Medical School of Chinese PLA, Chinese PLA General Hospital, Beijing, China.
Faculty of Hepato-Pancreato-Biliary Surgery, the First Medical Center, Chinese PLA General Hospital, Beijing, China.
Comb Chem High Throughput Screen. 2023;26(13):2358-2371. doi: 10.2174/1386207326666230314112238.
The limited efficacy of chemotherapy and immunotherapy for pancreatic cancer is thought to be largely influenced by the surrounding cancer microenvironment. The hypoxic microenvironment caused by insufficient local blood supply is very important. However, the method to assess the level of hypoxia in the microenvironment of pancreatic cancer (PC) remains unclear.
In our research, we downloaded transcriptomic and clinicopathological data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A prognostic model was developed using univariate and multivariate Cox regression. The ConsensuClusterPlus R package was used to consistently cluster PC samples through unsupervised clustering. Gene set variation analysis (GSVA) was performed to identify the different functional phenotypes. The CIBERSORT evaluated the infiltration status of immune cells. qRT-PCR was performed to detect the expression of genes in PC cells and tissues.
A preliminary risk model was developed to reflect the hypoxic environment of pancreatic cancer. We found that a high hypoxia risk score indicated poor long-term survival and the presence of an immunosuppressive microenvironment. In addition, based on prognostic hypoxia-related genes, 177 PC samples were divided into two subtypes. Compared with cluster 2, cluster 1 was defined as the "hypoxic subgroup". The infiltration of CD8 T cells, activated memory CD4 T cells, naive B cells, memory B cells, plasma cells, and neutrophils were lower in cluster 1, suggesting that there was significant immunosuppression in cluster 1. Beyond that, we constructed a ceRNA regulatory network composed of differentially expressed lncRNA, miRNA, and mRNA. LSAMPAS1/ hsa-miR-129-5p/S100A2 has been identified as a key ceRNA network that regulates the hypoxic environment and the prognosis of PC. Notably, in our study, qRT-PCR revealed the relative expression of LSAMP-AS1 and S100A2 was significantly upregulated in PC cells and tissue.
The hypoxia-related prognostic risk model and core ceRNA network established in our study will provide a new perspective for exploring the carcinogenic mechanism and potential therapeutic targets of pancreatic cancer.
胰腺癌的化疗和免疫治疗效果有限,这主要被认为受到周围癌症微环境的影响。局部供血不足导致的缺氧微环境非常重要。然而,评估胰腺癌(PC)微环境缺氧水平的方法仍不清楚。
在我们的研究中,我们从癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)下载了转录组学和临床病理数据。使用单变量和多变量 Cox 回归建立了预后模型。使用 ConsensuClusterPlus R 包通过无监督聚类一致地对 PC 样本进行聚类。进行基因集变异分析(GSVA)以鉴定不同的功能表型。CIBERSORT 评估免疫细胞的浸润状态。进行 qRT-PCR 以检测 PC 细胞和组织中基因的表达。
我们开发了一个初步的风险模型来反映胰腺癌的缺氧环境。我们发现,高缺氧风险评分表明预后不良且存在免疫抑制微环境。此外,基于与预后相关的缺氧基因,将 177 例 PC 样本分为两种亚型。与簇 2 相比,簇 1 被定义为“缺氧亚组”。簇 1 中 CD8 T 细胞、激活的记忆 CD4 T 细胞、幼稚 B 细胞、记忆 B 细胞、浆细胞和中性粒细胞的浸润较低,表明簇 1 中存在显著的免疫抑制。除此之外,我们构建了一个由差异表达的长链非编码 RNA、miRNA 和 mRNA 组成的 ceRNA 调控网络。LSAMPAS1/hsa-miR-129-5p/S100A2 已被确定为调节 PC 缺氧环境和预后的关键 ceRNA 网络。值得注意的是,在我们的研究中,qRT-PCR 显示 LSAMP-AS1 和 S100A2 的相对表达在 PC 细胞和组织中显著上调。
我们研究中建立的与缺氧相关的预后风险模型和核心 ceRNA 网络将为探索胰腺癌的致癌机制和潜在治疗靶点提供新视角。