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转录组图谱揭示了一种12指标代谢预测模型以及肌醇加氧酶在前列腺癌进展中的新作用。

Transcriptome Profiles Reveal a 12-Signature Metabolic Prediction Model and a Novel Role of Myo-Inositol Oxygenase in the Progression of Prostate Cancer.

作者信息

Liu Wangrui, Xiang Jianfeng, Wu Xinrui, Wei Shiyin, Huang Haineng, Xiao Yu, Zhai Bo, Wang Tao

机构信息

Department of Interventional Oncology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Department of Clinical Medicine, Medical School of Nantong University, Nantong, China.

出版信息

Front Oncol. 2022 May 20;12:899861. doi: 10.3389/fonc.2022.899861. eCollection 2022.

DOI:10.3389/fonc.2022.899861
PMID:35669435
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9163567/
Abstract

Prostate adenocarcinoma (PRAD) is an extremely common type of cancer in the urinary system. Here, we aimed to establish a metabolic signature to identify novel targets in a predictive model of PRAD patients. A total of 133 metabolic differentially expressed genes (MDEGs) were identified with significant prognostic value. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a 12-mRNA signature model, a metabolic prediction model (MPM), in 491 PRAD patients. The risk score of the MPM significantly predicted the progression of PRAD patients (p < 0.001, area under the curve (AUC) = 0.745). Furthermore, myo-inositol oxygenase (MIOX), the most prominently upregulated metabolic enzyme and hub gene in the protein-protein interaction network of the MPM, showed significant prognostic implications. Next, MIOX expression in normal prostate tissues was lower than in PRAD tissues, and high MIOX expression was significantly associated with disease progression (p = 0.005, HR = 2.274) in 81 PRAD patients undergoing first-line androgen receptor signaling inhibitor treatment from the Renji cohort. Additionally, MIOX was significantly involved in the abnormal immune infiltration of the tumor microenvironment and associated with the DNA damage repair process of PRAD. In conclusion, this study provides the first opportunity to comprehensively elucidate the landscape of prognostic MDEGs, establish novel prognostic modeling of MPM using large-scale PRAD transcriptomic data, and identify MIOX as a potential prognostic target in PRAD patients from multiple cohorts. These findings help manage risk assessment and provide valuable insights into treatment strategies for PRAD.

摘要

前列腺腺癌(PRAD)是泌尿系统中极为常见的一种癌症。在此,我们旨在建立一种代谢特征,以在PRAD患者的预测模型中识别新的靶点。共鉴定出133个具有显著预后价值的代谢差异表达基因(MDEG)。使用最小绝对收缩和选择算子(LASSO)回归分析,在491例PRAD患者中构建了一个包含12个mRNA的特征模型,即代谢预测模型(MPM)。MPM的风险评分显著预测了PRAD患者的病情进展(p < 0.001,曲线下面积(AUC) = 0.745)。此外,肌醇加氧酶(MIOX)是MPM蛋白质-蛋白质相互作用网络中上调最显著的代谢酶和枢纽基因,显示出显著的预后意义。接下来,正常前列腺组织中的MIOX表达低于PRAD组织,在来自仁济队列的81例接受一线雄激素受体信号抑制剂治疗的PRAD患者中,高MIOX表达与疾病进展显著相关(p = 0.005,HR = 2.274)。此外,MIOX显著参与肿瘤微环境的异常免疫浸润,并与PRAD的DNA损伤修复过程相关。总之,本研究首次全面阐明了预后MDEG的情况,利用大规模PRAD转录组数据建立了MPM的新预后模型,并在多个队列中确定MIOX为PRAD患者潜在的预后靶点。这些发现有助于进行风险评估,并为PRAD的治疗策略提供有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/470400113f3b/fonc-12-899861-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/f390e146702b/fonc-12-899861-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/7bdc881891cc/fonc-12-899861-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/52e7b3d6f484/fonc-12-899861-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/1c4665305e72/fonc-12-899861-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/48cf888247ba/fonc-12-899861-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/470400113f3b/fonc-12-899861-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/f390e146702b/fonc-12-899861-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/7bdc881891cc/fonc-12-899861-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/52e7b3d6f484/fonc-12-899861-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/1c4665305e72/fonc-12-899861-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/48cf888247ba/fonc-12-899861-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8e4/9163567/470400113f3b/fonc-12-899861-g006.jpg

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