03:13am Thursday 21 September 2017

New technology pinpoints genetic differences between cancer, non-cancer patients

The multidisciplinary team has created a design for a new DNA microarray that allows them to measure the 2 million microsatellites (short, repetitive DNA sequences) found within the human genome. Microsatellites, which tend to vary greatly among individuals and have traditionally been used in forensics and paternity tests, are also used to uncover information related to a number of other genetic diseases such as Fragile-X or Huntington’s disease. 

This advancement aided the discovery of a unique pattern of microsatellite variation in breast cancer patients that were not present in the DNA of patients who are cancer-free. Through their evaluation of global changes in the genome, the researchers determined that this pattern change alludes to a new mechanism disrupting the genome in cancer patients and represents a new breast cancer risk biomarker. There are indications that this could also serve as a general cancer signature. 

The results of the work, which includes contributions from researchers from the University of Texas Southwestern Medical Center, will be featured in an upcoming edition of the journal Genes, Chromosomes and Cancer. The study is currently available online.

“We have now arrived at a new biomarker – an indicator that could be used to evaluate the amount of risk that you have for developing cancer in the future,” explained Virginia Bioinformatics Institute Executive Director Harold “Skip” Garner, who also leads the institute’s Medical Informatics and Systems Division. “This is part of an effort to understand their (microsatellite) role in the genome and then proceed on directly towards something that is of utility in the clinic. What just came out in our paper is a description of the technology that allows us to very quickly and efficiently and inexpensively measure these 2 million places using a uniquely designed microarray. It’s the pattern on that microarray that provides us the information we need.”

Watch a video of Garner discussing the research and its implications.

Only a small percentage of microsatellites have been linked to cancer and other diseases because there hasn’t been an effective method available for evaluating large numbers of these sequences. This technology is enabling scientists to understand the role of these understudied parts of our genome for the first time and may help explain the difference between the known genetic components in disease and those that have been explained by genomic studies. This tool can be used to identify and better understand genetic changes in many different types of cancer with the potential to serve as a universal cancer biomarker. It has already been instrumental in the discovery of a new biomarker in the estrogen-related receptor gamma (ERR-γ) gene, which indicates an individual’s increased risk for breast cancer.  The group is now pursuing a number of these cancer predisposition risk markers in colon, lung, and other cancers.

This work was funded by the Virginia Bioinformatics Institute at Virginia Tech, the P.O’B Montgomery Distinguished Chair in Developmental Biology, and an National Institutes of Health Cardiology Fellowship, and was partially supported by the University of Texas’ National Institutes of Health’s National Cancer Institute SPORE project (P50CA70907).

The Virginia Bioinformatics Institute at Virginia Tech is a premier bioinformatics, computational biology, and systems biology research facility that uses transdisciplinary approaches to science combining information technology, biology, and medicine. These approaches are used to interpret and apply vast amounts of biological data generated from basic research to some of today’s key challenges in the biomedical, environmental, and agricultural sciences. With more than 240 highly trained multidisciplinary, international personnel, research at the institute involves collaboration in diverse disciplines such as mathematics, computer science, biology, plant pathology, biochemistry, systems biology, statistics, economics, synthetic biology, and medicine. The large amounts of data generated by this approach are analyzed and interpreted to create new knowledge that is disseminated to the world’s scientific, governmental, and wider communities.

Share on:

Health news