The cancer secretome is a valuable reservoir of cancer biomarkers. Besides containing circulating tumor cells, extracellular vesicles, and proteins, it is also rich in circulating tumor DNA (ctDNA)—a subpopulation of cell free DNA. The most efficient technology to capture ctDNA is next generation sequencing (NGS). Indeed, this analysis enables the identification of both quantitative (e.g., mutant allelic fraction - MAF) and qualitative (e.g., the variant type) information. Strikingly, by calculating these data in relation to time, cytopathologists can decodify and graphically report the ctDNA “message”, which may help to diagnose cancer, define treatment, and monitor disease evolution. In this paper, we report the most compelling evidence steadily accumulating on the successful application of NGS-based ctDNA analysis in cancer diagnosis, treatment decision, and monitoring of cancer progression. We also propose a mathematical model that calculates MAF evolution in relation to time.

癌症分泌组是癌症生物标志物的宝贵储存库。除了含有循环肿瘤细胞、细胞外囊泡和蛋白质外，它还富含循环肿瘤 DNA (ctDNA)——一种无细胞 DNA 亚群。捕获 ctDNA 的最有效技术是下一代测序 (NGS)。事实上，这种分析能够识别定量（例如突变等位基因部分 - MAF）和定性（例如变异类型）信息。引人注目的是，通过计算这些与时间相关的数据，细胞病理学家可以解码并以图形方式报告 ctDNA“信息”，这可能有助于诊断癌症、定义治疗和监测疾病演变。在本文中，我们报告了基于 NGS 的 ctDNA 分析在癌症诊断中的成功应用不断积累的最令人信服的证据，治疗决策和监测癌症进展。我们还提出了一个计算 MAF 随时间演化的数学模型。