Zhang Congjun, Ding Jun, Xu Xiao, Liu Yangyang, Huang Wei, Da Liangshan, Ma Qiang, Chen Shengyang
Department of Oncology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
Department of Hepatopancreatobiliary Surgery, Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Front Mol Biosci. 2021 Jun 8;8:645024. doi: 10.3389/fmolb.2021.645024. eCollection 2021.
Pancreatic cancer (PC) is one of the most lethal types of cancer with extremely poor diagnosis and prognosis, and the tumor microenvironment plays a pivotal role during PC progression. Poor prognosis is closely associated with the unsatisfactory results of currently available treatments, which are largely due to the unique pancreatic tumor microenvironment (TME). In this study, a total of 177 patients with PC from The Cancer Genome Atlas (TCGA) cohort and 65 patients with PC from the GSE62452 cohort in Gene Expression Omnibus (GEO) were included. Based on the proportions of 22 types of infiltrated immune cell subpopulations calculated by cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), the TME was classified by K-means clustering and differentially expressed genes (DEGs) were determined. A combination of the elbow method and the gap statistic was used to explore the likely number of distinct clusters in the data. The ConsensusClusterPlus package was utilized to identify radiomics clusters, and the samples were divided into two subtypes. Survival analysis showed that the patients with TMEscore-high phenotype had better prognosis. In addition, the TMEscore-high had better inhibitory effect on the immune checkpoint. A total of 10 miRNAs, 311 DEGs, and 68 methylation sites related to survival were obtained, which could be biomarkers to evaluate the prognosis of patients with pancreatic cancer. Therefore, a comprehensive description of TME characteristics of pancreatic cancer can help explain the response of pancreatic cancer to immunotherapy and provide a new strategy for cancer treatment.
胰腺癌（PC）是最致命的癌症类型之一，其诊断和预后极差，肿瘤微环境在PC进展过程中起着关键作用。预后不良与目前可用治疗方法的不理想结果密切相关，这在很大程度上归因于独特的胰腺肿瘤微环境（TME）。在本研究中，纳入了来自癌症基因组图谱（TCGA）队列的177例PC患者以及来自基因表达综合数据库（GEO）中GSE62452队列的65例PC患者。基于通过估计RNA转录本相对亚群的细胞类型鉴定（CIBERSORT）计算出的22种浸润免疫细胞亚群的比例，通过K均值聚类对TME进行分类，并确定差异表达基因（DEG）。使用肘部方法和间隙统计量的组合来探索数据中可能的不同簇数量。利用ConsensusClusterPlus软件包识别影像组学簇，并将样本分为两个亚型。生存分析表明，TMEscore高表型的患者预后较好。此外，TMEscore高对免疫检查点具有更好的抑制作用。共获得了10个与生存相关的miRNA、311个DEG和68个甲基化位点，它们可作为评估胰腺癌患者预后的生物标志物。因此，全面描述胰腺癌的TME特征有助于解释胰腺癌对免疫治疗的反应，并为癌症治疗提供新策略。
