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pmid:32076707

Co-expression network-based identification of biomarkers correlated with the lymph node metastasis of patients with head and neck squamous cell carcinoma.

Yu Jin · Xing Qin

Bioscience reports · 2020 doi:10.1042/BSR20194067

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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pmid:32076707
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title
Co-expression network-based identification of biomarkers correlated with the lymph node metastasis of patients with head and neck squamous cell carcinoma.
doi
10.1042/BSR20194067
pmid
32076707
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[0]
Yu Jin
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Xing Qin
journal
Bioscience reports
year
2020
abstract
Head and neck squamous cell carcinoma (HNSCC) is ranked as one of the most frequent malignancies worldwide with a high risk of lymph node metastasis, which serves as a main reason for cancer deaths. Identification of the potential biomarkers for lymph node metastasis in HNSCC patients may contribute to personalized treatment and better therapeutic effect. In the present study, GSE30788 microarray data and corresponding clinical parameters were downloaded from Gene Expression Omnibus (GEO) and Weighted Gene Co-expression Network Analysis (WGCNA) was performed to investigate significant modules associated with clinical traits. As a result, the genes in the blue module were determined as candidate genes related with HNSCC lymph node metastasis and ten hub genes were selected from the PPI network. Further analysis validated the close associations of hub gene expression with lymph node metastasis of HNSCC patients. Furthermore, survival analysis suggested the level of Loricrin (LOR) was statistically significantly associated with the disease-free survival of HNSCC patients, indicating the potential of utilizing it as prognosis predictor. Overall, our study conducted a co-expression network-based analysis to investigate significant genes underlying HNSCC metastasis, providing promising biomarkers and therapeutic targets.
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Comparisons between two groups were performed using non-parametric Mann–Whitney U test.
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Validation of an expression signature for lymph node metastasis detection in oral cavity squamous cell carcinoma
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analysis_only
id
assay:1
Complete file
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Identification of the potential biomarkers for lymph node metastasis in HNSCC patients may contribute to personalized treatment and better therapeutic effect. In the present study, GSE30788 microarray data and corresponding clinical parameters were downloaded from Gene Expression Omnibus (GEO) and Weighted Gene Co-expression Network Analysis (WGCNA) was performed to investigate significant modules associated with clinical traits. As a result, the genes in the blue module were determined as candidate genes related with HNSCC lymph node metastasis and ten hub genes were selected from the PPI network. Further analysis validated the close associations of hub gene expression with lymph node metastasis of HNSCC patients. Furthermore, survival analysis suggested the level of Loricrin (LOR) was statistically significantly associated with the disease-free survival of HNSCC patients, indicating the potential of utilizing it as prognosis predictor. 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