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Validation of an Automated Cell Counter Method for HLA-DR and CD3 Expression in Cells Obtained from Low Volume Human Tears. | LitMetric

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Article Abstract

: Tears are a promising source of biomarkers reflecting both ocular and systemic conditions. However, small sample volumes and low cell yields pose technical challenges in analytical workflows. This study aimed to evaluate the feasibility of quantifying total cell counts and characterizing HLA-DR and CD3 expression in tear-derived cells using an automated cell counter with fluorescence detection (Countess 3 FL). : Tears were collected from 31 patients, centrifuged and the resulting pellet was incubated with HLA-DR and CD3 antibodies, markers of inflammation and T lymphocytes, respectively. Data obtained from Countess 3 FL were compared with conventional flow cytometry and immunofluorescence. For technical performance analysis, precision and reproducibility of cell count and staining were measured. For method validation, an in vitro model of hyperosmolar stress was assessed by culturing conjunctival epithelial cells (CCL20.2) with 350 or 450 mOsm NaCl. : The total cell yield in each tear sample correlated with the tear surnatant volume, in a range of 1-40μL (mean total cell number: 1.3 ± 1.1 × 10, correlation analysis with tear volume: r = 0.47, < 0.05). HLA-DR and CD3 were detected in all samples, with a mean value, respectively, of 43.6% (±21.0) and 25.0% (±15.0) intensity. Data were comparable to those obtained from standard flow cytometry analysis.HLA-DR increase in CCL20.2 exposed to hyperosmolar stress was recorded using Countess 3FL reading, confirming the detection capacity of the proposed method. : The automated cell counter can provide HLA-DR and CD3 quantification in tear cell samples, despite the high variability and the low volume availability of tear samples. Method standardization and technical improvements are necessary to strengthen this application in the clinical setting.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12071788PMC
http://dx.doi.org/10.3390/diagnostics15091124DOI Listing

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