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Hindi Developing a Universal Diagnostic Algorithm for Hematologic Malignancies Based on Flow Cytometry and Single-Cell Transcriptomics
*Corresponding Author: Dr. Elena Novak, Department of Molecular Diagnostics, Charles University Faculty of Medicine, Czech Republic, Email: elena.n@gmail.comReceived Date: Mar 01, 2025 / Accepted Date: Mar 31, 2025 / Published Date: Mar 31, 2025
Citation: Elena N (2025) Developing a Universal Diagnostic Algorithmfor Hematologic Malignancies Based on Flow Cytometry and Single-CellTranscriptomics. J Cancer Diagn 9: 291.
Copyright: © 2025 Elena N. This is an open-access article distributed under theterms of the Creative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided the original author andsource are credited.
Abstract
Hematologic malignancies encompass a heterogeneous group of disorders, including leukemias, lymphomas, and myelomas, characterized by abnormal proliferation and differentiation of blood or bone marrow cells. Traditional diagnostic methods rely on morphology, immunophenotyping via flow cytometry, cytogenetics, and molecular assays. However, challenges persist in achieving early and precise diagnosis, especially in cases with ambiguous phenotypes or overlapping features. Recent advances in single-cell transcriptomics (scRNA-seq) offer unparalleled resolution of cellular heterogeneity and gene expression, while flow cytometry remains a gold standard for immunophenotyping. This article presents a comprehensive overview of a proposed universal diagnostic algorithm that integrates flow cytometry with single-cell transcriptomics to improve the classification, diagnosis, and subtyping of hematologic malignancies. The combined approach promises a scalable, data-rich, and precise diagnostic solution for routine clinical use.
