Print Email Facebook Twitter Systematic functional perturbations uncover a prognostic genetic network driving human breast cancer Title Systematic functional perturbations uncover a prognostic genetic network driving human breast cancer Author Gallenne, Tristan (Netherlands Cancer Institute; Merus BV) Ross, Kenneth N. (Massachusetts General Hospital; Harvard Medical School) Visser, Nils L. (Netherlands Cancer Institute) Desmet, Christian J. (Netherlands Cancer Institute) Wittner, Ben S. (Massachusetts General Hospital; Harvard Medical School) Wessels, L.F.A. (TU Delft Pattern Recognition and Bioinformatics; Netherlands Cancer Institute) Ramaswamy, Sridhar (Massachusetts General Hospital; Harvard Medical School; Broad Institute of MIT and Harvard; Harvard-Ludwig Center for Cancer Research) Peeper, Daniel Ss (Netherlands Cancer Institute) Date 2017 Abstract 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 ninegene 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. Subject Breast cancerMetastasisPrognosisTumor biology To reference this document use: http://resolver.tudelft.nl/uuid:8e8d0cc5-4e45-49c7-b884-872bc30608e9 DOI https://doi.org/10.18632/oncotarget.16244 Source OncoTarget, 8 (13), 20572-20587 Part of collection Institutional Repository Document type journal article Rights © 2017 Tristan Gallenne, Kenneth N. Ross, Nils L. Visser, Salony, Christian J. Desmet, Ben S. Wittner, L.F.A. Wessels, Sridhar Ramaswamy, Daniel Ss Peeper Files PDF 38242644.pdf 8.52 MB Close viewer /islandora/object/uuid:8e8d0cc5-4e45-49c7-b884-872bc30608e9/datastream/OBJ/view