Department of Radiation Oncology, University of California, Los Angeles, United States; Department of Urology, University of California, Los Angeles, United States.
Department of Biostatistics, University of California Los Angeles Fielding School of Public Health, Los Angeles, United States.
Radiother Oncol. 2022 Feb;167:226-232. doi: 10.1016/j.radonc.2021.12.040. Epub 2022 Jan 3.
The purpose of this study was to determine whether single nucleotide polymorphisms disrupting microRNA targets (mirSNPs) can serve as predictive biomarkers for toxicity after radiotherapy for prostate cancer and whether these may be differentially predictive depending on radiation fractionation.
We identified 201 men treated with two forms of definitive radiotherapy for prostate cancer at two institutions: 108 men received conventionally-fractionated radiotherapy (CF-RT) and 93 received stereotactic body radiotherapy (SBRT). Germline DNA was evaluated for the presence of functional mirSNPs. Random forest, boosted trees and elastic net models were developed to predict late grade ≥2 GU toxicity by the RTOG scale.
The crude incidence of late grade ≥2 GU toxicity was 16% after CF-RT and 15% after SBRT. An elastic net model based on 22 mirSNPs differentiated CF-RT patients at high risk (71.5%) versus low risk (7.5%) for toxicity, with an area under the curve (AUC) values of 0.76-0.81. An elastic net model based on 32 mirSNPs differentiated SBRT patients at high risk (64.7%) versus low risk (3.9%) for toxicity, with an area under the curve (AUC) values of 0.81-0.87. These models were specific to treatment type delivered. Prospective studies are warranted to further validate these results.
Predictive models using germline mirSNPs have high accuracy for predicting late grade ≥2 GU toxicity after either CF-RT or SBRT, and are unique for each treatment, suggesting that germline predictors of late radiation sensitivity are fractionation-dependent. Prospective studies are warranted to further validate these results.
本研究旨在确定破坏 microRNA 靶点的单核苷酸多态性(mirSNPs)是否可以作为前列腺癌放射治疗后毒性的预测生物标志物,以及这些 mirSNPs 是否可能因放射分割方式的不同而具有不同的预测能力。
我们在两个机构中鉴定了 201 名接受两种形式的前列腺癌根治性放疗的男性:108 名男性接受常规分割放疗(CF-RT),93 名接受立体定向体部放疗(SBRT)。评估了种系 DNA 中功能性 mirSNPs 的存在情况。采用随机森林、增强树和弹性网络模型,根据 RTOG 量表预测晚期≥2 级 GU 毒性。
CF-RT 后晚期≥2 级 GU 毒性的发生率为 16%,SBRT 后为 15%。基于 22 个 mirSNPs 的弹性网络模型区分了 CF-RT 患者的高风险(71.5%)和低风险(7.5%),曲线下面积(AUC)值为 0.76-0.81。基于 32 个 mirSNPs 的弹性网络模型区分了 SBRT 患者的高风险(64.7%)和低风险(3.9%),AUC 值为 0.81-0.87。这些模型是针对所给予的治疗类型特异性的。需要前瞻性研究进一步验证这些结果。
使用种系 mirSNPs 的预测模型对 CF-RT 或 SBRT 后晚期≥2 级 GU 毒性的预测具有很高的准确性,并且对每种治疗方法都是独特的,表明晚期放射敏感性的种系预测因子与分割方式有关。需要前瞻性研究进一步验证这些结果。