Small non-coding RNAs can be used to predict if individuals have breast cancer conclude researchers who contribute to The Cancer Genome Atlas project. The results, which are published in EMBO reports, indicate that differences in the levels of specific types of non-coding RNAs can be used to distinguish between cancerous and non-cancerous tissues. These RNAs can also be used to classify cancer patients into subgroups of individuals that have different survival outcomes.
Small non-coding RNAs are RNA molecules that do not give rise to proteins but which may have other important functions in the cell. "For many years, small non-coding RNAs near transcriptional start sites have been regarded as 'transcriptional noise' due to their apparent chaotic distribution and an inability to correlate these molecules with known functions or disease," explains Steven Jones, one of the lead authors of the study, a professor at Simon Fraser University and the University of British Columbia, and a distinguished scientist at the BC Cancer Agency. "By using a computational approach to analyze small RNA sequence information that we generated as part of The Cancer Genome Atlas project, we have been able to filter through this noise to find clinically useful information," adds Jones. "The data from our experiments show that genome-wide changes in the expression levels of small non-coding RNAs in the first exons of protein-coding genes are associated with breast cancer."
