News Summary

• University of Minnesota Medical School researchers have identified gene biomarkers that can predict which patients with advanced stages of ovarian cancer will respond to standard chemotherapy and which will fail.
• The research will allow physicians to identify patients who will not respond to the standard chemotherapy and to apply a different treatment from the outset, which could increase the survival of those patients.
• The results of the research are published in the latest online issue of the journal Cancer Informatics. 

Quotes

“This research will allow physicians to identify those patients who will not respond to the standard chemotherapy and to apply a different treatment from the outset, which could increase the survival of those patients. Furthermore, this research could lead to the development of new, more efficacious pharmaceuticals that could considerably extend the survival of those patients, or perhaps even constitute a cure for this disease.” - Dr. Jason B. Nikas

“The next step is to confirm these gene expression biomarkers with additional ovarian cancer patients in order to establish the clinical utility of these biomarkers. We’re obviously excited about this research and what it could mean for the advancement of treating this disease.” - Dr. Walter Low

Full Text

University of Minnesota Medical School researchers have identified gene biomarkers that can predict which patients with advanced stages of ovarian cancer (stages III-IV) will respond to standard chemotherapy (platinum/taxol) and which will fail.
The results of the research are published in the October 3, 2011 online issue of the journal Cancer Informatics.

Epithelial ovarian cancer is the most lethal gynecological cancer in the United States, but because of the lack of overt symptoms at the early stages of the disease more than 60 percent of patients receive a diagnosis when their disease has already reached an advanced stage.

As a result, health care providers need to know quickly which patients will respond to standard chemotherapy and which will not, shaving valuable time off their treatment approach.
“This research will allow physicians to identify those patients who will not respond to the standard chemotherapy and to apply a different treatment from the outset, which could increase the survival of those patients,” said the study’s lead author Dr. Jason B. Nikas of the University of Minnesota Medical School. “Furthermore, this research could lead to the development of new, more efficacious pharmaceuticals that could considerably extend the survival of those patients, or perhaps even constitute a cure for this disease.”

To arrive at their results, the study’s authors examined ovarian tumor tissue from patients with advanced cancer prior to chemotherapy and determined gene expression profiles. After treatment, patients were stratified as treatment responders and long-term survivors (living greater than 7 years) or treatment non-responders and short-term survivors (living less than 3 years).

The researchers found that specific combinations of genes were capable of predicting treatment responders vs. non-responders with accuracies greater than 95% based on 54 ovarian cancer patients (24 responders/long term survivors, and 30 non-responders/short term survivors).

In their report, the researchers also indicated that the biomarkers identified in their study represent altered gene networks that could serve as targets for the development of novel and more effective pharmacological treatments.

“The next step is to confirm these gene expression biomarkers with additional ovarian cancer patients in order to establish the clinical utility of these biomarkers,” said co-investigator Dr. Walter Low of the University of Minnesota’s Masonic Cancer Center. “We’re obviously excited about this research and what it could mean for the advancement of treating this disease.”

Other co-investigators participating in this study are Dr. Amy Skubitz and Dr. Kristin Boylan in the Department of Laboratory Medicine and Pathology at the University of Minnesota Medical School. This research was funded with grants from the National Institutes of Health and from the National Cancer Institute.

For a copy of the study visit: http://www.la-press.com/mathematical-prognostic-biomarker-models-for-treatment-response-and-su-article-a2863