Deletions linked to TP53 loss drive cancer through p53-independent mechanisms

Nature

Volumn 531, Issue 7595, 2016, Pages 471-475

  Liu, Yu ^a,b   Chen, Chong ^a,b   Xu, Zhengmin ^a   Scuoppo, Claudio ^c   Rillahan, Cory D ^b   Gao, Jianjiong ^b   Spitzer, Barbara ^b   Bosbach, Benedikt ^b   Kastenhuber, Edward R ^b   Baslan, Timour ^b   Ackermann, Sarah ^b   Cheng, Lihua ^a   Wang, Qingguo ^b   Niu, Ting ^a   Schultz, Nikolaus ^b   Levine, Ross L ^b   Mills, Alea A ^d   Lowe, Scott W ^b,e  

^a SICHUAN UNIVERSITY   (China)

^b MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

^c Department of Medicine   (United States)

^d Simons Center for Quantitative Biology   (United States)

^e HOWARD HUGHES MEDICAL INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALOX15B PROTEIN; INITIATION FACTOR 5A; MEMBRANE PROTEIN; PROTEIN P53; TRP53 PROTEIN; UNCLASSIFIED DRUG; INITIATION FACTOR; RNA BINDING PROTEIN;

ALLELE; CANCER; CHROMOSOME; MUTATION; RODENT; TUMOR;

ARTICLE; CANCER GENETICS; CARCINOGENESIS; CHROMOSOME 11; CHROMOSOME 17P; GENE DELETION; GENE DOSAGE; HETEROZYGOTE; HUMAN; LEUKEMIA; LYMPHOMA; NONHUMAN; PRIORITY JOURNAL; TUMOR SUPPRESSOR GENE; ACUTE MYELOID LEUKEMIA; ALLELE; ANIMAL; CELL TRANSFORMATION; CHROMOSOME; CHROMOSOME 17; DEFICIENCY; DISEASE COURSE; DISEASE MODEL; FEMALE; GENETICS; MALE; METABOLISM; MOUSE; NEOPLASM; PATHOLOGY; SYNTENY;

ALLELES; ANIMALS; CELL TRANSFORMATION, NEOPLASTIC; CHROMOSOMES, HUMAN, PAIR 17; CHROMOSOMES, MAMMALIAN; DISEASE MODELS, ANIMAL; DISEASE PROGRESSION; FEMALE; GENES, P53; HETEROZYGOTE; HUMANS; LEUKEMIA, MYELOID, ACUTE; LYMPHOMA; MALE; MICE; NEOPLASMS; PEPTIDE INITIATION FACTORS; RNA-BINDING PROTEINS; SEQUENCE DELETION; SYNTENY; TUMOR SUPPRESSOR PROTEIN P53;

EID: 84962219514     PISSN: 00280836     EISSN: 14764687     Source Type: Journal    
DOI: 10.1038/nature17157     Document Type: Article

References (55)

