PD-L1 protein expression by Combined Positive Score (CPS) in patients with muscle invasive or advanced urothelial carcinoma: a single institution experience.

Immune checkpoint inhibitors have revolutionized the treatment of patients with advanced urothelial carcinoma (UC) in the frontline and relapsed settings. Lebanon has one of the highest incidence of UC worldwide, yet no data exists regarding the expression of PD-L1 by Combined Positive Score (CPS) in advanced disease. We reviewed all patients treated at our institution for high grade UC, stage pT2 and above, between January 2017 and March 2021. We assessed the expression of PD-L1 by immunohistochemistry using 22C3 clone, and analyzed the association between PD-L1 expression and clinicopathological characteristics. PD-L1 positivity was defined as CPS score ≥ 10. A total of 101 patients with advanced UC were included, with a median age of 71 years (range, 38 to 96 years); 78% were ever-smokers. Ninety-three of 101 patients (92%) had conventional UC and 43 patients (43%) had positive PD-L1 expression, with 12 patients having CPS of 100. The analysis by molecular subtype showed that patients with maximal CPS of 100 were enriched in "basal" molecular subtype. However, no association was found between PD-L1 expression (positive versus negative) and clinicopathological characteristics. The positivity of PD-L1 expression as assessed by CPS using the 22C3 clone in our population was almost comparable to the results reported in the occidental literature. Therefore, PD-L1 expression, as a potential predictor of response to immunotherapy, concerns the same percentage of the Lebanese UC patients.

Nasr S ，Haddad FG ，Khazen J ，Kattan J ，Trak-Smayra V ... -  《BMC CANCER》

Programmed death ligand-1 (PD-L1) immunohistochemical assessment using the QR1 clone in muscle-invasive urothelial carcinomas: a comparison with reference clones 22C3 and SP263.

Loghin A ，Nechifor-Boilă A ，Borda A ，Nechifor-Boilă IA ，Voidazan S ，Decaussin-Petrucci M ... -  《-》

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity. An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-L1 22C3 cases collected from three institutions. There were 446 cases (82.1%) where the CPS results (CPS ≥10 or <10) were in complete agreement between three pathologists, and 486 cases (89.5%) where the AI-powered CPS results matched the consensus of two or more pathologists. In the pathologist's assessment of the CPS, statistically significant differences were noted depending on the source hospital (P = 0.003). Three pathologists reevaluated discrepancy cases with AI-powered CPS results. After using the AI as a guide and revising, the complete agreement increased to 93.9%. The AI model contributed to improving the concordance between pathologists across various factors including hospital, specimen type, pathologic T stage, histologic subtypes, and dominant PD-L1-positive cell type. In the revised results, the evaluation discordance among slides from different hospitals was mitigated. This study suggests that AI models can help pathologists to reduce discrepancies between pathologists in quantifying immunohistochemistry including PD-L1 22C3 CPS, especially when evaluating data from different institutions, such as in a telepathology setting.

Lee KS ，Choi E ，Cho SI ，Park S ，Ryu J ，Puche AV ，Ma M ，Park J ，Jung W ，Ro J ，Kim S ，Park G ，Song S ，Ock CY ，Choe G ，Park JH ... -  《-》

PD-L1 immunoexpression and molecular characterization of histological subtypes in urothelial carcinoma.

Urothelial carcinoma (UC) has histological subtypes whose phenotype reflects their molecular diversity, behavior and response to conventional therapy. Immune checkpoint inhibitors (ICIs) have improved the management of UC by evaluation of PD-L1. In the case of PD-L1 22C3, the initiation of ICI is considered from a combined positive score (CPS) greater than 10. However, UC subtypes with absent PD-L1 22C3 expression in cases with CPS>10 may not respond to these treatments. This study aims to establish a correlation between the PD-L1 immunoexpression and molecular alterations in divergent differentiation and histological subtypes of UC (UC-s). Twenty-six samples of UC were detected from a total of 24 patients. Two pathologists performed separately an assessment of UC-s on hematoxylin-eosin as well as PD-L1 expression. Molecular study of each case was performed by next generation sequencing (NGS). A descriptive analysis of the variables included was conducted. Nine cases (34.61%) showed a CPS>10, some with negative PD-L1 immunoexpression in aggressive UC-s. The molecular study revealed alterations in genes belonging to the p53/cell cycle control, RAS, and DNA repair pathways, among others. None of the alterations were exclusive to any histological subtype. Special attention should be paid to CPS>10 cases that include histological subtypes of UC with divergent expression for PD-L1 as they may not respond to treatment with ICI. We recommend examining the proportion and PD-L1 status of each subtype, especially if it has aggressive behavior.

Dawid de Vera MT ，Prieto Cuadra JD ，Álvarez Pérez M ，Garrido-Aranda A ，Alba Conejo E ，Hierro Martín I ... -  《-》

Clinicopathologic and Genomic Characterization of PD-L1 Positive Urothelial Carcinomas.

Pembrolizumab was approved with an accompanying companion diagnostic (CDx) assay (PD-L1 DAKO 22C3) for urothelial carcinoma (UC). In this study, we further characterize the clinicopathologic and genomic features of UC that are programmed death-ligand 1 (PD-L1) positive. The cohort of this study consisted of a total of 528 consecutive UC patients with PD-L1 immunohistochemistry (IHC) and comprehensive genomic profiling (CGP). All PD-L1 IHC testing was performed using the DAKO 22C3 CDx assay for UC. PD-L1 positivity was determined at a combined positive score ≥ 10. A total of 44.5% (235/528) patients with UC were PD-L1positive . A lower PD-L1 positivity rate was detected in primary (42.3%, 148/350) versus metastatic sites (48.9%, 87/178). PD-L1 positivity was dependent on the location of the metastatic sites. CGP revealed PD-L1positive patients had more frequent genomic alterations (GAs) in TP53 (p = .006) and RB1 (p = .003) and less frequent GAs in FGFR3 (p = .001) and MTAP (p = .028). The APOBEC mutational signature and tumor mutational burden (TMB)-high were more common in PD-L1positive patients. By testing patients with UC with CGP, in addition to PD-L1 IHC, an additional 97 patients (18.4%) in the total cohort were eligible for immunotherapy based on TMB status. PD-L1positive and PD-L1negative urothelial carcinomas are genomically different. Also, our study provides the framework for future clinical investigation with regard to specimen site selection for PD-L1 testing as well as candidate biomarker genomic alterations that may predict for better response or lack of response to immune checkpoint inhibitors. In this study, a higher prevalence of TP53 and RB1 alterations and APOBEC mutational signatures in the PD-L1positive urothelial carcinoma disease subset and enrichment of FGFR3 alterations in the PD-L1negative disease subset were found. These data provide the basis for future investigation into the role of these genomic changes as positive and negative predictors of immunotherapy response. Also, differences wer seen in PD-L1 positivity based on the collection site of the sample, which can provide a framework for future clinical trial design and could influence sample selection for PD-L1 testing in patients with urothelial carcinoma when multiple samples are available.

Huang RSP ，Haberberger J ，Harries L ，Severson E ，Duncan DL ，Ferguson NL ，Hemmerich A ，Edgerly C ，Murugesan K ，Xiao J ，McEwan D ，Holmes O ，Hiemenz M ，Venstrom J ，Elvin JA ，Creeden J ，Lin DI ，Ross JS ，Ramkissoon SH ... -  《-》