Zhang Yuan, Chen Jianbo, Zhao Yunan, Weng Lihong, Xu Yiquan
The First Affiliated Hospital of Xiamen University, Xiamen, China.
Department of Medical Oncology, Xiamen Key Laboratory of Antitumor Drug Transformation Research, The First Affiliated Hospital of Xiamen University, School of Clinical Medicine, Fujian Medical University, Xiamen, China.
Front Oncol. 2020 Oct 27;10:562574. doi: 10.3389/fonc.2020.562574. eCollection 2020.
The ceramide pathway is strongly associated with the regulation of tumor proliferation, differentiation, senescence, and apoptosis. This study aimed to explore the gene signatures, prognostic value, and immune-related effects of ceramide-regulated genes in lung adenocarcinoma (LUAD).
Public datasets of LUAD from The Cancer Genome Atlas and Gene Expression Omnibus were selected. Consensus clustering was adopted to classify LUAD patients, and a least absolute shrinkage and selection operator (LASSO) regression model was employed to develop a prognostic risk signature. CIBERSORT algorithm was used to estimate the association between the risk signature and the tumor immune microenvironment.
Most of the 22 ceramide-regulated genes were differentially expressed between LUAD and normal samples. LUAD patients were classified into two subgroups (cluster 1 and 2) and cluster 2 was associated with a poor prognosis. Furthermore, a prognostic risk signature was developed based on the three ceramide-regulated genes, Cytochrome C (CYCS), V-rel reticuloendotheliosis viral oncogene homolog A (RELA) and Fas-associated via death domain (FADD). LUAD patients with low- and high-risk scores differed concerning the subtypes of tumor-infiltrating immune cells. A moderate to weak correlation was observed between the risk score and tumor-infiltrating immune cells.
Ceramide-regulated genes could predict clinical prognostic risk and affect the tumor immune microenvironment in LUAD.
神经酰胺途径与肿瘤增殖、分化、衰老和凋亡的调节密切相关。本研究旨在探索肺腺癌（LUAD）中神经酰胺调节基因的基因特征、预后价值及免疫相关效应。
选取来自癌症基因组图谱（The Cancer Genome Atlas）和基因表达综合数据库（Gene Expression Omnibus）的LUAD公共数据集。采用一致性聚类对LUAD患者进行分类，并使用最小绝对收缩和选择算子（LASSO）回归模型构建预后风险特征。运用CIBERSORT算法评估风险特征与肿瘤免疫微环境之间的关联。
22个神经酰胺调节基因中的大多数在LUAD与正常样本之间存在差异表达。LUAD患者被分为两个亚组（簇1和簇2），簇2与不良预后相关。此外，基于三个神经酰胺调节基因，即细胞色素C（CYCS）、V-rel网状内皮增生症病毒癌基因同源物A（RELA）和死亡结构域相关蛋白（FADD），构建了一个预后风险特征。低风险和高风险评分的LUAD患者在肿瘤浸润免疫细胞亚型方面存在差异。风险评分与肿瘤浸润免疫细胞之间观察到中度至弱的相关性。
神经酰胺调节基因可预测LUAD的临床预后风险并影响肿瘤免疫微环境。
