首页> 外文期刊>Tumour biology : >A five-variable signature predicts radioresistance and prognosis in nasopharyngeal carcinoma patients receiving radical radiotherapy
【24h】

A five-variable signature predicts radioresistance and prognosis in nasopharyngeal carcinoma patients receiving radical radiotherapy

机译:五变量签名预测接受根治性放疗的鼻咽癌患者的放射抵抗和预后

获取原文
获取原文并翻译 | 示例
           

摘要

Radioresistance poses a major challenge in nasopharyngeal carcinoma (NPC) treatment. Clinical tumor-node-metastasis (TNM) staging has limited accuracy in predicting NPC radioresponse and determining its therapeutic regimens. To construct a risk score model for predicting NPC radioresistance, immunohistochemistry was used to assess the expression of four proteins (14-3-3 sigma, Maspin, RKIP, and GRP78) in 149 NPC samples with different radiosensitivity. Sequentially, a logistic regression analysis was performed to identify independent predictors of NPC radioresistance and establish a risk score model. As a result, a risk score model, Z = -3.189 -aEuro parts per thousand 1.478 (14-3-3 sigma) -aEuro parts per thousand 1.082 (Maspin) -aEuro parts per thousand 1.666 (RKIP) + 2.499 (GRP78) + 2.597 (TNM stage), was constructed, and a patient's risk score was estimated by the formula: e (Z)/(e (Z) + 1) x 100, where "e" is the base of natural logarithm. High-risk score was closely associated with NPC radioresistance, and was observed more frequently in the radioresistant patients than that in the radiosensitive patients. The sensitivity, specificity, and accuracy of the risk score model for predicting NPC radioresistance was 88.00, 86.48, and 87.25 %, respectively, which was clearly superior to each individual protein and TNM stage. Furthermore, Kaplan-Meier survival analysis showed that high-risk score correlated with the markedly reduced overall survival (OS) and disease-free survival (DFS) of the patients, and Cox regression analysis showed that the risk score model was an independent predictor for OS and DFS. This study constructs a risk score model for predicting NPC radioresistance and patient survival, and it may serve as a complement to current radioresistance risk stratification approaches.
机译:放射抵抗在鼻咽癌(NPC)治疗中提出了重大挑战。临床肿瘤淋巴结转移(TNM)分期在预测NPC放射反应和确定其治疗方案方面的准确性有限。为了构建预测NPC放射抗性的风险评分模型,采用免疫组织化学方法评估了149种具有不同放射敏感性的NPC样品中四种蛋白质(14-3-3 sigma,Maspin,RKIP和GRP78)的表达。依序进行逻辑回归分析,以识别NPC放射抵抗的独立预测因子并建立风险评分模型。结果,风险分数模型Z = -3.189-欧元千分之一1.478(14-3-3 sigma)-欧元千分之一1.082(Maspin)-欧元千分之一1.666(RKIP)+ 2.499(GRP78)构建+ 2.597(TNM阶段),并通过以下公式估算患者的风险评分:e(Z)/(e(Z)+1)x 100,其中“ e”是自然对数的底数。高危评分与NPC放射抵抗密切相关,并且在放射抵抗患者中比在放射敏感性患者中观察到的频率更高。风险评分模型预测NPC放射抵抗的敏感性,特异性和准确性分别为88.00%,86.48%和87.25%,明显优于各个蛋白质和TNM分期。此外,Kaplan-Meier生存分析表明,高风险评分与患者的总生存期(OS)和无病生存期(DFS)显着降低有关,Cox回归分析表明,风险评分模型是患者的独立预测指标OS和DFS。这项研究构建了预测NPC放射抵抗和患者生存的风险评分模型,并且可以作为当前放射抵抗风险分层方法的补充。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号