First Clinical Medical College, Guangxi Medical University, Nanning, China.
Department of Orthopedic Surgery, The Tenth Affiliated Hospital of Guangxi Medical University, Qinzhou First People's Hospital, Qinzhou, China.
Cancer Med. 2020 Jul;9(14):4980-4990. doi: 10.1002/cam4.2801. Epub 2020 May 20.
Gastric cancer remains one of the major causes for tumor-related deaths worldwide. Our study aimed to provide an understanding of primary gastric cancer and prompt its clinical diagnosis and treatment.
We integrated the expression profiles and overall survival information of primary gastric cancer in TCGA and GEO database and estimated the stromal score of each sample by the estimate R package. Stromal score and clinicopathologic characteristics associated with overall survival were analyzed by using Cox regression and the Kaplan-Meier method. Gene set enrichment analysis (GSEA) and KEGG analysis were performed to explore the potential molecular mechanism in TCGA dataset. The relationship between immunotherapy-associated markers or immune cell types and stromal score was explored by using Pearson correlation analysis.
A total of 796 samples were collected for the analysis. Patients with stromal score-high showed poor overall survival (P < .01, HR: 1.407, 95% CI: 1.144-1.731) and identified as an independent prognostic factor. KEGG analysis revealed that stromal score actively involved in diverse tumor-associated pathways. GSEA analysis also revealed stromal score associated with diverse immune-related biological processes. Furthermore, stromal score was related with immunotherapy-associated markers and multiple immune cells.
Our results showed that stromal score could serve as a potential prognostic biomarker in primary gastric cancer and play an important role in the recognition, surveillance, and prognosis of gastric cancer.
胃癌仍然是全球肿瘤相关死亡的主要原因之一。我们的研究旨在了解原发性胃癌,并为其临床诊断和治疗提供依据。
我们整合了 TCGA 和 GEO 数据库中原发性胃癌的表达谱和总生存期信息,并使用 estimate R 包估计每个样本的基质评分。使用 Cox 回归和 Kaplan-Meier 方法分析基质评分与总生存期相关的临床病理特征。在 TCGA 数据集上进行基因集富集分析(GSEA)和 KEGG 分析,以探讨潜在的分子机制。使用 Pearson 相关性分析探讨免疫治疗相关标志物或免疫细胞类型与基质评分之间的关系。
共纳入 796 例患者进行分析。基质评分高的患者总生存期较差(P<.01,HR:1.407,95%CI:1.144-1.731),并被确定为独立的预后因素。KEGG 分析显示基质评分积极参与多种肿瘤相关途径。GSEA 分析也显示基质评分与多种免疫相关的生物学过程相关。此外,基质评分与免疫治疗相关标志物和多种免疫细胞有关。
我们的研究结果表明,基质评分可作为原发性胃癌潜在的预后生物标志物,在胃癌的识别、监测和预后中发挥重要作用。