ArticleBioengineered2021
Identification of biomarkers, pathways and potential therapeutic target for docetaxel resistant prostate cancer.
Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Article
- A novel prognostic risk score associated with resistance to docetaxel chemotherapy for predicting biochemical recurrence-free survival in patients with prostate cancer.Discover oncology · 2025Article
- Exploration of the influence of GOLGA8B on prostate cancer progression and the resistance of castration-resistant prostate cancer to cabazitaxel.Discover oncology · 2024Article
- Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer.Cell biology and toxicology · 2024Article
- Icariin-Curcumol promotes docetaxel sensitivity in prostate cancer through modulation of the PI3K-Akt signaling pathway and the Warburg effect.Cancer cell international · 2023Article
- Identification of a NACC1-Regulated Gene Signature Implicated in the Features of Triple-Negative Breast Cancer.Biomedicines · 2023Article
- MicroRNA-506-3p inhibits colorectal cancer cell proliferation through targeting enhancer of zeste homologue 2.Bioengineered · 2021Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Docetaxel has been proved to provide survival benefit for advanced prostate cancer (PCa) patients. Resistance to docetaxel further reduces the survival of these patients. Herein, we performed a comprehensive bioinformatic analysis to identify differentially expressed genes (DEGs) between docetaxel sensitive and resistant PCa (DRPC) cell based on Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied for functional and pathway analysis of DEGs. The STRING database, cytoscape software and plug-in 'cytoHubba' were used to construct protein-protein interaction (PPI) networks and identify hub genes. Survival analysis were performed via GEPIA database. Finally, we conducted immune infiltration analysis by TIMER. A total of 460 DEGs were identified. GO functional analysis showed that these DEGs are mainly enriched in chemotaxis, negative regulation of intracellular signal transduction, and regulation of cell adhesion, positive regulation of inflammatory response, regulation of response to cytokine stimulus. According to the results of KEGG pathway analysis, these DEGs are mainly involved in signaling by Rho GTPases, Miro GTPases and RHOBTB3; interferon Signaling; arginine biosynthesis; PI3K-Akt signaling pathway; cytokine-cytokine receptor interaction; MAPK signaling pathway. Finally, CCNB1 and EZH2 were identified as prognostic hub genes and the expression of these two genes were associated with immune infiltration. The present study may helps to improve the understanding of the molecular mechanisms of DRPC and facilitate the selection of therapeutic and prognostic biomarkers for DRPC.
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