APOBEC3B expression in breast cancer reflects cellular proliferation, while a deletion polymorphism is associated with immune activation

Proceedings of the National Academy of Sciences of the United States of America

Volumn 112, Issue 9, 2015, Pages 2841-2846

  Cescon, David W ^a,b   Haibe Kains, Benjamin ^a,b   Mak, Tak W ^a,b  

^a PRINCESS MARGARET HOSPITAL   (Canada)

^b UNIVERSITY OF TORONTO   (Canada)

Author keywords

Cancer; Cellular proliferation; Mutagenesis

Indexed keywords

APOBEC3B PROTEIN; APOLIPOPROTEIN B; PHOSPHATIDYLINOSITOL 4,5 BISPHOSPHATE 3 KINASE; PHOSPHATIDYLINOSITOL 4,5 BISPHOSPHATE 3 KINASE CATALYTIC SUBUNIT ALPHA; PROTEIN P53; UNCLASSIFIED DRUG; APOBEC3B PROTEIN, HUMAN; CYTIDINE DEAMINASE; TUMOR PROTEIN;

ARTICLE; BREAST CANCER; BREAST CANCER CELL LINE; CANCER GENETICS; CANCER PROGNOSIS; CANCER RISK; CANCER SIZE; CELL PROLIFERATION; CONTROLLED STUDY; GENE DELETION; GENE EXPRESSION; GENE MUTATION; GENETIC ASSOCIATION; GENETIC POLYMORPHISM; GENOMICS; HUMAN; HUMAN CELL; IMMUNE RESPONSE; MAJOR CLINICAL STUDY; PHENOTYPE; POINT MUTATION; PRIORITY JOURNAL; TUMOR IMMUNITY; UPREGULATION; BIOSYNTHESIS; BREAST TUMOR; CELL CYCLE; ENZYMOLOGY; FEMALE; GENE EXPRESSION REGULATION; GENETIC DATABASE; GENETICS; IMMUNOLOGY; NUCLEOTIDE SEQUENCE;

BASE SEQUENCE; BREAST NEOPLASMS; CELL CYCLE; CYTIDINE DEAMINASE; DATABASES, GENETIC; FEMALE; GENE EXPRESSION REGULATION, ENZYMOLOGIC; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; NEOPLASM PROTEINS; POLYMORPHISM, GENETIC; SEQUENCE DELETION;

EID: 84924184255     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1424869112     Document Type: Article

References (54)

