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."
The scientists were able to distinguish between the many different small non-coding RNAs that are found near the transcriptional start sites of genes in healthy individuals and patients with breast cancer (in this case, breast invasive carcinoma). They mapped these RNA molecules to specific locations on the DNA sequence and looked for correlations between the non-coding RNAs that were strongly expressed and the disease status of the patients from whom the tissue samples were isolated. The resea
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European Molecular Biology Organization