The landscape of chromosomal aberrations in breast cancer mouse models reveals driver-specific routes to tumorigenesis

Nature Communications

Volumn 7, Issue , 2016, Pages

  Ben David, Uri ^a   Ha, Gavin ^a,b   Khadka, Prasidda ^a   Jin, Xin ^a   Wong, Bang ^a   Franke, Lude ^c   Golub, Todd R ^a,b,d,e  

^a BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^b DANA FARBER CANCER INSTITUTE   (United States)

^c UNIVERSITY OF GRONINGEN   (Netherlands)

^d HARVARD MEDICAL SCHOOL   (United States)

^e HOWARD HUGHES MEDICAL INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

STRATIFIN; EPIDERMAL GROWTH FACTOR RECEPTOR 2; ERBB2 PROTEIN, MOUSE; PROTEIN 14 3 3; SFN PROTEIN, MOUSE;

CANCER; CELLS AND CELL COMPONENTS; CHROMOSOME; EXPERIMENTAL STUDY; GENE EXPRESSION; GENETIC ENGINEERING; IDENTIFICATION METHOD; RODENT; TUMOR;

ANIMAL EXPERIMENT; ANIMAL MODEL; ANIMAL TISSUE; ARTICLE; BREAST CANCER CELL LINE; BREAST CARCINOGENESIS; BREAST EPITHELIUM CELL; CHROMOSOME ABERRATION; CONTROLLED STUDY; COPY NUMBER VARIATION; GENE EXPRESSION PROFILING; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENETICALLY ENGINEERED MOUSE STRAIN; HUMAN; HUMAN CELL; KARYOTYPING; MOUSE; NONHUMAN; PRIMARY TUMOR; SYNTENY; ANEUPLOIDY; ANIMAL; CARCINOGENESIS; DISEASE MODEL; DOWN REGULATION; EXPERIMENTAL MAMMARY NEOPLASM; FEMALE; GENETIC ENGINEERING; GENETICS; GENOMIC INSTABILITY; METABOLISM; MUTATION; PATHOLOGY; SPECIES DIFFERENCE; TRANSGENIC MOUSE; TUMOR CELL LINE;

14-3-3 PROTEINS; ANEUPLOIDY; ANIMALS; CARCINOGENESIS; CELL LINE, TUMOR; CHROMOSOME ABERRATIONS; DISEASE MODELS, ANIMAL; DNA COPY NUMBER VARIATIONS; DOWN-REGULATION; FEMALE; GENE EXPRESSION PROFILING; GENETIC ENGINEERING; GENOMIC INSTABILITY; HUMANS; MAMMARY NEOPLASMS, ANIMAL; MICE, TRANSGENIC; MUTATION; RECEPTOR, ERBB-2; SPECIES SPECIFICITY;

EID: 84977260515     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms12160     Document Type: Article

References (51)

