San Carlos, Calif. – October 05, 2026 -- A non-invasive urine test can now predict whether bladder cancer patients will respond to immunotherapy before treatment even begins, according to a Stanford-led study published in Nature Medicine and announced by Resero Bio.
Study analyzed 683 urine samples to validate cell-free RNA platform
Researchers from Stanford Cancer Institute and the VA Palo Alto Health Care System used uRARE-seq, Resero Bio's proprietary targeted cfRNA sequencing method, to analyze 683 urine samples from bladder cancer patients and controls. The platform distinguished low-grade from high-grade tumors and non-muscle invasive from muscle-invasive disease, determinations that currently require tissue biopsy or surgical resection.
Pre-treatment signature predicted BCG immunotherapy response
Patients who achieved a complete molecular response to BCG immunotherapy showed pre-existing anti-tumor immune signatures in their urine cfRNA before treatment started. The platform also identified molecular residual disease after treatment, separating patients with complete responses to surgery or adjuvant BCG, who showed lower recurrence risk, from those with detectable tumor cfRNA.
Platform shows preliminary signal across kidney and prostate cancer
The study detected transcriptionally distinct cfRNA profiles in urine from patients with renal cell carcinoma and prostate adenocarcinoma, extending potential applications beyond bladder cancer. Resero Bio has generated proof-of-concept cfRNA signal across ten solid tumor types to date, using capture panels optimized for both urine and plasma.
"We're not just asking whether cancer is present. We're reading out gene expression programs associated with tumor grade, stage, immune biology, and treatment response, all from a urine sample," said Monica Nesselbush, PhD, CEO and Co-founder of Resero Bio.
RARE-seq platform is now available for research use
Resero Bio holds an exclusive license to commercialize the RARE-seq platform, developed by researchers from Stanford Medicine. The technology is designed to be disease- and biofluid-agnostic, supporting applications including risk stratification, treatment response prediction, and resistance mechanism characterization without requiring tissue or prior tumor sequencing.