Mathematical prognostic biomarker models for treatment response and survival in epithelial ovarian cancer.
Mathematical prognostic biomarker models for treatment response and survival in epithelial ovarian cancer.
复制标题
作者：
Nikas JB;Boylan KL;Skubitz AP;Low WC
在最初的标准化疗（铂/紫杉醇）后，超过75%的晚期上皮性卵巢癌（EOC）患者复发。目前还没有准确的预后测试，在诊断/手术时，可以识别那些对化疗有反应的晚期EOC患者。利用一种新颖的数学理论，我们开发了三种预后生物标志物模型（复杂的数学函数），该模型基于手术期间和化疗开始前收集的肿瘤组织的全局基因表达分析，可以高精度地识别那些对标准化疗有反应的晚期EOC患者[长期幸存者（7年）]和那些不会这样做的患者[短期幸存者（<3年）]。我们的三种预后生物标志物模型在34名受试者中开发，并在20名未知（新的和不同的）受试者中验证。总体生物标志物模型敏感性和特异性范围为95.83% ~ 100.00%。确定的12个最重要的基因也是三个数学函数的输入变量，它们构成了三个不同的基因网络，具有以下功能：1)产生细胞骨架成分，2)细胞增殖，3)细胞能量产生。第一个基因网络与抗微管化疗药物的作用机制直接相关，如紫杉烷和埃泊霉素。这可能会对发现新的、更有效的药物治疗产生重大影响，可能会显著延长晚期EOC患者的生存期。
Following initial standard chemotherapy (platinum/taxol), more than 75% of those patients with advanced stage epithelial ovarian cancer (EOC) experience a recurrence. There are currently no accurate prognostic tests that, at the time of the diagnosis/surgery, can identify those patients with advanced stage EOC who will respond to chemotherapy. Using a novel mathematical theory, we have developed three prognostic biomarker models (complex mathematical functions) that—based on a global gene expression analysis of tumor tissue collected during surgery and prior to the commencement of chemotherapy—can identify with a high accuracy those patients with advanced stage EOC who will respond to the standard chemotherapy [long-term survivors (>7 yrs)] and those who will not do so [short-term survivors (<3 yrs)]. Our three prognostic biomarker models were developed with 34 subjects and validated with 20 unknown (new and different) subjects. Both the overall biomarker model sensitivity and specificity ranged from 95.83% to 100.00%. The 12 most significant genes identified, which are also the input variables to the three mathematical functions, constitute three distinct gene networks with the following functions: 1) production of cytoskeletal components, 2) cell proliferation, and 3) cell energy production. The first gene network is directly associated with the mechanism of action of anti-tubulin chemotherapeutic agents, such as taxanes and epothilones. This could have a significant impact in the discovery of new, more effective pharmacological treatments that may significantly extend the survival of patients with advanced stage EOC.