Rieger Kerri E, Hong Wan-Jen, Tusher Virginia Goss, Tang Jean, Tibshirani Robert, Chu Gilbert
Department of Medicine and Biochemistry, Stanford University School of Medicine, Stanford, CA 94305, USA.
Proc Natl Acad Sci U S A. 2004 Apr 27;101(17):6635-40. doi: 10.1073/pnas.0307761101. Epub 2004 Apr 19.
Toxicity from radiation therapy is a grave problem for cancer patients. We hypothesized that some cases of toxicity are associated with abnormal transcriptional responses to radiation. We used microarrays to measure responses to ionizing and UV radiation in lymphoblastoid cells derived from 14 patients with acute radiation toxicity. The analysis used heterogeneity-associated transformation of the data to account for a clinical outcome arising from more than one underlying cause. To compute the risk of toxicity for each patient, we applied nearest shrunken centroids, a method that identifies and cross-validates predictive genes. Transcriptional responses in 24 genes predicted radiation toxicity in 9 of 14 patients with no false positives among 43 controls (P = 2.2 x 10(-7)). The responses of these nine patients displayed significant heterogeneity. Of the five patients with toxicity and normal responses, two were treated with protocols that proved to be highly toxic. These results may enable physicians to predict toxicity and tailor treatment for individual patients.
放射治疗的毒性对癌症患者来说是一个严重问题。我们推测,某些毒性病例与对辐射的异常转录反应有关。我们使用微阵列来测量来自14例急性放射毒性患者的淋巴母细胞对电离辐射和紫外线辐射的反应。该分析使用了与异质性相关的数据转换,以解释由多种潜在原因引起的临床结果。为了计算每位患者的毒性风险,我们应用了最近收缩质心算法,这是一种识别和交叉验证预测基因的方法。24个基因的转录反应在14例患者中的9例中预测了放射毒性,在43例对照中无假阳性结果(P = 2.2 x 10(-7))。这9例患者的反应表现出显著的异质性。在5例有毒性但反应正常的患者中,有2例接受了被证明具有高毒性的治疗方案。这些结果可能使医生能够预测毒性并为个体患者量身定制治疗方案。