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p73-Governed miRNA Networks: Translating Bioinformatics Approaches to Therapeutic Solutions for Cancer Metastasis

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Computational Biology of Non-Coding RNA

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1912))

Abstract

The transcription factor p73 synthesizes a large number of isoforms and presents high structural and functional homology with p53, a well-known tumor suppressor and a famous “Holy Grail” of anticancer targeting. p73 has attracted increasing attention mainly because (a) unlike p53, p73 is rarely mutated in cancer, (b) some p73 isoforms can inhibit all hallmarks of cancer, and (c) it has the ability to mimic oncosuppressive functions of p53, even in p53-mutated cells. These attributes render p73 and its downstream pathways appealing for therapeutic targeting, especially in mutant p53-driven cancers. p73 functions are, at least partly, mediated by microRNAs (miRNAs), which constitute nodal components of p73-governed networks. p73 not only regulates transcription of crucial miRNA genes, but is also predicted to affect miRNA populations in a transcription-independent manner by developing protein-protein interactions with components of the miRNA processing machinery. This combined effect of p73, both in miRNA transcription and maturation, appears to be isoform-dependent and can result in a systemic switch of cell miRNomes toward either an anti-oncogenic or oncogenic outcome. In this review, we combine literature search with bioinformatics approaches to reconstruct the p73-governed miRNA network and discuss how these crosstalks may be exploited to develop next-generation therapeutics.

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Acknowledgments

This work was supported by the German Cancer Aid, Dr. Mildred Scheel Stiftung [grant 70112353], the German Research Foundation (DFG) [grant PU188/17-1], Wilhelm Sander-Stiftung [grant 2015.036.1], German Federal Ministry of Education and Research (BMBF) grant 0316171 as part of the project eBio:SysMet, and Rostock University Medical Faculty for the project Systems Medicine of Cancer Invasion and Metastasis to B.M.P.

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  1. Institute of Experimental Gene Therapy and Cancer Research, Rostock University Medical Center, Rostock, Germany

    Stella Logotheti, Stephan Marquardt & Brigitte M. Pützer

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  1. Stella Logotheti
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  2. Stephan Marquardt
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  3. Brigitte M. Pützer
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Correspondence to Brigitte M. Pützer .

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  1. Department of Dermatology, Erlangen University Hospital, Erlangen, Germany

    Xin Lai

  2. Department of Systems Biology and Bioinformatics, University of Rostock, Rostock, Germany

    Shailendra K. Gupta

  3. Department of Dermatology, Erlangen University Hospital, Erlangen, Germany

    Julio Vera

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Logotheti, S., Marquardt, S., Pützer, B.M. (2019). p73-Governed miRNA Networks: Translating Bioinformatics Approaches to Therapeutic Solutions for Cancer Metastasis. In: Lai, X., Gupta, S., Vera, J. (eds) Computational Biology of Non-Coding RNA. Methods in Molecular Biology, vol 1912. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8982-9_2

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