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Translating Proteomic Into Functional Data: An High Mobility Group A1 (HMGA1) Proteomic Signature Has Prognostic Value in Breast Cancer

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Wisniewski,  Jacek R.
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Citation

Maurizio, E., Wisniewski, J. R., Ciani, Y., Amato, A., Arnoldo, L., Penzo, C., et al. (2016). Translating Proteomic Into Functional Data: An High Mobility Group A1 (HMGA1) Proteomic Signature Has Prognostic Value in Breast Cancer. Molecular and Cellular Proteomics, 15(1), 109-123. doi:10.1074/mcp.M115.050401.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0029-75B0-F
Abstract
Cancer is a very heterogeneous disease, and biological variability adds a further level of complexity, thus limiting the ability to identify new genes involved in cancer development. Oncogenes whose expression levels control cell aggressiveness are very useful for developing cellular models that permit differential expression screenings in isogenic contexts. HMGA1 protein has this unique property because it is a master regulator in breast cancer cells that control the transition from a nontumorigenic epithelial-like phenotype toward a highly aggressive mesenchymal-like one. The proteins extracted from HMGA1-silenced and control MDA-MB-231 cells were analyzed using label-free shotgun mass spectrometry. The differentially expressed proteins were cross-referenced with DNA microarray data obtained using the same cellular model and the overlapping genes were filtered for factors linked to poor prognosis in breast cancer gene expression meta-data sets, resulting in an HMGA1 protein signature composed of 21 members (HRS, HMGA1 reduced signature). This signature had a prognostic value (overall survival, relapse-free survival, and distant metastasis-free survival) in breast cancer. qRT-PCR, Western blot, and immunohistochemistry analyses validated the link of three members of this signature (KIFC1, LRRC59, and TRIP13) with HMGA1 expression levels both in vitro and in vivo and wound healing assays demonstrated that these three proteins are involved in modulating tumor cell motility. Combining proteomic and genomic data with the aid of bioinformatic tools, our results highlight the potential involvement in neoplastic transformation of a restricted list of factors with an as-yet-unexplored role in cancer. These factors are druggable targets that could be exploited for the development of new, targeted therapeutic approaches in triple-negative breast cancer.