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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Remarkable developments in immuno-oncology have changed the landscape of gastric cancer (GC) treatment. Because immunotherapy intervenes with tumor immune response rather than directly targeting tumor cells, it is important to develop a greater understanding of tumor immunity. This review paper summarizes the tumor immune reaction and immune escape mechanisms while focusing on the role of T cells and their co-inhibitory signals, such as the immune checkpoint molecules programmed death-1 and programmed deathligand 1 (PD-L1). This paper also describes past clinical trials of immunotherapy for patients with GC and details their clinical implications. Strong predictive markers are essential to improve response to immunotherapy. Microsatellite instability, Epstein-Barr virus, PD-L1 expression, and tumor mutational burden are now regarded as potent predictive markers for immunotherapy in patients with GC. Novel immunotherapy and combination therapy targeting new immune checkpoint molecules such as lymphocyte-activation gene 3, T cell immunoglobulin, and mucin domain containing-3, and indoleamine 2,3-dioxygenase have been suggested, and trials are ongoing to evaluate their safety and efficacy. Immunotherapy is an important treatment option for patients with GC and has great potential for improving patient outcome, and further research in immuno-oncology should be carried out.
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Background Assessment of programmed cell death-ligand 1 (PD-L1) immunohistochemical staining is used for treatment decisions in non-small cell lung cancer (NSCLC) regarding use of PD-L1/programmed cell death protein 1 (PD-1) immunotherapy. The reliability of the PD-L1 22C3 pharmDx assay is critical in guiding clinical practice. The Cardiopulmonary Pathology Study Group of the Korean Society of Pathologists investigated the interobserver reproducibility of PD-L1 staining with 22C3 pharmDx in NSCLC samples.
Methods Twenty-seven pathologists individually assessed the tumor proportion score (TPS) for 107 NSCLC samples. Each case was divided into three levels based on TPS: <1%, 1%–49%, and ≥50%.
Results The intraclass correlation coefficient for TPS was 0.902±0.058. Weighted κ coefficient for 3-step assessment was 0.748±0.093. The κ coefficients for 1% and 50% cut-offs were 0.633 and 0.834, respectively. There was a significant association between interobserver reproducibility and experience (formal PD-L1 training, more experience for PD-L1 assessment, and longer practice duration on surgical pathology), histologic subtype, and specimen type.
Conclusions Our results indicate that PD-L1 immunohistochemical staining provides a reproducible basis for decisions on anti–PD-1 therapy in NSCLC.
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Blockade of the programmed cell death-1 (PD-1) axis has already been established as an effective treatment of non-small cell lung cancer. Immunohistochemistry (IHC) for programmed death-ligand 1 (PD-L1) protein is the only available biomarker that can guide treatment with immune checkpoint inhibitors in non-small cell lung cancer. Because each PD-1/PD-L1 blockade was approved together with a specific PD-L1 IHC assay used in the clinical trials, pathologists have been challenged with performing various assays with a limited sample. To provide a more unified understanding of this, several cross-validation studies between platforms have been performed and showed consistent results. However, the interchangeability of assays may be limited in practice because of the risk of misclassification of patients for the treatment. Furthermore, several issues, including the temporal and spatial heterogeneity of PD-L1 expression in the tumor, and the potential for cytology specimens to be used as an alternative to tissue samples for PD-L1 testing, have still not been resolved. In the future, one of the main aims of immunotherapy research should be to find a novel predictive biomarker for PD-1 blockade therapy and a way to combine it with PD-L1 IHC and other tests.
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Background Both human leukocyte antigen (HLA) class I and programmed death-ligand 1 (PD-L1) molecules are known to play important roles in cancer immunity. In this study, we evaluated HLA class I expression in resected adenocarcinoma of the lung, and investigated its prognostic impact in correlation with PD-L1 expression.
Methods HLA class I and PD-L1 expression was evaluated by immunohistochemistry in a total of 403 resected lung adenocarcinomas using tissue microarray. Correlations between the expression of HLA class I/PD-L1 and clinicopathologic features and prognostic significance were analyzed.
Results HLA class I expression was reduced in 91.6% of adenocarcinoma, and more frequently reduced in patients with younger age, absence of vascular invasion, and low pathologic stage (p = .033, p = .007, and p = .012, respectively). Positive PD-L1 expression in tumor cells was 16.1% (1% cut-off), and associated with poor differentiation, presence of vascular invasion and nodal metastasis (p < .001, p = .002, and p = .032, respectively). On survival analysis, HLA class I or PD-L1 expression alone did not show any statistical significance. On the integrated analysis, HLA class I (+)/PD-L1 (+) subgroup showed a significantly shorter overall survival than other groups (p = .001). Multivariate analysis revealed that coexpression of HLA class I and PD-L1 was an independent poor prognostic factor of lung adenocarcinoma. (p < .001; hazard ratio, 6.106; 95% confidence interval, 2.260 to 16.501).
Conclusions Lung adenocarcinoma with coexpression of HLA class I and PD-L1 was associated with poor prognosis. This subgroup may evade immune attack by expressing PD-L1 protein despite HLA expression.
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