ArticleMolecular and clinical oncology2018
Non-small-cell lung cancer pathological subtype-related gene selection and bioinformatics analysis based on gene expression profiles.
Article in Molecular and clinical oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Lower SLC7A2 expression is associated with enhanced multidrug resistance, less immune infiltrates and worse prognosis of NSCLC.Cell communication and signaling : CCS · 2023Article
- The clinical outcome and risk factors analysis of immune checkpoint inhibitor-based treatment in lung adenocarcinoma patients with brain metastases.Translational lung cancer research · 2022Article
- Characterization of DNA methylation as well as mico-RNA expression and screening of epigenetic markers in adipogenesis.Journal of translational medicine · 2022Article
- Dissection of the Functional Mechanism of Human Gut Bacterial Strain AD16 by Secondary Metabolites' Identification, Network Pharmacology, and Experimental Validation.Frontiers in pharmacology · 2021Article
- Identification of Candidate Biomarkers Correlated With the Pathogenesis and Prognosis of Non-small Cell Lung Cancer via Integrated Bioinformatics Analysis.Frontiers in genetics · 2018Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
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Abstract
Lung cancer is one of the most common malignant diseases and a major threat to public health on a global scale. Non-small-cell lung cancer (NSCLC) has a higher degree of malignancy and a lower 5-year survival rate compared with that of small-cell lung cancer. NSCLC may be mainly divided into two pathological subtypes, adenocarcinoma and squamous cell carcinoma. The aim of the present study was to identify disease genes based on the gene expression profile and the shortest path analysis of weighted functional protein association networks with the existing protein-protein interaction data from the Search Tool for the Retrieval of Interacting Genes. The gene expression profile (GSE10245) was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database, including 40 lung adenocarcinoma and 18 lung squamous cell carcinoma tissues. A total of 8 disease genes were identified using Naïve Bayesian Classifier based on the Maximum Relevance Minimum Redundancy feature selection method following preprocessing. An additional 21 candidate genes were selected using the shortest path analysis with Dijkstra's algorithm. The
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