Is it possible detect tumor cells in body fluid with an automated hematology analyzer?

Nucleated cell differential analysis of body fluid (BF) samples is an important diagnostic tool for several diseases including cancer metastasis. However, detection of tumor cells in BF by manual differential is time-consuming and labor-intensive. We aimed to develop a scatter gram gating analysis for detection of tumor cells in BF using the automated hematology analyzer Sysmex XN-1000 (Sysmex, Kobe, Japan).

To construct the novel scatter gram gating criteria targeting the tumor cells, we utilized more than 200 BF samples obtained from patients with cytological diagnoses (papanicolaou stain) including negative and positive for malignancy, and chronic inflammation with an elevated lymphocyte and histiocyte fractions.  We comparted these results to the reference method, morphological manual differentials (200 cells counts).  The XN BF mode on the XN-1000 determines the differential cell counts of BF samples using side scatter and fluorescence intensity in WDF channel after the nuclear DNA/RNA stain by nucleic acid dye. The polymorphonuclear, mononuclear and high fluorescence cells (HF-BF) that contain a high nucleic acid concentration are differentiated by this method. Mesothelial cells and macrophages are theoretically categorized as HF-BF cells and included in the total nucleated cell count, but not in the WBC count.

We selected the malignancy positive and chronic inflammation positive samples by morphological manual differential, and reviewed their scatter gram patterns in the XN BF mode. Then the novel scatter gram gating strategy targeting the tumor cells was evaluated. The gating criteria were based on the WDF scatter plots; #1: detects the cells with larger size and higher fluorescence signal in comparison with general leukocytes, which mainly derived from clustered tumor cells, #2: detects the middle sized mononuclear cells with less granules rather than neutrophils and similar fluorescence signal to monocytes. BF samples that meet at least one criterion were interpreted as positive for tumor cells.

We observed that the malignant BF showed different scatter gram patterns from the benign BF samples of chronic inflammation, which typically showed increased histiocytes and reactive mesothelial cells. Whereas the benign BF often showed the continuous expansion into the HF-BF area, the malignant BF formed the isolated cellular clusters in our gating system. Our scatter gram gating analysis achieved an overall sensitivity of >75% and specificity of > 95% in detecting malignancy when screening against all samples’ outcomes. For the samples with absence of malignancy and inflammatory observations, no false positive results were detected.

A simple measurement of BF by automated hematology analyzer has the potential to reduce costs and allow routine cell screening in clinical applications. For BF malignancy diagnostics, a scatter gram gating analysis is promising to (i) augment diagnostic routines without requiring additional sample preparation procedure, (ii) limit operator bias, and (iii) provide a standardized measurement.  How easily could this be implemented in your laboratory?