Man Tsz-Kwong, Chintagumpala Murali, Visvanathan Jaya, Shen Jianhe, Perlaky Laszlo, Hicks John, Johnson Mark, Davino Nelson, Murray Jeffrey, Helman Lee, Meyer William, Triche Timothy, Wong Kwong-Kwok, Lau Ching C
Department of Pediatrics, Texas Children's Cancer Center, Houston, Texas, USA.
Cancer Res. 2005 Sep 15;65(18):8142-50. doi: 10.1158/0008-5472.CAN-05-0985.
Osteosarcoma is the most common malignant bone tumor in children. After initial diagnosis is made with a biopsy, treatment consists of preoperative chemotherapy followed by definitive surgery and postoperative chemotherapy. The degree of tumor necrosis in response to preoperative chemotherapy is a reliable prognostic factor and is used to guide the choice of postoperative chemotherapy. Patients with tumors, which reveal > or = 90% necrosis (good responders), have a much better prognosis than those with < 90% necrosis (poor responders). Despite previous attempts to improve the outcome of poor responders by modifying the postoperative chemotherapy, their prognosis remains poor. Therefore, there is a need to predict at the time of diagnosis patients' response to preoperative chemotherapy. This will provide the basis for developing potentially effective therapy that can be given at the outset for those who are likely to have a poor response. Here, we report the analysis of 34 pediatric osteosarcoma samples by expression profiling. Using parametric two-sample t test, we identified 45 genes that discriminate between good and poor responders (P < 0.005) in 20 definitive surgery samples. A support vector machine classifier was built using these predictor genes and was tested for its ability to classify initial biopsy samples. Five of six initial biopsy samples that had corresponding definitive surgery samples in the training set were classified correctly (83%; confidence interval, 36%, 100%). When this classifier was used to predict eight independent initial biopsy samples, there was 100% accuracy (confidence interval, 63%, 100%). Many of the predictor genes are implicated in bone development, drug resistance, and tumorigenesis.
骨肉瘤是儿童中最常见的恶性骨肿瘤。在通过活检做出初步诊断后，治疗包括术前化疗，随后是确定性手术和术后化疗。术前化疗后肿瘤坏死的程度是一个可靠的预后因素，用于指导术后化疗的选择。肿瘤坏死率≥90%（反应良好者）的患者预后比坏死率<90%（反应不良者）的患者好得多。尽管此前曾试图通过调整术后化疗来改善反应不良者的预后，但其预后仍然很差。因此，有必要在诊断时预测患者对术前化疗的反应。这将为开发潜在有效的治疗方法提供依据，对于那些可能反应不良的患者可以从一开始就给予这种治疗。在此，我们报告了通过表达谱分析34例儿童骨肉瘤样本的情况。使用参数双样本t检验，我们在20例确定性手术样本中确定了45个能区分反应良好者和反应不良者的基因（P<0.005）。利用这些预测基因构建了一个支持向量机分类器，并测试了其对初始活检样本进行分类的能力。训练集中有相应确定性手术样本的6例初始活检样本中有5例被正确分类（83%；置信区间为36%，100%）。当使用该分类器预测8个独立的初始活检样本时，准确率为100%（置信区间为63%，100%）。许多预测基因与骨骼发育、耐药性和肿瘤发生有关。
