High-content stimulated Raman pathology imaging and transcriptomics reveal leukemia subtype-specific lipid metabolic heterogeneity.

Introduction: Leukemia, a heterogeneous group of hematological malignancies, is characterized by abnormal proliferation of immature hematopoietic cells. Current diagnostics primarily rely on morphological evaluation for subtype classification, methods that are subjective and labor-intensive. To overcome these limitations, a High-Content Spectral Raman Pathology Imaging platform (H-SRPI) was introduced. Methods: H-SRPI imaging enables profiling of proteins, nucleic acids, saturated and unsaturated lipids in leukemia. We analyzed leukemia samples from 12 patients with six distinct subtypes, alongside CD34 Results: The single-cell phenotyping algorithm to distinguish leukemia subtypes, achieving 88.21% accuracy. H-SRPI and RNA-seq transcriptomes revealed elevated saturated and unsaturated lipid levels in acute myeloid leukemia (AML); AML-M3 favored lipid desaturation, whereas AML-M5 upregulated saturated lipid synthesis and elongation. ALL had weaker lipid metabolism characteristics than AML. Conclusions: Our study establishes H-SRPI as a label-free tool for metabolic profiling, enabling precise leukemia subclassification and revealing lipid metabolic heterogeneity as a potential therapeutic target.