SPIRAL的分析验证：一种整合基因组与表观基因组的液体活检检测

Introduction: Genomic and epigenomic alterations serve as key biomarkers for tumor detection, yet conventional approaches require separate workflows and DNA inputs for each signal type, which is impractical when sample quantity is limited. Because tumor initiation and progression arise from coordinated genomic and epigenomic dysregulation, simultaneous assessment of both layers is critical for accurate tumor classification, mechanistic insight, and clinical decision-making. Genomic profiling captures oncogenic drivers such as mutations, copy number alterations, and fusions, whereas epigenomic features-particularly DNA methylation-provide complementary information on histological subtype, gene regulation, prognosis, and tumor burden. To address the limitations of segregated assays, we developed SPIRAL (Single Portion Input Resourceful Assay of Liquid biopsy), an integrated multi-omics method that generates genomic and methylation libraries from the same DNA aliquot. Here, we present a preliminary evaluation of SPIRAL in a liquid biopsy setting, demonstrating its ability to concurrently profile genomic and epigenomic signals from a single blood-derived DNA sample. Results: Analytical validation of SPIRAL was conducted using both cell line-derived and clinical samples. For genomic detection, the observed LoD95 was 0.8% for SNVs/indels (0.3% for hotspot variants), 0.3% for fusions, 20% tumor fraction for CNAs at six copies, 30% tumor fraction for homozygous deletions, and 1% tumor fraction for MSI. For epigenomic analysis, the LoD95 for global methylation was 5×10⁻⁵ in cell lines and 1×10⁻⁴ in clinical samples, with a limit of quantitation of 0.05% and a specificity of 98% in clinical samples. The LoD for promoter methylation was 1%. Conclusion: SPIRAL is a liquid biopsy technology capable of simultaneously profiling genomic and epigenomic alterations from the same portion of cfDNA. In addition to comprehensive genomic profiling, it enables tissue-free MRD detection, therapy-response monitoring through tumor-fraction quantification, tumor subtyping, and broader phenotypic characterization. This integrated approach provides a robust platform for biomarker discovery and has the potential to substantially advance precision cancer management.