ArticleOncology letters2020
Identification of key candidate tumor biomarkers in non-small-cell lung cancer by
Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 7 citations in OpenAlex.
- Preclinical Evaluation of Combined Polo-like Kinase 1 Inhibition and Navitoclax in Experimental Models of Lung Cancer.International journal of molecular sciences · 2026Article
- Mitotic Machinery Dysregulation in Lung Cancer: Biological Roles, Therapeutic Targeting, and Combination Strategies.Pharmaceutics · 2026Review
- The role of miR-21 in early-stage lung adenocarcinoma: clinical and bioinformatics insights.Scientific reports · 2025Article
- Knockdown of RFC4 inhibits the cell proliferation of nasopharyngeal carcinoma in vitro and in vivo.Frontiers of medicine · 2023Article
- Single-cell RNA-seq analysis to identify potential biomarkers for diagnosis, and prognosis of non-small cell lung cancer by using comprehensive bioinformatics approaches.Translational oncology · 2023Article
- Polo-like kinase (PLK) 5, a new member of the PLK family, serves as a biomarker to indicate anabatic tumor burden and poor prognosis for resectable non-small cell lung cancer.Frontiers in surgery · 2022Article
- Pan-cancer analysis of non-oncogene addiction to DNA repair.Scientific reports · 2021Article
- Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis.Cancer management and research · 2020Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer is a common malignancy worldwide. The aim of the present study was to investigate differentially expressed genes (DEGs) between non-small-cell lung cancer (NSCLC) and normal lung tissue, and to reveal the potential molecular mechanism underlying NSCLC. The Gene Expression Omnibus database was used to obtain three gene expression profiles (GSE18842, GSE30219 and GSE33532). DEGs were obtained by GEO2R. Gene Ontology and pathway enrichment analyses were performed for DEGs in the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of DEGs was constructed and analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins database and Cytoscape software. A survival analysis was performed and protein expression levels of DEGs in human NSCLC were analyzed in order to determine clinical significance. A total of 764 DEGs were identified, consisting of 428 upregulated and 336 downregulated genes in NSCLC tissues compared with normal lung tissues, which were enriched in the 'cell cycle', 'cell adhesion molecules', 'p53 signaling pathway', 'DNA replication' and 'tight junction'. A PPI network of DEGs consisting of 51 nodes and 192 edges was constructed. The top 10 genes were identified as hub genes from the PPI network. High expression of 4 of the 10 hub genes was associated with worse overall survival rate in patients with NSCLC, including CDK1, PLK1, RAD51 and RFC4. In conclusion, the present study aids in improving the current understanding of aberrant gene expression between NSCLC tissues and normal lung tissues underlying tumorgenesis in NSCLC. Identified hub genes can be used as a tumor marker for diagnosis and prognosis or as a drug therapy target in NSCLC.
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Registered trials
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