Chinese Medical Sciences Journal ›› 2023, Vol. 38 ›› Issue (3): 178-190.doi: 10.24920/004222

• Original Article • Previous Articles     Next Articles

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

Hao-Ling Li1, 2, Jun-Xian Wang1, Heng-Wen Dai2, Jun-Jie Liu2, Zi-Yang Liu1, 2, Ming-Yuan Zou2, Lei Zhang1, 3, *(), Wen-Rui Wang1, 4, *()   

  1. 1Anhui Province Key Laboratory of Translational Cancer Research, Bengbu Medical College, Bengbu, Anhui 233030, China
    2Department of Clinical Medicine, Bengbu Medical College, Bengbu, Anhui 233030, China
    3Department of Life Sciences, Bengbu Medical College, Bengbu, Anhui 233030, China
    4Department of Thoracic Surgery, First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui 233030, China
  • Received:2023-03-15 Accepted:2023-07-10 Published:2023-09-30 Online:2023-08-25
  • Contact: * wenrui-wang, E-mail:; Lei Zhang, E-mail:

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, p53 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, 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.

Key words: lung adenocarcinoma, apoptosis, regutated cell dealth, prognostic model, tumor microenvironment, immunotherapy


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