Category: Basic Science: Oncology

MP1-10 - Renal Cancer Cell Carcinoma Detection Using Targeted Plasma Metabolic Profiling

Thu, Sep 20
4:00 PM - 6:00 PM

Introduction & Objective :

Renal cell carcinoma (RCC) has increased in incidence with 65,340 new cases.   Previous studies have demonstrated detectable disturbances in metabolite profiles are indicative of pathophysiological or oncogenic changes. Consequently, metabolite markers may potentially provide improved diagnostic ability & earlier detection. Despite the role of product metabolites in the molecular pathogenesis of cancer, robust metabolic markers to enable screening for recurrence of cancer and therapeutic monitoring of RCC are lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolic profiling approach for identifying metabolic marker candidates that could enable highly sensitive and specific RCC detection using human plasma samples.


Methods :

We developed a pathway-specific assay which covers ~400 metabolites of biological significance. These metabolites, which are representative of more than 35 metabolic pathways, were monitored in 14 plasma samples taken from two groups of subjects (10 RCC patients and 4 healthy controls) collected at the University of Arizona College of Medicine (Tucson, AZ). Univariate statistical methods were applied for significance testing. For LC-MS/MS data, multivariate statistical analyses were applied to determine latent factor structure as well build a predictive model.


Results :

In this targeted approach, 131 metabolites were detected from a panel of >400. Of these, 33 metabolites exhibited statistically significant differences between RCC patients and healthy controls (p< 0.05), and 22 metabolites demonstrated both p < 0.05 and fold changes >2 in the volcano plot. Principal component analysis (PCA) clearly separated RCC & control groups, with PC1 carrying 51% of data variance. A receiver operating characteristic (ROC) curve generated based on these PLS-DA models showed ability to distinguishing RCC from normal controls (Figure 1). Cross validation was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach. Pathway analysis was conducted using 22 significant metabolites; demonstrating altered purine metabolism as well as altered taurine and hypotaurine metabolism.


Conclusions :

In this pilot study, the results indicate the effectiveness of our metabolomics approach for renal cancer diagnosis and potential early detection of recurrence. Future studies should examine larger cohorts from multiple locations to validate the altered metabolites and metabolic pathways related to RC pathogenesis discovered in our study.

Benjamin R. Lee

Professor and Chief, Urology
University of Arizona College of Medicine
Tucson, Arizona

Dr. Benjamin Lee, Professor & Chief of Urology at the University of Arizona College of Medicine has focused his career on advancing new treatments for renal cell carcinoma as well as calculus disease, while developing new technologies & techniques for Urologic Oncology & Endourology. He is author or co-author of more than 200 manuscripts, book chapters, videos and abstracts. Dr. Lee graduated from Cornell University magna cum laude. He then attended the Johns Hopkins School of Medicine, and continued his training at the James Buchanan Brady Urological Institute at the Johns Hopkins Hospital. He was Assistant Professor at the North Shore Long Island Jewish Medical Center, and then promoted to Associate Professor. He was promoted to Professor with tenure at the Department of Urology at the Tulane University School of Medicine in 2008, and assumed the position of Professor and Chief of Urology at the University of Arizona College of Medicine in 2016. He has published on methods identifying methods of decreasing recurrence of cancer; explanations why the immune system may be activated differently following laparoscopy compared to open surgery, and has developed nanotechnology applications in urologic disease as well as studies into preserving kidney function during laparoscopic & robotic kidney surgery. Dr. Lee’s research has been recognized by awards from the American Urological Association, The Endourological Society and Urology Journal. He was awarded the prestigious Arthur Smith Award in 2008 for his contributions to the discipline of robotics, laparoscopy, and minimally invasive surgery. He was Organizing Secretary of the 31st World Congress of Endourology which was held in New Orleans, LA in 2013.

Xiaojian Shi

Phoenix, Arizona

Ken Batai

Division of Urology, University of Arizona College of Medicine
Tucson, Arizona

Xinchen Wang

Tucson, Arizona

Andrew Bergersen

Tucson, Arizona

Haiwei Gu

Assistant Professor
Arizona State University
Phoenix, Arizona