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用于预测胰腺癌预后的铜依赖性联合预后模型。

The combined prognostic model of copper-dependent to predict the prognosis of pancreatic cancer.

作者信息

Guan Xiao, Lu Na, Zhang Jianping

机构信息

Department of General Surgery, The Second Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, China.

出版信息

Front Genet. 2022 Aug 10;13:978988. doi: 10.3389/fgene.2022.978988. eCollection 2022.

Abstract

To assess the prognostic value of copper-dependent genes, copper-dependent-related genes (CDRG), and CDRG-associated immune-infiltrating cells (CIC) for pancreatic cancer. CDRG were obtained by single-cell analysis of the GSE156405 dataset in the Gene Expression Omnibus (GEO) database. In a ratio of 7:3, we randomly divided the Cancer Genome Atlas (TCGA) cohort into a training cohort and a test cohort. Tumor samples from the GSE62452 dataset were used as the validation cohort. CIBERSORT was used to obtain the immune cell infiltration. We identified the prognostic CDRG and CIC by Cox regression and the least absolute selection operator (LASSO) method. The clinical significance of these prognostic models was assessed using survival analysis, immunological microenvironment analysis, and drug sensitivity analysis. 536 CDRG were obtained by single-cell sequencing analysis. We discovered that elevated LIPT1 expression was associated with a worse prognosis in pancreatic cancer patients. EPS8, CASC8, TATDN1, NT5E, and LDHA comprised the CDRG-based prognostic model. High infiltration of Macrophages.M2 in pancreatic cancer patients results in poor survival. The combined prognostic model showed great predictive performance, with the area under the curve (AUC) values being basically between 0.7 and 0.9 in all three cohorts. We found a cohort of CDRG and CIC in patients with pancreatic cancer. The combined prognostic model provided new insights into the prognosis and treatment of pancreatic cancer.

摘要

评估铜依赖性基因、铜依赖性相关基因(CDRG)以及CDRG相关免疫浸润细胞(CIC)对胰腺癌的预后价值。通过对基因表达综合数据库(GEO)中GSE156405数据集进行单细胞分析获得CDRG。按照7:3的比例,我们将癌症基因组图谱(TCGA)队列随机分为训练队列和测试队列。将GSE62452数据集中的肿瘤样本用作验证队列。使用CIBERSORT获得免疫细胞浸润情况。我们通过Cox回归和最小绝对收缩选择算子(LASSO)方法确定预后性CDRG和CIC。使用生存分析、免疫微环境分析和药物敏感性分析评估这些预后模型的临床意义。通过单细胞测序分析获得536个CDRG。我们发现,LIPT1表达升高与胰腺癌患者预后较差相关。EPS8、CASC8、TATDN1、NT5E和LDHA构成基于CDRG的预后模型。胰腺癌患者中M2巨噬细胞的高浸润导致生存率较低。联合预后模型显示出良好的预测性能,在所有三个队列中,曲线下面积(AUC)值基本在0.7至0.9之间。我们在胰腺癌患者中发现了一组CDRG和CIC。联合预后模型为胰腺癌的预后和治疗提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4677/9399350/7991505c746b/fgene-13-978988-g001.jpg

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