Wang Hai, Chen Yuxiao, Zhao Wei, Liu Haolin, Tu Hongtao, Xia Zhongyou, Wang Rui, Tang Jinze, Zhu Chuang, Li Rui, Liu Xiaodong, Gu Peng
Department of Urology, The First Affiliated Hospital of Kunming Medical University, Kunming 650032, China.
The First Affiliated Hospital of Kunming Medical University, Yunnan Province Clinical Research Center for Chronic Kidney Disease, Kunming 650032, China.
J Clin Med. 2023 Mar 14;12(6):2243. doi: 10.3390/jcm12062243.
Glutamine has been recognized as an important amino acid that provide a variety of intermediate products to fuel biosynthesis. Glutamine metabolism participates in the progression of the tumor via various mechanisms. However, glutamine-metabolism-associated signatures and its significance in prostate cancer are still unclear. In this current study, we identified five genes associated with glutamine metabolism by univariate and Lasso regression analysis and constructed a model to predict the biochemical recurrence free survival (BCRFS) of PCa. Further validation of the prognostic risk model demonstrated a good efficacy in predicting the BCRFS in PCa patients. Interestingly, based on the CIBERSORTx, ssGSEA and ESTIMATE algorithms predictions, we noticed a distinct immune cell infiltration and immune pathway pattern in the prediction of the two risk groups stratified by the risk model. Drug sensitivity prediction revealed that patients in the high-risk group were more suitable for chemotherapy. Last but not least, glutamine deprivation significantly inhibited cell growth in GLUL or ASNS knock down prostate cancer cell lines. Therefore, we proposed a novel prognostic model by using glutamine metabolism genes for PCa patients and identified potential mechanism of PCa progression through glutamine-related tumor microenvironment remodeling.
谷氨酰胺已被公认为一种重要的氨基酸,它能提供多种中间产物以促进生物合成。谷氨酰胺代谢通过多种机制参与肿瘤的进展。然而,谷氨酰胺代谢相关特征及其在前列腺癌中的意义仍不明确。在本研究中,我们通过单变量和Lasso回归分析鉴定了五个与谷氨酰胺代谢相关的基因,并构建了一个模型来预测前列腺癌的无生化复发生存期(BCRFS)。对预后风险模型的进一步验证表明,该模型在预测前列腺癌患者的BCRFS方面具有良好的效果。有趣的是,基于CIBERSORTx、ssGSEA和ESTIMATE算法预测,我们注意到在由风险模型分层的两个风险组的预测中,免疫细胞浸润和免疫途径模式存在明显差异。药物敏感性预测显示,高危组患者更适合化疗。最后但同样重要的是,谷氨酰胺剥夺显著抑制了GLUL或ASNS敲低的前列腺癌细胞系中的细胞生长。因此,我们提出了一种利用谷氨酰胺代谢基因的前列腺癌患者预后新模型,并通过谷氨酰胺相关的肿瘤微环境重塑确定了前列腺癌进展的潜在机制。