Programmed cell death-ligand 1 assessment in urothelial carcinoma: prospect and limitation
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Programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) inhibition has revolutionized the treatment paradigm of urothelial carcinoma (UC). Several PD-L1 assays are conducted to formulate appropriate treatment decisions for PD-1/PD-L1 target therapy in UC. However, each assay has its own specific requirement of antibody clones, staining platforms, scoring algorithms, and cutoffs for the determination of PD-L1 status. These prove to be challenging constraints to pathology laboratories and pathologists. Thus, the present article comprehensively demonstrates the scoring algorithm used and differences observed in each assay (22C3, SP142, and SP263). Interestingly, the SP142 score algorithm considers only immune cells and not tumor cells (TCs). It remains controversial whether SP142 expressed only in TCs truly accounts for a negative PD-L1 case. Moreover, the scoring algorithm of each assay is complex and divergent, which can result in inter-observer heterogeneity. In this regard, the development of artificial intelligence for providing assistance to pathologists in obtaining more accurate and objective results has been actively researched. To facilitate efficiency of PD-L1 testing, several previous studies attempted to integrate and harmonize each assay in UC. The performance comparison of the various PD-L1 assays demonstrated in previous studies was encouraging, the exceptional concordance rate reported between 22C3 and SP263. Although these two assays may be used interchangeably, a clinically validated algorithm for each agent must be applied.
Abstract
Programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) inhibition has revolutionized the treatment paradigm of urothelial carcinoma (UC). Several PD-L1 assays are conducted to formulate appropriate treatment decisions for PD-1/PD-L1 target therapy in UC. However, each assay has its own specific requirement of antibody clones, staining platforms, scoring algorithms, and cutoffs for the determination of PD-L1 status. These prove to be challenging constraints to pathology laboratories and pathologists. Thus, the present article comprehensively demonstrates the scoring algorithm used and differences observed in each assay (22C3, SP142, and SP263). Interestingly, the SP142 score algorithm considers only immune cells and not tumor cells (TCs). It remains controversial whether SP142 expressed only in TCs truly accounts for a negative PD-L1 case. Moreover, the scoring algorithm of each assay is complex and divergent, which can result in inter-observer heterogeneity. In this regard, the development of artificial intelligence for providing assistance to pathologists in obtaining more accurate and objective results has been actively researched. To facilitate efficiency of PD-L1 testing, several previous studies attempted to integrate and harmonize each assay in UC. The performance comparison of the various PD-L1 assays demonstrated in previous studies was encouraging, the exceptional concordance rate reported between 22C3 and SP263. Although these two assays may be used interchangeably, a clinically validated algorithm for each agent must be applied.
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