ArticleOncology letters2019
Five genes may predict metastasis in non-small cell lung cancer using bioinformatics analysis.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- The aryl hydrocarbon receptor controls IFN-γ-induced immune checkpoints PD-L1 and IDO via the JAK/STAT pathway in lung adenocarcinoma.Journal of immunology (Baltimore, Md. : 1950) · 2025Article
- The NIMA-related kinase family and cancer.Frontiers in oncology · 2025Review
- The Aryl Hydrocarbon Receptor Controls IFNγ-Induced Immune Checkpoints PD-L1 and IDO via the JAK/STAT Pathway in Lung Adenocarcinoma.bioRxiv : the preprint server for biology · 2024Article
- Advances in the expression and function of Fyn in different human tumors.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023Review
- Integrative Analysis for Identification of Therapeutic Targets and Prognostic Signatures in Non-Small Cell Lung Cancer.Bioinformatics and biology insights · 2022Article
- Article
- A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD).Cancer cell international · 2021Article
- Cytoskeletal Remodeling in Cancer.Biology · 2020Review
- Comprehensive Exome Analysis of Immunocompetent Metastatic Head and Neck Cancer Models Reveals Patient Relevant Landscapes.Cancers · 2020Article
- Analysis of genomic and transcriptomic variations as prognostic signature for lung adenocarcinoma.BMC bioinformatics · 2020Article
- FOXO transcription factor family in cancer and metastasis.Cancer metastasis reviews · 2020Review
- Integrated analysis of the roles and prognostic value of RNA binding proteins in lung adenocarcinoma.PeerJ · 2020Article
- Expression and prognostic analyses ofPeerJ · 2019Article
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Authors and funding
10 authors.
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Abstract
Lung cancer is one of the most common types of malignancy worldwide. The prognosis of lung cancer is poor, due to the onset of metastases. The aim of the present study was to examine lung cancer metastasis-associated genes. To identify novel metastasis-associated targets, our previous study detected the differentially expressed mRNAs and long non-coding RNAs between the large-cell lung cancer high-metastatic 95D cell line and the low-metastatic 95C cell line by microarray assay. In the present study, these differentially expressed genes (DEGs) were analyzed via bioinformatics methods, including Gene Ontology functional analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. A protein-protein interaction network was subsequently constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins online database and Cytoscape software, and 17 hub genes were screened out on the basis of connectivity degree. These hub genes were further validated in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) using the online Gene Expression Profiling Interactive Analysis database. A total of seven hub genes were identified to be significantly differentially expressed in LUAD and LUSC. The prognostic information was detected using Kaplan-Meier plotter. As a result, five genes were revealed to be closely associated with the overall survival time of patients with lung cancer, including phosphoinositide-3-kinase regulatory subunit 1, FYN, thrombospondin 1, nonerythrocytic α-spectrin 1 and secreted phosphoprotein 1. In addition, lung cancer and adjacent lung tissue samples were used to validate these hub genes by reverse transcription-quantitative polymerase chain reaction. In conclusion, the results of the present study may provide novel metastasis-associated therapeutic strategies or potential biomarkers in non-small cell lung cancer.
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