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

Hao-Ling Li; Jun-Xian Wang; Heng-Wen Dai; Jun-Jie Liu; Zi-Yang Liu; Ming-Yuan Zou; Lei Zhang; Wen-Rui Wang

doi:10.24920/004222

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

Chinese Medical Sciences Journal Vol. 38, Issue 3, Pages: 178-190(2023)

Original Article | Updated：2024-11-26

- Prognostic Prediction Value and Biological Functions of Non-Apoptotic Regulated Cell Death Genes in Lung Adenocarcinoma
- Affiliations：
  
  1. 1Anhui Province Key Laboratory of Translational Cancer Research, Bengbu Medical College, Bengbu, Anhui 233030, China
  2. 2Department of Clinical Medicine, Bengbu Medical College, Bengbu, Anhui 233030, China
  3. 3Department of Life Sciences, Bengbu Medical College, Bengbu, Anhui 233030, China
  4. 4Department of Thoracic Surgery, First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui 233030, China
- Author bio：
  
  Lei Zhang, E-mail: 727302227@qq.com
- Funds：
- DOI：10.24920/004222
  CLC：
- Received：15 March 2023，
  
  Accepted：2023-7-10，
  
  Published Online：25 August 2023，
  
  Published：30 September 2023
- Accepted：
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Hao-Ling Li, Jun-Xian Wang, Heng-Wen Dai, et al. Prognostic Prediction Value and Biological Functions of Non-Apoptotic Regulated Cell Death Genes in Lung Adenocarcinoma[J]. Chinese medical sciences journal, 2023, 38(3): 178-190.
DOI：

Hao-Ling Li, Jun-Xian Wang, Heng-Wen Dai, et al. Prognostic Prediction Value and Biological Functions of Non-Apoptotic Regulated Cell Death Genes in Lung Adenocarcinoma[J]. Chinese medical sciences journal, 2023, 38(3): 178-190. DOI： 10.24920/004222.

摘要

目的

探究非凋亡调节性细胞死亡基因（non-apoptotic regulatory cell death genes，NARCDs）预测肺腺癌预后的价值及其潜在生物学功能。

方法

我们下载癌症基因组图谱（The Cancer Genome Atla，TCGA）及基因表达综合（Gene Expression Omnibus，GEO）数据库中肺腺癌的转录组数据。使用R软件分析在肺腺癌组织和正常组织之间存在差异表达的NARCDs。采用单变量Cox分析和LASSO-Cox回归分析构建NARCDs预后模型。采用生存分析曲线、受试者工作特征曲线、单因素和多因素Cox回归分析评估NARCDs预后模型对肺腺癌预后的预测能力。采用GSVA、GO和KEGG分析NARCDs预后模型的功能富集情况。此外，我们分析了高、低NARCDs评分组间的肿瘤突变负担、肿瘤微环境、肿瘤免疫功能障碍与排斥（Tumor Immune Dysfunction and Exclusion，TIDE）评分和化疗药物敏感性的差异。最后，使用STRING和Cytoscape软件构建NARCDs与免疫相关基因的蛋白-蛋白相互作用网络。

结果

我们确定了34个与预后相关的差异表达NARCDs，其中16个基因（

ATIC

、

AURKA

、

CA9

、

ITGB4

、

DDIT4

、

CDK5R1

、

CAV1

、

RRM2

、

GAPDH

、

SRXN1

、

NLRC4

、

GLS2

、

ADRB2

、

CX3CL1

、

GDF15

和

ADRA1A

）被用于构建NARCDs预后模型。NARCDs风险评分是肺腺癌的独立预后因素（

0.001）。功能分析显示：高NARCDs评分组与低

NARCDs

评分组间在错配修复、p53信号通路和细胞周期方面存在显著差异（

0.05）。低NARCD评分组的肿瘤突变负荷较低，免疫评分及TIDE评分较高，对药物的敏感性较低（

0.05）。此外，蛋白-蛋白相互作用网络的10个关键基因（

CXCL5

、

TLR4

、

JUN

、

IL6

、

CCL2

、

CXCL2

、

ILA

、

IFNG

、

IL33

和

GAPDH

）均为免疫相关基因。

结论

基于16个基因构建的NARCDs预后模型是肺腺癌的独立预后因素，其能有效预测患者预后，并为临床治疗提供帮助。

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 (

0.001). Functional analysis showed that there were significant differences in mismatch repair

p53 signaling pathway

and cell cycle between the high NARCDs score group and low NARCDs score group (all

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

0.05). In addition

the 10 hub genes (

CXCL5

TLR4

JUN

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.

关键词

Keywords

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