1. Garraway, L. A., Lander, E. S. Lessons from the cancer genome. Cell 153, 17-37 (2013).
2. Zack, T. I. et al. Pan-cancer patterns of somatic copy number alteration. Nat. Genet. 45, 1134-1140 (2013).
3. Beroukhim, R. et al. The landscape of somatic copy-number alteration across human cancers. Nature 463, 899-905 (2010).
4. van Miltenburg, M. H., Jonkers, J. Using genetically engineered mouse models to validate candidate cancer genes and test new therapeutic approaches. Curr. Opin. Genet. Dev. 22, 21-27 (2012).
5. Menezes, M. E. et al. Genetically engineered mice as experimental tools to dissect the critical events in breast cancer. Adv. Cancer Res. 121, 331-382 (2014).
6. Weaver, Z. A. et al. A recurring pattern of chromosomal aberrations in mammary gland tumours of MMTV-cmyc transgenic mice. Genes Chromosomes Cancer 25, 251-260 (1999).
7. Weaver, Z. et al. Mammary tumours in mice conditionally mutant for Brca1 exhibit gross genomic instability and centrosome amplification yet display a recurring distribution of genomic imbalances that is similar to human breast cancer. Oncogene 21, 5097-5107 (2002).
8. Fabris, V. T. From chromosomal abnormalities to the identification of target genes in mouse models of breast cancer. Cancer Genet. 207, 233-246 (2014).
9. Silva, G. O. et al. Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer. Breast Cancer Res. Treat. 152, 347-356 (2015).
10. Hollern, D. P., Andrechek, E. R. A genomic analysis of mouse models of breast cancer reveals molecular features of mouse models and relationships to human breast cancer. Breast Cancer Res. 16, R59 (2014).
11. Herschkowitz, J. I. et al. Comparative oncogenomics identifies breast tumours enriched in functional tumour-initiating cells. Proc. Natl Acad. Sci. USA 109, 2778-2783 (2012).
12. Herschkowitz, J. I. et al. Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumours. Genome Biol. 8, R76 (2007).
13. Carter, S. L., Eklund, A. C., Kohane, I. S., Harris, L. N., Szallasi, Z. A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers. Nat. Genet. 38, 1043-1048 (2006).
14. Patel, A. P. et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344, 1396-1401 (2014).
15. Ben-David, U., Mayshar, Y., Benvenisty, N. Virtual karyotyping of pluripotent stem cells on the basis of their global gene expression profiles. Nat. Protoc. 8, 989-997 (2013).
16. Mayshar, Y. et al. Identification and classification of chromosomal aberrations in human induced pluripotent stem cells. Cell Stem Cell 7, 521-531 (2010).
17. Fehrmann, R. S. et al. Gene expression analysis identifies global gene dosage sensitivity in cancer. Nat. Genet. 47, 115-125 (2015).
18. Westcott, P. M. et al. The mutational landscapes of genetic and chemical models of Kras-driven lung cancer. Nature 517, 489-492 (2015).
19. Nassar, D., Latil, M., Boeckx, B., Lambrechts, D., Blanpain, C. Genomic landscape of carcinogen-induced and genetically induced mouse skin squamous cell carcinoma. Nat. Med. 21, 946-954 (2015).
20. McCreery, M. Q. et al. Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers. Nat. Med. 21, 1514-1520 (2015).
21. Neve, R. M. et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell. 10, 515-527 (2006).
22. Fantozzi, A., Christofori, G. Mouse models of breast cancer metastasis. Breast Cancer Res. 8, 212 (2006).
23. Andrechek, E. R. et al. Genetic heterogeneity of Myc-induced mammary tumours reflecting diverse phenotypes including metastatic potential. Proc. Natl Acad. Sci. USA 106, 16387-16392 (2009).
24. Van Keymeulen, A. et al. Reactivation of multipotency by oncogenic PIK3CA induces breast tumour heterogeneity. Nature 525, 119-123 (2015).
25. Cancer Genome Atlas, N. Comprehensive molecular portraits of human breast tumours. Nature 490, 61-70 (2012).
26. Ciriello, G. et al. Comprehensive molecular portraits of invasive lobular breast cancer. Cell 163, 506-519 (2015).
27. Eirew, P. et al. Dynamics of genomic clones in breast cancer patient xenografts at single-cell resolution. Nature 518, 422-426 (2015).
