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.