Abstract
The numerous genome sequencing projects produced unprecedented amount of data providing significant information to the discovery of novel non-coding RNA (ncRNA). Several ncRNAs have been described to control gene expression and display important role during cell differentiation and homeostasis. In the last decade, high throughput methods in conjunction with approaches in bioinformatics have been used to identify, classify, and evaluate the expression of hundreds of ncRNA in normal and pathological states, such as cancer. Patient outcomes have been already associated with differential expression of ncRNAs in normal and tumoral tissues, providing new insights in the development of innovative therapeutic strategies in oncology. In this review, we present and discuss bioinformatics advances in the development of computational approaches to analyze and discover ncRNA data in oncology using high throughput sequencing technologies.
Highlights
The ENCODE project discovered that most of the human genome is transcribed, but only a tiny fraction of human DNA encode for proteins (ENCODE Project Consortium et al, 2007; Elgar and Vavouri, 2008)
Some non-coding RNA (ncRNA) classes are known for years, such as ribosomal and transport RNAs; small nucleolar RNAs; and small nuclear RNAs
The most studied ncRNA class in oncology is miRNA. These small RNAs have on average 22 nucleotides in length and mediate gene silencing by partially paring with specific regions of messenger RNAs to prevent its translation (Wu et al, 2012)
Summary
The ENCODE project discovered that most of the human genome is transcribed, but only a tiny fraction of human DNA encode for proteins (ENCODE Project Consortium et al, 2007; Elgar and Vavouri, 2008). Keller et al (2011) evaluated the miRNAs differentially expressed in the blood of NSLC patients and found some unknown miRNAs, including novel mature forms from known precursors Another example of HTS as tool to the identification of novel small ncRNA class is found in the study of Meiri et al (2010). The authors used HTS to evaluate the miRNA transcriptome of 23 solid tumor samples, including breast, bladder, colon, and lung They discovered 49 novel miRNA and sequence variants with different expression patterns among the samples and identified a novel class of small ncRNAs derived from Y-RNAs and endogenous siRNAs. Most of the HTS studies published so far have tried to identify miRNA to use as diagnostic or prognostic biomarkers in solid tumors or in circulation.
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