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通过生物信息学分析确定的具有SPOP突变的前列腺癌关键信号通路。

Key pathways in prostate cancer with SPOP mutation identified by bioinformatic analysis.

作者信息

Ding Guanxiong, Sun Jianliang, Jiang Lianhua, Gao Peng, Zhou Qidong, Wang Jianqing, Tong Shijun

机构信息

Department of Urology, Huashan Hospital, Fudan University, 12 Central Urumqi Rd, Shanghai 200040, People's Republic of China.

Department of Urology, The Affiliated Suzhou Hospital of Nanjing Medical University, 26 Daoqian Rd, Suzhou, Jiangsu 215000, People's Republic of China.

出版信息

Open Med (Wars). 2020 Oct 9;15(1):1039-1047. doi: 10.1515/med-2020-0237. eCollection 2020.

DOI:10.1515/med-2020-0237
PMID:33336059
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7718645/
Abstract

Prostate cancer (PCa) is a leading adult malignant tumor. Recent research has shown that speckle-type BTB/POZ protein (SPOP) mutant is the top frequently mutated gene in PCa, which makes it an important biomarker. In this paper, we aimed at identifying critical genes and pathways related to SPOP mutation in PCa. Recent The Cancer Genome Atlas data showed that 12% of patients with PCa were SPOP mutant. There were 1,570 differentially expressed genes, and online enrichment analysis showed that these genes were mainly enriched in metabolism, pathways in cancer and reactive oxygen species. INS, GNG13, IL6, HTR5A, SAA1, PPY, CXCR5, CXCL13, CD19 and CCL20 were identified as hub genes. The lower SPOP expression level was associated with poor prognosis. In all, our findings showed that various pathways and genes could play critical roles in SPOP mutation in PCa, providing potential options for individualized treatment.

摘要

前列腺癌(PCa)是一种主要的成人恶性肿瘤。最近的研究表明,斑点型BTB/POZ蛋白(SPOP)突变是PCa中最常发生突变的基因,这使其成为一种重要的生物标志物。在本文中,我们旨在鉴定与PCa中SPOP突变相关的关键基因和通路。最新的癌症基因组图谱数据显示,12%的PCa患者为SPOP突变型。有1570个差异表达基因,在线富集分析表明这些基因主要富集在代谢、癌症通路和活性氧中。INS、GNG13、IL6、HTR5A、SAA1、PPY、CXCR5、CXCL13、CD19和CCL20被鉴定为枢纽基因。SPOP表达水平较低与预后不良相关。总之,我们的研究结果表明,多种通路和基因可能在PCa的SPOP突变中起关键作用,为个体化治疗提供了潜在选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/1d7f6f8d32ec/j_med-2020-0237-fig006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/27f7b7d87149/j_med-2020-0237-fig001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/811a0e896c7a/j_med-2020-0237-fig002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/337820fb4012/j_med-2020-0237-fig003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/fd744ba183f8/j_med-2020-0237-fig004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/8fb3ab544cb4/j_med-2020-0237-fig005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/1d7f6f8d32ec/j_med-2020-0237-fig006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/27f7b7d87149/j_med-2020-0237-fig001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/811a0e896c7a/j_med-2020-0237-fig002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/337820fb4012/j_med-2020-0237-fig003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/fd744ba183f8/j_med-2020-0237-fig004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/8fb3ab544cb4/j_med-2020-0237-fig005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a65f/7718645/1d7f6f8d32ec/j_med-2020-0237-fig006.jpg

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本文引用的文献

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Exosome proteomic analyses identify inflammatory phenotype and novel biomarkers in African American prostate cancer patients.外泌体蛋白质组分析鉴定非裔美国前列腺癌患者的炎症表型和新型生物标志物。
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Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.
利用人工智能算法分析浆细胞亚型,预测前列腺癌的生化复发、免疫逃逸潜能和免疫治疗反应。
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