The clinical and biological characterization of acute myeloid leukemia patients with S100A4 overexpression
- PMID: 36428148
- DOI: 10.1016/j.jfma.2022.11.003
The clinical and biological characterization of acute myeloid leukemia patients with S100A4 overexpression
Abstract
Background/purpose: The S100 family proteins are involved in a variety of important biological processes, most notably immune and inflammatory responses. Their dysregulation also plays a role in the pathogenesis of human cancers. S100A4, also known as metastasin, has long been regarded as a biological marker in tumor progression and metastasis in multiple solid cancers, but its clinical significance in acute myeloid leukemia (AML) has not been extensively studied.
Methods: We retrospectively studied the association between S100A4 gene expression and the clinical characteristics, mutational and transcriptomic profiles of 227 AML patients treated with standard intensive chemotherapy. Genetic mutations of myeloid disease associated genes were analyzed by Sanger sequencing. Microarray-based transcriptomic gene expression profiling was performed on archived bone marrow mononuclear cells. Bioinformatic analyses, including differential gene expression and gene set enrichment analysis, were conducted to delineate the underlying pathogenic mechanisms.
Results: Higher S100A4 expression was associated with older age, monocytic differentiation of leukemic cells, and adverse clinical outcome. S100A4 high-expressors had inferior overall survival and disease-free survival; this finding could be validated in the TCGA AML cohort (both the microarray and RNA-seq platforms). Multivariate Cox regression analysis supported S100A4 as an independent prognostic factor. Bioinformatic analysis showed that AML with higher S100A4 expression was enriched for the interferon, NLRP3 inflammasome, and epithelial-mesenchymal transition pathways.
Conclusion: This study provides evidence that S100A4 overexpression serves as a poor prognostic biomarker in AML, holds potential to guide treatment planning in the clinic, and indicates novel therapeutic directions.
Keywords: Acute myeloid leukemia; Gene expression profiling; Prognosis; S100A4.
Copyright © 2022. Published by Elsevier B.V.
Conflict of interest statement
Declaration of competing interest The authors have no conflicts of interest relevant to this article.
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