Xu Peipei, Liu Sailiang, Song Shu, Yao Xiang, Li Xuechuan, Zhang Jie, Liu Yinbing, Zheng Ye, Gao Ganglong, Xu Jingjing
Department of Biliary-Pancreatic Surgery, Renji Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
State Key Laboratory of Oncogenes and Related Genes, Shanghai, China.
Front Oncol. 2023 Jan 16;12:965102. doi: 10.3389/fonc.2022.965102. eCollection 2022.
Angiogenesis is a major promotor of tumor progression and metastasis in gastric adenocarcinoma (STAD). We aimed to develop a novel lncRNA gene signature by identifying angiogenesis-related genes to better predict prognosis in STAD patients.
The expression profiles of angiogenesis-related mRNA and lncRNA genes were collected from The Cancer Genome Atlas (TCGA). Then, the "limma" package was used to identify differentially expressed genes (DEGs). The expression profiles of angiogenesis-related genes were clustered by consumusclusterplus. The Pearson correlation coefficient was further used to identify lncRNAs coexpressed with angiogenesis-related clustere genes. We used Lasso Cox regression analysis to construct the angiogenesis-related lncRNAs signature. Furthermore, the diagnostic accuracy of the prognostic risk signature were validated by the TCGA training set, internal test sets and external test set. We used multifactor Cox analysis to determine that the risk score is an independent prognostic factor different from clinical characteristics. Nomogram has been used to quantitatively determine personal risk in a clinical environment. The ssGSEA method or GSE176307 data were used to evaluate the infiltration state of immune cells or predictive ability for the benefit of immunotherapy by angiogenesis-related lncRNAs signature. Finally, the expression and function of these signature genes were explored by RT-PCR and colony formation assays.
Among angiogenesis-related genes clusters, the stable number of clusters was 2. A total of 289 DEGs were identified and 116 lncRNAs were screened to have a significant coexpression relationship with angiogenic DEGs (P value<0.001 and |R| >0.5). A six-gene signature comprising LINC01579, LINC01094, RP11.497E19.1, AC093850.2, RP11.613D13.8, and RP11.384P7.7 was constructed by Lasso Cox regression analysis. The multifactor Cox analysis and Nomogram results showed that our angiogenesis-related lncRNAs signature has good predictive ability for some different clinical factors. For immune, angiogenesis-related lncRNAs signature had the ability to efficiently predict infiltration state of 23 immune cells and immunotherapy. The qPCR analysis showed that the expression levels of the six lncRNA signature genes were all higher in gastric adenocarcinoma tissues than in adjacent tissues. The functional experiment results indicated that downregulation of the expression of these six lncRNA signature genes suppressed the proliferation of ASG and MKN45 cells.
Six angiogenesis-related genes were identified and integrated into a novel risk signature that can effectively assess prognosis and provide potential therapeutic targets for STAD patients.
血管生成是胃腺癌（STAD）肿瘤进展和转移的主要促进因素。我们旨在通过鉴定血管生成相关基因来开发一种新的长链非编码RNA（lncRNA）基因特征，以更好地预测STAD患者的预后。
从癌症基因组图谱（TCGA）收集血管生成相关mRNA和lncRNA基因的表达谱。然后，使用“limma”软件包鉴定差异表达基因（DEG）。通过consensusclusterplus对血管生成相关基因的表达谱进行聚类。进一步使用Pearson相关系数来鉴定与血管生成相关聚类基因共表达的lncRNA。我们使用Lasso Cox回归分析构建血管生成相关的lncRNA特征。此外，通过TCGA训练集、内部测试集和外部测试集验证了预后风险特征的诊断准确性。我们使用多因素Cox分析来确定风险评分是一个不同于临床特征的独立预后因素。列线图已用于在临床环境中定量确定个体风险。使用单样本基因集富集分析（ssGSEA）方法或GSE176307数据来评估免疫细胞的浸润状态或通过血管生成相关的lncRNA特征预测免疫治疗获益的能力。最后，通过逆转录聚合酶链反应（RT-PCR）和集落形成试验探索这些特征基因的表达和功能。
在血管生成相关基因簇中，稳定的簇数为2。共鉴定出289个DEG，并筛选出116个lncRNA与血管生成相关的DEG具有显著的共表达关系（P值<0.001且|R|>0.5）。通过Lasso Cox回归分析构建了一个由LINC01579、LINC01094、RP11.497E19.1、AC093850.2、RP11.613D13.8和RP11.384P7.7组成的六基因特征。多因素Cox分析和列线图结果表明，我们的血管生成相关lncRNA特征对一些不同的临床因素具有良好的预测能力。对于免疫方面，血管生成相关的lncRNA特征能够有效预测23种免疫细胞的浸润状态和免疫治疗效果。定量聚合酶链反应（qPCR）分析表明，这六个lncRNA特征基因在胃腺癌组织中的表达水平均高于相邻组织。功能实验结果表明，下调这六个lncRNA特征基因的表达可抑制AGS和MKN45细胞的增殖。
鉴定出六个血管生成相关基因并将其整合到一个新的风险特征中，该特征可以有效评估预后，并为STAD患者提供潜在的治疗靶点。
