Costa Jacopo, Membrino Alexandro, Zanchetta Carol, Rizzato Simona, Cortiula Francesco, Rossetto Ciro, Pelizzari Giacomo, Aprile Giuseppe, Macerelli Marianna
Department of Medicine (DAME), University of Udine, 33100 Udine, Italy.
Department of Oncology, University Hospital of Udine, 33100 Udine, Italy.
Int J Mol Sci. 2024 Dec 20;25(24):13669. doi: 10.3390/ijms252413669.
Liquid biopsy (LB) involves the analysis of circulating tumour-derived DNA (ctDNA), providing a minimally invasive method for gathering both quantitative and qualitative information. Genomic analysis of ctDNA through next-generation sequencing (NGS) enables comprehensive genetic profiling of tumours, including non-driver alterations that offer prognostic insights. LB can be applied in both early-stage disease settings, for the diagnosis and monitoring of minimal residual disease (MRD), and advanced disease settings, for monitoring treatment response and understanding the mechanisms behind disease progression and tumour heterogeneity. Currently, LB has limited use in clinical practice, primarily due to its significant costs, limited diagnostic yield, and uncertain prognostic role. The application of artificial intelligence (AI) in the medical field is a promising approach to processing extensive information and applying it to individual cases to enhance therapeutic decision-making and refine risk assessment.
液体活检（LB）涉及对循环肿瘤来源DNA（ctDNA）的分析，为收集定量和定性信息提供了一种微创方法。通过下一代测序（NGS）对ctDNA进行基因组分析能够实现肿瘤的全面基因分型，包括提供预后见解的非驱动改变。液体活检可应用于早期疾病情况，用于微小残留病（MRD）的诊断和监测，也可应用于晚期疾病情况，用于监测治疗反应以及了解疾病进展和肿瘤异质性背后的机制。目前，液体活检在临床实践中的应用有限，主要是因为其成本高昂、诊断率有限以及预后作用不明确。人工智能（AI）在医学领域的应用是一种很有前景的方法，可用于处理大量信息并将其应用于个体病例，以加强治疗决策并优化风险评估。
