Novel flowcytometry-based approach of malignant cell detection in body fluids using an automated hematology analyzer

• Published in: PloS one Vol. 13; no. 2; p. e0190886
• Main Authors: Ai, Tomohiko, Tabe, Yoko, Takemura, Hiroyuki, Kimura, Konobu, Takahashi, Toshihiro, Yang, Haeun, Tsuchiya, Koji, Konishi, Aya, Uchihashi, Kinya, Horii, Takashi, Ohsaka, Akimichi
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 09.02.2018; Public Library of Science (PLoS)
• Subjects: Algorithms; Biology and Life Sciences; Body fluids; Cellular biology; Cerebrospinal fluid; Channel gating; Differentiation; Flow cytometry; Fluids; Fluorescence; Gene expression; Granule cells; Hematology; Laboratories; Leukocytes; Leukocytes (mononuclear); Leukocytes (neutrophilic); Malignancy; Medical diagnosis; Medicine; Medicine and Health Sciences; Microscopy; Monocytes; Pathology; Physical Sciences; Research and Analysis Methods; Sensitivity; Solid tumors; Stem cells; Studies; Tumor cells; University graduates; Japan
• DOI: 10.1371/journal.pone.0190886
• ISSN: 1932-6203

Morphological microscopic examinations of nucleated cells in body fluid (BF) samples are performed to screen malignancy. However, the morphological differentiation is time-consuming and labor-intensive. This study aimed to develop a new flowcytometry-based gating analysis mode "XN-BF gating algorithm" to detect malignant cells using an automated hematology analyzer, Sysmex XN-1000. XN-BF mode was equipped with WDF white blood cell (WBC) differential channel. We added two algorithms to the WDF channel: Rule 1 detects larger and clumped cell signals compared to the leukocytes, targeting the clustered malignant cells; Rule 2 detects middle sized mononuclear cells containing less granules than neutrophils with similar fluorescence signal to monocytes, targeting hematological malignant cells and solid tumor cells. BF samples that meet, at least, one rule were detected as malignant. To evaluate this novel gating algorithm, 92 various BF samples were collected. Manual microscopic differentiation with the May-Grunwald Giemsa stain and WBC count with hemocytometer were also performed. The performance of these three methods were evaluated by comparing with the cytological diagnosis. The XN-BF gating algorithm achieved sensitivity of 63.0% and specificity of 87.8% with 68.0% for positive predictive value and 85.1% for negative predictive value in detecting malignant-cell positive samples. Manual microscopic WBC differentiation and WBC count demonstrated 70.4% and 66.7% of sensitivities, and 96.9% and 92.3% of specificities, respectively. The XN-BF gating algorithm can be a feasible tool in hematology laboratories for prompt screening of malignant cells in various BF samples.