Zheng Sheng, Zhang Zizhen, Ding Ning, Sun Jiawei, Lin Yifeng, Chen Jingyu, Zhong Jing, Shao Liming, Lin Zhenghua, Xue Meng
Department of Gastroenterology, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.
Institute of Gastroenterology, Zhejiang University, Hangzhou, China.
BMC Gastroenterol. 2021 Apr 1;21(1):146. doi: 10.1186/s12876-021-01734-4.
Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC).
mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively.
Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan-Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation.
We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It's assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy.
血管生成是促进肿瘤生长、侵袭和转移的关键因素。在本研究中，我们旨在探讨血管生成相关基因（ARGs）在胃癌（GC）中的预后价值。
从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载了具有GC临床信息的mRNA测序数据。使用limma软件包分析正常组织和肿瘤组织之间差异表达的ARGs，然后通过Cox回归分析筛选与预后相关的基因。通过最小绝对收缩和选择算子（LASSO）回归确定了9个血管生成基因与患者的总生存期（OS）密切相关。基于9个ARGs建立了预后模型和相应的列线图，并分别在TCGA和GEO GC队列中进行了验证。
确认了85个差异表达的ARGs及其富集通路。显著富集分析表明，ARGs相关通路基因与肿瘤血管生成发展高度相关。Kaplan-Meier分析显示，在训练队列和验证队列中，高危组患者的OS率低于低危组。此外，风险评分（RS）对不同临床特征的GC患者，尤其是晚期GC患者具有良好的预后预测作用。此外，校准曲线验证了列线图预测模型与实际观察之间的良好一致性。
我们开发了一种与血管生成相关的九基因特征，可预测GC患者的总生存期。它被认为是一种高效且有价值的预后模型，为靶向治疗提供了新的视角。
