CTDvic：用于鉴定和临床解释癌症中 ctDNA 驱动基因和变异的综合数据库

循环肿瘤 DNA （ctDNA） 变体因其微创检测方法和捕获综合肿瘤景观的能力而成为液体活检中的癌症生物标志物，具有重要前景。然而，仍然缺乏研究 ctDNA 变体的综合资源。在这里，我们开发了 CTDdgv，旨在识别 ctDNA 变异并系统地解释它们的临床相关性。我们手动整理了 1674 例经过实验验证的 ctDNA 变异临床解释，涉及预后意义、耐药性、与肿瘤特征的关联、转移监测、治疗指导、检测前景等。此外，我们开发并集成了一个管道，用于识别肿瘤驱动基因 （TDG） 和变异 （TDV） 并评估潜在 TDG 的预后意义。使用公开可用的 ctDNA 突变谱，我们从 17 种癌症类型的 38 个数据集中确定了潜在的 TDG 和 TDV。基于这些数据集，我们提供了特定癌症类型中 TDG 基因集的多维分析，从而深入了解其驱动效应。总的来说，CTDdgv 具有巨大的潜力，可以作为 ctDNA 变体的分子诊断和治疗决策的宝贵资源。

Circulating tumor DNA (ctDNA) variants hold great promise as cancer biomarkers in liquid biopsies due to their minimally invasive detection methods and ability to capture the comprehensive tumor landscape. However, comprehensive resources dedicated to the study of ctDNA variants remain scarce. Here, we developed CTDdgv, which aims to identify ctDNA variants and systematically interpret their clinical correlations. We manually curated 1,674 experimentally validated ctDNA variants with clinical annotations, covering prognostic significance, drug resistance, associations with tumor characteristics, metastasis monitoring, treatment guidance, diagnostic prospects, and other aspects. Furthermore, we developed and integrated an analysis pipeline to identify tumor driver genes (TDGs) and tumor driver variants (TDVs), and evaluate the prognostic significance of potential TDGs. Using publicly available ctDNA mutation profiles, we identified potential TDGs and TDVs from 38 datasets across 17 cancer types. Based on these datasets, we conducted multi-dimensional analyses of TDG gene sets in specific cancer types, providing in-depth insights into their driver effects. In summary, CTDdgv holds great potential as a valuable resource for molecular diagnosis and treatment decision-making related to ctDNA variants.