Temporal analysis of oncogenesis using microRNA expression data

• MicroRNAs (miRNAs) have rapidly become the focus of many cancer research studies. These small non-coding RNAs have been shown to play important roles in the regulation of oncogenes and tumor suppressors. It has also been demonstrated that miRNA expression profiles differ significantly between normal and cancerous cells, which indicates the possibility of using miRNAs as markers for cancer diagnosis and prognosis. However, not much is known about the regulation of miRNA expression. One of the issues worth investigating is whether deregulations of miRNA expression in cancer cells occur according to some pattern or in a random order. We therefore selected two approaches, previously used to derive graph models of oncogenesis using chromosomal imbalance data, and adapted them to miRNA expression data. Applying the adapted algorithms to a breast cancer data set, we obtained results indicating the temporal order of miRNA deregulations during tumor development. When analyzing the specific deregulations appearing at different time points in the derived model, we found that several of the deregulations identified as early events could be supported through literature studies.

Nyckelord

Breast cancer data

Cancer cells

Cancer diagnosis

Cancer research

Cancerous cells

Expression data

Expression profile

Graph model

MicroRNA expression

MicroRNAs

Non-coding RNAs

Oncogenesis

Temporal analysis

Temporal order

Time points

Tumor development

Tumor suppressors

Bioinformatics

Deregulation

Diagnosis

Diseases

Oncogenic viruses

Tumors

RNA

Bioinformatik

Bioinformatics

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)