Priority Research Papers:
Systematic functional perturbations uncover a prognostic genetic network driving human breast cancer
Metrics: PDF 2061 views | HTML 2812 views | ?
Tristan Gallenne1,9, Kenneth N. Ross4,5,*, Nils L. Visser1,*, Salony4,5,*, Christophe J. Desmet1, Ben S. Wittner4,5, Lodewyk F.A. Wessels2,3, Sridhar Ramaswamy4,5,6,7,8 and Daniel S. Peeper1
1 Department of Molecular Oncology, The Netherlands Cancer Institute, Plesmanlaan, CX, Amsterdam, The Netherlands
2 Department of Molecular Carcinogenesis, The Netherlands Cancer Institute, Plesmanlaan, CX, Amsterdam, The Netherlands
3 Faculty of EEMCS Delft University of Technology, Delft, The Netherlands
4 Massachusetts General Hospital Cancer Center, Boston, MA, USA
5 Harvard Medical School, Boston, MA, USA
6 Broad Institute of Harvard & MIT, Cambridge, MA, USA
7 Harvard Stem Cell Institute, Cambridge, MA, USA
8 Harvard-Ludwig Center for Cancer Research, Boston, MA, USA
9 Current address: Merus B.V., Padualaan, CH Utrecht, The Netherlands
* These authors have contributed equally
Sridhar Ramaswamy, email:
Daniel S. Peeper, email:
Keywords: breast cancer, metastasis, prognosis, tumor biology
Received: December 14, 2016 Accepted: January 28, 2017 Published: March 15, 2017
Prognostic classifiers conceivably comprise biomarker genes that functionally contribute to the oncogenic and metastatic properties of cancer, but this has not been investigated systematically. The transcription factor Fra-1 not only has an essential role in breast cancer, but also drives the expression of a highly prognostic gene set. Here, we systematically perturbed the function of 31 individual Fra-1-dependent poor-prognosis genes and examined their impact on breast cancer growth in vivo. We find that stable shRNA depletion of each of nine individual signature genes strongly inhibits breast cancer growth and aggressiveness. Several factors within this nine-gene set regulate each other’s expression, suggesting that together they form a network. The nine-gene set is regulated by estrogen, ERBB2 and EGF signaling, all established breast cancer factors. We also uncover three transcription factors, MYC, E2F1 and TP53, which act alongside Fra-1 at the core of this network. ChIP-Seq analysis reveals that a substantial number of genes are bound, and regulated, by all four transcription factors. The nine-gene set retains significant prognostic power and includes several potential therapeutic targets, including the bifunctional enzyme PAICS, which catalyzes purine biosynthesis. Depletion of PAICS largely cancelled breast cancer expansion, exemplifying a prognostic gene with breast cancer activity. Our data uncover a core genetic and prognostic network driving human breast cancer. We propose that pharmacological inhibition of components within this network, such as PAICS, may be used in conjunction with the Fra-1 prognostic classifier towards personalized management of poor prognosis breast cancer.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 License.