Specific Class of Biomarkers May help Take Uncertainty Out of Cancer Prognosis

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A cancer diagnosis is a terrifying experience, and for most patients the associated uncertainty is especially frightening. Researchers at Cold Spring Harbor Laboratory in Cold Spring Harbor, New York, have now identified a specific class of biomarkers that may help them predict how how aggressive a patient’s cancer will be.

“There are undoubtedly dozens or hundreds of mutations that cause cancer, and that can be found in almost any tumor,” noted Jason Sheltzer, fellow at Cold Spring Harbor Laboratory.

“That’s why it was surprising to discover that these mutations are pretty evenly distributed in early-stage benign cancer as well as in the really aggressive, highly-malignant cancers,” Sheltzer added.

Easily identifiable factors
Mutations that cause cancer don’t actually tell you all that much about who will end up surviving and who will end up dying from cancer. And that’s why Sheltzer and his colleagues set out to find easily identifiable factors that can determine a cancer patient’s prognosis. Together with the help of software engineer Joan Smith, Sheltzer collected and analyzed the comprehensive history of nearly 20,000 cancer patients.

Figure 1.0: An analysis of breast cancer patient gene reveals that copy number alterations (CNAs) within cancer-causing genes is more likely to accurately indicate the severity of the disease (shown) than simply measuring how many of those genes are actually mutated to cause cancer (not shown).

According to an article recently published in the journal eLife, Sheltzer and his team not only traced each patient’s outcome – whether it be recovery or tragedy – but also took a closer look at genetic sites commonly associated with cancer causing mutations.

“While there wasn’t very much of a difference in the types of mutations that benign and aggressive tumors had, when we looked at copy number changes in these same genes, we found a very significant difference,” Sheltzer explained.

Gain or loss
Normally, the genetic information in a human cell comes in two copies distributed among 23 pairs of chromosomes. However, cancer cells often gain or lose chromosomes.

“A lot of cancers instead of having two copies of a gene, will have three copies, four copies, five copies, or only one copy of a gene instead,” explained Sheltzer. “We looked at the relationship between these copy number alterations and what happens to cancer patients and found a strong relationship.”

Sheltzer now hopes to launch a prospective analysis, closely studying new cancer patients for years after diagnosis. This could highlight which kinds of copy number changes are associated with which outcomes.

“That would be one of the first steps towards taking what we’ve learned and translating it into a clinically useful tool that could also provide patients with peace of mind,” Sheltzer concluded.

Reference
Smith, J, Sheltzer, J. Systematic identification of mutations and copy number alterations associated with cancer patient prognosis. December 11, 2018. DOI: https://doi.org/10.7554/eLife.39217


Last Editorial Review: January 2, 2019

Featured Image: Laboratory. Courtesy: © 2010 – 2019 Fotolia. Used with permission. Photo 1.0: An analysis of breast cancer patient gene reveals that copy number alterations (CNAs) within cancer-causing genes is more likely to accurately indicate the severity of the disease (shown) than simply measuring how many of those genes are actually mutated to cause cancer (not shown). Courtesy:  © 2010 – 2018 Sheltzer/CSHL 2018. Used with permission.

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