A model combining clinical and genomic factors to predict response to PD-1/PD-L1 blockade in advanced urothelial carcinoma. Academic Article uri icon

Overview

abstract

  • BACKGROUND: In metastatic urothelial carcinoma (mUC), predictive biomarkers that correlate with response to immune checkpoint inhibitors (ICIs) are lacking. Here, we interrogated genomic and clinical features associated with response to ICIs in mUC. METHODS: Sixty two mUC patients treated with ICI who had targeted tumour sequencing were studied. We examined associations between candidate biomarkers and clinical benefit (CB, any objective reduction in tumour size) versus no clinical benefit (NCB, no change or objective increase in tumour size). Both univariable and multivariable analyses for associations were conducted. A comparator cohort of 39 mUC patients treated with taxanes was analysed by using the same methodology. RESULTS: Nine clinical and seven genomic factors correlated with clinical outcomes in univariable analysis in the ICI cohort. Among the 16 factors, neutrophil-to-lymphocyte ratio (NLR) ≥5 (OR = 0.12, 95% CI, 0.01-1.15), visceral metastasis (OR = 0.05, 95% CI, 0.01-0.43) and single-nucleotide variant (SNV) count < 10 (OR = 0.04, 95% CI, 0.006-0.27) were identified as independent predictors of NCB to ICI in multivariable analysis (c-statistic = 0.90). None of the 16 variables were associated with clinical benefit in the taxane cohort. CONCLUSIONS: This three-factor model includes genomic (SNV count >9) and clinical (NLR <5, lack of visceral metastasis) variables predictive for benefit to ICI but not taxane therapy for mUC. External validation of these hypothesis-generating results is warranted to enable use in routine clinical care.

publication date

  • December 20, 2019

Research

keywords

  • Antineoplastic Agents, Immunological
  • Biomarkers, Tumor
  • Carcinoma, Transitional Cell
  • Urologic Neoplasms

Identity

PubMed Central ID

  • PMC7028947

Scopus Document Identifier

  • 85077033296

Digital Object Identifier (DOI)

  • 10.1200/PO.17.00011

PubMed ID

  • 31857723

Additional Document Info

volume

  • 122

issue

  • 4