1. Hanahan D., & Weinberg R. A. Hallmarks of cancer: the next generation. Cell 144, 646-674 (2011
2. Zender L., et al. An oncogenomics-based in vivo RNAi screen identifies tumor suppressors in liver cancer. Cell 135, 852-864 (2008
3. Xue W., et al. A cluster of cooperating tumor-suppressor gene candidates in chromosomal deletions. Proc. Natl Acad. Sci. USA 109, 8212-8217 (2012
4. Solimini N. L., et al. Recurrent hemizygous deletions in cancers may optimize proliferative potential. Science 337, 104-109 (2012
5. Davoli T., et al. Cumulative haploinsufficiency and triplosensitivity drive aneuploidy patterns and shape the cancer genome. Cell 155, 948-962 (2013
6. Miller L. D., et al. An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. Proc. Natl Acad. Sci. USA 102, 13550-13555 (2005
7. Petitjean A., Achatz M. I., Borresen-Dale A. L., Hainaut P., & Olivier M. TP53 mutations in human cancers: functional selection and impact on cancer prognosis and outcomes. Oncogene 26, 2157-2165 (2007
8. Gao J., et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013
9. Wattel E., et al. p53 mutations are associated with resistance to chemotherapy and short survival in hematologic malignancies. Blood 84, 3148-3157 (1994
10. El-Ghammaz A. M., Abdelwahed E., Mostafa N. N., & Mansour D. A. De novo deletion 17p13.1 as a predictor for disease progression in chronic lymphocytic leukemia. Clin. Exp. Med. 15, 493-499 (2015
11. Scuoppo C., et al. A tumour suppressor network relying on the polyamine-hypusine axis. Nature 487, 244-248 (2012
12. Wales M. M., et al. p53 activates expression of HIC-1, a new candidate tumour suppressor gene on 17p13.3. Nature Med. 1, 570-577 (1995
13. Ahn Y. H., et al. Map2k4 functions as a tumor suppressor in lung adenocarcinoma and inhibits tumor cell invasion by decreasing peroxisome proliferator-activated receptor γ2 expression. Mol. Cell. Biol. 31, 4270-4285 (2011
14. Mermel C. H., et al. GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers. Genome Biol. 12, R41 (2011
15. Adams D. J., et al. Mutagenic insertion and chromosome engineering resource (MICER). Nature Genet. 36, 867-871 (2004
16. Schmitt C. A., et al. Dissecting p53 tumor suppressor functions in vivo. Cancer Cell 1, 289-298 (2002
17. Eischen C. M., Weber J. D., Roussel M. F., Sherr C. J., & Cleveland J. L. Disruption of the ARF-Mdm2-p53 tumor suppressor pathway in Myc-induced lymphomagenesis. Genes Dev. 13, 2658-2669 (1999
18. Monti S., et al. Integrative analysis reveals an outcome-associated and targetable pattern of p53 and cell cycle deregulation in diffuse large B cell lymphoma. Cancer Cell 22, 359-372 (2012
19. Levine A. J., & Oren M. The first 30 years of p53: growing ever more complex. Nature Rev. Cancer 9, 749-758 (2009
20. Vousden K. H., & Prives C. Blinded by the light: the growing complexity of p53. Cell 137, 413-431 (2009
21. Olive K. P., et al. Mutant p53 gain of function in two mouse models of Li-Fraumeni syndrome. Cell 119, 847-860 (2004
22. Hanel W., et al. Two hot spot mutant p53 mouse models display differential gain of function in tumorigenesis. Cell Death Differ. 20, 898-909 (2013
23. Hemann M. T., et al. Suppression of tumorigenesis by the p53 target PUMA. Proc. Natl Acad. Sci. USA 101, 9333-9338 (2004
24. Kelly G. L., et al. Targeting of MCL-1 kills MYC-driven mouse and human lymphomas even when they bear mutations in p53. Genes Dev. 28, 58-70 (2014
25. Tang D. G., et al. Suppression of W256 carcinosarcoma cell apoptosis by arachidonic acid and other polyunsaturated fatty acids. Int. J. Cancer 72, 1078-1087 (1997
26. Balatti V., et al. TCL1 targeting miR-3676 is codeleted with tumor protein p53 in chronic lymphocytic leukemia. Proc. Natl Acad. Sci. USA 112, 2169-2174 (2015
27. Slovak M. L., et al. Karyotypic analysis predicts outcome of preremission and postremission therapy in adult acute myeloid leukemia: a Southwest Oncology Group/Eastern Cooperative Oncology Group Study. Blood 96, 4075-4083 (2000
28. Byrd J. C., et al. Pretreatment cytogenetic abnormalities are predictive of induction success, cumulative incidence of relapse, and overall survival in adult patients with De novo acute myeloid leukemia: results from Cancer and Leukemia Group B (CALGB 8461). Blood 100, 4325-4336 (2002
