Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >10⁵ informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to parts per million. This resulted in median area under the curve (AUC) values of 0.98 in advanced cancers and 0.80 in early-stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that INVAR may be applied without requiring personalized sequencing panels so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

循环肿瘤衍生 DNA (ctDNA) 可用于无创监测癌症动态。ctDNA 的检测在患有低体积或残留疾病的患者中可能具有挑战性，因为在这些患者中，血浆中含有非常少的肿瘤来源的 DNA 片段。我们表明，通过分析首先由肿瘤基因分型鉴定的成百上千个突变，可以提高血浆中 ctDNA 检测的灵敏度。我们描述了可变读取集成 (INVAR) 管道，它结合了自定义错误抑制方法和基于 ctDNA 生物学特征的信号富集方法。使用这种方法，可以根据跨多个患者特定基因座测序的信息读数的数量独立估计每个样本的检测限。我们将 INVAR 应用于来自 105 名患有黑色素瘤、肺癌、肾癌、神经胶质瘤和乳腺癌的早期和晚期疾病患者的 176 个血浆样本的自定义杂交捕获测序数据。通过在 >10 的中位数上整合信号^{5 个}信息读数，ctDNA 通常被量化为每 100,000 个突变分子 1 个，在某些具有高肿瘤突变负荷和/或血浆输入材料的情况下，量化为百万分之一。这导致晚期癌症的中值曲线下面积 (AUC) 值为 0.98，在早期阶段和具有挑战性的 ctDNA 检测环境中为 0.80。我们将这种方法推广到全外显子组和全基因组测序，表明只要有肿瘤突变列表，就可以应用 INVAR 而无需个性化测序 panel。随着越来越多地进行肿瘤测序，这种用于个性化癌症监测的方法可能会提高癌症液体活检的灵敏度。