MicroRNAs in Prostate Cancer: A Possible Role as Novel Biomarkers and Therapeutic Targets?

  • Paolo Gandellini
  • Marco Folini
  • Nadia Zaffaroni


Eradication of advanced prostate cancer still represents an unsolved clinical problem, making the development of alternative treatment approaches highly desirable. Understanding the molecular alterations that distinguish the non-progressive from progressive disease will allow the identification of novel biomarkers for improved staging and prognostication, and will also provide mechanistic information to facilitate treatment selection and design of novel therapeutic approaches. MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate gene expression. Recent findings indicate that miRNAs are deregulated in human tumors, suggesting a potential role for these molecules in the pathogenesis of cancer. Thus far, only a limited number of studies have investigated miRNA expression in prostate cancer. Results indicate that miRNA expression profiles may distinguish carcinoma from non-neoplastic specimens and further classify tumors according to androgen dependence. In addition, a prognostic significance has been attributed to specific miRNAs as predictors of clinical recurrence following radical prostatectomy. These findings, together with the documented possibility to detect cancer-related miRNAs in blood and core biopsies, open a window on the possibility to utilize them as novel biomarkers. For a handful of miRNAs, functional investigation has also been pursued in prostate cancer experimental models to establish the rationale for the development of miRNA-based therapies. However, a better understanding of the role exerted by specific miRNAs in the onset and progression of prostate cancer is needed, as is a precise definition of their targets relevant to the disease, before translating these molecules into the clinical setting.


Benign Prostatic Hyperplasia Radical Prostatectomy miRNA Expression Gleason Score miRNA Expression Profile 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Netherlands 2011

Authors and Affiliations

  • Paolo Gandellini
    • 1
  • Marco Folini
    • 2
  • Nadia Zaffaroni
    • 2
  1. 1.Molecular Pharmacology Unit, Department of Experimental Oncology and Molecular MedicineFondazione IRCCS Istituto Nazionale dei TumoriMilanItaly
  2. 2.Department of Experimental Oncology and Molecular MedicineFondazione IRCCS Istituto Nazionale dei TumoriMilanItaly

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