Research News

Cleveland Clinic data scientist Daniel Rotroff, PhD, and anesthesiologist Joseph Foss, MD, have received a nearly five million dollar grant from the National Institute of Neurological Disorders and Stroke, part of the National Institutes of Health (NIH), to identify biomarkers that can help physicians determine which cancer patients are most likely to develop a chemotherapy-associated pain condition.

“The ultimate utility of our study findings, we hope, will be to help physicians deliver more personalized therapies to patients living with cancer,” said Dr. Rotroff, assistant staff in the Department of Quantitative Health Sciences, “and to improve patients’ quality of life during and after treatment.”

Chemotherapy-associated pain: an undue patient burden

Chemotherapy-induced peripheral neuropathic pain (CIPNP) is a painful condition experienced by roughly 40 percent of patients who undergo treatment with a class of chemotherapy drugs called taxanes. It is one of the most common side effects of treatment that may cause patients to receive a reduced course of therapy. Symptoms can last for up to two years or longer, even after treatment has ceased, and many patients report it as “worse than death” on a validated quality of life indicator.

If care providers could accurately predict which patients are most likely to experience CIPNP, they could potentially prescribe different doses of taxane treatments or use different treatment strategies altogether, improving quality of life for patients and their families without compromising treatment effectiveness. “Having the ability to predict and measure chemotherapy-induced peripheral neuropathic pain will also provide a foundation for identifying new treatments for this challenging problem,” expanded Dr. Foss.

With this new support, Drs. Rotroff and Foss, in collaboration with Ken Johnson, MD, University of Utah Health, will look to uncover biological signatures associated with CIPNP. This work is based on studies into the mechanisms of CIPNP that the team performed with the late Dr. Mohamed Naguib, who was also one of the original principal investigators on the grant.

Taking a machine learning approach to personalized medicine in cancer care

Working with physician colleagues in oncology, they will collect clinical outcomes data and blood samples from breast cancer patients at various phases of taxane treatment. They will compare genetic, epigenetic and metabolic characteristics of patients who report experiencing treatment-associated pain against those who do not. Self-reported patient data from a standardized and validated CIPNP questionnaire will also help the researchers gain insights into clinical indicators of the condition.

Using machine learning technology, Dr. Rotroff and his team will develop mathematical algorithms that combine these biological and clinical biomarkers and can be used to forecast an individual patient’s likelihood of developing CIPNP.

“Our ultimate hope is that one day our algorithms will be widely available, perhaps in the electronic medical records of all cancer patients, so that risk for chemotherapy-induced peripheral neuropathic pain is considered before any treatment is initiated. Then, physicians could design personalized treatment plans that still provide strong efficacy while also minimizing adverse side effects as much as possible,” said Dr. Rotroff.

Dr. Rotroff is also the recipient of an NIH Mentored Clinical Research Scholar Award through the Clinical and Translational Science Collaborative of Cleveland. His lab uses a wide range of computational approaches to leverage multi-omics technologies and electronic health records to investigate aspects of precision medicine, including biomarkers of drug response and disease outcomes.

Dr. Foss, staff in the Anesthesiology Institute, is involved in research to define the mechanisms of neuropathic pain and develop novel treatments for the condition. He has received funding from Cleveland Clinic Innovations, the Alzheimer’s Drug Discovery Foundation and the Alzheimer’s Association.