Checkpoint Inhibitors in Urothelial Carcinoma-Future Directions and Biomarker Selection

Joshua J Meeks1, Peter C Black2, Matthew Galsky3

  • 1Department of Urology, Feinberg School of Medicine, Chicago, IL, USA; Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Chicago, IL, USA; Jesse Brown VAMC, Chicago, IL, USA.

European Urology
|May 31, 2023
PubMed
Abstract

Insights

Checkpoint inhibitor (CPI) therapy shows broad activity in urothelial carcinoma (UC) across various stages. Further research is needed to optimize CPI combinations and identify patient selection criteria for improved outcomes.

Area of Science:

  • Urothelial Carcinoma Research
  • Immunotherapy
  • Oncology

Background:

  • Checkpoint inhibitor (CPI) therapy has emerged as a significant treatment modality for urothelial carcinoma (UC).
  • Recent trials have assessed CPI efficacy and toxicity in metastatic, muscle-invasive (MIUC), upper tract UC, and non-muscle-invasive bladder cancer (NMIBC).

Purpose of the Study:

  • To evaluate the outcomes and toxicity of CPIs in the diverse treatment landscape of UC.
  • To contextualize the real-world application of CPIs for UC management.

Main Methods:

  • Systematic literature search of PubMed, Web of Science, EMBASE, and conference abstracts for prospective CPI trials in UC.
  • Primary endpoints included overall survival, recurrence-free survival, and toxicity.
  • Secondary analysis focused on biomarker evaluation for treatment response.

Main Results:

  • 21 trials (12 phase 2, 9 phase 3) involving CPIs in metastatic UC, MIUC, and NMIBC were identified.
  • First-line metastatic UC: CPIs with chemotherapy showed no superiority; switch maintenance avelumab is a standard of care.
  • CPIs are used in adjuvant settings (nivolumab for MIUC) and for BCG-unresponsive carcinoma in situ (pembrolizumab).

Conclusions:

  • Checkpoint inhibitors (CPIs) are integral to UC treatment across multiple disease states.
  • Future applications may expand with ongoing trials evaluating CPI combinations with other therapies.
  • Development of predictive biomarkers is crucial for patient selection and optimizing CPI therapy effectiveness.