MSH2
MSH6型
PMS2系统
PD-L1
免疫组织化学
癌症研究
MLH1
免疫疗法
DNA错配修复
组织微阵列
癌
生物
免疫系统
医学
病理
癌症
内科学
免疫学
结直肠癌
作者
Annukka Pasanen,Terhi Ahvenainen,Teijo Pellinen,Pia Vahteristo,Mikko Loukovaara,Ralf Bützow
标识
DOI:10.1097/pas.0000000000001395
摘要
Programmed death-ligand 1 (PD-L1) is a biomarker that may predict the response to anti-programmed death 1/PD-L1 immunotherapy. We evaluated the expression of PD-L1 in carcinoma cells (Ca) and immune cells (ICs) across histopathologic and The Cancer Genome Atlas (TCGA) molecular subgroups of endometrial carcinoma (EC). Our study included 842 patients with EC. Direct sequencing of polymerase epsilon ( POLE ) exonuclease domain hot spots and conventional immunohistochemistry (MLH1, PMS2, MSH2, MSH6, p53) were conducted to identify TCGA classification–based molecular subgroups of EC: POLE -mutated, mismatch repair deficient, no specific molecular profile, and p53 aberrant. Multiplex immunohistochemistry was performed to evaluate PD-L1 expression in Ca and tumor-infiltrating ICs. PD-L1 expression in Ca and in ICs was detected in 8.6% and 27.7% of the cases, respectively. A combined positive score (CPS) was ≥1% in 19.4% of the samples. PD-L1 positivity in Ca and ICs, and CPS correlated with tumor T-cell density ( P <0.001). POLE -mutated and mismatch repair-deficient tumors were more likely to present PD-L1-expressing ICs, CPS positivity, and abundant tumor-infiltrating lymphocytes compared with other TCGA subgroups ( P <0.001). No differences existed in Ca-PD-L1 expression ( P =0.366). Within various histotypes, non-endometrioid carcinomas displayed the highest Ca-PD-L1, ICs, and CPS ( P <0.03). Advanced cancers showed more frequent Ca-PD-L1 positivity ( P =0.016), and CPS ( P =0.029) and IC≥1% ( P =0.037) positivity compared with early disease. In conclusion, PD-L1 expression profiles differ between molecular subclasses, histologic subtypes, and disease stage of EC. Prospective studies are needed to explore the predictive value of various PD-L1 scoring systems within the subgroups of EC. CPS presents methodological advantages over cell type–specific scoring systems.
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