DNA-methylome-derived epigenetic fingerprint as an immunophenotype indicator of durable clinical immunotherapeutic benefits in head and neck squamous cell carcinoma.

IF 4.9 2区 医学 Q2 CELL BIOLOGY
Cellular Oncology Pub Date : 2024-08-01 Epub Date: 2024-02-05 DOI:10.1007/s13402-024-00917-x
Rui Li, Xin Wen, Ru-Xue Lv, Xian-Yue Ren, Bing-Lin Cheng, Yi-Kai Wang, Ru-Zhen Chen, Wen Hu, Xin-Ran Tang
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引用次数: 0

Abstract

Background: Cancer immunotherapy provides durable response and improves survival in a subset of head and neck squamous cell carcinoma (HNSC) patients, which may due to discriminative tumor microenvironment (TME). Epigenetic regulations play critical roles in HNSC tumorigenesis, progression, and activation of functional immune cells. This study aims to identify an epigenetic signature as an immunophenotype indicator of durable clinical immunotherapeutic benefits in HNSC patients.

Methods: Unsupervised consensus clustering approach was applied to distinguish immunophenotypes based on five immune signatures in The Cancer Genome Atlas (TCGA) HNSC cohort. Two immunophenotypes (immune 'Hot' and immune 'Cold') that had different TME features, diverse prognosis, and distinct DNA methylation patterns were recognized. Immunophenotype-related methylated signatures (IPMS) were identified by the least absolute shrinkage and selector operation algorithm. Additionally, the IPMS score by deconvolution algorithm was constructed as an immunophenotype classifier to predict clinical outcomes and immunotherapeutic response.

Results: The 'Hot' HNSC immunophenotype had higher immunoactivity and better overall survival (p = 0.00055) compared to the 'Cold' tumors. The immunophenotypes had distinct DNA methylation patterns, which was closely associated with HNSC tumorigenesis and functional immune cell infiltration. 311 immunophenotype-related methylated CpG sites (IRMCs) was identified from TCGA-HNSC dataset. IPMS score model achieved a strong clinical predictive performance for classifying immunophenotypes. The area under the curve value (AUC) of the IPMS score model reached 85.9% and 89.8% in TCGA train and test datasets, respectively, and robustness was verified in five HNSC validation datasets. It was also validated as an immunophenotype classifier for predicting durable clinical benefits (DCB) in lung cancer patients who received anti-PD-1/PD-L1 immunotherapy (p = 0.017) and TCGA-SKCM patients who received distinct immunotherapy (p = 0.033).

Conclusions: This study systematically analyzed DNA methylation patterns in distinct immunophenotypes to identify IPMS with clinical prognostic potential for personalized epigenetic anticancer approaches in HNSC patients. The IPMS score model may serve as a reliable epigenome prognostic tool for clinical immunophenotyping to guide immunotherapeutic strategies in HNSC.

Abstract Image

DNA-甲基组衍生的表观遗传学指纹是头颈部鳞状细胞癌临床免疫治疗持久疗效的免疫表型指标。
背景:癌症免疫疗法为部分头颈部鳞状细胞癌(HNSC)患者提供了持久的应答并提高了生存率,这可能是由于肿瘤微环境(TME)的鉴别作用。表观遗传调控在头颈部鳞状细胞癌的肿瘤发生、进展和功能性免疫细胞的激活过程中发挥着关键作用。本研究旨在确定表观遗传特征,作为HNSC患者获得持久临床免疫治疗效果的免疫表型指标:方法:采用无监督共识聚类方法,根据癌症基因组图谱(TCGA)HNSC队列中的五个免疫特征区分免疫表型。研究发现,两种免疫表型(免疫 "热 "型和免疫 "冷 "型)具有不同的TME特征、不同的预后和不同的DNA甲基化模式。免疫表型相关甲基化特征(IPMS)是通过最小绝对缩减和选择器操作算法确定的。此外,通过解卷积算法得出的IPMS得分被构建为免疫表型分类器,用于预测临床结果和免疫治疗反应:结果:与 "冷 "肿瘤相比,"热 "HNSC免疫表型具有更高的免疫活性和更好的总生存率(p = 0.00055)。免疫表型具有不同的DNA甲基化模式,这与HNSC肿瘤发生和功能性免疫细胞浸润密切相关。从 TCGA-HNSC 数据集中发现了 311 个免疫表型相关的甲基化 CpG 位点(IRMCs)。IPMS 评分模型对免疫表型的分类具有很强的临床预测性能。在 TCGA 训练数据集和测试数据集中,IPMS 评分模型的曲线下面积值(AUC)分别达到了 85.9% 和 89.8%,其稳健性在五个 HNSC 验证数据集中得到了验证。该模型还被验证为一种免疫表型分类器,可预测接受抗PD-1/PD-L1免疫疗法的肺癌患者的持久临床获益(DCB)(p = 0.017)和接受不同免疫疗法的TCGA-SKCM患者的持久临床获益(p = 0.033):本研究系统分析了不同免疫分型中的DNA甲基化模式,以确定具有临床预后潜力的IPMS,为HNSC患者的个性化表观遗传抗癌方法提供依据。IPMS评分模型可作为临床免疫分型的可靠表观基因组预后工具,指导HNSC的免疫治疗策略。
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来源期刊
Cellular Oncology
Cellular Oncology ONCOLOGY-CELL BIOLOGY
CiteScore
10.30
自引率
1.50%
发文量
86
审稿时长
12 months
期刊介绍: The Official Journal of the International Society for Cellular Oncology Focuses on translational research Addresses the conversion of cell biology to clinical applications Cellular Oncology publishes scientific contributions from various biomedical and clinical disciplines involved in basic and translational cancer research on the cell and tissue level, technical and bioinformatics developments in this area, and clinical applications. This includes a variety of fields like genome technology, micro-arrays and other high-throughput techniques, genomic instability, SNP, DNA methylation, signaling pathways, DNA organization, (sub)microscopic imaging, proteomics, bioinformatics, functional effects of genomics, drug design and development, molecular diagnostics and targeted cancer therapies, genotype-phenotype interactions. A major goal is to translate the latest developments in these fields from the research laboratory into routine patient management. To this end Cellular Oncology forms a platform of scientific information exchange between molecular biologists and geneticists, technical developers, pathologists, (medical) oncologists and other clinicians involved in the management of cancer patients. In vitro studies are preferentially supported by validations in tumor tissue with clinicopathological associations.
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