Abstract

BackgroundAn 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.ResultsHere, 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.ConclusionsConsidering 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0599-z) contains supplementary material, which is available to authorized users.

Highlights

  • An essential question in cancer is why individuals with the same disease have different clinical outcomes

  • These results suggest that the C57BL/6 genetic background carries genetic determinants that build up resistance to most of these breast tumor pathophenotypes in a dominant manner

  • We identified a number of possible liver signaling quantitative trait locus (QTL) (LsQTLs; Figure 6; Table S14 in Additional file 1), but few of these overlap with tumor signaling quantitative trait locus (tsQTL), such as LsQTL3 and tsQTL6, indicating that the genetic control of these signaling molecules could in part be tissue-specific (Figure 6)

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Summary

Introduction

An essential question in cancer is why individuals with the same disease have different clinical outcomes. Identifying associations at different levels, and the influence of the genetic background in them, is crucial if we are to fully understand the different patterns of behavior of the disease, and will help to design better strategies for individualized cancer prevention and therapy. The identification of these complex networks in human populations is a difficult task owing to genetic heterogeneity and complex interactions with the environment [7,9,10]. Crosses of inbred mouse strains with homogenous genomes and fairly uniform phenotypes offer a unique opportunity to tackle these questions under simpler conditions [7,11,12]

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