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Novel and Alternative Bioinformatics Approaches to Understand miRNA-mRNA Interactome in Cancer Research

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Systems Biology in Cancer Research and Drug Discovery

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Abstract

MicroRNAs (miRNAs) are short, non-coding RNAs which play important regulatory roles on target messenger RNAs (mRNAs) that in turn, result into posttranslational repression. This intricate interplay between miRNAs and mRNA plays significant roles in complex diseases such as cancer. In this review we will introduce the role of several miRNAs known to be associated with different human cancers. More importantly, we will outline many existing computational algorithms that predict miRNA targets. These target prediction algorithms can potentially provide valuable data-based information for further experimental validation of meaningful miRNA-mRNA interactomes responsible for serious diseases including cancer.

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Abbreviations

miRNA:

MicroRNA

mRNA:

Messenger RNA

ncRNA:

Non coding RNA

tRNA:

Translational RNA

UTR:

Untranslated region

piRNA:

PIWI interacting RNA

siRNA:

Short interfering RNA

PicTar:

Probabilistic identification of combinations of target sites

IPA:

Ingenuity pathway analysis

RISC:

RNA-induced silencing complex

APC:

Adenomatous polyposis coli gene

SNP:

Single nucleotide polymorphism

DsRNA:

Double stranded RNA

DsRBD:

dsRNA binding domain protein

CBC:

Components of the cap binding complex

ORF:

Open reading frame

AGO:

Argonaut protein

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Acknowledgements

We would like to thank Dr. Timothy O’Toole for assistance with manuscript preparation. This work was supported by NIH-CA133844 (S. Datta), NIH-R01 CA138410 (C. M. Klinge) and the center grant NIH-P20RR16481.

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Authors and Affiliations

  1. Department of Bioinformatics and Biostatistics, University of Louisville, 485 E. Gray Street, Louisville, KY, 40202, USA

    Xiaohong Li & Susmita Datta

  2. Department of Anatomical Sciences and Neurobiology, University of Louisville, 505 S. Hancock Street, Louisville, KY, 40202, USA

    Xiaohong Li

  3. Department of Biochemistry and Molecular Biology, University of Louisville, 580 S. Preston Street, Delia Baxter (Baxter II) Building, Room 221E, Louisville, KY, 40202, USA

    Carolyn M. Klinge

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  1. Xiaohong Li
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  2. Carolyn M. Klinge
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  3. Susmita Datta
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Correspondence to Susmita Datta .

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  1. Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA

    Asfar S. Azmi

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Li, X., Klinge, C.M., Datta, S. (2012). Novel and Alternative Bioinformatics Approaches to Understand miRNA-mRNA Interactome in Cancer Research. In: Azmi, A.S. (eds) Systems Biology in Cancer Research and Drug Discovery. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4819-4_11

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