ArticleJournal of the National Cancer Center2025
Chinese expert consensus on flow cytometric detection of hematological malignant cells in tissue samples.
Article in Journal of the National Cancer Center, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Evaluating TGF-β1 gene expression and promoter polymorphism in cervical cancer progression.Journal of molecular histology · 2025Article
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23 authors.
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Abstract
Flow cytometry (FCM), characterized by its simplicity, rapid processing, multiparameter analysis, and high sensitivity, is widely used in the diagnosis, treatment, and prognosis of hematological malignancies. FCM testing of tissue samples not only aids in diagnosing and classifying hematological cancers, but also enables the detection of solid tumors. Its ability to detect numerous marker parameters from small samples is particularly useful when dealing with limited cell quantities, such as in fine-needle biopsy samples. This attribute not only addresses the challenge posed by small sample sizes, but also boosts the sensitivity of tumor cell detection. The significance of FCM in clinical and pathological applications continues to grow. To standardize the use of FCM in detecting hematological malignant cells in tissue samples and to improve quality control during the detection process, experts from the Cell Analysis Professional Committee of the Chinese Society of Biotechnology jointly drafted and agreed upon this consensus. This consensus was formulated based on current literature and clinical practices of all experts across clinical, laboratory, and pathological fields in China. It outlines a comprehensive workflow of FCM-based assay for the detection of hematological malignancies in tissue samples, including report content, interpretation, quality control, and key considerations. Additionally, it provides recommendations on antibody panel designs and analytical approaches to enhancing FCM tests, particularly in cases with limited sample sizes.
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