Tanya Jindal, Senior, Clinical Research Coordinator, University of California, San Francisco, highlights and expands upon the findings of the UNITE study relative to biomarkers of response to sacituzumab govitecan and enfortumab vedotin for patients with advanced urothelial carcinoma.
Can you describe the UNITE study? What was the design, what types of patients were included, and how did you recently assess biomarkers of response associated with different ADCs?
Tanya Jindal: UNITE is a retrospective, multi-institutional study that examines patients with advanced urothelial carcinoma treated with targeted agents, such as enfortumab vedotin and sacituzumab govitecan. The main objective of the study is to analyze real-world outcomes. Unlike clinical trials, which often exclude certain patients based on specific criteria like variant histology, poor performance status, or aggressive disease, UNITE aims to include a broader range of patients to assess their actual treatment outcomes. The study involves 16 US sites, providing comprehensive data for our analyses.
Previously, we have focused on outcomes with EV and studied biomarkers associated with treatment outcomes. However, our current analysis and future investigations will explore various aspects beyond biomarkers to address existing knowledge gaps. This study allows us to conduct different analyses and examine multiple angles to gain a more comprehensive understanding of the disease and its treatments.
Why was it determined that defining outcomes and biomarkers of response to these therapies was worth studying?
Tanya Jindal: Before 2016, chemotherapy was the only available treatment for advanced urothelial carcinoma. However, since then, several options have emerged, including immunotherapy, EV, SG, and targeted therapies like erdafitinib. With this expanding therapeutic landscape, the challenge lies in deciding which treatment to offer first to patients.
Given the poor prognosis of patients diagnosed with advanced or metastatic urothelial carcinoma, it is crucial to select the most effective therapy as early as possible. Biomarkers play a vital role in this decision-making process, as they can help us prioritize treatments that are most likely to benefit the patient. Having tools to aid in treatment selection is essential as the therapeutic options continue to grow. Our goal is to provide the best possible therapy to these patients and improve their outcomes.
What were your findings in terms of biomarkers and predictors of response relative to sacituzumab govitecan?
Tanya Jindal: In our analysis, we observed that patients with alterations in TP53 or MDM2 showed improved outcomes when treated with SG. To ensure accuracy, we conducted both univariable and multi-variable analyses, adjusting for various clinical characteristics. During the univariable analysis, we examined clinical characteristics and molecular biomarkers to identify potential associations with outcomes. Some clinical factors, like neutrophil-to-lymphocyte ratio and hemoglobin levels, showed correlations with outcomes. To discern the specific molecular biomarkers linked to outcomes, we included significant variables from the univariable analysis, along with clinically relevant factors like histology, age, and ECOG status, in the multi-variable analysis.
After considering these factors, we found a statistically significant association (P = .02) between improved outcomes and alterations in TP53 and MDM2. However, it is essential to note that these findings are hypothesis-generating, and we must validate them before implementing any changes in patient treatment or selection.
As a retrospective study, this analysis provides valuable insights, but further research is necessary before incorporating these findings into clinical practice. While this information can potentially guide clinical decision-making, we must conduct more extensive research before applying it routinely in patient care.
What were your findings in terms of biomarkers and predictors of response relative to enfortumab vedotin?
Tanya Jindal: Similarly, in our analysis of EV, we adjusted for clinical variables and identified specific molecular biomarkers associated with treatment outcomes. Patients with alterations in ERBB2 and KDM6A showed improved outcomes, whereas those with high expression of PDL1 and low tumor mutational burden had inferior outcomes when treated with EV. Notably, we had a larger sample size for this analysis, with 303 patients compared to the 90 patients in our SG analysis.
Are there any ongoing efforts to assess for toxicities in these patient populations?
Tanya Jindal: We did conduct an analysis on that, but the data has not been presented yet. We hope to present it in the future, possibly at a later time, but it is not part of this current analysis.