1. Cancer Genome Atlas Network (2012) Comprehensive molecular portraits of human breast tumours. Nature 490(7418): 61-70.
2. Alexandrov LB, et al.; Australian Pancreatic Cancer Genome Initiative; ICGC Breast Cancer Consortium; ICGC MMML-Seq Consortium; ICGC PedBrain (2013) Signatures of mutational processes in human cancer. Nature 500(7463): 415-421.
3. Nik-Zainal S, et al.; Breast Cancer Working Group of the International Cancer Genome Consortium (2012) Mutational processes molding the genomes of 21 breast cancers. Cell 149(5): 979-993.
4. Stephens PJ, et al.; Oslo Breast Cancer Consortium (OSBREAC) (2012) The landscape of cancer genes and mutational processes in breast cancer. Nature 486(7403): 400-404.
5. Roberts SA, et al. (2013) An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nat Genet 45(9): 970-976.
6. Burns MB, Temiz NA, Harris RS (2013) Evidence for APOBEC3B mutagenesis in multiple human cancers. Nat Genet 45(9): 977-983.
7. Burns MB, et al. (2013) APOBEC3B is an enzymatic source of mutation in breast cancer. Nature 494(7437): 366-370.
8. Taylor BJ, et al. (2013) DNA deaminases induce break-associated mutation showers with implication of APOBEC3B and 3A in breast cancer kataegis. eLife 2: e00534.
9. Lawrence MS, et al. (2013) Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499(7457): 214-218.
10. Silwal-Pandit L, et al. (2014) TP53 mutation spectrum in breast cancer is subtype specific and has distinct prognostic relevance. Clin Cancer Res 20(13): 3569-3580.
11. Henderson S, Chakravarthy A, Su X, Boshoff C, Fenton TR (2014) APOBEC-mediated cytosine deamination links PIK3CA helical domain mutations to human papillomavirus-driven tumor development. Cell Rep 7(6): 1833-1841.
12. Harris RS (2013) Cancer mutation signatures, DNA damage mechanisms, and potential clinical implications. Genome Med 5(9): 87.
13. Sieuwerts AM, et al. (2014) Elevated APOBEC3B correlates with poor outcomes for estrogen-receptor-positive breast cancers. Horm Cancer 5(6): 405-413.
14. Kidd JM, Newman TL, Tuzun E, Kaul R, Eichler EE (2007) Population stratification of a common APOBEC gene deletion polymorphism. PLoS Genet 3(4): e63.
15. Long J, et al. (2013) A common deletion in the APOBEC3 genes and breast cancer risk. J Natl Cancer Inst 105(8): 573-579.
16. Xuan D, et al. (2013) APOBEC3 deletion polymorphism is associated with breast cancer risk among women of European ancestry. Carcinogenesis 34(10): 2240-2243.
17. Nik-Zainal S, et al. (2014) Association of a germline copy number polymorphism of APOBEC3A and APOBEC3B with burden of putative APOBEC-dependent mutations in breast cancer. Nat Genet 46(5): 487-491.
18. Curtis C, et al.; METABRIC Group (2012) The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486(7403): 346-352.
19. Gao J, et al. (2013) Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal 6(269): pl1.
20. Barretina J, et al. (2012) The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483(7391): 603-607.
21. Haibe-Kains B, et al. (2012) A three-gene model to robustly identify breast cancer molecular subtypes. J Natl Cancer Inst 104(4): 311-325.
22. Spearman C (2010) The proof and measurement of association between two things. Int J Epidemiol 39(5): 1137-1150.
23. Wilcoxon F (1945) Individual comparisons by ranking methods. Biometrics Bulletin 1(6): 80-83.
24. Kruskal WH, Wallis WA (1952) Use of ranks in one-criterion variance analysis. J Am Stat Assoc 47(260): 583-621.
25. Cox DR (1972) Regression models and life-tables. J R Stat Soc Series B Stat Methodol 34(2): 187-220.
26. Royston P, Sauerbrei W (2004) A new measure of prognostic separation in survival data. Stat Med 23(5): 723-748.
27. Bland JM, Altman DG (2004) The logrank test. BMJ 328(7447): 1073.
28. Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J Am Stat Assoc 53(282): 457-481.
29. Huang W, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1): 44-57.
30. Subramanian A, et al. (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102(43): 15545-15550.
31. Ashburner M, et al.; The Gene Ontology Consortium (2000) Gene ontology: Tool for the unification of biology. Nat Genet 25(1): 25-29.
32. Liberzon A, et al. (2011) Molecular signatures database (MSigDB) 3.0. Bioinformatics 27(12): 1739-1740.
33. Gentleman R (2005) Reproducible research: A bioinformatics case study. Stat Appl Genet Mol Biol 4(2005): 2.
34. Wang C, et al. (2014) The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance. Nat Biotechnol 32(9): 926-932.
35. Sotiriou C, et al. (2006) Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98(4): 262-272.
36. Carter SL, Eklund AC, Kohane IS, Harris LN, Szallasi Z (2006) A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat Genet 38(9): 1043-1048.
37. van't Veer LJ, et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415(6871): 530-536.
38. Paik S, et al. (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351(27): 2817-2826.
39. Desmedt C, Sotiriou C (2006) Proliferation: The most prominent predictor of clinical outcome in breast cancer. Cell Cycle 5(19): 2198-2202.
40. Lawrence MS, et al. (2014) Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 505(7484): 495-501.
41. Chen DS, Mellman I (2013) Oncology meets immunology: The cancer-immunity cycle. Immunity 39(1): 1-10.
42. de Bruin EC, et al. (2014) Spatial and temporal diversity in genomic instability processes defines lung cancer evolution. Science 346(6206): 251-256.
43. Leonard B, et al. (2013) APOBEC3B upregulation and genomic mutation patterns in serous ovarian carcinoma. Cancer Res 73(24): 7222-7231.
44. Peña-Diaz J, et al. (2013) Transcription profiling during the cell cycle shows that a subset of Polycomb-targeted genes is upregulated during DNA replication. Nucleic Acids Res 41(5): 2846-2856.
45. Zhang J, et al. (2014) Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing. Science 346(6206): 256-259.
46. Caval V, Suspène R, Shapira M, Vartanian JP, Wain-Hobson S (2014) A prevalent cancer susceptibility APOBEC3A hybrid allele bearing APOBEC3B 3'UTR enhances chromosomal DNA damage. Nat Commun 5(2014): 5129.
47. Conticello SG, Thomas CJF, Petersen-Mahrt SK, Neuberger MS (2005) Evolution of the AID/APOBEC family of polynucleotide (deoxy)cytidine deaminases. Mol Biol Evol 22(2): 367-377.
48. Moris A, Murray S, Cardinaud S (2014) AID and APOBECs span the gap between innate and adaptive immunity. Front Microbiol 5: 534.
49. Loi S, et al. (2013) Prognostic and predictive value of tumor-infiltrating lymphocytes in a phase III randomized adjuvant breast cancer trial in node-positive breast cancer comparing the addition of docetaxel to doxorubicin with doxorubicin-based chemotherapy: BIG 02-98. J Clin Oncol 31(7): 860-867.
50. Loi S, et al. (2014) Tumor infiltrating lymphocytes are prognostic in triple negative breast cancer and predictive for trastuzumab benefit in early breast cancer: Results from the FinHER trial. Ann Oncol 25(8): 1544-1550.
51. Pardoll DM (2012) The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer 12(4): 252-264.
52. Snyder A, et al. (2014) Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med 371(23): 2189-2199.
53. Herbst RS, et al. (2014) Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 515(7528): 563-567.
54. Gubin MM, et al. (2014) Checkpoint blockade cancer immunotherapy targets tumourspecific mutant antigens. Nature 515(7528): 577-581.