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Research Article
Ming Chen
Southeast University Zhongda Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-3572-6886
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Prostate cancer (PCa) is one of the most common malignancies affecting men’s health. Docetaxel chemotherapy has been utilized in castration resistant prostate cancer (CRPC). However, docetaxel resistance further reduces the survival of PCa patients. Thus, it is necessary to explore effective biomarkers for docetaxel chemotherapy resistant PCa (DCRPC).
Methods: A comprehensive bioinformatic analysis was performed to identify differentially expressed genes (DEGs) between DCRPC and docetaxel chemotherapy sensitive PCa (DCSPC) cell. DEGs were selected between GSE33455 and GSE36135 obtained from the Gene Expression Omnibus (GEO) database. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied for functional enrichment and pathway analysis. The STRING database were used to construct protein-protein interaction (PPI) networks. Diseases free survival (DFS) was used for prognostic analysis via GEPIA.
Results: A total of 89 DEGs from GSE33455 and GSE36135 were screened. GO functional analysis showed that these DEGs are mainly enriched in the extracellular exosome, cell adhesion molecule binding, ATP binding and cellular response to tumor necrosis factor. KEGG pathway analysis showed that these DEGs are mainly involved in the TNF signaling pathway, chemokine pathway, and nicotinate and nicotinamide metabolism. 30 closely related DEGs were used for PPI network construction. Finally, four prognostic relative genes (RHOF, ADCY7, DOCK2, LMO7) were identified.
Conclusion: The present study identified prognostic hub genes and related signaling pathways, which may help improve understanding of the molecular mechanisms of DCRPC. These hub genes can potentially serve as therapeutic and prognostic biomarkers for DCRPC.
Keywords
CRPC, docetaxel resistance, prognosis, GEO
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This is a preprint. It has not completed peer review.
Research Article
Ming Chen
Southeast University Zhongda Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-3572-6886
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 15 Mar, 2021
No community comments so far
Subject Areas
Cancer Biology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: Prostate cancer (PCa) is one of the most common malignancies affecting men’s health. Docetaxel chemotherapy has been utilized in castration resistant prostate cancer (CRPC). However, docetaxel resistance further reduces the survival of PCa patients. Thus, it is necessary to explore effective biomarkers for docetaxel chemotherapy resistant PCa (DCRPC).
Methods: A comprehensive bioinformatic analysis was performed to identify differentially expressed genes (DEGs) between DCRPC and docetaxel chemotherapy sensitive PCa (DCSPC) cell. DEGs were selected between GSE33455 and GSE36135 obtained from the Gene Expression Omnibus (GEO) database. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied for functional enrichment and pathway analysis. The STRING database were used to construct protein-protein interaction (PPI) networks. Diseases free survival (DFS) was used for prognostic analysis via GEPIA.
Results: A total of 89 DEGs from GSE33455 and GSE36135 were screened. GO functional analysis showed that these DEGs are mainly enriched in the extracellular exosome, cell adhesion molecule binding, ATP binding and cellular response to tumor necrosis factor. KEGG pathway analysis showed that these DEGs are mainly involved in the TNF signaling pathway, chemokine pathway, and nicotinate and nicotinamide metabolism. 30 closely related DEGs were used for PPI network construction. Finally, four prognostic relative genes (RHOF, ADCY7, DOCK2, LMO7) were identified.
Conclusion: The present study identified prognostic hub genes and related signaling pathways, which may help improve understanding of the molecular mechanisms of DCRPC. These hub genes can potentially serve as therapeutic and prognostic biomarkers for DCRPC.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
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