检验医学 ›› 2023, Vol. 38 ›› Issue (9): 818-824.DOI: 10.3969/j.issn.1673-8640.2023.09.003

• 肿瘤标志物基础与临床专题 • 上一篇    下一篇

前列腺癌进展相关转录因子研究

孙传玉1, 赵晓君2(), 葛圣阳1, 张扬3   

  1. 1.复旦大学附属华山医院,上海 200040
    2.上海市临床检验中心,上海 200126
    3.复旦大学生物医学研究院,上海 200032
  • 收稿日期:2022-05-24 修回日期:2022-12-04 出版日期:2023-09-30 发布日期:2023-11-29
  • 通讯作者: 赵晓君,E-mail:zhaoxiaojun@sccl.org.cn
  • 作者简介:孙传玉,男,1984年生,博士,副主任医师,主要从事前列腺癌相关生物标记物筛选研究。

Transcription factors in prostate cancer progression

SUN Chuanyu1, ZHAO Xiaojun2(), GE Shengyang1, ZHANG Yang3   

  1. 1. Huashan Hospital,Fudan University,Shanghai 200040,China
    2. Shanghai Center for Clinical Laboratory,Shanghai 200126,China
    3. Institutes of Biomedical Sciences,Fudan University,Shanghai 200032,China
  • Received:2022-05-24 Revised:2022-12-04 Online:2023-09-30 Published:2023-11-29

摘要:

目的 对相关研究发现的46个前列腺癌差异表达蛋白的上游转录调控机制进行分析和探讨。方法 采用GeneGo MetaCore软件和IPA软件对46个差异蛋白进行生物信息学分析,明确这些差异蛋白的转录因子调控网络。采用GEPIA2数据库分析鉴定出的转录因子的表达量及其对前列腺癌患者生存情况的影响。结果 共鉴定出20个转录调控网络。按差异表达蛋白的富集度进行排序,筛选出居前6位的转录调控网络,分别由特化蛋白1(SP1)、p53、阴阳1(YY1)、雄激素受体(AR)、c-Myc和Slug 6个转录因子调控。Kaplan-Meier生存曲线分析结果显示,高表达p53的前列腺癌患者无病生存期和总生存期均长于低表达p53的患者(P值分别为0.047、0.019),低表达AR的前列腺癌患者无病生存期长于高表达AR的患者(P=0.023),其余4个转录因子对前列腺癌患者预后无影响(P>0.05)。IPA软件分析结果显示,SP1、p53、YY1、AR和c-Myc由表没食子儿茶素没食子酸酯(EGCG)、蛋白激酶B(AKT)1、成纤维细胞生长因子2(FGF2)、β-雌二醇调控。结论 通过分析46个前列腺癌差异表达蛋白的转录调控网络,发现6个与前列腺癌相关的转录因子和4个上游调节分子,可为前列腺癌早期筛查和预后评估提供新的靶标。

关键词: 蛋白质组学, 转录因子, 转录调控, 前列腺癌

Abstract:

Objective To investigate the 46 differentially expressed proteins of upstream transcriptional regulation mechanism in prostate cancer. Methods GeneGo MetaCore software and IPA software were used to conduct bioinformatics analysis on differential proteins and clarify the transcriptional regulatory network of these differential proteins. GEPIA2 database was used to analyze the expression level of identified transcription factors and their impacts on the survival of prostate cancer patients. Results Totally,20 transcriptional regulatory networks were identified. According to the enrichment of differentially expressed proteins,the top 6 networks were screened out to be regulated by 6 transcription factors,specificity protein 1(SP1),p53,Yin-Yang 1(YY1),androgen receptor(AR),c-Myc and Slug. Kaplan-Meier survival curve analysis showed that prostate cancer patients with high expression of p53 had long disease-free survival and overall survival compared to patients with low expression of p53(P=0.047 and 0.019,respectively). The disease-free survival of prostate cancer patients with low expression of AR was longer than that of patients with high expression of AR(P=0.023). The other 4 transcription factors had no impact on the prognosis of prostate cancer patients(P>0.05). IPA software analysis results showed that SP1,p53,YY1,AR and c-Myc were regulated by epigallocatechin gallate(EGCG),protein kinase B(AKT)1,fibroblast growth factor 2(FGF2) and beta-estradiol regulation. Conclusions By analyzing the transcriptional regulatory network of 46 prostate cancer differentially expressed proteins,6 transcription factors and 4 upstream regulatory molecules related to prostate cancer have been found,which can provide new targets for early screening and prognostic evaluation of prostate cancer.

Key words: Proteomics, Transcription factor, Transcription regulation, Prostate cancer

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