Coller Janet K, White Imogen A, Logan Richard M, Tuke Jonathan, Richards Alison M, Mead Kelly R, Karapetis Christos S, Bowen Joanne M
Discipline of Pharmacology, School of Medical Sciences, University of Adelaide, Level 5 Medical School North, Frome Road, Adelaide, South Australia, 5005, Australia,
Support Care Cancer. 2015 May;23(5):1233-6. doi: 10.1007/s00520-014-2481-z. Epub 2014 Oct 16.
Severe chemotherapy-induced gastrointestinal toxicity (CIGT) is common and results in treatment delays, dose reductions, and potential premature treatment discontinuation. Currently, there is no diagnostic marker to predict CIGT. Proinflammatory cytokines, produced via toll-like receptor signaling, are key mediators of this toxicity. Hence, this pilot study investigated the association between immune genetic variability and severe CIGT risk.
Genomic DNA from 34 patients (10 with severe CIGT) who had received 5-fluoruracil-based chemotherapy regimens was analyzed for variants of IL-1B, IL-2, IL-6, IL-6R, IL-10, TNF-a, TGF-b, TLR2, TLR4, MD2, MYD88, BDNF, CRP, ICE, and OPRM1. Multivariate logistic regression created a prediction model of severe CIGT risk.
There were no significant differences between patients with and without severe CIGT with regards to age, sex, type of cancer, or chemotherapy treatment regimens. The prediction model of severe CIGT risk included TLR2 and TNF-a genetic variability and cancer type (colorectal and gastric). This prediction model was both specific and sensitive, with a receiver operator characteristic area under the curve of 87.3 %.
This is the first report of immune genetic variability, together with cancer type, being predictive of severe CIGT risk. These outcomes are being validated in a larger patient population.
严重的化疗引起的胃肠道毒性（CIGT）很常见，会导致治疗延迟、剂量减少以及可能提前终止治疗。目前，尚无预测CIGT的诊断标志物。通过Toll样受体信号传导产生的促炎细胞因子是这种毒性的关键介质。因此，这项初步研究调查了免疫基因变异性与严重CIGT风险之间的关联。
对34例接受基于5-氟尿嘧啶化疗方案的患者（10例有严重CIGT）的基因组DNA进行分析，检测白细胞介素-1β（IL-1B）、白细胞介素-2（IL-2）、白细胞介素-6（IL-6）、白细胞介素-6受体（IL-6R）、白细胞介素-10（IL-10）、肿瘤坏死因子-α（TNF-a）、转化生长因子-β（TGF-b）、Toll样受体2（TLR2）、Toll样受体4（TLR4）、髓样分化蛋白2（MD2）、髓样分化初级反应基因88（MYD88）、脑源性神经营养因子（BDNF）、C反应蛋白（CRP）、白细胞介素-1β转换酶（ICE）和阿片受体μ1（OPRM1）的变体。多变量逻辑回归建立了严重CIGT风险的预测模型。
有严重CIGT和无严重CIGT的患者在年龄、性别、癌症类型或化疗治疗方案方面无显著差异。严重CIGT风险的预测模型包括TLR2和TNF-a基因变异性以及癌症类型（结直肠癌和胃癌）。该预测模型具有特异性和敏感性，曲线下面积为87.3%。
这是免疫基因变异性与癌症类型一起可预测严重CIGT风险的首次报告。这些结果正在更大的患者群体中进行验证。
