A New Way to Predict Cancer

Disclaimer: Results are not guaranteed*** and may vary from person to person***.

Predict cancer like thisBreast cancer is a very tricky disease to fight—not because it can’t be sent into remission—but because no one is able to predict if and when malignant tumors might reappear. Sometimes a breast cancer survivor’s cancer can come back five years later and sometimes it can remain dormant, only to reappear after 25 years.

This is obviously problematic for breast cancer survivors. When doctors can’t predict who is at high risk and who is at low risk for relapse, women may not be getting the individualized treatment they need. For those who are at high risk, their cancer may not be treated aggressively enough. On the other hand, those who have a low risk for relapse could be needlessly subjected to harsh and debilitating cancer treatments.

A research team from the University of Illinois in Chicago has found a potential solution to this problem. They have located a protein that they say can help predict breast cancer prognosis. The researchers used bioinformatics techniques to make their discovery.

Bioinfomatics is a field of medicine that develops and improves the ways researchers store, retrieve, organize, and analyze data. This usually involves developing software tools that will help researchers glean useful biological knowledge from their data. Although there are many different areas of medicine in which bioinformatics have proven useful, the study of genetics has particularly benefitted. Bioinformatics helps scientists to sequence and record genomes and their mutations. By utilizing the analytical capabilities of bioinformatics, the Chicago researchers discovered that the levels of expression of approximately 1,200 genes that are controlled by a specific enzyme—called EXH2—relate directly to the aggressiveness of breast cancer progression.

For the study, the researchers created breast cancer cells where they could dampen the expression of EZH2. By shutting down EZH2 expression, the genes that are controlled by this enzyme were reactivated. This, in turn, resulted in less aggressive cancer phenotypes.

At this point, you’re likely asking yourself the question, “Why don’t they inhibit EZH2 expression as a treatment if it makes cancer cells less aggressive?” Well, good question! That’s exactly what the researchers hope. Not only can EZH2 predict breast cancer aggressiveness, but it could also be developed as a therapeutic drug. Scientists have already developed small molecules that can inhibit the expression of EZH2. These tiny molecules could be manufactured at a lower cost to the consumer than other treatments involving larger molecules plus they are easier to absorb in the body. They could be taken by mouth rather than a more painful injection.

In another recent study, researchers used protein activation mapping technology combined with the genomic fingerprint of cancer to treat patients with breast cancer. These 25 patients had not responded to standard chemotherapy. They were signed up for the 2.5 year study to try to prevent the spread of breast cancer to other organs in their bodies. By using molecular profiling, the doctors treating the patients were inspired to try treatments that they would not normally have prescribed.

At least half the patients showed a 30% increase in surviving breast cancer that was “progression-free.” This is part of a radical shift that has oncologists targeting and treating the molecular makeup of cancer rather than simply a cancer’s location and hoping for the best in terms of relapse.

Source(s) for Today’s Article:
Jene-Sanz, A., et al., “Expression of Polycomb targets predicts breast cancer prognosis.” Molecular and Cellular Biology. August 5, 2013.
“Protein predicts breast cancer prognosis.” Science Daily web site, August 30, 2013; http://www.sciencedaily.com/releases/2013/08/130829155848.htm?utm_source=feedburner&utm_medium=email&utm_campaign=Feed%3A+sciencedaily%2Ftop_news%2Ftop_health+%28ScienceDaily%3A+Top+News+–+Top+Health%29, last accessed September 1, 2013.
Willis, L., et al., “What can be learnt about disease progression in breast cancer dormancy from relapse data?” PLoS One. May 2013; 8(5): e62320.
Jameson, G.S., et al., “A pilot study utilizing molecular profiling to find potential targets and select individualized treatments for patients with metastatic breast cancer,” J Clin Oncol.