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The identification of novel biomarkers offers potential avenues for therapeutic interventions in lung adenocarcinoma
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Abstract
Background: Lung cancer stands as a prominent contributor to cancer-related fatalities, with lung adenocarcinoma emerging as one of its primary histological subtypes. Regrettably, the 5-year survival rate for patients afflicted by this condition remains below 20%. Mitochondria, being indispensable organelles responsible for upholding cellular functionality, are susceptible to malfunctioning and can consequently give rise to diverse diseases. Henceforth, the objective of this study is to scrutinize the correlation between genes associated with mitochondria and the onset and progression of lung adenocarcinoma tumors .
Method: The lung adenocarcinoma gene expression dataset was obtained from the TCGA database for conducting differential gene expression analysis. Subsequently, Kaplan-Meier survival analysis, univariate and multivariate Cox regression analyses were performed on the differentially expressed genes (DEGs), leading to the construction of a nomogram based on these analytical results. Additionally, GO, KEGG, and GSEA enrichment analyses were carried out on the DEGs.
Results: Differential gene expression analysis revealed the presence of 13 upregulated genes related to mitochondrial fission in lung adenocarcinoma tissues, which were found to be associated with prognosis. After excluding one unfavorable prognostic gene, survival analysis was conducted on the remaining 12 genes. Univariate and multivariate Cox regression analyses demonstrated that N stage, T stage, risk score, and age significantly influenced the prognosis of lung adenocarcinoma. Based on these findings, a nomogram was developed for predicting the survival probability of patients with lung adenocarcinoma at different time points (1 year, 3 years, 5 years, and 10 years). Furthermore, GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes), and GSEA (Gene Set Enrichment Analysis) enrichment analyses indicated that the differentially expressed genes were predominantly enriched in pathways associated with cellular senescence and cell cycle regulation. These results suggest their potential relevance to tumor development in lung adenocarcinoma.
Conclusion: This study identified 12 differentially expressed genes, namely BIRC5, BRCA1, CA9, CDK1, CERS1, FOXM1, GAPDH, GPI, MTFR2, PPIF, RACGAP1 and S100A9. These genes hold promising potential as prognostic biomarkers for lung adenocarcinoma.
Title: The identification of novel biomarkers offers potential avenues for therapeutic interventions in lung adenocarcinoma
Description:
Abstract
Background: Lung cancer stands as a prominent contributor to cancer-related fatalities, with lung adenocarcinoma emerging as one of its primary histological subtypes.
Regrettably, the 5-year survival rate for patients afflicted by this condition remains below 20%.
Mitochondria, being indispensable organelles responsible for upholding cellular functionality, are susceptible to malfunctioning and can consequently give rise to diverse diseases.
Henceforth, the objective of this study is to scrutinize the correlation between genes associated with mitochondria and the onset and progression of lung adenocarcinoma tumors .
Method: The lung adenocarcinoma gene expression dataset was obtained from the TCGA database for conducting differential gene expression analysis.
Subsequently, Kaplan-Meier survival analysis, univariate and multivariate Cox regression analyses were performed on the differentially expressed genes (DEGs), leading to the construction of a nomogram based on these analytical results.
Additionally, GO, KEGG, and GSEA enrichment analyses were carried out on the DEGs.
Results: Differential gene expression analysis revealed the presence of 13 upregulated genes related to mitochondrial fission in lung adenocarcinoma tissues, which were found to be associated with prognosis.
After excluding one unfavorable prognostic gene, survival analysis was conducted on the remaining 12 genes.
Univariate and multivariate Cox regression analyses demonstrated that N stage, T stage, risk score, and age significantly influenced the prognosis of lung adenocarcinoma.
Based on these findings, a nomogram was developed for predicting the survival probability of patients with lung adenocarcinoma at different time points (1 year, 3 years, 5 years, and 10 years).
Furthermore, GO (Gene Ontology), KEGG (Kyoto Encyclopedia of Genes and Genomes), and GSEA (Gene Set Enrichment Analysis) enrichment analyses indicated that the differentially expressed genes were predominantly enriched in pathways associated with cellular senescence and cell cycle regulation.
These results suggest their potential relevance to tumor development in lung adenocarcinoma.
Conclusion: This study identified 12 differentially expressed genes, namely BIRC5, BRCA1, CA9, CDK1, CERS1, FOXM1, GAPDH, GPI, MTFR2, PPIF, RACGAP1 and S100A9.
These genes hold promising potential as prognostic biomarkers for lung adenocarcinoma.
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