Detection of minimal residual disease (MRD) in cancer patients after surgery can provide an early marker for disease recurrence and guide subsequent treatment decisions. Accurate and sensitive estimation of tumour burden after cancer surgery may be obtained through liq- uid biopsies, measuring circulating tumour DNA (ctDNA) using, for example, mutation-based Variant Allele Frequency (VAF) values. However, to be applicable to all patients this ei- ther requires tumour-informed, patient-specific mutation panels or sensitive, tumour-agnostic genome-wide measurements. We propose a solution that accounts for patient-specific charac- teristics in genome-wide screens. For that, we introduce a bivariate deconvolution model to estimate tumour proportion from circulating cell-free DNA (cfDNA) methylation profiles of patients before and after surgery. The observations are modelled as a convolution of two bivariate latent variables, corresponding to tumour and background signals, mixed by the tumour proportion at each measurement. This bivariate approach links pre- and post-surgery measurements improving estimation of the tumour proportion after surgery, when the tumour signal is potentially very weak, or absent. We approximate likelihood of the convolution through a discretisation of the bivariate density for each latent variable into a two-dimensional grid for each pair of observations which allows for fast maximum likelihood estimation. We evaluate the predictive performance of the estimated post-surgery tumour proportions based on cfDNA methylation against available mutation-based VAF values in one-year recurrence-free survival.

翻译：摘要：癌症患者术后微小残留病（MRD）的检测可为疾病复发提供早期标志物，并指导后续治疗决策。通过液体活检测量循环肿瘤DNA（ctDNA）（例如基于突变的变异等位基因频率（VAF）值）可获得对癌症术后肿瘤负荷的准确灵敏估计。然而，该方法若要适用于所有患者，则需使用肿瘤信息指导的、患者特异性突变panel或灵敏的、非肿瘤特异性全基因组检测。我们提出了一种在全基因组筛查中考虑患者特异性特征的解决方案。为此，我们引入一种双变量反卷积模型，通过术前和术后患者循环游离DNA（cfDNA）甲基化图谱估计肿瘤比例。观测值建模为两个双变量潜在变量（对应肿瘤信号和背景信号）的卷积，该卷积由每次测量时的肿瘤比例混合。此双变量方法将术前与术后测量关联，从而在肿瘤信号可能极弱或缺失时，改善术后肿瘤比例的估计。我们通过将每个潜在变量的双变量密度离散化为每对观测值的二维网格来近似卷积似然，实现快速最大似然估计。基于cfDNA甲基化估计的术后肿瘤比例的预测性能评估，以可用基于突变的VAF值在一年无复发生存期中的表现为参照。