Volume 8, Issue 1 (Spring & Summer 2024)
J Res Urol 2024, 8(1): 36-44 |
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Taherkhani A, Mohseni M. Identification of Signaling Pathways and Prognostic Biomarkers in Prostate Cancer using Bioinformatics Approaches. J Res Urol 2024; 8 (1) :36-44
URL: http://urology.umsha.ac.ir/article-1-164-en.html
URL: http://urology.umsha.ac.ir/article-1-164-en.html
1- Research Center for Molecular Medicine, Institute of Cancer, Avicenna Health Research Institute, Hamadan University of Medical Sciences, Hamadan, Iran
2- Urology and Nephrology Research Center, Avicenna Institute of Clinical Sciences, Avicenna Health Research Institute, Hamadan University of Medical Sciences, Hamadan, Iran ,mao.mohseni@gmail.com
2- Urology and Nephrology Research Center, Avicenna Institute of Clinical Sciences, Avicenna Health Research Institute, Hamadan University of Medical Sciences, Hamadan, Iran ,
Abstract: (631 Views)
Background and Objective: Prostate cancer is one of the most common cancers in males, with 1,466,680 new cases reported in 2022, making it the fourth most prevalent cancer. This disease is observed to have a higher incidence and mortality rate among African-American males, compared to other races. This study aimed to investigate the differential gene expression and identify prognostic biomarkers in prostate cancer. The main objectives of this research included the identification of differential genes in prostate cancer, determining the biological processes and signaling pathways associated with tumorigenesis, and demonstrating genes related to poor prognosis in patients with this disease.
Materials and Methods: This study used bioinformatics to analyze the RNA sequencing dataset with the identifier code GSE104131. High-grade prostate tumor samples and adjacent healthy tissue samples were collected from 16 patients (8 African-American men and 8 European-American men). Differential genes were identified using the GEO2R tool. A protein-protein interaction network was also established to identify hub genes and examine their roles in patient prognosis.
Results: Results indicated that 534 differential genes were identified, 320 and 214 of which were upregulated and downregulated, respectively. Analyses revealed that increased expressions of GATA6 and ABCC4 genes are associated with poor prognosis in patients with prostate adenocarcinoma. Furthermore, signaling pathways, such as "biological oxidation" and "insulin secretion" were significantly involved in the progression of prostate cancer.
Conclusion: The simultaneous increase in the expressions of GATA6 and ABCC4 may serve as key biomarkers for the prediction of adverse outcomes in patients. Targeting these genes and related pathways could provide new therapeutic strategies for the management of prostate cancer.
Materials and Methods: This study used bioinformatics to analyze the RNA sequencing dataset with the identifier code GSE104131. High-grade prostate tumor samples and adjacent healthy tissue samples were collected from 16 patients (8 African-American men and 8 European-American men). Differential genes were identified using the GEO2R tool. A protein-protein interaction network was also established to identify hub genes and examine their roles in patient prognosis.
Results: Results indicated that 534 differential genes were identified, 320 and 214 of which were upregulated and downregulated, respectively. Analyses revealed that increased expressions of GATA6 and ABCC4 genes are associated with poor prognosis in patients with prostate adenocarcinoma. Furthermore, signaling pathways, such as "biological oxidation" and "insulin secretion" were significantly involved in the progression of prostate cancer.
Conclusion: The simultaneous increase in the expressions of GATA6 and ABCC4 may serve as key biomarkers for the prediction of adverse outcomes in patients. Targeting these genes and related pathways could provide new therapeutic strategies for the management of prostate cancer.
Type of Study: Research |
Subject:
Urologic oncology
Received: 2024/12/6 | Accepted: 2024/12/13 | Published: 2024/08/31
Received: 2024/12/6 | Accepted: 2024/12/13 | Published: 2024/08/31
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