Zhang Yunxuan, Liu Yuenan, Chen Kailei, Miao Qi, Cao Qi, Zhang Xiaoping
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Institute of Urology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Mol Biotechnol. 2025 Jan 20. doi: 10.1007/s12033-024-01353-w.
Opioids are the primary regimens for perioperative analgesia with controversial effects on oncological survival. The underlying mechanism remains unexplored. This study developed survival-related gene co-expression networks based on RNA-seq and clinical characteristics from TCGA cohort. Two survival-related networks were identified, and drug-induced transcriptional profiles were predicted. Immune cell infiltration algorithm, least absolute shrinkage and selection operator (LASSO) regression, and cox proportional models were executed to explore the correlation between opioid-related drugs and prostate cancer patient prognosis. The opioid receptor agonists, represented by tramadol, were evidenced for anti-survival effects on prostate cancer by facilitating the DNA replication and cell cycle, and immune cell infiltration. Conversely, opioid receptor antagonists showed pro-survival effects. A novel prognostic model containing CNIH2, MCCC1, and Gleason scores was established and validated in two independent cohorts. This study revealed opioids' effect on prostate cancer progression, and provided a novel model to predict these regulations in clinical outcomes.
阿片类药物是围手术期镇痛的主要方案，但其对肿瘤生存的影响存在争议。其潜在机制仍未得到探索。本研究基于RNA测序和来自TCGA队列的临床特征，构建了与生存相关的基因共表达网络。识别出两个与生存相关的网络，并预测了药物诱导的转录谱。运用免疫细胞浸润算法、最小绝对收缩和选择算子（LASSO）回归以及Cox比例模型，以探讨阿片类相关药物与前列腺癌患者预后之间的相关性。以曲马多为代表的阿片受体激动剂，通过促进DNA复制、细胞周期进程和免疫细胞浸润，对前列腺癌具有抗生存作用。相反，阿片受体拮抗剂则显示出促生存作用。建立了一个包含CNIH2、MCCC1和Gleason评分的新型预后模型，并在两个独立队列中进行了验证。本研究揭示了阿片类药物对前列腺癌进展的影响，并提供了一个预测这些调节对临床结局影响的新模型。
