Liu Jingchun, Zhang Xiaoyi, Wang Haoyu, Zuo Xiaohu, Hong Li
Department of Obstetrics and Gynecology, Renmin Hospital of Wuhan University, Wuhan 430060, China.
J Pers Med. 2023 Apr 29;13(5):776. doi: 10.3390/jpm13050776.
Purine metabolism is an important branch of metabolic reprogramming and has received increasing attention in cancer research. Ovarian cancer is an extremely dangerous gynecologic malignancy for which there are no adequate tools to predict prognostic risk. Here, we identified a prognostic signature consisting of nine genes related to purine metabolism, including ACSM1, CACNA1C, EPHA4, TPM3, PDIA4, JUNB, EXOSC4, TRPM2, and CXCL9. The risk groups defined by the signature are able to distinguish the prognostic risk and the immune landscape of patients. In particular, the risk scores offer promising personalized drug options. By combining risk scores with clinical characteristics, we have created a more detailed composite nomogram that allows for a more complete and individualized prediction of prognosis. In addition, we demonstrated metabolic differences between platinum-resistant and platinum-sensitive ovarian cancer cells. In summary, we have performed the first comprehensive analysis of genes related to purine metabolism in ovarian cancer patients and created a feasible prognostic signature that will aid in risk prediction and support personalized medicine.
嘌呤代谢是代谢重编程的一个重要分支，在癌症研究中受到越来越多的关注。卵巢癌是一种极其危险的妇科恶性肿瘤，目前尚无足够的工具来预测预后风险。在此，我们鉴定出一个由九个与嘌呤代谢相关的基因组成的预后特征，包括ACSM1、CACNA1C、EPHA4、TPM3、PDIA4、JUNB、EXOSC4、TRPM2和CXCL9。由该特征定义的风险组能够区分患者的预后风险和免疫格局。特别是，风险评分提供了有前景的个性化药物选择。通过将风险评分与临床特征相结合，我们创建了一个更详细的综合列线图，能够对预后进行更全面和个性化的预测。此外，我们展示了铂耐药和铂敏感卵巢癌细胞之间的代谢差异。总之，我们首次对卵巢癌患者中与嘌呤代谢相关的基因进行了全面分析，并创建了一个可行的预后特征，这将有助于风险预测并支持个性化医疗。
