AML-1263: Transcriptomic Profiling of Acute Myeloid Leukemia Before and After Induction Therapy: A Public Data-Based Analysis

Document Type

Conference Proceeding

Publication Date

9-1-2025

Publication Title

Clin Lymphoma Myeloma Leuk

Abstract

Acute myeloid leukemia (AML) presents a variable response to induction therapy, necessitating the identification of early transcriptomic biomarkers that reflect treatment effectiveness. Publicly available gene expression data offer a noninvasive approach to study such shifts. Objective: To identify differentially expressed genes (DEGs) in patients with AML before and after induction chemotherapy, and to elucidate biological pathways associated with treatment response. Design: A secondary analysis of publicly available microarray data (GSE10358) using GEO2R. Samples included paired bone marrow aspirates from patients collected pre- and postchemotherapy. DEGs were filtered by adjusted P < 0.05 and |log2FC| >1. Functional enrichment was performed using Enrichr. Setting: Data were collected from an academic oncology research center, archived on the NCBI Gene Expression Omnibus platform. Patients or Other Participants: Ten adult patients with AML with paired samples (n = 20 total). Inclusion was based on dataset availability and treatment label metadata. No additional selection criteria were applied beyond dataset-defined identifiers. Interventions: All patients received standard induction chemotherapy (details not disclosed in dataset). The analysis was observational and did not involve clinical interventions by the investigators. Main Outcome Measures: Differential gene expression levels pre- and posttreatment; significantly enriched pathways relevant to AML biology. Results: A total of 324 DEGs were identified posttreatment, including 145 upregulated and 179 downregulated genes. Post-treatment upregulation was noted for genes such as CDKN1A, GADD45B, and BCL2A1, implicated in DNA damage response and apoptosis. Downregulated genes included MYC, CDC20, and CCNA2, consistent with suppression of proliferation. Enrichment analysis revealed significant activation of p53 signaling and apoptotic pathways, alongside repression of cell cycle and mitotic progression. Conclusions: Transcriptomic changes in AML following chemotherapy demonstrate a shift from proliferative signaling toward cellular stress and apoptotic regulation. Public data mining can reveal candidate biomarkers of early treatment response. Further validation in prospective studies is warranted before clinical implementation.

Volume

25

First Page

S495

Last Page

S496

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