IIT Home Page CNR Home Page

Interplay Between Long Noncoding RNAs and MicroRNAs in Cancer

In the last decade noncoding RNAs (ncRNAs) have been extensively studied in several biological processes and human diseases including cancer. microRNAs (miRNAs) are the best-known class of ncRNAs. miRNAs are small ncRNAs of around 20–22 nucleotides (nt) and are crucial posttranscriptional regulators of protein coding genes. Recently, new classes of ncRNAs, longer than miRNAs have been discovered. Those include intergenic noncoding RNAs (lincRNAs) and circular RNAs (circRNAs). These novel types of ncRNAs opened a very exciting field in biology, leading researchers to discover new relationships between miRNAs and long noncoding RNAs (lncRNAs), which act together to control protein coding gene expression. One of these new discoveries led to the formulation of the “competing endogenous RNA (ceRNA) hypothesis.” This hypothesis suggests that an lncRNA acts as a sponge for miRNAs reducing their expression and causing the upregulation of miRNA targets. In this chapter we first discuss some recent discoveries in this field showing the mutual regulation of miRNAs, lncRNAs, and protein-coding genes in cancer. We then discuss the general approaches for the study of ceRNAs and present in more detail a recent computational approach to explore the ability of lncRNAs to act as ceRNAs in human breast cancer that has been shown to be, among the others, the most precise and promising.


Autori esterni: Francesco Russo (Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark), Giulia Fiscon (Institute for Systems Analysis and Computer Science "A. Ruberti" (IASI), National Research Council (CNR), Rome, Italy), Milena Rizzo (Institute of Clinical Physiology, National Research Council (CNR), Pisa, Italy), Paola Paci (Institute for Systems Analysis and Computer Science "A. Ruberti" (IASI), National Research Council (CNR), Rome, Italy)
Autori IIT:

Tipo: Capitolo di libro
Area di disciplina: Information Technology and Communication Systems

File: Russo_et_al_Springer_v2.pdf

Attività: Biologia computazionale