Exosome Signatures of Kidney Cancer Response to Immune Checkpoint Inhibitor

Project Summary Combined immune checkpoint inhibitor therapy with nivolumab plus ipilimumab has become a standard first-line treatment for metastatic renal cell carcinoma (RCC). Unfortunately, information regarding whether patients are responding to this treatment regimen is not known until tumor diameters are measured on a computed tomography (CT) scan 2-3 months after starting therapy. This is because changes in tumor size typically cannot be reliably measured before this time frame. Patients for whom therapy is ineffective endure treatment side effects without benefit. Therefore, early biomarkers for therapeutic response are needed so that effective and ineffective treatment can be distinguished earlier than current standard of care and patients who do not derive benefit from this combination therapy can move on quicker to a potentially more effective treatment. Blood and urine exosomes are a prime candidate for serving as such a biomarker. The complex mechanisms of action of these drugs involve tumor cells, epithelial cells, immune cells, and other host factors. All these cells release exosomes into the blood stream, which contain protein and RNA derived from these cell types. Therefore, we hypothesize that early molecular effects in these cell types that lead to changes in tumor size on a 3-month CT scan can be measured in plasma proteins and/or exosomal proteins and RNA, specifically changes in KIM- 1, PD-L1, and exosomal micro-RNAs. Thus, exosomes may carry an early biomarker for therapeutic response that can be measured by protein analysis and transcriptomic profiling of exosomes isolated from blood and urine. In this pilot study, we will sequence exosomal RNA from the blood and urine of 50 patients with RCC at 3 time points: at treatment baseline and 3 and 6 weeks after initiating therapy with nivolumab and ipilimumab. We will 1) define for each analyte an exosome signature of response by determining the subset of exosomal transcripts that is differentially expressed on therapy compared to baseline and that correlates with the relative change in tumor burden; and 2) determine how early on treatment such a predictive signature can be feasibly detected (week 3 vs. week 6); and 3) whether blood exosomes alone, urine exosomes alone, or both in combination allow for the most accurate prediction of response. We will use this information to select the on-therapy time point and sampling strategy for validating this candidate predictive biomarker for response in a follow-up study.