| First Author | Castellanos-Martín A | Year | 2015 |
| Journal | Genome Biol | Volume | 16 |
| Issue | 1 | Pages | 40 |
| PubMed ID | 25853295 | Mgi Jnum | J:345620 |
| Mgi Id | MGI:7610095 | Doi | 10.1186/s13059-015-0599-z |
| Citation | Castellanos-Martin A, et al. (2015) Unraveling heterogeneous susceptibility and the evolution of breast cancer using a systems biology approach. Genome Biol 16(1):40 |
| abstractText | BACKGROUND: An essential question in cancer is why individuals with the same disease have different clinical outcomes. Progress toward a more personalized medicine in cancer patients requires taking into account the underlying heterogeneity at different molecular levels. RESULTS: Here, we present a model in which there are complex interactions at different cellular and systemic levels that account for the heterogeneity of susceptibility to and evolution of ERBB2-positive breast cancers. Our model is based on our analyses of a cohort of mice that are characterized by heterogeneous susceptibility to ERBB2-positive breast cancers. Our analysis reveals that there are similarities between ERBB2 tumors in humans and those of backcross mice at clinical, genomic, expression, and signaling levels. We also show that mice that have tumors with intrinsically high levels of active AKT and ERK are more resistant to tumor metastasis. Our findings suggest for the first time that a site-specific phosphorylation at the serine 473 residue of AKT1 modifies the capacity for tumors to disseminate. Finally, we present two predictive models that can explain the heterogeneous behavior of the disease in the mouse population when we consider simultaneously certain genetic markers, liver cell signaling and serum biomarkers that are identified before the onset of the disease. CONCLUSIONS: Considering simultaneously tumor pathophenotypes and several molecular levels, we show the heterogeneous behavior of ERBB2-positive breast cancer in terms of disease progression. This and similar studies should help to better understand disease variability in patient populations. |
