Authors
Jing Hu, Zhi Guo, Bolin Wan, Chengming He, Min Zou
Published in
Journal of visualized experiments : JoVE. Issue 234. Aug 04, 2026. Epub Aug 04, 2026.
Abstract
Acute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy in which relapse and acquired chemoresistance remain major causes of treatment failure. This article presents a bioinformatic protocol for transcriptomic analysis of bone marrow aspirates. The primary goal of the protocol is to provide a standardized workflow to identify molecular signatures associated with disease progression and therapy resistance in relapsed AML. The pipeline details the computational procedures for comparing unpaired bone marrow samples, demonstrated using sequencing data from five newly diagnosed cases and four relapsed cases. This method outlines the essential steps for processing RNA sequencing data, performing differential gene expression analysis, and conducting downstream functional evaluations. Applying this workflow identified 2,025 differentially expressed genes (DEGs), including FOXC1, HOXA11, HOXA11-AS, and AXL, as candidate transcripts associated with relapse in this representative dataset. Functional and network analyses further prioritized gene sets and interaction hubs related to small GTPase signaling, inflammatory signaling, extracellular matrix interactions, and RNA biosynthetic processes. Overall, this methodology provides a reproducible computational pipeline for mapping transcriptomic signatures associated with relapsed AML and for generating hypotheses that require subsequent experimental validation.
PMID:
42612023
Bibliographic data and abstract were imported from PubMed on 19 Aug 2026.
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