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A network-biology perspective of microRNA function and dysfunction in cancer

Nature Reviews Genetics volume 17, pages 719–732 (2016)Cite this article

Subjects

Key Points

  • MicroRNAs (miRNAs) have important functions in controlling many cell properties, including cell growth and differentiation. Their dysregulation is a frequent contributor to cancer growth and progression.

  • miRNAs post-transcriptionally regulate biological processes through their coordinated activities on pathways and networks.

  • miRNAs act cooperatively with other miRNAs and with transcription factors, which are frequent targets of miRNAs.

  • miRNAs typically act as control nodes or hubs in regulatory networks. Delineating their functional effects requires elucidation of their upstream regulators and downstream targets.

  • In silico and experimental methods for identifying direct targets of miRNAs are advancing rapidly.

  • Information from patient-derived mass-transcriptomic data sets will contribute enormously to future efforts to derive clinically relevant outcomes from complex biological networks.

Abstract

MicroRNAs (miRNAs) participate in most aspects of cellular differentiation and homeostasis, and consequently have roles in many pathologies, including cancer. These small non-coding RNAs exert their effects in the context of complex regulatory networks, often made all the more extensive by the inclusion of transcription factors as their direct targets. In recent years, the increased availability of gene expression data and the development of methodologies that profile miRNA targets en masse have fuelled our understanding of miRNA functions, and of the sources and consequences of miRNA dysregulation. Advances in experimental and computational approaches are revealing not just cancer pathways controlled by single miRNAs but also intermeshed regulatory networks controlled by multiple miRNAs, which often engage in reciprocal feedback interactions with the targets that they regulate.

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Figure 1: An example of microRNAs from a single gene that jointly regulate multiple targets in a network.
Figure 2: Individual and co-expressed microRNAs target multiple genes in common pathways to mediate effects.
Figure 3: Schematic representation of common microRNA–transcription factor auto-regulatory network motifs.

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Acknowledgements

C.P.B. is supported by a Florey Fellowship from the Royal Adelaide Hospital Research Foundation, and H.S.S. and G.J.G. are supported by fellowships from the Australian National Health and Medical Research Council (GNT1023059 and GNT1026191). C.P.B., H.S.S. and G.J.G. acknowledge grant funding from the Australian National Health and Medical Research Council (GNT1034633 and GNT1069128 to G.J.G. and C.P.B., and GNT1068773 to G.J.G.) and the Australian National Breast Cancer Foundation.

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Authors and Affiliations

  1. Centre for Cancer Biology, an alliance of SA Pathology and University of South Australia, Adelaide, 5000, South Australia, Australia

    Cameron P. Bracken, Hamish S. Scott & Gregory J. Goodall

  2. Department of Medicine, University of Adelaide, Adelaide, 5005, South Australia, Australia

    Cameron P. Bracken, Hamish S. Scott & Gregory J. Goodall

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  1. Cameron P. Bracken
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Related links

DATABASES

miRBase

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Glossary

MicroRNA

(miRNA). Short (∼ 19–25 nucleotides in length) non-coding RNA that forms the target recognition component of the RNA-induced silencing complex.

RNA-induced silencing complex

(RISC). Ribonucleoprotein complex containing an Argonaute-bound microRNA that enables target recognition and accessory proteins that collectively mediate target destabilization and translational inhibition.

Argonaute

(AGO). The microRNA-binding protein in RNA-induced silencing complex. Four different AGO proteins, AGO1–AGO4, are present in mammals.

Seed region

The predominant target-recognition region of a microRNA, typically nucleotides 2–8 from the 5′ end. In recognition of the importance of the seed, microRNAs are grouped into families of shared seed sequence.

Liquid biopsies

Analyses of gene expression from circulating tumour cells and cell-free tumour DNA released into the blood or lymphatic system. Used as a means to improve diagnosis and treatment strategy.

Focal adhesion

Dynamic membrane-associated protein complexes through which the internal cell cytoskeleton connects with the surrounding extracellular matrix.

Invadopodia

Actin-rich extensions of the cell membrane that are associated with extracellular matrix degradation in cancer cell invasion.

Polycistronic cluster

Two or more genes or microRNAs that are encoded (and presumably co-expressed) from a single parental transcript.

3′ untranslated regions

(3′ UTRs). The part of the mRNA transcript 3′ to the protein coding region that constitutes the main functional microRNA-targeting region.

KEGG

(Kyoto Encyclopedia of Genes and Genomes). Database of biological pathways commonly used as a resource for understanding high-level functions of a biological system from gene-level information derived from high-throughput experimental techniques.

Epithelial–mesenchymal transition

(EMT). A process regulated by a complex gene-expression programme through which epithelial cells, which normally maintain close contacts with their neighbours through tight junctions, adherens junctions and desmosomes, transition towards a mesenchymal phenotype, whereby cells dissociate from their neighbours and become motile. Carcinomas, the most common form of solid tumours, arise from epithelial cells, with EMT being an important (although controversial) step in the progression to metastasis.

Drosha

The nuclear RNase-type III enzyme in the microprocessor complex (along with DGCR8) that cleaves the precursor microRNA stem–loop from the microRNA primary transcript (pri-miRNA).

Dicer

A second RNase-type III enzyme that operates in the biogenesis pathway downstream of Drosha to cleave precursor microRNAs in the cytoplasm to generate mature microRNAs that are loaded onto Argonaute.

Mammosphere

Spherical structures that are formed from the clonal growth of mammary-derived cells that have stem cell-like properties.

Xenograft

Cell, tissue or organ transplant from the donor of one species into a recipient of another species.

OncomiR

A microRNA that has been functionally associated with the promotion of cancer.

Axial patterning

Control of body morphology through the actions of homeotic genes.

Network motif

Recurrent and statistically significant patterns of genetic interconnections in complex biological networks.

HITS–CLIP

(High-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation). Methodology by which Argonaute–microRNA–mRNA targets are crosslinked (by ultraviolet light) and purified (by Argonaute immunoprecipitation) to reveal microRNA targets on a global scale using high-throughput sequencing.

Fragile sites

Specific and heritable chromosomal locations that are prone to breakage on replication stress, especially in cancer.

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Bracken, C., Scott, H. & Goodall, G. A network-biology perspective of microRNA function and dysfunction in cancer. Nat Rev Genet 17, 719–732 (2016). https://doi.org/10.1038/nrg.2016.134

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