Details

Autor(en) / Beteiligte

• Larkin, Paige M K
• Lawson, Katy L
• Contreras, Deisy A
• Le, Catherine Q
• Trejo, Marisol
• Realegeno, Susan
• Hilt, Evann E
• Chandrasekaran, Sukantha
• Garner, Omai B
• Fishbein, Gregory A
• Yang, Shangxin

Titel

Amplicon-Based Next-Generation Sequencing for Detection of Fungi in Formalin-Fixed, Paraffin-Embedded Tissues: Correlation with Histopathology and Clinical Applications

Ist Teil von

• The Journal of molecular diagnostics : JMD, 2020-10, Vol.22 (10), p.1287-1293

Ort / Verlag

United States

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Access via ScienceDirect (Elsevier)

Beschreibungen/Notizen

• Invasive fungal infections are increasing in prevalence because of an expanding population of immunocompromised individuals. To reduce morbidity and mortality, it is critical to accurately identify fungal pathogens to guide treatment. Current methods rely on histopathology, fungal culture, and serology, which are often insufficient for diagnosis. Herein, we describe the use of a laboratory-developed internal transcribed spacer-targeted amplicon-based next-generation sequencing (NGS) assay for the identification of fungal etiology in fungal stain-positive formalin-fixed, paraffin-embedded tissues by using Illumina MiSeq. A total of 44 specimens from 35 patients were included in this study, with varying degrees of fungal burden from multiple anatomic sites. NGS identified 20 unique species across the 54 total organisms detected, including 40 molds, 10 yeasts, and 4 dimorphic fungi. The histopathologic morphology and the organisms suspected by surgical pathologist were compared with the organisms identified by NGS, with 100% (44/44) and 93.2% (41/44) concordance, respectively. In contrast, fungal culture only provided an identification in 27.3% (12/44) of specimens. We demonstrated that NGS is a powerful method for accurate and unbiased fungal identification in formalin-fixed, paraffin-embedded tissues. A retrospective evaluation of the clinical utility of the NGS results also suggests this technology can potentially improve both the speed and the accuracy of diagnosis for invasive fungal infections.