用于肺腺癌预后风险预测的内质网应激和有丝分裂的基因特征。

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2024-05-30 DOI:10.1049/syb2.12092
Xiong Lin, Miaoling Yang, Yuanling Huang, Xiaoli Huang, Huibo Shi, Binbin Chen, Jianle Kang, Sunkui Ke
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引用次数: 0

摘要

与内质网应激(ERS)和有丝分裂相关的基因有助于预测实体瘤的预后。作者旨在为肺腺癌(LUAD)中的这些基因开发一个预后预测模型。研究人员从基因表达总库(GEO)和癌症基因组图谱(TCGA)等公共数据库中收集了相关的基因表达和临床信息。最终在 LUAD 数据集中筛选出 265 个差异表达基因(71 个上调,194 个下调)。其中,根据与ERS和线粒体自噬基因交叉后的表达分析,15个候选ERS和线粒体自噬基因(ATG12、CSNK2A1、MAP1LC3A、MAP1LC3B、MFN2、PGAM5、PINK1、RPS27A、SQSTM1、SRC、UBA52、UBB、UBC、ULK1和VDAC1)可能对LUAD至关重要。在GEO和TCGA数据库中,该预测模型都能有效预测LUAD患者的5年、3年和1年预后。此外,VDAC1的高表达与LUAD患者的总生存率低有关(p
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Gene signatures of endoplasmic reticulum stress and mitophagy for prognostic risk prediction in lung adenocarcinoma

Genes associated with endoplasmic reticulum stress (ERS) and mitophagy can be conducive to predicting solid tumour prognosis. The authors aimed to develop a prognosis prediction model for these genes in lung adenocarcinoma (LUAD). Relevant gene expression and clinical information were collected from public databases including Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). A total of 265 differentially expressed genes was finally selected (71 up-regulated and 194 downregulated) in the LUAD dataset. Among these, 15 candidate ERS and mitophagy genes (ATG12, CSNK2A1, MAP1LC3A, MAP1LC3B, MFN2, PGAM5, PINK1, RPS27A, SQSTM1, SRC, UBA52, UBB, UBC, ULK1, and VDAC1) might be critical to LUAD based on the expression analysis after crossing with the ERS and mitochondrial autophagy genes. The prediction model demonstrated the ability to effectively predict the 5-, 3-, and 1-year prognoses of LUAD patients in both GEO and TCGA databases. Moreover, high VDAC1 expression was associated with poor overall survival in LUAD (p < 0.001), suggesting it might be a critical gene for LUAD prognosis prediction. Overall, the prognosis model based on ERS and mitophagy genes in LUAD can be useful for evaluating the prognosis of patients with LUAD, and VDAC1 may serve as a promising biomarker for LUAD prognosis.

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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
期刊最新文献
iGATTLDA: Integrative graph attention and transformer-based model for predicting lncRNA-Disease associations. A tumour-associated macrophage-based signature for deciphering prognosis and immunotherapy response in prostate cancer. Identification and analysis of epithelial-mesenchymal transition-related key long non-coding RNAs in hypospadias Revealing the potential role of hub metabolism-related genes and their correlation with immune cells in acute ischemic stroke Gene signatures of endoplasmic reticulum stress and mitophagy for prognostic risk prediction in lung adenocarcinoma
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