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微卫星不稳定性、爱泼斯坦-巴尔病毒联合程序性死亡受体配体1可作为预测胃癌术后化疗预后和疗效的潜在策略。

Microsatellite instability and Epstein-Barr virus combined with PD-L1 could serve as a potential strategy for predicting the prognosis and efficacy of postoperative chemotherapy in gastric cancer.

作者信息

Yang Na, Wu Yanhua, Jin Meishan, Jia Zhifang, Wang Yueqi, Cao Donghui, Qin Lili, Wang Xueying, Zheng Min, Cao Xueyuan, Jiang Jing

机构信息

Division of Clinical Research, First Hospital of Jilin University, Changchun, Jilin Province, China.

Division of Pathology, First Hospital of Jilin University, Changchun, Jilin Province, China.

出版信息

PeerJ. 2021 May 18;9:e11481. doi: 10.7717/peerj.11481. eCollection 2021.

DOI:10.7717/peerj.11481
PMID:34046266
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8139270/
Abstract

BACKGROUND

Microsatellite instability (MSI) and Epstein-Barr virus (EBV)-positive molecular subtypes exhibit complex immune responses in gastric cancer (GC), and PD-L1 has emerged as a prognostic biomarker associated with the cancer immune microenvironment. This study aimed to determine the prognostic value of molecular subtypes and whether the addition of PD-L1 would accurately predict the prognosis and guide postoperative chemotherapy for GC patients.

METHODS

We performed molecular subtyping of tissue microarray slides from 226 GC patients who were treated with radical gastrectomy. The MSI status and PD-L1 expression were evaluated through immunohistochemistry (IHC) and EBV status through situ hybridization. Multiplex polymerase chain reaction (PCR) was also performed on 50 cases to validate the accuracy of IHC in defining MSI status. Differences in overall survival (OS) were assessed using the Kaplan-Meier method, log-rank test and Cox proportional hazards regression model.

RESULTS

Among the 226 GC patients, 52 (23.2%) patients were classified as the MSI subtype, 11 (4.9%) were EBV subtype, and 161 (71.9%) were MSS (Microsatellite stable) /EBV subtype according to TCGA analysis. Two patients were both positive for MSI and EBV infection. EBV cases showed higher PD-L1 positivity than MSI cases and MSS/EBV cases (81.8% 50.0% 35.4%, = 0.003). Compared with the non-MSS/EBV (MSI or EBV cases) subgroup, GC patients with MSS/EBV were associated with the worst outcomes (HR = 1.610, 95% CI [1.0462.479], = 0.031). MSS/EBV GCs alone could benefit from postoperative chemotherapy (HR = 0.452, 95% CI [0.2990.682], <0.001), and PD-L1-positive expression could also predict a better prognosis (HR = 0.612, 95% CI [0.3890.962], = 0.033) in this subgroup. Considering both chemotherapy efficacy and PD-L1 expression in the MSS/EBV subgroup, chemotherapy could improve the prognosis for PD-L1-negative MSS/EBV GCs (HR = 0.357, 95% CI [0.2170.587], <0.001) but not PD-L1-positive MSS/EBV GCs.

CONCLUSIONS

Molecular subtyping combined with PD-L1 expression could serve as a potential strategy to better predict prognosis and guide postoperative chemotherapy of GC patients.

摘要

背景

微卫星不稳定性(MSI)和爱泼斯坦-巴尔病毒(EBV)阳性分子亚型在胃癌(GC)中表现出复杂的免疫反应,而程序性死亡受体配体1(PD-L1)已成为与癌症免疫微环境相关的预后生物标志物。本研究旨在确定分子亚型的预后价值,以及PD-L1的加入是否能准确预测GC患者的预后并指导术后化疗。

方法

我们对226例行根治性胃切除术的GC患者的组织微阵列玻片进行了分子分型。通过免疫组织化学(IHC)评估MSI状态和PD-L1表达,通过原位杂交评估EBV状态。还对50例患者进行了多重聚合酶链反应(PCR),以验证IHC在定义MSI状态方面的准确性。使用Kaplan-Meier法、对数秩检验和Cox比例风险回归模型评估总生存期(OS)的差异。

结果

根据癌症基因组图谱(TCGA)分析,在226例GC患者中,52例(23.2%)患者被分类为MSI亚型,11例(4.9%)为EBV亚型,161例(71.9%)为微卫星稳定(MSS)/EBV亚型。2例患者MSI和EBV感染均为阳性。EBV病例的PD-L1阳性率高于MSI病例和MSS/EBV病例(81.8%对50.0%对35.4%,P = 0.003)。与非MSS/EBV(MSI或EBV病例)亚组相比,MSS/EBV的GC患者预后最差(风险比[HR]=1.610,95%置信区间[CI][1.046至2.479],P = 0.031)。单独的MSS/EBV GC患者可从术后化疗中获益(HR = 0.452,95%CI[0.299至0.682],P<0.001),在该亚组中,PD-L1阳性表达也可预测较好的预后(HR = 0.612,95%CI[0.389至0.962],P = 0.033)。综合考虑MSS/EBV亚组中的化疗疗效和PD-L1表达,化疗可改善PD-L1阴性的MSS/EBV GC患者的预后(HR = 0.357,95%CI[0.217至0.587],P<0.001),但对PD-L1阳性的MSS/EBV GC患者无效。

结论

分子分型联合PD-L1表达可作为更好地预测GC患者预后并指导术后化疗的潜在策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03c9/8139270/4cdf67d4df7f/peerj-09-11481-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03c9/8139270/9b6381ddeac1/peerj-09-11481-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03c9/8139270/4cdf67d4df7f/peerj-09-11481-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03c9/8139270/9b6381ddeac1/peerj-09-11481-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03c9/8139270/4cdf67d4df7f/peerj-09-11481-g002.jpg

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