Automated Decentralized cfDNA NGS Assay Identifies Alterations in Advanced Solid Tumors

Current circulating cell-free DNA (cfDNA) assays are typically centralized, requiring specialized handling and transportation of samples. Introducing a flexible, decentralized sequencing system at the point of care, which requires minimal technical oversight, could significantly improve turnaround times and expand patient access to genomic profiling. In a new study, researchers assessed the clinical feasibility of an automated, decentralized cfDNA next-generation sequencing (NGS) assay designed to identify actionable genetic alterations in advanced solid tumors.

The study, conducted by researchers at the Japanese Foundation for Cancer Research (JFCR, Tokyo, Japan), involved genomic profiling of plasma cfDNA from 298 patients with advanced solid tumors using an automated NGS assay. The team compared the tumor mutations detected in plasma cfDNA with those found in patient-matched tumor tissues, which were analyzed using an FDA-approved assay. They also examined clinical factors that could influence the sensitivity of ctDNA aberration (mut-ctDNA) detection. The researchers discovered that the sequencing success rates for cfDNA genomic profiling were significantly higher compared to archived tumor tissue (99% vs. 96%). The detection rates of mut-ctDNA ranged from 20% to 67% across various solid tumors, and targetable or resistance alterations were identified in 18% of patients.

The results, published in the journal Clinical Chemistry, also revealed that approximately 72% of patients showed consistent alterations between tissue and plasma samples. This level of concordance was linked to factors such as cancer type, tumor burden, and the metastatic location. Importantly, 63 plasma-only alterations were identified in 18% of patients, with these alterations being more common in patients who had previously received targeted treatments (24%) compared to those who had undergone chemotherapy (10%). The findings highlight the clinical viability of an automated, decentralized cfDNA genomic profiling method and emphasize the need to consider clinical factors when choosing between plasma- or tissue-based assays. This approach holds promise for improving patient access to timely genomic profiling and facilitating targeted therapy selection.

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