Multiplexed Quantification of Urinary Biomarkers for Noninvasive Classification of Imaged Kidney Tumors
Abstract
According to the National Cancer Institute, more than 79,000 new cases of kidney cancer are diagnosed annually, and almost 14,000 patients die. Nationally, kidney cancer is more common than leukemia and pancreatic cancer in men, and ovarian and pancreatic cancer in women, and it now accounts for almost 4% of adult cancers. Unfortunately, kidney cancer is 5-6 times greater in the military than the civilian population. There is currently no approved method for widespread assessment for kidney cancer. Providing proper care is predicated on the detection of kidney tumors either incidentally through abdominal imaging or by means of screening at-risk groups. Radiologic screening is impractical and expensive and, even if a kidney mass is detected, CT imaging cannot reliably differentiate malignant from benign tumors. The objective of this project is to develop a simple urine test to: (1) rule in the presence of malignant kidney cancer in unsuspecting patients; (2) rule out malignant kidney cancer through pre-surgical differential diagnosis of benign from malignant CT-imaged kidney masses, all to guide and inform physicians for appropriate treatment. Our laboratory has been instrumental in identifying the first-ever urine biomarkers for the non-invasive diagnosis of metastatic kidney cancer and in developing highly sensitive and specific nanotechnology-based assays for various biodiagnostic applications. In addition to the urine protein biomarkers that we have identified in the past, our collaborators have recently identified novel biomarkers of metastatic and benign tumors of the kidney. Over the next 3 years, we propose to combine kidney cancer biomarker assays with ultrasensitive fluorescence-based biosensors introduced by our lab to fully develop a rapid informative urine test to identify metastatic and benign kidney tumors. We will develop technology to simultaneously measure the concentration of five proteins in urine using an ultrabright nanostructure developed in our lab. We will measure protein biomarkers in the urine identified as diagnostic of metastatic or benign kidney tumors of patients with CT-imaged kidney masses, and compare results to the urine of demographically matched control individuals. Based on the concentrations of five proteins in the urine, we will develop a formula to accurately classify the tumors as benign or malignant. Our study will help fulfill the unmet need of a sensitive and specific diagnostic assay to non-invasively differentially diagnose imaged kidney masses or to identify individuals in at-risk groups who harbor a silent kidney tumor. Our study will rule in or rule out metastatic kidney cancer and guide pre-surgical decisions to best tailor treatment. This technology would enable non-invasive diagnosis of kidney cancer and avoid a costly and risky invasive needle biopsy of tumors that were incidentally discovered by imaging of patient abdomens. While developing a test to evaluate kidney tumors discovered by CT-imaging, our study will set the stage for development of a non-invasive diagnostic screening test to identify individuals in at risk populations harboring asymptomatic kidney tumors. If successful, this project will establish a novel diagnostic assay to help identify people with a devastating disease that severely impacts individuals and families both financially and emotionally within the military and civilian populations. Funding for this project would put the Department of Defense in position to make this test available to help people both in the military and civilian sectors, and to reduce medical costs and risks associated with kidney tumors. By using a non-invasive urinary biomarker test as a first-line diagnostic tool to molecularly diagnose an imaged kidney mass, we may be able to avoid both surgical overtreatment of small kidney tumors and overextending health care budgets. Avoiding surgery of benign small tumors of the kidney could significantly de
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310996
Entities
People
- Srikanth Singamaneni
Organizations
- United States Army
- Washington University in St. Louis