Department of Radiation Oncology, University of Michigan, 1500 E Medical Center Drive, UH B2 C490 SPC 5010, Ann Arbor, MI, 48109, USA.
Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
J Cancer Res Clin Oncol. 2019 Jun;145(6):1635-1643. doi: 10.1007/s00432-019-02903-5. Epub 2019 Mar 28.
Radiation-induced cardiac toxicity (RICT) is an increasingly well-appreciated source of morbidity and mortality in patients receiving thoracic radiotherapy (RT). Currently available methods to predict RICT are suboptimal. We investigated circulating microRNAs (c-miRNAs) as potential biomarkers of RICT in patients undergoing definitive RT for non-small-cell lung cancer (NSCLC).
Data from 63 patients treated on institutional trials were analyzed. Prognostic models of grade 3 or greater (G3 +) RICT based on pre-treatment c-miRNA levels ('c-miRNA'), mean heart dose (MHD) and pre-existing cardiac disease (PCD) ('clinical'), and a combination of these ('c-miRNA + clinical') were developed. Elastic net Cox regression and full cross validation were used for variable selection, model building, and model evaluation. Concordance statistic (c-index) and integrated Brier score (IBS) were used to evaluate model performance.
MHD, PCD, and serum levels of 14 c-miRNA species were identified as jointly prognostic for G3 + RICT. The 'c-miRNA and 'clinical' models yielded similar cross-validated c-indices (0.70 and 0.72, respectively) and IBSs (0.26 and 0.28, respectively). However, prognostication was not improved by combining c-miRNA and clinical factors (c-index 0.70, IBS 0.28). The 'c-miRNA' and 'clinical' models were able to significantly stratify patients into high- and low-risk groups of developing G3 + RICT. Chi-square testing demonstrated a marginally significantly higher prevalence of PCD in patients with high- compared to low-risk c-miRNA profile (p = 0.09), suggesting an association between some c-miRNAs and PCD.
We identified a pre-treatment c-miRNA signature prognostic for G3 + RICT. With further development, pre- and mid-treatment c-miRNA profiling could contribute to patient-specific dose selection and treatment adaptation.
放射性心脏毒性(RICT)是接受胸部放射治疗(RT)的患者发病率和死亡率日益增加的一个重要原因。目前可用的预测 RICT 的方法并不理想。我们研究了循环 microRNAs(c-miRNAs)作为接受确定性 RT 治疗的非小细胞肺癌(NSCLC)患者 RICT 的潜在生物标志物。
分析了 63 名接受机构试验治疗患者的数据。基于治疗前 c-miRNA 水平('c-miRNA')、平均心脏剂量(MHD)和预先存在的心脏疾病(PCD)('临床'),以及这些因素的组合('c-miRNA+临床'),建立了 3 级或更高级别(G3+)RICT 的预后模型。弹性网络 Cox 回归和完全交叉验证用于变量选择、模型构建和模型评估。一致性统计量(c 指数)和综合 Brier 评分(IBS)用于评估模型性能。
MHD、PCD 和 14 种 c-miRNA 血清水平被确定为 G3+RICT 的联合预后因素。'c-miRNA 和 '临床'模型的交叉验证 c 指数(分别为 0.70 和 0.72)和 IBS(分别为 0.26 和 0.28)相似。然而,将 c-miRNA 和临床因素结合并不能改善预后(c 指数 0.70,IBS 0.28)。'c-miRNA'和'临床'模型能够显著将患者分为发生 G3+RICT 的高风险和低风险组。卡方检验显示,高风险 c-miRNA 谱患者的 PCD 患病率明显高于低风险组(p=0.09),提示某些 c-miRNAs 与 PCD 之间存在关联。
我们确定了一个预测 G3+RICT 的治疗前 c-miRNA 特征。随着进一步的发展,治疗前和中期 c-miRNA 分析可能有助于患者特异性剂量选择和治疗适应。