28. Marsicano, S. R. et al. Survinin expression in patients with breast cancer during chemotherapy. Tumour Biol. 36, 3441-3445 (2015).
29. Tanaka, K. et al. Expression of survivin and its relationship to loss of apoptosis in breast carcinomas. Clin. Cancer Res. 6, 127-134 (2000).
30. Wang, C., Zheng, X., Shen, C., Shi, Y. MicroRNA-203 suppresses cell proliferation and migration by targeting BIRC5 and LASP1 in human triple-negative breast cancer cells. J. Exp. Clin. Cancer Res. 31, 58 (2012).
31. Li, Q. X. et al. Survivin stable knockdown by siRNA inhibits tumour cell growth and angiogenesis in breast and cervical cancers. Cancer Biol. Ther. 5, 860-866 (2006).
32. Xia, W. et al. Regulation of survivin by ErbB2 signaling: therapeutic implications for ErbB2-overexpressing breast cancers. Cancer Res. 66, 1640-1647 (2006).
33. Gatza, M. L., Silva, G. O., Parker, J. S., Fan, C., Perou, C. M. An integrated genomics approach identifies drivers of proliferation in luminal-subtype human breast cancer. Nat. Genet. 46, 1051-1059 (2014).
34. Lodygin, D., Hermeking, H. The role of epigenetic inactivation of 14-3-3sigma in human cancer. Cell Res. 15, 237-246 (2005).
35. Boudreau, A. et al. 14-3-3sigma stabilizes a complex of soluble actin and intermediate filament to enable breast tumour invasion. Proc. Natl Acad. Sci. USA 110, E3937-E3944 (2013).
36. Lu, J. et al. 14-3-3zeta Cooperates with ErbB2 to promote ductal carcinoma in situ progression to invasive breast cancer by inducing epithelialmesenchymal transition. Cancer Cell 16, 195-207 (2009).
37. Ling, C., Su, V. M., Zuo, D., Muller, W. J. Loss of the 14-3-3sigma tumour suppressor is a critical event in ErbB2-mediated tumour progression. Cancer Discov. 2, 68-81 (2012).
38. Seton-Rogers, S. E. et al. Cooperation of the ErbB2 receptor and transforming growth factor beta in induction of migration and invasion in mammary epithelial cells. Proc. Natl Acad. Sci. USA 101, 1257-1262 (2004).
39. Hong, H. Y. et al. 14-3-3 sigma and 14-3-3 zeta plays an opposite role in cell growth inhibition mediated by transforming growth factor-beta 1. Mol. Cells 29, 305-309 (2010).
40. Hong, H. Y., Jeon, W. K., Kim, S. J., Kim, B. C. 14-3-3 sigma is a new target up-regulated by transforming growth factor-beta1 through a Smad3-dependent mechanism. Biochem. Biophys. Res. Commun. 432, 193-197 (2013).
41. Hu, F. et al. PBK/TOPK interacts with the DBD domain of tumour suppressor p53 and modulates expression of transcriptional targets including p21. Oncogene 29, 5464-5474 (2010).
42. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2014).
43. Lingjaerde, O. C., Baumbusch, L. O., Liestol, K., Glad, I. K., Borresen-Dale, A. L. CGH-Explorer: a program for analysis of array-CGH data. Bioinformatics 21, 821-822 (2005).
44. Barretina, J. et al. The Cancer Cell Line Encyclopaedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603-607 (2012).
45. 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).
46. Gyorffy, B. et al. An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients. Breast Cancer Res. Treat. 123, 725-731 (2010).
47. Liu, J. C. et al. Combined deletion of Pten and p53 in mammary epithelium accelerates triple-negative breast cancer with dependency on eEF2K. EMBO Mol. Med. 6, 1542-1560 (2014).
48. Li, Z. et al. ETV6-NTRK3 fusion oncogene initiates breast cancer from committed mammary progenitors via activation of AP1 complex. Cancer Cell 12, 542-558 (2007).
49. Diaz-Cruz, E. S., Cabrera, M. C., Nakles, R., Rutstein, B. H., Furth, P. A. BRCA1 deficient mouse models to study pathogenesis and therapy of triple negative breast cancer. Breast Dis. 32, 85-97 (2010).
50. Konieczkowski, D. J. et al. A melanoma cell state distinction influences sensitivity to MAPK pathway inhibitors. Cancer Discov. 4, 816-827 (2014).
51. Stewart, M. L. et al. KRAS genomic status predicts the sensitivity of ovarian cancer cells to decitabine. Cancer Res. 75, 2897-2906 (2015).