ArticleThoracic cancer2020
Identification and validation of key genes with prognostic value in non-small-cell lung cancer via integrated bioinformatics analysis.
Article in Thoracic cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed, 34 citations in OpenAlex.
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- [Holliday junction-recognizing protein is a potential predictive and prognostic biomarker for kidney renal clear cell carcinoma].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- The Impact of DAXX, HJURP and CENPA Expression in Uveal Melanoma Carcinogenesis and Associations with Clinicopathological Parameters.Biomedicines · 2024Article
- Implementation of Artificial Intelligence in Personalized Prognostic Assessment of Lung Cancer: A Narrative Review.Cancers · 2024Review
- Advancements in the diagnosis and treatment of sub‑centimeter lung cancer in the era of precision medicine (Review).Molecular and clinical oncology · 2024Review
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- A novel approach to topological network analysis for the identification of metrics and signatures in non-small cell lung cancer.Scientific reports · 2023Article
- A Unique Gene Signature Predicting Recurrence Free Survival in Stage IA Lung Adenocarcinoma.The Journal of thoracic and cardiovascular surgery · 2023Article
- Advances in holliday junction recognition protein (HJURP): Structure, molecular functions, and roles in cancer.Frontiers in cell and developmental biology · 2023Review
- To explore the effect of kaempferol on non-small cell lung cancer based on network pharmacology and molecular docking.Frontiers in pharmacology · 2023Article
- DriverMP enables improved identification of cancer driver genes.GigaScience · 2022Article
- Pan-cancer analysis based on epigenetic modification explains the value of HJURP in the tumor microenvironment.Scientific reports · 2022Article
- microRNA-1321 and microRNA-7515 contribute to the progression of non-small cell lung cancer by targeting CDC20.The Kaohsiung journal of medical sciences · 2022Article
- Integrative Analysis for Identification of Therapeutic Targets and Prognostic Signatures in Non-Small Cell Lung Cancer.Bioinformatics and biology insights · 2022Article
- Identifying potential prognosis markers in hepatocellular carcinomaFrontiers in genetics · 2022Article
- Proliferating cell nuclear antigen clamp associated factor, a potential proto-oncogene with increased expression in malignant gastrointestinal tumors.World journal of gastrointestinal oncology · 2021Review
- Genetic variants of CHEK1, PRIM2 and CDK6 in the mitotic phase-related pathway are associated with nonsmall cell lung cancer survival.International journal of cancer · 2021Article
- A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD).Cancer cell international · 2021Article
- Gene Targets Network Analysis for the Revealing and Guidance of Molecular Driving Mechanism of Lung Cancer.Frontiers in genetics · 2021Article
- Exploration of predictive and prognostic alternative splicing signatures in lung adenocarcinoma using machine learning methods.Journal of translational medicine · 2020Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundLung cancer is the most common cause of cancer-related death among all human cancers and the five-year survival rates are only 23%. The precise molecular mechanisms of non-small cell lung cancer (NSCLC) are still unknown. The aim of this study was to identify and validate the key genes with prognostic value in lung tumorigenesis.
methodsFour GEO datasets were obtained from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (DEGs) were selected for Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology enrichment analysis. Protein-protein interaction (PPI) networks were constructed using the STRING database and visualized by Cytoscape software and Molecular Complex Detection (MCODE) were utilized to PPI network to pick out meaningful DEGs. Hub genes, filtered from the CytoHubba, were validated using the Gene Expression Profiling Interactive Analysis database. The expressions and prognostic values of hub genes were carried out through Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier plotter. Finally, quantitative PCR and the Oncomine database were used to verify the differences in the expression of hub genes in lung cancer cells and tissues.
resultsA total of 121 DEGs (49 upregulated and 72 downregulated) were identified from four datasets. The PPI network was established with 121 nodes and 588 protein pairs. Finally, AURKA, KIAA0101, CDC20, MKI67, CHEK1, HJURP, and OIP5 were selected by Cytohubba, and they all correlated with worse overall survival (OS) in NSCLC.
conclusionThe results showed that AURKA, KIAA0101, CDC20, MKI67, CHEK1, HJURP, and OIP5 may be critical genes in the development and prognosis of NSCLC. KEY POINTS: Our results indicated that AURKA, KIAA0101, CDC20, MKI67, CHEK1, HJURP, and OIP5 may be critical genes in the development and prognosis of NSCLC. Our methods showed a new way to explore the key genes in cancer development.
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