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Tools produce different answers in microRNA profiles

When researchers at Baylor College of Medicine (www.bcm.edu) sought to mine The Cancer Genome Atlas for information on the effects of small bits of genetic material called microRNAs on survival for patients with ovarian cancer, they made a startling discovery.

Using a technique called microarray or gene chips, they identified 61 microRNAs associated with survival in 469 ovarian cancers. However, when they used next generation sequencing to ask the same question, they found 12 in the same specimens. Only one microRNA was associated with survival in both data sets. A report on their work appears in the open access journal PLOS One.

Choice of tool significant

“The choice of tools in genomic profiling can make a difference in the answers at which you arrive,” said Dr. Matthew L. Anderson, one of the corresponding authors of the report and an assistant professor of obstetrics and gynecology at Baylor.  “If you have a reliable tool for profiling, the picture should look the same or at least similar. For microRNAs in ovarian cancer, it doesn’t.  This discrepancy appears to be something specific to microRNAs, as other data dealing with genes and other genetic material are more consistent.”

This may occur because a tool that works on a long sequence of genetic material is less accurate on a shorter sequence, said Dr. Zhandong Liu, an assistant professor of pediatrics – neurology at Baylor and a member of the Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital and the other corresponding author. MicroRNAs are about 22 nucleotides in length and regulate the expression of genes.  By contrast, genes vary in length from several thousand nucleotides to more than 2 million. Nucleotides are the A (adenine), T (thymine), C (cytocine) and G (guanine) or U (uracil) that are the alphabet of genetic material.

“The impact of this could be important,” said Liu. “MicroRNAs are believed to be key drivers for cancer. This could have an important impact on similar studies. For now, I would urge caution in interpreting the microRNA data.”

Usable microRNA data

Both Anderson and Liu said that The Cancer Genome Atlas is an important tool for understanding cancer at all levels. However, they said, it is clear that more work is needed to understand how to mine it for usable microRNA data.

Others who took part in this work include Claire M. Mach and Genevra Allen, also of Baylor. Mach is also a faculty member in the College of Pharmacy at the University of Houston and Allen is a member of the department of statistics and electrical and & computer engineering at Rice University.

Funding for this work came from the Partnership for Baylor College of Medicine; the Collaborative Advances in Biomedical Computing Seed Funding Program at the Ken Kennedy Institute for Information Technology at Rice University supported by the John and Ann Doerr Fund for Computational Biomedicine and through the Center for Computational and Integrative Biomedical Research Seed Funding Program at Baylor College of Medicine; the National Science Foundation (Grant DMS-1209017 and DMS-1263932) and the Houston Bioinformatics Endowment.