Biomarkers for Predicting Benefit from Neoadjuvant Pembrolizumab in Muscle-Invasive Bladder Cancer - Beyond the Abstract

In recent years, several clinical trials have investigated and set new standard therapies with the use of checkpoint inhibitors as first-line or later-line therapy in patients with locally advanced or metastatic urothelial cancer. In early disease stages, pembrolizumab was evaluated in the Phase II KEYNOTE-057 study in non-muscle-invasive bladder cancer (NMIBC) patients with a carcinoma-in-situ component and unresponsive to Bacillus Calmette-Guérin (BCG). The drug resulted in a three-month clinical complete response in 41.2% of patients by central assessment and a median response duration of 16.2 months. Based on this data, pembrolizumab was granted accelerated approval by the US Food and Drug Administration (FDA). However, the efficacy of checkpoint inhibition in muscle-invasive bladder cancer (MIBC) is under-reported. Based on the preliminary data of the PURE-01 study, pembrolizumab resulted in a pathological complete response rate of 42%, similar to the rate observed for neoadjuvant chemotherapy (NAC).¹ The question remains on how to improve response rates by selecting patients who would receive the most benefit from immune therapy.

In this study, we performed whole-transcriptome profiling, targeted-exome sequencing, and PD-L1 staining on a cohort of 84 patients treated with neoadjuvant pembrolizumab and radical cystectomy (RC).² These data were compared to a cohort of 140 patients treated with NAC and RC from several international institutions.

Interestingly, neither basal nor immune-infiltrated tumor biology alone were associated with significant progression-free survival (PFS) benefit of pembrolizumab. However, in tumors with a combination of these tumor biology attributes (e.g. the Decipher® (GSC) claudin-low subtype),³ we observed preliminary, yet impressive outcomes, with zero events over two years. Critically, these same benefits can be achieved when selecting basal patients using either the Cancer Genome Atlas (TCGA)⁴ or Consensus classifiers⁵ and splitting on median Immune190 signature scores. Given that the claudin-low subtype is, by definition, a basal tumor with high levels of immune infiltration, we can conclude that tumors with intrinsic basal character and with high levels of immune infiltration are most likely to benefit from pembrolizumab. Notably, there was also a trend towards improved pathological responses among the basal-like tumors in general, but this did not reach statistical significance.

The other molecular subtype that appeared to receive benefit from pembrolizumab was the Decipher® luminal-infiltrated group. These tumors were originally described as luminal tumors with high levels of immune infiltration, but recent evidence suggests these tumors are more appropriately defined as having higher levels of stromal/fibroblast activity and only modest immune activity. Like the claudin-low tumors, the luminal-infiltrated cases showed superior PFS, with only one of 20 patients experiencing a progression in two years after cystectomy. While the Decipher® and TCGA luminal-infiltrated subtypes share nomenclature, they are in fact clinically and biologically distinct subtypes, making internal validation of the luminal-infiltrated PFS rates challenging. In fact, the luminal subtype is becoming increasingly complex with more research, suggesting we have a long way to go.⁶ Why Decipher® luminal-infiltrated tumors receive PFS benefit from pembrolizumab remains an unanswered question.

This then begs the question: what’s in a model? Both the TCGA and Consensus classifiers are biological models, driven by the accumulated knowledge of our understanding of the gene expression profiles that define the heterogeneity within bladder cancer. However, the Decipher® classifier is a model built primarily using artificial intelligence/machine learning algorithms to parse patients with similar tumor transcriptomes into subtypes, with little input from our understanding of bladder cancer biology. Yet this four-class model has consistently performed with respect to the stratification of patients; first for predicting basal patients showing improved overall survival with NAC,³ then for finding luminal tumors have lower rates of upstaging at surgery,⁷ and now for predicting improved PFS for claudin-low patients.² It is possible that the biology of bladder cancer, at least as we currently understand it, does not define the clinical behavior of bladder cancer quite as expected.

The clinical and biological behavior of bladder cancer is surprisingly complex and heterogeneous.

1. Necchi, Andrea, Andrea Anichini, Daniele Raggi, Alberto Briganti, Simona Massa, Roberta Lucianò, Maurizio Colecchia et al. "Pembrolizumab as neoadjuvant therapy before radical cystectomy in patients with muscle-invasive urothelial bladder carcinoma (PURE-01): an open-label, single-arm, phase II study." Journal of Clinical Oncology 36, no. 34 (2018): 3353-3360.
2. Necchi, Andrea, Daniele Raggi, Andrea Gallina, Jeffrey S. Ross, Elena Farè, Patrizia Giannatempo, Laura Marandino et al. "Impact of Molecular Subtyping and Immune Infiltration on Pathological Response and Outcome Following Neoadjuvant Pembrolizumab in Muscle-invasive Bladder Cancer." European Urology (2020).
3. Seiler, Roland, Hussam Al Deen Ashab, Nicholas Erho, Bas WG van Rhijn, Brian Winters, James Douglas, Kim E. Van Kessel et al. "Impact of molecular subtypes in muscle-invasive bladder cancer on predicting response and survival after neoadjuvant chemotherapy." European urology 72, no. 4 (2017): 544-554.
4. Robertson, A. Gordon, Jaegil Kim, Hikmat Al-Ahmadie, Joaquim Bellmunt, Guangwu Guo, Andrew D. Cherniack, Toshinori Hinoue et al. "Comprehensive molecular characterization of muscle-invasive bladder cancer." Cell 171, no. 3 (2017): 540-556.
5. Kamoun, Aurélie, Aurélien de Reyniès, Yves Allory, Gottfrid Sjödahl, A. Gordon Robertson, Roland Seiler, Katherine A. Hoadley et al. "A consensus molecular classification of muscle-invasive bladder cancer." European urology (2019).
6. de Jong, Joep J., and Ellen C. Zwarthoff. "Molecular and clinical heterogeneity within the luminal subtype." Nature Reviews Urology 17, no. 2 (2020): 69-70.
7. Lotan, Yair, Stephen A. Boorjian, Jingbin Zhang, Trinity J. Bivalacqua, Sima P. Porten, Thomas Wheeler, Seth P. Lerner et al. "Molecular subtyping of clinically localized urothelial carcinoma reveals lower rates of pathological upstaging at radical cystectomy among luminal tumors." European urology 76, no. 2 (2019): 200-206.