Division of Medical Oncology, Department of Medicine and Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
SWOG Statistics and Data Management Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Eur Urol Oncol. 2023 Oct;6(5):516-524. doi: 10.1016/j.euo.2023.03.008. Epub 2023 Apr 20.
Neoadjuvant chemotherapy (NAC) is the standard of care in muscle-invasive bladder cancer (MIBC). However, treatment is intense, and the overall benefit is small, necessitating effective biomarkers to identify patients who will benefit most.
To characterize cell-free DNA (cfDNA) methylation in patients receiving NAC in SWOG S1314, a prospective cooperative group trial, and to correlate the methylation signatures with pathologic response at radical cystectomy.
DESIGN, SETTING, AND PARTICIPANTS: SWOG S1314 is a prospective cooperative group trial for patients with MIBC (cT2-T4aN0M0, ≥5 mm of viable tumor), with a primary objective of evaluating the coexpression extrapolation (COXEN) gene expression signature as a predictor of NAC response, defined as achieving pT0N0 or ≤pT1N0 at radical cystectomy. For the current exploratory analysis, blood samples were collected prospectively from 72 patients in S1314 before and during NAC, and plasma cfDNA methylation was measured using the Infinium MethylationEPIC BeadChip array.
No additional interventions besides plasma collection.
Differential methylation between pathologic responders (≤pT1N0) and nonresponders was analyzed, and a classifier predictive of treatment response was generated using the Random Forest machine learning algorithm.
Using prechemotherapy plasma cfDNA, we developed a methylation-based response score (mR-score) predictive of pathologic response. Plasma samples collected after the first cycle of NAC yielded mR-scores with similar predictive ability. Furthermore, we used cfDNA methylation data to calculate the circulating bladder DNA fraction, which had a modest but independent predictive ability for treatment response. In a model combining mR-score and circulating bladder DNA fraction, we correctly predicted pathologic response in 79% of patients based on their plasma collected at baseline and after one cycle of chemotherapy. Limitations of this study included a limited sample size and relatively low circulating bladder DNA levels.
Our study provides the proof of concept that cfDNA methylation can be used to generate classifiers of NAC response in bladder cancer patients.
In this exploratory analysis of S1314, we demonstrated that cell-free DNA methylation can be profiled to generate biomarker signatures associated with neoadjuvant chemotherapy response. With validation in additional cohorts, this minimally invasive approach may be used to predict chemotherapy response in locally advanced bladder cancer and perhaps also in metastatic disease.
新辅助化疗（NAC）是肌层浸润性膀胱癌（MIBC）的标准治疗方法。然而，治疗强度大，整体获益较小，因此需要有效的生物标志物来识别最受益的患者。
在 SWOG S1314 前瞻性合作组试验中，对接受 NAC 的患者的游离 DNA（cfDNA）甲基化进行特征描述，并将甲基化特征与根治性膀胱切除术时的病理反应相关联。
设计、地点和参与者：SWOG S1314 是一项 MIBC（cT2-T4aN0M0，≥5mm 存活肿瘤）患者的前瞻性合作组试验，主要目的是评估 COEX 基因表达谱作为 NAC 反应预测因子的作用，定义为根治性膀胱切除术后达到 pT0N0 或≤pT1N0。对于当前的探索性分析，从 S1314 中的 72 名患者前瞻性采集血液样本，在 NAC 之前和期间，使用 Infinium MethylationEPIC BeadChip 阵列测量血浆 cfDNA 甲基化。
除了采集血浆外，没有其他干预措施。
分析了病理反应者（≤pT1N0）和非反应者之间的差异甲基化，并使用随机森林机器学习算法生成了预测治疗反应的分类器。
使用化疗前血浆 cfDNA，我们开发了一种预测病理反应的基于甲基化的反应评分（mR-score）。在 NAC 第一周期后采集的血浆样本得出的 mR-score 具有相似的预测能力。此外，我们使用 cfDNA 甲基化数据计算了循环膀胱 DNA 分数，该分数对治疗反应具有适度但独立的预测能力。在结合 mR-score 和循环膀胱 DNA 分数的模型中，我们根据基线和化疗一个周期后采集的血浆，正确预测了 79%的患者的病理反应。本研究的局限性包括样本量有限和相对较低的循环膀胱 DNA 水平。
我们的研究提供了概念验证，表明 cfDNA 甲基化可用于生成膀胱癌患者 NAC 反应的分类器。
在 S1314 的这项探索性分析中，我们证明了可以对游离 DNA 甲基化进行分析，以生成与新辅助化疗反应相关的生物标志物特征。在额外的队列中进行验证后，这种微创方法可用于预测局部晚期膀胱癌的化疗反应，也许还可用于转移性疾病。
