Prognostic Prediction Value and Biological Functions of Non-Apoptotic Regulated Cell Death Genes in Lung Adenocarcinoma

Q2 Medicine Chinese Medical Sciences Journal Pub Date : 2023-09-01 DOI:10.24920/004222
Hao-Ling Li , Jun-Xian Wang , Heng-Wen Dai , Jun-Jie Liu , Zi-Yang Liu , Ming-Yuan Zou , Lei Zhang , Wen-Rui Wang
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Abstract

Objective

To explore the potential biological functions and prognostic prediction values of non-apoptotic regulated cell death genes (NARCDs) in lung adenocarcinoma.

Methods

Transcriptome data of lung adenocarcinoma were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. We identified differentially expressed NARCDs between lung adenocarcinoma tissues and normal tissues with R software. NARCDs signature was constructed with univariate Cox regression analysis and the least absolute shrinkage and selection operator Cox regression. The prognostic predictive capacity of NARCDs signature was assessed by Kaplan-Meier survival curve, receiver operating characteristic curve, and univariate and multivariate Cox regression analyses. Functional enrichment of NARCDs signature was analyzed with gene set variation analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes. In addition, differences in tumor mutational burden, tumor microenvironment, tumor immune dysfunction and exclusion score, and chemotherapeutic drug sensitivity were analyzed between the high and low NARCDs score groups. Finally, a protein-protein interaction network of NARCDs and immune-related genes was constructed by STRING and Cytoscape software.

Results

We identified 34 differentially expressed NARCDs associated with the prognosis, of which 16 genes (ATIC, AURKA, CA9, ITGB4, DDIT4, CDK5R1, CAV1, RRM2, GAPDH, SRXN1, NLRC4, GLS2, ADRB2, CX3CL1, GDF15, and ADRA1A) were selected to construct a NARCDs signature. NARCDs signature was identified as an independent prognostic factor (P < 0.001). Functional analysis showed that there were significant differences in mismatch repair, pS3 signaling pathway, and cell cycle between the high NARCDs score group and low NARCDs score group (all P < 0.05). The NARCDs low score group had lower tumor mutational burden, higher immune score, higher tumor immune dysfunction and exclusion score, and lower drug sensitivity (all P < 0.05). In addition, the 10 hub genes (CXCL5, TLR4JUN, IL6, CCL2, CXCL2, ILA, IFNG, IL33, and GAPDH) in protein-protein interaction network of NARCDs and immune-related genes were all immune-related genes.

Conclusion

The NARCDs prognostic signature based on the above 16 genes is an independent prognostic factor, which can effectively predict the clinical prognosis of patients of lung adenocarcinoma and provide help for clinical treatment.

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[肺腺癌中非凋亡调控细胞死亡基因的预后预测价值和生物学功能]。
目的探讨非凋亡调控细胞死亡基因(NARCDs)在肺腺癌中的潜在生物学功能和预后预测价值。方法从癌症基因组图谱和基因表达综合数据库下载肺腺癌的转录组数据。我们用R软件鉴定了肺腺癌组织和正常组织之间差异表达的NARCDs。NARCDs签名采用单变量Cox回归分析和最小绝对收缩和选择算子Cox回归构建。通过Kaplan-Meier生存曲线、受试者操作特征曲线以及单变量和多变量Cox回归分析来评估NARCDs特征的预后预测能力。使用基因集变异分析、基因本体论和京都基因和基因组百科全书分析NARCDs签名的功能富集。此外,分析了高和低NARCDs评分组在肿瘤突变负荷、肿瘤微环境、肿瘤免疫功能障碍和排斥评分以及化疗药物敏感性方面的差异。最后,利用STRING和Cytoscape软件构建了NARCDs与免疫相关基因的蛋白质-蛋白质相互作用网络。结果我们鉴定了34个与预后相关的差异表达的NARCDs,其中选择了16个基因(ATIC、AURKA、CA9、ITGB4、DDIT4、CDK5R1、CAV1、RRM2、GAPDH、SRXN1、NLRC4、GLS2、ADRB2、CX3CL1、GDF15和ADRA1A)来构建NARACDs标记。NARCDs标记被确定为一个独立的预后因素(P<0.001)。功能分析显示,高NARCDs评分组和低NARCDs分数组在错配修复、p53信号通路和细胞周期方面存在显著差异(均P<0.05),NARCDs蛋白-蛋白相互作用网络中的10个hub基因(CXCL5、TLR4、JUN、IL6、CCL2、CXCL2、ILA、IFNG、IL33和GAPDH)和免疫相关基因均为免疫相关基因。结论基于上述16个基因的NARCDs预后标志是一个独立的预后因素,可有效预测肺腺癌患者的临床预后,为临床治疗提供帮助。
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来源期刊
Chinese Medical Sciences Journal
Chinese Medical Sciences Journal Medicine-Medicine (all)
CiteScore
2.40
自引率
0.00%
发文量
1275
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