Despite progress in the understanding of tumor biology, clinical trials designed using specialized new therapies against specific biologic and genetic changes in patient’s tumors commonly fail. This is most likely, because current methods are limited by identifying those specific changes in the tumor using thousands of cells from tumor biopsies, which mask the changes in the small number of cancer cells that determine the patient’s outcome. In order to overcome this limitation these specific changes might need to be analyzed on a single cell level, given that tumors start and grow from a single cell.
Even though ovarian cancer is subdivided into 4 molecular subtypes, the current treatment approach uses a one size fits all approach. Over half of women treated with the standard chemotherapy for ovarian cancer in addition to radical surgery, relapse within three years of treatment. Once relapsed, the majority of women die within five years of diagnosis.
Recent advances using immune system based treatments have significantly improved outcomes for patients with melanoma and lung cancer. Initial clinical trial in ovarian cancer suggest that only about 10% of all patients with recurrent ovarian cancer might benefit from these immune treatments.
In this current proposal we like to leverage on the successful application of single cell analysis of ovarian cancer tumors in our initial proposal and apply these advanced and more detailed analysis to tumor samples from two immune based clinical trials in recurrent ovarian cancer. This can help to possibly better identify the 10% of patients to benefit from these treatments. Furthermore we will apply the single cell analysis to samples from a feasibility pilot study testing immune cell based treatment for future clinical trials in ovarian cancer. Finally we will leverage the existing single cell ovarian cancer datasets generated in the initial proposal to develop hypothesis for future immune based clinical trials in ovarian cancer.
Using the improved resolution of single cell analysis data in ovarian cancer can help to the promise of immune therapies in ovarian cancer to improve patients’ lives. If successful this unique approach can be used for other tumors or disease processes for true patient precision medical care.
Boris J.N. Winterhoff, MD, MS, is an assistant professor in the Division of Gynecologic Oncology at the University of Minnesota. Dr. Winterhoff, a native of Germany, completed his fellowship in Gynecologic Oncology at the Mayo Clinic. Prior to his fellowship, he did his OB/Gyn residency training and a translational research fellowship in cancer genomics at the Mayo Clinic in collaboration with UCLA. Dr. Winterhoff obtained his medical degree and a doctoral degree in molecular oncology from the Christian Albrecht’s University in Kiel, Germany.
Dr. Winterhoff has a strong background and interest in clinical translation of cancer genomics and precision medicine and its application in ovarian cancer through work in various national and international collaborations