A novel tumor-derived exosomal gene signature predicts prognosis in patients with pancreatic cancer.

IF 1.5 4区医学 Q4 ONCOLOGY

Translational cancer research Pub Date : 2024-08-31 Epub Date: 2024-08-26 DOI:10.21037/tcr-23-2354

Yang Wang, Chao Liang, Xinbo Liu, Shu-Qun Cheng

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引用次数: 0

Abstract

Background: Pancreatic cancer is a devastating disease with poor prognosis. Accumulating evidence has shown that exosomes and their cargo have the potential to mediate the progression of pancreatic cancer and are promising non-invasive biomarkers for the early detection and prognosis of this malignancy. This study aimed to construct a gene signature from tumor-derived exosomes with high prognostic capacity for pancreatic cancer using bioinformatics analysis.

Methods: Gene expression data of solid pancreatic cancer tumors and blood-derived exosome tissues were downloaded from The Cancer Genome Atlas (TCGA) and ExoRBase 2.0. Overlapping differentially expressed genes (DEGs) in the two datasets were analyzed, followed by functional enrichment analysis, protein-protein interaction networks, and weighted gene co-expression network analysis (WGCNA). Using the least absolute shrinkage and selection operator (LASSO) regression of prognosis-related exosomal DEGs, a tumor-derived exosomal gene signature was constructed based on the TCGA dataset, which was validated by an external validation dataset, GSE62452. The prognostic power of this gene signature and its relationship with various pathways and immune cell infiltration were analyzed.

Results: A total of 166 overlapping DEGs were identified from the two datasets, which were markedly enriched in functions and pathways associated with the cell cycle. Two key modules and corresponding 70 exosomal DEGs were identified using WGCNA. Using LASSO Cox regression of prognosis-related exosomal DEGs, a tumor-derived exosomal gene signature was built using six exosomal DEGs (ARNTL2, FHL2, KRT19, MMP1, CDCA5, and KIF11), which showed high predictive performance for prognosis in both the training and validation datasets. In addition, this prognostic signature is associated with the differential activation of several pathways, such as the cell cycle, and the infiltration of some immune cells, such as Tregs and CD8+ T cells.

Conclusions: This study established a six-exosome gene signature that can accurately predict the prognosis of pancreatic cancer.

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一种新型肿瘤外泌体基因特征可预测胰腺癌患者的预后。

背景：胰腺癌是一种预后不良的毁灭性疾病：胰腺癌是一种预后不良的毁灭性疾病。越来越多的证据表明，外泌体及其载体有可能介导胰腺癌的进展，是有望用于早期检测和预后的非侵入性生物标志物。本研究旨在通过生物信息学分析，从肿瘤衍生的外泌体中构建出具有高度预后能力的胰腺癌基因特征：方法：从癌症基因组图谱（TCGA）和ExoRBase 2.0下载胰腺癌实体瘤和血源性外泌体组织的基因表达数据。对两个数据集中重叠的差异表达基因（DEGs）进行分析，然后进行功能富集分析、蛋白-蛋白相互作用网络分析和加权基因共表达网络分析（WGCNA）。利用最小绝对收缩和选择算子（LASSO）对预后相关的外泌体DEGs进行回归，构建了基于TCGA数据集的肿瘤外泌体基因特征，并通过外部验证数据集GSE62452进行了验证。分析了该基因特征的预后能力及其与各种通路和免疫细胞浸润的关系：结果：从两个数据集中共发现了 166 个重叠的 DEGs，这些 DEGs 明显富集于与细胞周期相关的功能和通路中。利用WGCNA确定了两个关键模块和相应的70个外泌体DEGs。通过对预后相关的外泌体 DEGs 进行 LASSO Cox 回归，利用六个外泌体 DEGs（ARNTL2、FHL2、KRT19、MMP1、CDCA5 和 KIF11）建立了肿瘤衍生外泌体基因特征，该特征在训练数据集和验证数据集中均显示出较高的预后预测性能。此外，这一预后特征还与细胞周期等多个通路的不同激活以及Tregs和CD8+ T细胞等免疫细胞的浸润有关：本研究建立的六外显子基因特征可准确预测胰腺癌的预后。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Translational cancer research ONCOLOGY-

CiteScore

2.10

自引率

0.00%

发文量

252

期刊介绍： Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.