Cargando…
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...
Autores principales: | , , , , , , , , , , |
---|---|
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 |
_version_ | 1784807017860300800 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9556187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT wangwenxuan identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT wuqinghui identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT mohyeddinali identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT liuyousheng identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT liuzhitao identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT gejianqiang identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT zhangbao identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT shigan identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT wangweifu identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT wudinglan identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer AT wangfei identificationofthekeygenesinvolvedinthetumorigenesisandprognosisofprostatecancer |