2017; 02(02): 034-040 bmr/16/1622/gmj

Original Research Article

Predicting and Identifying Human Glioblastoma MiRNA Targets Using RRSM and qPCR Methods

Jian Shi*1 and Shiwei Huang2
1* Department of Neurology, Department of Veterans Affairs Medical Center, San Francisco and University of California, San Francisco, CA 94121, USA;
22Drexel University College of Medicine, Philadelphia, PA 19102, USA.

Correspondence to
J. Shi, Department of Neurology, Department of Veterans Affairs Medical Center, San Francisco and University of California, San Francisco, CA 94121, USA

First Published Online 10 February 2017

ABSTRACT

The pathogenesis and progression of glioblastoma multiforme (GBM) have been investigated extensively, but the genetic factors involved in the development of the disease remain poorly understood. The outcome of GBM is still grim. Recently, numerous microRNA (miRNA) mediated gene regulation and interactions have been found to be involved in the development of the disease, making the disease more difficult to understand using the traditional methods. This study used a bioinformatics pipeline-the relative R-squared method (RRSM)-to predict cancer related miRNA targets using gene expression profiles and motif complementary sequences, prior to quantitative real-time PCR experiments in human GBM tissues and cancer cell lines. This study predicted and confirmed 25 miRNA candidates associated to GBM in a comprehensive and non-biased manner, and ten miRNA candidates were also investigated as potential GBM biomarkers. The combination of bioinformatics algorithm and molecular techniques may yield clues to the mechanism of transcriptional and post-transcriptional regulation in the development of glioblastoma and new information about the genetic networks related to the disease.

Keywords: miRNA, GBM, bioinformatics, real-time PCR, biomarker

[Full Text - PDF]

© 2017 - Grant Medical Publishing Group | Privacy policy