胰腺癌中 T 淋巴细胞相关生物标志物分析。

Analysis of T lymphocyte-related biomarkers in pancreatic cancer.

机构信息

Department of Oncology, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University. Address: No. 198 Hongqi Road, Huzhou, Zhejiang Province, 313000, China.

Graduate School of Nursing, Huzhou university. Address: No. 1 Bachelor Road, Huzhou, Zhejiang Province, 313000, China.

出版信息

Pancreatology. 2020 Oct;20(7):1502-1510. doi: 10.1016/j.pan.2020.09.005. Epub 2020 Sep 11.

DOI:10.1016/j.pan.2020.09.005

PMID:32952042

Abstract

BACKGROUND

Pancreatic cancer remains one of the most lethal cancers.

OBJECTIVE

This study aimed to analyze T cell-related biomarkers and their molecular network in pancreatic cancer.

METHODS

RNAseq sequencing data and clinical data of pancreatic cancer were obtained from TCGA database. The STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm was used to screen the DEGs related to the tumor immune cells. The pearson correlation analysis were used to analyze the relationships between DEGs and T cells. Additionally, the T cell-related DEGs were subjected to protein-protein interaction, competing endogenous RNA (ceRNA), and chemical small molecule-target network construction. Furthermore, the prognosis-associated DEGs were screened.

RESULTS

A total of 412 stromal score-associated and 312 immune score-associated DEGs were obtained. From these DEGs, 50 CD4 T cell-related genes and 13 CD8 T cell-related genes were selected. The PPI networks associated with immune cell-related genes were constructed and found that CD22, SELL, and OLR1 had higher degrees in the PPI network. The number of ceRNA regulatory relation pairs obtained from CD4 T cells and CD8 T cells were 59 and 48, respectively. Additionally, both CD4 T cell- and CD8 T cell-related genes predicted 29 small molecules. CXCL9 and GIMAP7 were screened out from CD4 T cell-related genes, which were related with the survival of pancreatic cancer.

CONCLUSION

We mapped T cell-related gene profile in pancreatic cancer and constructed their potential regulatory network.

摘要

背景

胰腺癌仍然是最致命的癌症之一。

目的

本研究旨在分析胰腺癌中的 T 细胞相关生物标志物及其分子网络。

方法

从 TCGA 数据库中获取胰腺癌的 RNAseq 测序数据和临床数据。使用 ESTIMATE 算法分析肿瘤免疫细胞相关的 DEGs。采用 pearson 相关性分析 DEGs 与 T 细胞的关系。此外，对 T 细胞相关的 DEGs 进行蛋白质-蛋白质相互作用、竞争性内源性 RNA（ceRNA）和化学小分子-靶标网络构建。进一步筛选与预后相关的 DEGs。

结果

共获得 412 个基质评分相关和 312 个免疫评分相关的 DEGs。从这些 DEGs 中，选择了 50 个 CD4 T 细胞相关基因和 13 个 CD8 T 细胞相关基因。构建了与免疫细胞相关基因相关的 PPI 网络，发现 CD22、SELL 和 OLR1 在 PPI 网络中具有较高的度数。从 CD4 T 细胞和 CD8 T 细胞中获得的 ceRNA 调控关系对分别为 59 对和 48 对。此外，CD4 T 细胞和 CD8 T 细胞相关基因均预测了 29 个小分子。从 CD4 T 细胞相关基因中筛选出与胰腺癌生存相关的 CXCL9 和 GIMAP7。