Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in Pancreatic adenocarcinoma
Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in Pancreatic adenocarcinoma
复制标题
DOI：
10.18632/aging.102931
复制
发表时间：
2020-03-31
期刊：
影响因子：
5.2
通讯作者：
Wu, Heshui
中科院分区：
文献类型：
--
作者：
Meng, Zibo;Ren, Dianyun;Wu, Heshui
目的：肿瘤微环境是导致胰腺癌发生的重要因素之一。然而，肿瘤微环境影响PAAD预后的潜在机制尚不完全清楚。结果：从TCGA数据库下载了182例PAAD方案病例的转录组和临床数据。用Estimate Score鉴定高、低间质组间的差异表达基因333个，免疫评分高、低组间的差异表达基因314个。基于两个评分相关的比较中同时差异表达的203个基因，我们建立了一个8-mRNA信号来评估PAAD患者的预后。Kaplan-Meier曲线显示，在训练组和验证组中，高危评分的患者的存活率都明显较差。风险评分是一个独立的预后因素，对PAAD患者的预后有较高的预测价值。通过检索TCGA数据库，我们发现8-mRNA信号中的CA9、CXCL9和GIMAP7通过调节PAAD中FOXO1的表达而与免疫细胞的渗透水平相关。结论：不同于传统的在肿瘤和健康组织中筛选差异基因的方法，我们通过对基于RNA序列的转录组数据进行估计评分，构建了一种新的预测PAAD患者预后的8-mRNA信号。最重要的是，我们通过调节FOXO1在PAAD中的表达，从上述8个基因中鉴定出CA9、CXCL9和GIMAP7是免疫细胞渗透的调节因子。因此，CA9、CXCL9和GIMAP7可能是PAAD免疫治疗的理想靶点。方法：从TCGA数据库下载转录组数据，采用估计计分方法确定间质和免疫评分。通过套索Cox回归模型，为训练队列建立了基于mRNA的预后信号。签名是使用验证队列进行验证的。采用Kaplan-Meier曲线和对数秩次分析进行生存差异分析。Western印迹分析和RT-qPCR分析特异性蛋白和mRNAs的表达。免疫组织化学方法检测PAAD组织芯片中Forkhead box-O 1(FOXO1)、CA9、C-X-C基序趋化因子配体9(CXCL9)、GTPase、IMAP家族成员7(GIMAP7)的蛋白水平。
Objective: The tumour microenvironment is one of the significant factors driving the carcinogenesis of Pancreatic adenocarcinoma (PAAD). However, the underlying mechanism of how the tumour microenvironment impacts the prognosis of PAAD is not completely clear.Results: The transcriptome and clinical data of 182 PAAD program cases were downloaded from the TCGA database. Three hundred thirty-three differentially expressed genes (DEGs) between high and low stromal groups and 314 DEGs between high and low immune score groups were identified using ESTIMATE score. Based on the 203 genes differentially expressed simultaneously in two score-related comparisons, we established an 8-mRNA signature to evaluate the prognosis of PAAD patients. Kaplan-Meier curves showed significantly worse survival for patients with high-risk scores in both the training and validation groups. The risk score was an independent prognostic factor and had a high predictive value for the prognosis of patients with PAAD. By searching the TCGA database, we showed that CA9, CXCL9, and GIMAP7 from the 8-mRNA signature were associated with the infiltration levels of immunocytes by regulating FOXO1 expression in PAAD.Conclusions: Unlike traditional methods of screening for differential genes in cancer and healthy tissues, we constructed a novel 8-mRNA signature to predict the prognosis of PAAD patients by applying ESTIMATE scoring to RNA-seq-based transcriptome data. Most importantly, we identified CA9, CXCL9, and GIMAP7 from the above eight genes as regulators of immunocyte infiltration by adjusting the expression of FOXO1 in PAAD. Thus, CA9, CXCL9, and GIMAP7 might be the ideal targets of immune therapy of PAAD.Methods: ESTIMATE scoring was used to determine the stromal and immune scores of transcriptome datasets downloaded from the TCGA database. An mRNA-based prognostic signature was built for the training cohort via the LASSO Cox regression model. The signature was verified using a validation cohort. Kaplan-Meier curves and log-rank analysis were used to identify survival differences. Western blot analysis and RT-qPCR analysis were carried out to analyze the expression of specific proteins and mRNAs. IHC was performed to assess the protein levels of Forkhead box-O 1 (FOXO1), Carbonic anhydrase 9 (CA9), C-X-C motif chemokine ligand 9 (CXCL9), and GTPase, IMAP family member 7 (GIMAP7) in the tissue microarray of PAAD.