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| Status |
Public on Apr 14, 2026 |
| Title |
Targeting STAT3-Mediated Lipid Metabolism Reprogramming Overcomes Chemoresistance in Acute Myeloid Leukemia |
| Organism |
Homo |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Chemotherapy resistance and intolerance pose significant challenges in the effective treatment of leukemia. Among the distinctive features associated with chemoresistance, metabolic reprogramming emerges as a key factor. In this study, we unveil a novel mechanism contributing to chemoresistance in leukemia, specifically highlighting the pivotal role of altered lipid homeostasis.We found that multiple lipid metabolism processes are aberrantly activated in Ara-C resistant AML cells, with upregulation of JAK-STAT3 signaling pathways and multiple enzymes in the process of fatty acid metabolism. A potent, and highly selective STAT3 inhibitor, W1307, was designed, and exhibited significant anti-tumor activities in vitro and in vivo. Genetic and pharmacological inhibition of STAT3 leads to inhibition of lipid synthesis and catabolism, resulting lipids metabolic disorder. Mechanistically, STAT3 binds to consensus DNA response elements in the promoters of the lipid metabolism associated genes (SREBP1, CPT2) and regulates their expression. Furthermore, inhibition of STAT3 enhances the anti-tumor effect of Ara-C and sensitizes resistant AML cell line to Ara-C through disrupting lipid homeostasis and triggering lipotoxicity. Collectively, our work illuminates the pivotal role of lipid metabolism adaptation driven by STAT3 in chemoresistance. The identification of W1307 as a promising candidate compound underscores its potential as a therapeutic intervention in leukemia treatment and overcoming chemoresistance.
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| Overall design |
Conparative gene expression profiling analysis of RNA-seq data for MOLM-13 and MOLM-13/AR (Ara-C resistant) cells.
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| Contributor(s) |
Peng K, Mo J, Yang Z, Ding W |
| Citation missing |
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| Submission date |
Apr 09, 2026 |
| Last update date |
Apr 14, 2026 |
| Contact name |
Keren Peng |
| E-mail(s) |
pengkr3@mail2.sysu.edu.cn
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| Organization name |
Sun Yat-sen University
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| Street address |
Guangzhou University Town, Panyu District
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| City |
Guangzhou |
| ZIP/Postal code |
510006 |
| Country |
China |
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| Platforms (1) |
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| Samples (4)
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| Relations |
| BioProject |
PRJNA1451102 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE327495_gene_tpm_ALL_SAMPLE.txt.gz |
335.1 Kb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
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