29. Chen C., et al. MLL3 is a haploinsufficient 7q tumor suppressor in acute myeloid leukemia. Cancer Cell 25, 652-665 (2014
30. Salaverria I., et al. Specific secondary genetic alterations in mantle cell lymphoma provide prognostic information independent of the gene expression-based proliferation signature. J. Clin. Oncol. 25, 1216-1222 (2007
31. Rubio-Moscardo F., et al. Mantle-cell lymphoma genotypes identified with CGH to BAC microarrays define a leukemic subgroup of disease and predict patient outcome. Blood 105, 4445-4454 (2005
32. Chen W., et al. Array comparative genomic hybridization reveals genomic copy number changes associated with outcome in diffuse large B-cell lymphomas. Blood 107, 2477-2485 (2006
33. Bea S., et al. Diffuse large B-cell lymphoma subgroups have distinct genetic profiles that influence tumor biology and improve gene-expression-based survival prediction. Blood 106, 3183-3190 (2005
34. Mestre-Escorihuela C., et al. Homozygous deletions localize novel tumor suppressor genes in B-cell lymphomas. Blood 109, 271-280 (2007
35. Rücker F. G., et al. TP53 alterations in acute myeloid leukemia with complex karyotype correlate with specific copy number alterations, monosomal karyotype, and dismal outcome. Blood 119, 2114-2121 (2012
36. Chigrinova E., et al. Two main genetic pathways lead to the transformation of chronic lymphocytic leukemia to Richter syndrome. Blood 122, 2673-2682 (2013
37. The Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult De novo acute myeloid leukemia. N. Engl. J. Med. 368, 2059-2074 (2013
38. Brown T. Southern blotting. Curr. Protoc. Prot. Sci. 13, 4G: A.4G.1-4G: A.4G.8 (2001
39. Adams J. M., et al. The c-myc oncogene driven by immunoglobulin enhancers induces lymphoid malignancy in transgenic mice. Nature 318, 533-538 (1985
40. De Boer J., et al. Transgenic mice with hematopoietic and lymphoid specific expression of Cre. Eur. J. Immunol. 33, 314-325 (2003
41. Lakso M., et al. Efficient in vivo manipulation of mouse genomic sequences at the zygote stage. Proc. Natl Acad. Sci. USA 93, 5860-5865 (1996
42. Jacks T., et al. Tumor spectrum analysis in p53-mutant mice. Curr. Biol. 4, 1-7 (1994
43. Marino S., & Vooijs M., Van Der Gulden H., Jonkers J., & Berns A. Induction of medulloblastomas in p53-null mutant mice by somatic inactivation of Rb in the external granular layer cells of the cerebellum. Genes Dev. 14, 994-1004 (2000
44. Mombaerts P., et al. RAG-1-deficient mice have no mature B and T lymphocytes. Cell 68, 869-877 (1992
45. Kamijo T., et al. Tumor suppression at the mouse INK4a locus mediated by the alternative reading frame product p19ARF. Cell 91, 649-659 (1997
46. Chien Y., et al. Control of the senescence-associated secretory phenotype by NF-?B promotes senescence and enhances chemosensitivity. Genes Dev. 25, 2125-2136 (2011
47. Hemann M. T., et al. Evasion of the p53 tumour surveillance network by tumour-derived MYC mutants. Nature 436, 807-811 (2005
48. Fellmann C., et al. An optimized microRNA backbone for effective single-copy RNAi. Cell Reports 5, 1704-1713 (2013
49. Chicas A., et al. Dissecting the unique role of the retinoblastoma tumor suppressor during cellular senescence. Cancer Cell 17, 376-387 (2010
50. Simpson E. M., et al. Genetic variation among 129 substrains and its importance for targeted mutagenesis in mice. Nature Genet. 16, 19-27 (1997
51. Navin N., et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90-94 (2011
52. Baslan T., et al. Genome-wide copy number analysis of single cells. Nature Protocols 7, 1024-1041 (2012
53. Baslan T., & Hicks J. Single cell sequencing approaches for complex biological systems. Curr. Opin. Genet. Dev. 26, 59-65 (2014
54. Folch J., Lees M., & Sloane Stanley G. H. A simple method for the isolation and purification of total lipides from animal tissues. J. Biol. Chem. 226, 497-509 (1957
55. Ye X., et al. Development and validation of a UPLC-MS/MS method for quantification of SKLB010, an investigational anti-inflammatory compound, and its application to pharmacokinetic studies in beagle dogs. J. Pharm. Biomed. Anal. 56, 366-372 (2011