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Establishment of a Primary Culture of Patient-derived Soft Tissue Sarcoma
Published on: April 11, 2018
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Co-expression Network Analysis Identifies Four Hub Genes Associated With Prognosis in Soft Tissue Sarcoma
Zhenhua Zhu1, Zheng Jin2, Yuyou Deng3
1Department of Orthopaedic Trauma, The First Hospital of Jilin University, Changchun, China.
Frontiers in Genetics
|February 20, 2019
Summary
This study identified four key genes (RRM2, BUB1B, CENPF, KIF20A) linked to poor prognosis in soft tissue sarcomas (STS). These genes impact cell cycle and metabolism, offering potential therapeutic targets for STS.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Soft tissue sarcomas (STS) are diverse tumors originating from mesenchymal cells.
- Patient prognosis in STS is significantly affected by intricate gene regulatory networks.
Purpose of the Study:
- To identify gene modules and hub genes associated with soft tissue sarcomas (STS) prognosis.
- To investigate the functional pathways influenced by these identified genes.
Main Methods:
- Weighted gene co-expression network analysis (WGCNA) was applied to 156 STS samples.
- Module preservation analysis and protein-protein interaction network analysis were conducted.
- Gene set enrichment analysis (GSEA) was used to identify enriched pathways.
Main Results:
- The blue module was identified as significantly correlated with STS.
- Four hub genes (RRM2, BUB1B, CENPF, KIF20A) within the blue module were associated with poorer overall and disease-free survival.
- High expression of the blue module eigengene was linked to enrichment in cell cycle and metabolism pathways.
Conclusions:
- Co-expression network analysis revealed four prognostic hub genes in STS.
- These genes may negatively impact STS prognosis by modulating cell cycle and metabolism signaling pathways.
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