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Jan 1, 2011 (Vol. 31, No. 1)

Power in Numbers for Cancer Biomarkers

Developing Effective Targeted Therapies Requires Elucidation of Multigene Signatures

  • miRNA Signatures

    miRNAs hold much promise as cancer biomarkers. These are small, noncoding RNAs that affect gene expression on the post-transcriptional level. Over 1,200 miRNAs are identified to date, and the expression profiles for many of these have been established.

    “miRNA profiles, like protein or mRNA profiles, reflect the functional, physiological state of a cell, tissue, or tumor, says Bernard Andruss, Ph.D., director of collaborations and business development at Asuragen (www.asuragen.com). “A particularly valuable application for miRNAs will be to augment the information obtained from other classes of biomarkers. The combination of miRNA profiles with other marker classes has the potential to drive higher overall biomarker performance.”

    miRNAs are known to regulate oncogenes and tumor suppressor genes. What makes them promising as biomarkers is that they are stable in a variety of biofluids (serum, saliva, cerebrospinal fluid) as well as in paraffin-fixed specimens, and their expression profile does not seem to be affected by normal physiological variations to the same extent as proteins.

    “I envision that miRNAs will become valuable biomarkers for cancer diagnostics, prognostic for survival, or predictive of disease recurrence or response to therapy,” says Glen Weiss, M.D., associate investigator, Translational Genomics Research Institute and director, thoracic oncology, at Scottsdale Healthcare’s Virginia G. Piper Cancer Center.

    “My research is focusing on using miRNAs as prognostic predictors of brain metastasis from lung cancer. By combining miRNA expression values with brain imaging and other validation techniques, our initial results show that we may be able to identify miRNAs that indicate increased probability of the future onset of brain metastasis,” says Dr. Weiss.

    In addition to other statistical measurements, the researchers utilized an algorithm called in silico conditioning. The algorithm identifies a set of miRNAs with a consistent expression pattern when brain metastasis are present. “Some of the tumors were collected months before the metastasis developed in the brain,” adds Dr. Weiss. “Validating the miRNA biomarkers predictive of the metastasis could have high impact on treatment decisions.”

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