ArticlePloS one2018
Network-based co-expression analysis for exploring the potential diagnostic biomarkers of metastatic melanoma.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Acute myeloid leukemia risk stratification in younger and older patients through transcriptomic machine learning models.Scientific reports · 2025Article
- Kallikrein-8 mediates furin-independent Activin-A precursor processing to stimulate tumor growth in melanoma.Nature communications · 2025Article
- Overexpression of TMEM79 combined with SMG5 is related to prognosis, tumor immune infiltration and drug sensitivity in hepatocellular carcinoma.European journal of medical research · 2023Article
- Identification of immune-related genes contributing to head and neck squamous cell carcinoma development using weighted gene co-expression network analysis.Cancer reports (Hoboken, N.J.) · 2023Article
- Prognostic prediction of lung adenocarcinoma by integrative analysis of RHOH expression and methylation.The clinical respiratory journal · 2023Article
- Expression Profile and Gene Regulation Network of NUSAP1 in Pan Cancers Based on Integrated Bioinformatics Analysis.International journal of general medicine · 2023Article
- RNA-seq and ChIP-seq Identification of Unique and Overlapping Targets of GLI Transcription Factors in Melanoma Cell Lines.Cancers · 2022Article
- Bioinformatic analysis identifies epidermal development genes that contribute to melanoma progression.Medical oncology (Northwood, London, England) · 2022Article
- Identification of Core Genes and Pathways in Melanoma Metastasis via Bioinformatics Analysis.International journal of molecular sciences · 2022Article
- The mitochondrial proteomic changes of rat hippocampus induced by 28-day simulated microgravity.PloS one · 2022Article
- In-depth systems biological evaluation of bovine alveolar macrophages suggests novel insights into molecular mechanisms underlyingFrontiers in microbiology · 2022Article
- Relationships of Ferroptosis and Pyroptosis-Related Genes with Clinical Prognosis and Tumor Immune Microenvironment in Head and Neck Squamous Cell Carcinoma.Oxidative medicine and cellular longevity · 2022Article
- Comparative mRNA/micro-RNA co-expression network drives melanomagenesis by promoting epithelial-mesenchymal transition and vasculogenic mimicry signaling.Translational oncology · 2021Article
- Bimodal expression ofEJHaem · 2021Article
- SMARCA4 promotes benign skin malignant transformation into melanoma through Adherens junction signal transduction.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2021Article
- Transcript levels of keratin 1/5/6/14/15/16/17 as potential prognostic indicators in melanoma patients.Scientific reports · 2021Article
- Identification and Validation of Immune- and Stemness-Related Prognostic Signature of Melanoma.Frontiers in cell and developmental biology · 2021Article
- Identification of Potential Prognostic Biomarkers Associated With Cancerometastasis in Skin Cutaneous Melanoma.Frontiers in genetics · 2021Article
- Identification of Keratinocyte Differentiation-Involved Genes for Metastatic Melanoma by Gene Expression Profiles.Computational and mathematical methods in medicine · 2021Article
- Assessing immune infiltration and the tumor microenvironment for the diagnosis and prognosis of sarcoma.Cancer cell international · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metastatic melanoma is an aggressive skin cancer and is one of the global malignancies with high mortality and morbidity. It is essential to identify and verify diagnostic biomarkers of early metastatic melanoma. Previous studies have systematically assessed protein biomarkers and mRNA-based expression characteristics. However, molecular markers for the early diagnosis of metastatic melanoma have not been identified. To explore potential regulatory targets, we have analyzed the gene microarray expression profiles of malignant melanoma samples by co-expression analysis based on the network approach. The differentially expressed genes (DEGs) were screened by the EdgeR package of R software. A weighted gene co-expression network analysis (WGCNA) was used for the identification of DEGs in the special gene modules and hub genes. Subsequently, a protein-protein interaction network was constructed to extract hub genes associated with gene modules. Finally, twenty-four important hub genes (RASGRP2, IKZF1, CXCR5, LTB, BLK, LINGO3, CCR6, P2RY10, RHOH, JUP, KRT14, PLA2G3, SPRR1A, KRT78, SFN, CLDN4, IL1RN, PKP3, CBLC, KRT16, TMEM79, KLK8, LYPD3 and LYPD5) were treated as valuable factors involved in the immune response and tumor cell development in tumorigenesis. In addition, a transcriptional regulatory network was constructed for these specific modules or hub genes, and a few core transcriptional regulators were found to be mostly associated with our hub genes, including GATA1, STAT1, SP1, and PSG1. In summary, our findings enhance our understanding of the biological process of malignant melanoma metastasis, enabling us to identify specific genes to use for diagnostic and prognostic markers and possibly for targeted therapy.
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