Case report: Metastatic urothelial cancer with an exceptional response to immunotherapy and comprehensive understanding of the tumor and the tumor microenvironment - Sternberg, Cora N.; Shin, Nara; Chernyshov, Konstantin; Calabro, Fabio; Cerbone, Linda; Procopio, Giuseppe; Miheecheva, Natalia; Sagaradze, Georgy; Zaichikova, Alisa; Samarina, Naira; Boyko, Alexandra; Brown, Jessica H.; et al. (Frontiers in Oncology, 2022)
Although immune checkpoint inhibitors (ICIs) are increasingly used as second-line treatments for urothelial cancer (UC), only a small proportion of patients respond. Therefore, understanding the mechanisms of response to ICIs is critical to improve clinical outcomes for UC patients. The tumor microenvironment (TME) is recognized as a key player in tumor progression and the response to certain anti-cancer treatments. This study aims to investigate the mechanism of response using integrated genomic and transcriptomic profiling of a UC patient who was part of the KEYNOTE-045 trial and showed an exceptional response to pembrolizumab. Diagnosed in 2014 and receiving first line chemotherapy without success, the patient took part in the KEYNOTE-045 trial for 2 years. She showed dramatic improvement and has now been free of disease for over 6 years. Recently described by Bagaev et al., the Molecular Functional (MF) Portrait was utilized to dissect genomic and transcriptomic features of the patient’s tumor and TME. The patient’s tumor was characterized as Immune Desert, which is suggestive of a non-inflamed microenvironment. Integrated whole-exome sequencing (WES) and RNA sequencing (RNA-seq) analysis identified an ATM mutation and high TMB level (33.9 mut/mb), which are both positive biomarkers for ICI response. Analysis further revealed the presence of the APOBEC complex, indicating the potential for use of APOBEC signatures as predictive biomarkers for immunotherapy response. Overall, comprehensive characterization of the patient’s tumor and TME with the MF Portrait revealed important insights that could potentially be hypothesis generating to identify clinically useful biomarkers and improve treatment for UC patients.