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Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis

Prostate cancer (PCa) is a life-threatening heterogeneous malignancy of the urinary tract. Due to the incidence of prostate cancer and the crucial need to elucidate its molecular mechanisms, we searched for possible prognosis impactful genes in PCa using bioinformatics analysis. A script in R langua...

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Autores principales: Bagherabadi, Arash, Hooshmand, Amirreza, Shekari, Nooshin, Singh, Prithvi, Zolghadri, Samaneh, Stanek, Agata, Dohare, Ravins
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140438/
https://www.ncbi.nlm.nih.gov/pubmed/35627227
http://dx.doi.org/10.3390/genes13050840
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author Bagherabadi, Arash
Hooshmand, Amirreza
Shekari, Nooshin
Singh, Prithvi
Zolghadri, Samaneh
Stanek, Agata
Dohare, Ravins
author_facet Bagherabadi, Arash
Hooshmand, Amirreza
Shekari, Nooshin
Singh, Prithvi
Zolghadri, Samaneh
Stanek, Agata
Dohare, Ravins
author_sort Bagherabadi, Arash
collection PubMed
description Prostate cancer (PCa) is a life-threatening heterogeneous malignancy of the urinary tract. Due to the incidence of prostate cancer and the crucial need to elucidate its molecular mechanisms, we searched for possible prognosis impactful genes in PCa using bioinformatics analysis. A script in R language was used for the identification of Differentially Expressed Genes (DEGs) from the GSE69223 dataset. The gene ontology (GO) of the DEGs and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. A protein–protein interaction (PPI) network was constructed using the STRING online database to identify hub genes. GEPIA and UALCAN databases were utilized for survival analysis and expression validation, and 990 DEGs (316 upregulated and 674 downregulated) were identified. The GO analysis was enriched mainly in the “collagen-containing extracellular matrix”, and the KEGG pathway analysis was enriched mainly in “focal adhesion”. The downregulation of neurotrophic receptor tyrosine kinase 1 (NTRK1) was associated with a poor prognosis of PCa and had a significant positive correlation with infiltrating levels of immune cells. We acquired a collection of pathways related to primary PCa, and our findings invite the further exploration of NTRK1 as a biomarker for early diagnosis and prognosis, and as a future potential molecular therapeutic target for PCa.
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spelling pubmed-91404382022-05-28 Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis Bagherabadi, Arash Hooshmand, Amirreza Shekari, Nooshin Singh, Prithvi Zolghadri, Samaneh Stanek, Agata Dohare, Ravins Genes (Basel) Article Prostate cancer (PCa) is a life-threatening heterogeneous malignancy of the urinary tract. Due to the incidence of prostate cancer and the crucial need to elucidate its molecular mechanisms, we searched for possible prognosis impactful genes in PCa using bioinformatics analysis. A script in R language was used for the identification of Differentially Expressed Genes (DEGs) from the GSE69223 dataset. The gene ontology (GO) of the DEGs and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. A protein–protein interaction (PPI) network was constructed using the STRING online database to identify hub genes. GEPIA and UALCAN databases were utilized for survival analysis and expression validation, and 990 DEGs (316 upregulated and 674 downregulated) were identified. The GO analysis was enriched mainly in the “collagen-containing extracellular matrix”, and the KEGG pathway analysis was enriched mainly in “focal adhesion”. The downregulation of neurotrophic receptor tyrosine kinase 1 (NTRK1) was associated with a poor prognosis of PCa and had a significant positive correlation with infiltrating levels of immune cells. We acquired a collection of pathways related to primary PCa, and our findings invite the further exploration of NTRK1 as a biomarker for early diagnosis and prognosis, and as a future potential molecular therapeutic target for PCa. MDPI 2022-05-08 /pmc/articles/PMC9140438/ /pubmed/35627227 http://dx.doi.org/10.3390/genes13050840 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bagherabadi, Arash
Hooshmand, Amirreza
Shekari, Nooshin
Singh, Prithvi
Zolghadri, Samaneh
Stanek, Agata
Dohare, Ravins
Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis
title Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis
title_full Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis
title_fullStr Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis
title_full_unstemmed Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis
title_short Correlation of NTRK1 Downregulation with Low Levels of Tumor-Infiltrating Immune Cells and Poor Prognosis of Prostate Cancer Revealed by Gene Network Analysis
title_sort correlation of ntrk1 downregulation with low levels of tumor-infiltrating immune cells and poor prognosis of prostate cancer revealed by gene network analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140438/
https://www.ncbi.nlm.nih.gov/pubmed/35627227
http://dx.doi.org/10.3390/genes13050840
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