Supplementary data for the biological age linked to oxidative stress modifies breast cancer aggressiveness

  1. Sáez-Freire, María del Mar 123
  2. Blanco-Gómez, Adrián 12
  3. Castillo-Lluva, Sonia 124
  4. Gómez-Vecino, Aurora 12
  5. Galvis-Jiménez, Julie Milena 125
  6. Martín-Seisdedos, Carmen 26
  7. Isidoro-García, María 26
  8. Hontecillas-Prieto, Lourdes 12
  9. García-Cenador, María Begoña 27
  10. García-Criado, Francisco Javier 27
  11. Patino-Alonso, María Carmen 28
  12. Galindo-Villardón, Purificación 289
  13. Mao, Jian-Hua 9
  14. Prieto, Carlos 10
  15. Castellanos-Martín, Andrés 12
  16. Kaderali, Lars 11
  17. Pérez-Losada, Jesús 12
  1. 1 Instituto de Biología Molecular y Celular del Cáncer (IBMCC-CIC). Universidad de Salamanca/CSIC. Salamanca, Spain
  2. 2 Instituto de Investigación Biosanitaria de Salamanca (IBSAL). Salamanca, Spain
  3. 3 Departamento de Fisiología y Farmacología. Universidad de Salamanca. Salamanca. Spain
  4. 4 Departamento de Bioquímica y Biología Molecular I. Facultad de Biología. Universidad Complutense de Madrid. Madrid, Spain
  5. 5 Instituto Nacional de Cancerología, Bogotá, D.C., Colombia
  6. 6 Servicio de Bioquímica Clínica. Hospital Universitario de Salamanca. Salamanca, Spain
  7. 7 Departamento de Cirugía. Universidad de Salamanca. Salamanca. Spain
  8. 8 Departamento de Estadística. Universidad de Salamanca. Spain
  9. 9 Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
  10. 10 Bioinformatics Service, Nucleus, University of Salamanca (USAL), Salamanca, Spain
  11. 11 Institute for Bioinformatics. University Medicine Greifswald. Greifswald, Germany
Revista:
Data in Brief

ISSN: 2352-3409

Año de publicación: 2018

Volumen: 18

Páginas: 1172-1184

Tipo: Artículo

DOI: 10.1016/J.DIB.2018.03.132 GOOGLE SCHOLAR

Otras publicaciones en: Data in Brief

Resumen

The data presented in this article are related to the research paper entitled “The biological age linked to oxidative stress modifies breast cancer aggressiveness” (M.M. Sáez-Freire, A. Blanco-Gómez, S. Castillo-Lluva, A. Gómez-Vecino, J.M. Galvis-Jiménez, C. Martín-Seisdedos, M. Isidoro-García, L. Hontecillas-Prieto, M.B. García-Cenador, F.J. García-Criado, M.C. Patino-Alonso, P. Galindo-Villardón, J.H. Mao, C. Prieto, A. Castellanos-Martín, L. Kaderali, J. Pérez-Losada). The data shown were obtained from a population of transgenic mice, MMTV-Erbb2/Neu, with different susceptibility to breast cancer and a mixed genetic background generated by backcrossing. It was observed that the aggressiveness of breast cancer negatively correlates with age, being lower in chronologically old mice, similar to what occurs in humans. Given that oxidative stress is associated with tumour susceptibility and the degree of aging, the association between the aggressiveness of breast cancer and multiple intermediate phenotypes directly or indirectly related to oxidative stress was studied. Using a mathematical model, we defined biological age and the degree of aging as the difference between biological and chronological ages. As a result, we observed that biologically old mice predominated among those that developed the disease early on, that is, those that were chronologically young. We then identified the specific and common genetic components of Quantitative Trait loci or QTL associated with different evolution of breast cancer, the intermediate phenotypes related to oxidative stress studied, the biological age and the degree of aging. Lastly, we showed that the expression pattern in the livers of biologically old mice were enriched in signalling pathways related to inflammation and response to infections; whereas the biologically young mice exhibited enriched pathways related to mitochondrial activity. For the explanation and discussion of these data refer to the research article cited above.

Referencias bibliográficas

  • Guy, (1992), Proc, Natl. Acad. Sci USA, 89, pp. 10578, 10.1073/pnas.89.22.10578
  • Yau, (2007), Breast Cancer Res., 9, pp. R59, 10.1186/bcr1765
  • Narod, (2012), Nat. Rev. Clin. Oncol., 9, pp. 460, 10.1038/nrclinonc.2012.102
  • Benz, (2008), Nat. Rev. Cancer, 8, pp. 875, 10.1038/nrc2522
  • De Flora, (2001), Carcinogenesis, 22, pp. 999, 10.1093/carcin/22.7.999
  • Mitsui, (2002), Antioxid. Redox Signal., 4, pp. 693, 10.1089/15230860260220201
  • Blanco-Gomez, (2016), BioEssays: News and Reviews in Molecular, Cellular and Developmental Biology, 38, pp. 664, 10.1002/bies.201600084
  • Cho, (2012), PLoS Comput. Biol., 8, pp. e1002820, 10.1371/journal.pcbi.1002820
  • Castellanos-Martin, (2015), Genome Biol., 16, pp. 40, 10.1186/s13059-015-0599-z
  • Lin, (2016), Nature, 540, pp. 124, 10.1038/nature20558
  • Tomayko, (1989), Cancer Chemother. Pharmacol., 24, pp. 148, 10.1007/BF00300234
  • Hastie, (1990), Nature, 346, pp. 866, 10.1038/346866a0
  • Livak, (2001), Methods, 25, pp. 402, 10.1006/meth.2001.1262
  • Lander, (1995), Nature genetics, 11, pp. 241, 10.1038/ng1195-241
  • Broman, (2003), Bioinformatics, 19, pp. 889, 10.1093/bioinformatics/btg112