, S., Ki, M., Bitner, L., Chu, T., Shah, H., Liu, B., et al. (2020) · Cancer Discovery · doi:10.1158/2159-8290.cd-19-1330 · Cited by 118
Gandhi, A. K., Mendy, D., Waldman, M., Chen, G., Rychak, E., Miller, K., Gaidarova, S., Ren, Y., Wang, M., Breider, M., et al. (2014) · British Journal of Haematology · doi:10.1111/bjh.12622 · Cited by 106
RNA-Binding Proteins Hold Key Roles in Function, Dysfunction, and Disease
Kelaini, S., Chan, C., Cornelius, V. A., & Margariti, A. (2021) · Biology · doi:10.3390/biology10050366 · Cited by 94
Ojha, J., Codd, V., Nelson, C. P., Samani, N. J., Smirnov, I. V., Madsen, N. R., Hansen, H. M., de Smith, A. J., Bracci, P. M., Wiencke, J. K., et al. (2016) · Cancer Epidemiology, Biomarkers & Prevention · doi:10.1158/1055-9965.epi-15-1329 · Cited by 71
Hamasy, A., Wang, Q., Blomberg, K. E. M., Mohammad, D. K., Yu, L., Vihinen, M., Berglöf, A., & Smith, C. I. E. (2017) · Leukemia · doi:10.1038/leu.2016.153 · Cited by 62
Stress and non-stress roles of inflammatory signals during HSC Emergence and maintenance
Clapes, T., Lefkopoulos, S., & Trompouki, E. (2016) · Frontiers in Immunology · doi:10.3389/fimmu.2016.00487 · Cited by 62
Gángó, A., Alpár, D., Galik, B., Marosvári, D., Kiss, R., Fésüs, V., Aczél, D., Eyüpoglu, E., Nagy, N., Nagy, Á., et al. (2020) · International Journal of Cancer · doi:10.1002/ijc.32502 · Cited by 54
Berman, E., Jhanwar, S., Hedvat, C., Arcila, M. E., Wahab, O. A., Levine, R., Maloy, M., Ma, W., & Albitar, M. (2016) · Leukemia Research · doi:10.1016/j.leukres.2016.08.006 · Cited by 41
Yao, T., Zhang, Z., Li, Q., Huang, R., Hong, Y., Li, C., Zhang, F., Huang, Y., Fang, Y., Cao, Q., et al. (2023) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-23-0083 · Cited by 22
Sun, L., Liu, Y., Guo, X., Cui, T., Wu, C., Tao, J., Cheng, C., Chu, Q., Ji, C., Li, X., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-49573-7 · Cited by 18
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Metadata
- Authors
- Wang, L., Lawrence, M. S., Wan, Y., Stojanov, P., Sougnez, C., Stevenson, K., Werner, L., Sivachenko, A., DeLuca, D. S., Zhang, L., Zhang, W., Vartanov, A. R., Fernandes, S. M., Goldstein, N. R., Folco, E. G., Cibulskis, K., Tesar, B., Sievers, Q. L., Shefler, E., Gabriel, S., Hacohen, N., Reed, R., Meyerson, M., Golub, T. R., Lander, E. S., Neuberg, D., Brown, J. R., Getz, G., & Wu, C. J.
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2011-12-29
- Volume
- 365
- Issue
- 26
- Pages
- 2497-2506
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2145842706
- Cited by
- 1,080
- References
- 3
- FWCI
- 51.99
- Type
- journal article
- Language
- en
- Open access
- bronze
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