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Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer

BACKGROUND: Prostate cancer (PCa) is a malignant tumor in males, with a majority of the cases advancing to metastatic castration resistance. Metastasis is the leading cause of mortality in PCa. The traditional early detection and prediction approaches cannot differentiate between the different stage...

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Autores principales: Wang, Wenxuan, Wu, Qinghui, Mohyeddin, Ali, Liu, Yousheng, Liu, Zhitao, Ge, Jianqiang, Zhang, Bao, Shi, Gan, Wang, Weifu, Wu, Dinglan, Wang, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556187/
https://www.ncbi.nlm.nih.gov/pubmed/36245843
http://dx.doi.org/10.1155/2022/5500416
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author Wang, Wenxuan
Wu, Qinghui
Mohyeddin, Ali
Liu, Yousheng
Liu, Zhitao
Ge, Jianqiang
Zhang, Bao
Shi, Gan
Wang, Weifu
Wu, Dinglan
Wang, Fei
author_facet Wang, Wenxuan
Wu, Qinghui
Mohyeddin, Ali
Liu, Yousheng
Liu, Zhitao
Ge, Jianqiang
Zhang, Bao
Shi, Gan
Wang, Weifu
Wu, Dinglan
Wang, Fei
author_sort Wang, Wenxuan
collection PubMed
description BACKGROUND: Prostate cancer (PCa) is a malignant tumor in males, with a majority of the cases advancing to metastatic castration resistance. Metastasis is the leading cause of mortality in PCa. The traditional early detection and prediction approaches cannot differentiate between the different stages of PCa. Therefore, new biomarkers are necessary for early detection and clear differentiation of PCa stages to provide precise therapeutic intervention. METHODS: The objective of the study was to find significant differences in genes and combine the three GEO datasets with TCGA-PRAD datasets (DEG). Weighted gene coexpression network analysis (WGCNA) determined the gene set and PCa clinical feature correlation module utilizing the TGGA-PRAD clinical feature data. The correlation module genes were rescreened using the biological information analysis tools, with the three hub genes (TOP2A, NCAPG, and BUB1B) for proper verification. Finally, internal (TCGA) and external (GSE32571, GSE70770) validation datasets were used to validate and predict the value of last hub genes. RESULTS: The hub gene was abnormally upregulated in PCa samples during verification. The expression of each gene was favorably connected with the Gleason score and TN tumor grade in clinical samples but negatively correlated with the overall survival rate. The expression of these genes was linked to CD8 naive cells and macrophages, among other cells. Antitumor immune cells like NK and NKT were favorably and adversely correlated with infiltrating cells, respectively. Simultaneously, the GSCV and GSEA indicated that the hub gene is connected with cell proliferation, death, and androgen receptor, among other signaling pathways. Therefore, these genes could influence the incidence and progression of PCa by participating in or modulating various signaling pathways. Furthermore, using the online tool of CMap, we examined the individual medications for Hughes and determined that tipifarnib could be useful for the clinical therapy of PCa. CONCLUSION: TOP2A, NCAPG, and BUB1B are important genes intimately linked to the clinical prognosis of PCa and can be employed as reliable biomarkers for early diagnosis and prognosis. Moreover, these genes can provide a theoretical basis for precision differentiation and treatment of PCa.
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spelling pubmed-95561872022-10-13 Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer Wang, Wenxuan Wu, Qinghui Mohyeddin, Ali Liu, Yousheng Liu, Zhitao Ge, Jianqiang Zhang, Bao Shi, Gan Wang, Weifu Wu, Dinglan Wang, Fei Comput Math Methods Med Research Article BACKGROUND: Prostate cancer (PCa) is a malignant tumor in males, with a majority of the cases advancing to metastatic castration resistance. Metastasis is the leading cause of mortality in PCa. The traditional early detection and prediction approaches cannot differentiate between the different stages of PCa. Therefore, new biomarkers are necessary for early detection and clear differentiation of PCa stages to provide precise therapeutic intervention. METHODS: The objective of the study was to find significant differences in genes and combine the three GEO datasets with TCGA-PRAD datasets (DEG). Weighted gene coexpression network analysis (WGCNA) determined the gene set and PCa clinical feature correlation module utilizing the TGGA-PRAD clinical feature data. The correlation module genes were rescreened using the biological information analysis tools, with the three hub genes (TOP2A, NCAPG, and BUB1B) for proper verification. Finally, internal (TCGA) and external (GSE32571, GSE70770) validation datasets were used to validate and predict the value of last hub genes. RESULTS: The hub gene was abnormally upregulated in PCa samples during verification. The expression of each gene was favorably connected with the Gleason score and TN tumor grade in clinical samples but negatively correlated with the overall survival rate. The expression of these genes was linked to CD8 naive cells and macrophages, among other cells. Antitumor immune cells like NK and NKT were favorably and adversely correlated with infiltrating cells, respectively. Simultaneously, the GSCV and GSEA indicated that the hub gene is connected with cell proliferation, death, and androgen receptor, among other signaling pathways. Therefore, these genes could influence the incidence and progression of PCa by participating in or modulating various signaling pathways. Furthermore, using the online tool of CMap, we examined the individual medications for Hughes and determined that tipifarnib could be useful for the clinical therapy of PCa. CONCLUSION: TOP2A, NCAPG, and BUB1B are important genes intimately linked to the clinical prognosis of PCa and can be employed as reliable biomarkers for early diagnosis and prognosis. Moreover, these genes can provide a theoretical basis for precision differentiation and treatment of PCa. Hindawi 2022-10-05 /pmc/articles/PMC9556187/ /pubmed/36245843 http://dx.doi.org/10.1155/2022/5500416 Text en Copyright © 2022 Wenxuan Wang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Wenxuan
Wu, Qinghui
Mohyeddin, Ali
Liu, Yousheng
Liu, Zhitao
Ge, Jianqiang
Zhang, Bao
Shi, Gan
Wang, Weifu
Wu, Dinglan
Wang, Fei
Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer
title Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer
title_full Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer
title_fullStr Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer
title_full_unstemmed Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer
title_short Identification of the Key Genes Involved in the Tumorigenesis and Prognosis of Prostate Cancer
title_sort identification of the key genes involved in the tumorigenesis and prognosis of prostate cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9556187/
https://www.ncbi.nlm.nih.gov/pubmed/36245843
http://dx.doi.org/10.1155/2022/5500416
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