Diagnostic value of nanopore-based metagenomic third-generation sequencing in the diagnosis of infection in patients with lung cancer.

pneumonia (PJP, formerly known as pneumonia), an opportunistic fungal infection caused by the fungus , is a severe pulmonary infection that primarily affects immunocompromised patients, including those with lung cancer. Traditional diagnostic methods for PJP, such as Grocott-Gomori's methenamine silver staining and real-time PCR, have limitations, including low positivity and high missed diagnosis rates. Despite the critical need for accurate and sensitive diagnostic tools for PJP, especially in immunocompromised populations, existing methods fall short in providing the necessary reliability and efficiency. This study aims to evaluate the efficacy of nanopore-based metagenomic third-generation sequencing in diagnosing infection in lung cancer patients, hypothesizing that this approach may offer superior sensitivity and specificity. A prospective observational study was conducted on 118 lung cancer patients with suspected pulmonary infection at the Sixth Hospital of Nantong City, China, from January 2021 to December 2023. The identification of pathogens in bronchoalveolar lavage fluid samples was performed using both metagenomics and traditional tests. Metagenomics showed a significantly higher detection rate of (33.0%) compared to methenamine silver staining (4.2%) and real-time PCR (30.5%). The sensitivity, specificity and accuracy of metagenomics detection were all 100%, which is markedly superior to traditional methods. Furthermore, metagenomics also identified mixed infections with other pathogens, such as and Epstein-Barr virus. Metagenomics technology demonstrates high sensitivity and specificity in diagnosing infection, including mixed infections with other pathogens, in lung cancer patients. It provides a clear direction for clinical treatment and is a powerful tool for diagnosing PJP, contributing to improved diagnostic efficiency and accuracy, reducing misdiagnosis and missed diagnosis rates and improving clinical outcomes in these patients.