ArticleFrontiers in molecular biosciences2024
NUF2 is associated with cancer stem cell characteristics and a potential drug target for prostate cancer.
Article in Frontiers in molecular biosciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- NCAPG reprograms glycolytic and lipid metabolism by sustaining glycerophospholipid flux in small-cell lung cancer.Molecular and cellular biochemistry · 2026Article
- NUF2 interacts with BUB3 and drives lung adenocarcinoma progression through activation of the NF-κB pathway.World journal of surgical oncology · 2026Article
- Unravelling TPX2-centered co-expression networks as key drivers of aggressive prostate cancer.Scientific reports · 2025Article
- A core stemness-associated module reveals PLK1, NUF2, KIF23, CDCA8, TOP2A, CENPF, AURKA, and ASPM as key genes in rectal cancer.European journal of medical research · 2025Article
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6 authors.
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Abstract
Background: Cancer stem cells are characterized by self-renewal, clonal tumor initiation capacity, and treatment resistance, which play essential roles in the tumor progression of prostate cancer (PCa). In this study, we aim to explore the features of cancer stemness and characterize the expression of stem cell-related genes for PCa. Methods: We downloaded RNA-seq data and related clinical information from The Cancer Genome Atlas (TCGA) database. The mRNA stemness index (mRNAsi) was analyzed for various clinical features, overall survival (OS), and disease-free survival (DFS), and a weighted gene co-expression network analysis (WGCNA) was performed to identify crucial gene modules and key genes, which may play a role in CSCs. The key gene functions were verified using multiple databases, including the TCGA and Gene Expression Omnibus database (GEO). Next, we explored the potential function of the modules and genes obtained using WGCNA using an enrichment analysis. Finally, we performed Results: We found that mRNAsi were higher in PCa tissues than in normal tissues, and the mRNAsi were closely related to the clinical characteristics of PCa. A total of 16 key genes associated with the mRNAsi scores were identified by WGCNA analysis, including NCAPG, NEK2, DLGAP5, CENPA, CENPF, TPX2, GTSE1, KIF4A, NEIL3, CDC25C, UBE2C, CDCA5, MELK, SKA3, NUF2, and BIRC5. These genes were explicitly highly expressed in PCa across TCGA cancers and were validated in 3 independent GEO PCa datasets. The functional annotations of the key genes were linked with the cell proliferation processes. NUF2 may be a potential biomarker for PCa. Conclusion: The 16 key genes identified in this study significantly correlate with PCa stem cell characteristics and showed prognosis-oriented effects in PCa patients. Further, the NUF2 gene may be used as a drug target for treating PCa.
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