ArticleMedicine2020
Mining of gene modules and identification of key genes in head and neck squamous cell carcinoma based on gene co-expression network analysis.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- The role and therapeutic value of NUSAP1 in human cancers.Journal of translational medicine · 2025Review
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- PRRGO: A Tool for Visualizing and Mapping Globally Expressed Genes in Public Gene Expression Omnibus RNA-Sequencing Studies to PageRank-scored Gene Ontology Terms.bioRxiv : the preprint server for biology · 2024Article
- Envoplakin Inhibits Macrophage Polarization by Altering the Inflammatory Tumor Microenvironment of Melanoma Through the RAS / ERK Signaling Pathway.Journal of inflammation research · 2024Article
- Oncogenic Viruses as Entropic Drivers of Cancer Evolution.Frontiers in virology (Lausanne, Switzerland) · 2021Article
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Authors and funding
5 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To explore the gene modules and key genes of head and neck squamous cell carcinoma (HNSCC), a bioinformatics algorithm based on the gene co-expression network analysis was proposed in this study.Firstly, differentially expressed genes (DEGs) were identified and a gene co-expression network (i-GCN) was constructed with Pearson correlation analysis. Then, the gene modules were identified with 5 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Gene Ontology (GO) analysis was used to annotate the biological pathways of the gene modules. Then, the key genes were identified with 2 methods, gene significance (GS) and PageRank algorithm. Moreover, we used the Disgenet database to search the related diseases of the key genes. Lastly, the online software onclnc was used to perform the survival analysis on the key genes and draw survival curves.There were 2600 up-regulated and 1547 down-regulated genes identified in HNSCC. An i-GCN was constructed with Pearson correlation analysis. Then, the i-GCN was divided into 9 gene modules. The result of association analysis showed that, sex was mainly related to mitosis and meiosis processes, event was mainly related to responding to interferons, viruses and T cell differentiation processes, T stage was mainly related to muscle development and contraction, regulation of protein transport activity processes, N stage was mainly related to mitosis and meiosis processes, while M stage was mainly related to responding to interferons and immune response processes. Lastly, 34 key genes were identified, such as CDKN2A, HOXA1, CDC7, PPL, EVPL, PXN, PDGFRB, CALD1, and NUSAP1. Among them, HOXA1, PXN, and NUSAP1 were negatively correlated with the survival prognosis.HOXA1, PXN, and NUSAP1 might play important roles in the progression of HNSCC and severed as potential biomarkers for future diagnosis.
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