Department of Pancreatic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Sino-German Laboratory of Personalized Medicine for Pancreatic Cancer, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Aging (Albany NY). 2020 Mar 17;12(6):5048-5070. doi: 10.18632/aging.102931.
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.
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.
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.
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.
肿瘤微环境是驱动胰腺导管腺癌（PAAD）发生的重要因素之一。然而，肿瘤微环境如何影响 PAAD 预后的潜在机制尚不完全清楚。
从 TCGA 数据库下载了 182 例 PAAD 病例的转录组和临床数据。使用 ESTIMATE 评分，在高和低基质组之间鉴定出 333 个差异表达基因（DEGs），在高和低免疫评分组之间鉴定出 314 个 DEGs。基于在两个评分相关比较中同时差异表达的 203 个基因，我们建立了一个 8-mRNA 特征来评估 PAAD 患者的预后。Kaplan-Meier 曲线显示，在训练和验证组中，高风险评分患者的生存明显较差。风险评分是一个独立的预后因素，对 PAAD 患者的预后具有较高的预测价值。通过搜索 TCGA 数据库，我们表明，来自 8-mRNA 特征的 CA9、CXCL9 和 GIMAP7 通过调节 FOXO1 在 PAAD 中的表达，与免疫细胞浸润水平相关。
与传统的筛选癌症和健康组织中差异基因的方法不同，我们通过应用 ESTIMATE 评分对基于 RNA-seq 的转录组数据进行分析，构建了一个新的 8-mRNA 特征来预测 PAAD 患者的预后。最重要的是，我们确定 CA9、CXCL9 和 GIMAP7 是调节免疫细胞浸润的调节因子，通过调节 FOXO1 在 PAAD 中的表达。因此，CA9、CXCL9 和 GIMAP7 可能是 PAAD 免疫治疗的理想靶点。
使用 ESTIMATE 评分确定从 TCGA 数据库下载的转录组数据集的基质和免疫评分。通过 LASSO Cox 回归模型为训练队列构建基于 mRNA 的预后特征。使用验证队列验证该特征。Kaplan-Meier 曲线和对数秩分析用于识别生存差异。Western blot 分析和 RT-qPCR 分析用于分析特定蛋白质和 mRNAs 的表达。免疫组化分析用于评估组织微阵列中 Forkhead box-O 1（FOXO1）、碳酸酐酶 9（CA9）、C-X-C 基序趋化因子配体 9（CXCL9）和 GTPase，IMAP 家族成员 7（GIMAP7）的蛋白水平。
