The identification and prediction of lung adenocarcinoma prognosis using a novel gene signature associated with DNA replication

Background: Lung adenocarcinoma (LUAD) is the most aggressive lung cancer phenotype, and patients’ clinical response is often limited by primary or acquired mechanisms of resistance to oncological therapy. One of the current clinical needs is to define clinical predictors for the prognosis of LUAD,...

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Hauptverfasser: Wu, Xiujuan (VerfasserIn) , Xu, Qiang (VerfasserIn) , Aiyiti, Paerhati (VerfasserIn) , Meng, Defeng (VerfasserIn) , Zhang, Jingang (VerfasserIn) , Citarella, Fabrizio (VerfasserIn) , Christopoulos, Petros (VerfasserIn) , Liu, Tong (VerfasserIn) , Duan, Wei (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: March 30, 2025
In: Translational cancer research
Year: 2025, Jahrgang: 14, Heft: 3, Pages: 1971-1981
ISSN:2219-6803
DOI:10.21037/tcr-2024-2536
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.21037/tcr-2024-2536
Verlag, lizenzpflichtig, Volltext: https://tcr.amegroups.org/article/view/98256
Volltext
Verfasserangaben:Xiujuan Wu, Qiang Xu, Paerhati Aiyiti, Defeng Meng, Jingang Zhang, Fabrizio Citarella, Petros Christopoulos, Tong Liu, Wei Duan

MARC

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520 |a Background: Lung adenocarcinoma (LUAD) is the most aggressive lung cancer phenotype, and patients’ clinical response is often limited by primary or acquired mechanisms of resistance to oncological therapy. One of the current clinical needs is to define clinical predictors for the prognosis of LUAD, aiming at offering patients a persistent treatment likely to delay disease progression as much as possible. This study relies on data from The Cancer Genome Atlas (TCGA) to define the functional roles and prognostic implications of DNA replication-related genes in LUAD. Methods: Clinical features and RNA-sequencing data were collected from 607 LUAD patients from TCGA-LUAD dataset, with the aims to identify the genes related to patient prognosis, and the pathways related to DNA replication in LUAD. Results: A total of 2,412 prognostic genes were obtained, and the DNA replication-related pathways closely associated with LUAD were identified by a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. TCGA-LUAD patients were divided into a high- (G1) and low- (G2) risk groups based on the 15 DNA replication-related genes (i.e., FEN1, MCM5, POLD2, MCM4, MCM6, SSBP1, POLE2, RFC2, MCM2, PCNA, POLA2, MCM7, RFC3, POLE4, and RPA3). The upregulated genes were mainly related to the hallmarks of cancer (e.g., chromosome segregation, DNA replication, the cell cycle checkpoint, and DNA helicase activity), while the downregulated genes were mainly related to leukocyte activation involved in inflammatory macrophage activation, and passive transmembrane transporter activity. The immune cells, including the B cells, endothelial cells, natural killer (NK) cells, cluster of differentiation (CD)4+ T cells, and CD8+ T cells, of the Group 1 (G1) LUAD samples were clearly different from those of the Group (G2) LUAD samples. In addition, 5 of the 10 immune checkpoint inhibitor (ICI)-related genes (i.e., CD274, LAG3, PDCD1, PDCD1LG2, and SIGLEC15) were of a higher level in the G1 LUAD samples than in the G2 LUAD samples. The tumor stemness of the two risk groups differed significantly. Furthermore, a six-gene (FEN1, MCM5, POLD2, MCM4, SSBP1, and POLE4) prognostic model was constructed to predict the prognosis of LAD patients. Conclusions: There is a close relationship between the DNA replication-related genes and the tumor classification of LUAD patients. An innovative signature related to DNA replication was found to be a good prognostic predictor of LUAD. Our findings may provide novel insights into the diagnosis and treatment of LUAD. 
700 1 |a Xu, Qiang  |e VerfasserIn  |4 aut 
700 1 |a Aiyiti, Paerhati  |e VerfasserIn  |4 aut 
700 1 |a Meng, Defeng  |e VerfasserIn  |4 aut 
700 1 |a Zhang, Jingang  |e VerfasserIn  |4 aut 
700 1 |a Citarella, Fabrizio  |e VerfasserIn  |4 aut 
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700 1 |a Liu, Tong  |e VerfasserIn  |4 aut 
700 1 |a Duan, Wei  |e VerfasserIn  |4 aut 
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