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ACSL4 mediated H3K9 and H3K27 hyperacetylation upregulates SNAIL to drive TNBC metastasis

GSE283282 Homo sapiens Expression profiling by high throughput sequencing 9 samples Submitted 2024/12/20 Platform GPL24676
Summary
Triple-Negative Breast Cancer (TNBC) has profound unmet medical need globally for its devastating clinical outcome associated with rapid metastasis and lack of targeted therapies. Recently, lipid metabolic reprogramming especially fatty acid oxidation (FAO) has emerged as a major driver of breast cancer metastasis. Analyzing the expression of major FAO regulatory genes in breast cancer, we found selective overexpression of acyl-CoA synthetase 4 (ACSL4) in TNBC, which is primarily attributed by the absence of progesterone receptor (PR). Loss of ACSL4 function, by genetic ablation or pharmacological inhibition significantly reduces metastatic potential of TNBC. Global transcriptome analysis reveals that ACSL4 activity positively influences the gene expression related to TNBC migration and invasion. Mechanistically, ACSL4 modulates FAO and intracellular acetyl-CoA levels, leading to hyper-acetylation of particularly H3K9ac and H3K27ac marks resulting in overexpression of SNAIL during the course of TNBC metastatic spread to lymph node and lung. Further, human TNBC metastasis exhibits positive correlation among ACSL4, H3K9ac, H3K27ac, and SNAIL expression. Altogether, our findings provide new molecular insights regarding the intricate interplay between metabolic alterations and epigenetic modifications, intertwined to orchestrate TNBC metastasis and posit a rational understanding for the development of ACSL4 inhibitors as a targeted therapy against TNBC.
Published in
ACSL4-mediated H3K9 and H3K27 hyperacetylation upregulates SNAIL to drive TNBC metastasis
Sinha A, Saini KK, Chandramouli A et al. · Proceedings of the National Academy of Sciences of the United States of America 2024 · PMID 39700137 · doi:10.1073/pnas.2408049121
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Also filed as BioProject PRJNA1193020 and SRA study SRP548670. Searching any of these in the dataset finder brings you back here.

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