DOI: 10.1097/bs9.0000000000000304 ISSN: 2543-6368

Application value and challenges associated with plasma cell-free DNA metagenomic sequencing technology in the diagnosis of infections in patients with hematological disorders

Chunhui Xu, Teng Liu, Xuyan Zhang, Sizhou Feng

In patients with hematological disorders, the high risk of complex infections caused by immune dysfunction and intensive therapies poses a major challenge to the use of conventional microbiological tests (CMTs). Plasma cell-free DNA (cfDNA) metagenomic next-generation sequencing (mNGS) has emerged as a revolutionary noninvasive tool that enables unbiased, broad-spectrum, and rapid pathogen identification directly from blood samples. This review summarizes the core applications of plasma cfDNA mNGS in patients with hematological disorders, including the diagnosis of febrile neutropenia, bloodstream infections, focal infections, and infections caused by uncommon/fastidious pathogens. It highlights the advantages of this technology in overcoming antibiotic interference, enabling early detection, and providing diagnostic value in cases without clear infection foci or when invasive sampling is not feasible. This review further discusses how China has facilitated the widespread adoption of this technology through a localized application model, cost reduction, and the development of clinically relevant interpretation models. Nevertheless, challenges remain, such as lower sensitivity than site-specific specimens in focal infections, and the difficulty in predicting antimicrobial resistance (AMR) on the basis of cfDNA mNGS. Future developmental directions should focus on technical optimization (eg, combined plasma cell-fraction testing), quality assurance and quality control management, multidimensional data integration (eg, host immune response analysis), artificial intelligence (AI)–assisted interpretation, and cost reduction through technology popularization and insurance coverage. These efforts will advance cfDNA mNGS from a pathogen detection tool toward an intelligent clinical decision-support platform, ultimately improving the diagnostic accuracy and clinical outcomes of hematological patients with infections.

More from our Archive