First People's Hospital of Hangzhou Lin'an District, Affiliated Lin'an People's Hospital, Hangzhou Medical College, Hangzhou, China.
Department of Research and Development, Zhejiang Zhongwei Medical Research Center, Hangzhou, 310018, Zhejiang, China.
Sci Rep. 2023 Sep 11;13(1):15006. doi: 10.1038/s41598-023-41444-3.
In recent years, molecular and genetic research hotspots of gastric cancer have been investigated, including microRNAs, long noncoding RNAs (lncRNAs) and messenger RNA (mRNAs). The study on the role of lncRNAs may help to develop personalized treatment and identify potential prognostic biomarkers in gastric cancer. The RNA-seq and miRNA-seq data of gastric cancer were downloaded from the TCGA database. Differential analysis of RNA expression between gastric cancer samples and normal samples was performed using the edgeR package. The ceRNA regulatory network was visualized using Cytoscape. KEGG pathway analysis of mRNAs in the ceRNA network was performed using the clusterProfiler package. CIBERSORT was used to distinguish 22 immune cell types and the prognosis-related genes and immune cells were determined using Kaplan-Meier and Cox proportional hazard analyses. To estimate these nomograms, we used receiver operating characteristic and calibration curve studies. The ceRNA regulation network of gastric cancer was built in this study, and the genes in the network were analyzed for prognosis. A total of 980 lncRNAs were differentially expressed, of which 774 were upregulated and 206 were downregulated. A survival study identified 15 genes associated with gastric cancer prognosis, including VCAN-AS1, SERPINE1, AL139002.1, LINC00326, AC018781.1, C15orf54, hsa-miR-145. Monocytes and Neutrophils were associated with the survival rate of gastric cancer. Our research uncovers new ceRNA network for the detection, treatment, and monitoring of gastric cancer.
近年来，胃癌的分子和遗传研究热点包括 microRNAs、长链非编码 RNA（lncRNAs）和信使 RNA（mRNAs）。对 lncRNAs 作用的研究可能有助于开发个性化治疗方法，并确定胃癌潜在的预后生物标志物。从 TCGA 数据库下载胃癌的 RNA-seq 和 miRNA-seq 数据。使用 edgeR 包对胃癌样本和正常样本之间的 RNA 表达进行差异分析。使用 Cytoscape 可视化 ceRNA 调控网络。使用 clusterProfiler 包对 ceRNA 网络中的 mRNAs 进行 KEGG 通路分析。使用 CIBERSORT 区分 22 种免疫细胞类型，并使用 Kaplan-Meier 和 Cox 比例风险分析确定与预后相关的基因和免疫细胞。使用 receiver operating characteristic 和校准曲线研究来估计这些 nomograms。本研究构建了胃癌的 ceRNA 调控网络，并对网络中的基因进行了预后分析。共鉴定出 980 个差异表达的 lncRNAs，其中 774 个上调，206 个下调。生存研究确定了 15 个与胃癌预后相关的基因，包括 VCAN-AS1、SERPINE1、AL139002.1、LINC00326、AC018781.1、C15orf54、hsa-miR-145。单核细胞和中性粒细胞与胃癌的生存率有关。我们的研究揭示了胃癌检测、治疗和监测的新 ceRNA 网络。
