C/EBPa confers dependence to fatty acid anabolic pathways and vulnerability to lipid oxidative stress-induced ferroptosis in FLT3-mutant leukemia [batch1-3]
While transcription factor C/AAT-enhancer binding protein a (C/EBPa) is critical for normal and leukemic differentiation, its role on cell and metabolic homeostasis is largely unknown in cancer. Here, multi-omics analyses uncovered a coordinated activation of C/EBPa and Fms-like tyrosine kinase 3 (FLT3) that increased lipid anabolism in vivo and in patients with FLT3-mutant acute myeloid leukemia (AML). Mechanistically, C/EBPa regulated FASN-SCD axis to promote fatty acid (FA) biosynthesis and desaturation. We further demonstrated that FLT3 or C/EBPa inactivation decreased mono-unsaturated FAs incorporation to membrane phospholipids through SCD downregulation. Consequently, SCD inhibition enhanced susceptibility to lipid redox stress, which was exploited by combining FLT3 and glutathione peroxidase 4 inhibition to trigger lipid oxidative stress, enhancing ferroptotic death of FLT3-mutant AML cells. Altogether, our study reveals a C/EBPa function in lipid homeostasis and adaptation to redox stress, and a previously unreported vulnerability of FLT3-mutant AML to ferroptosis with promising therapeutic application. Overall design: Total RNA was prepared with GenElute Mammalian Total RNA miniprep (Sigma-Aldrich). RNA quality was evaluated with a Bioanalyzer 2100 (using Agilent RNA6000 nano chip kit, Santa Clara, USA). RNA sequencing library preparation was performed using Illumina TruSeq stranded mRNA protocol. We mapped the reads to the human genome reference “hg38_chr_only_and_herpes.fa” using STAR aligner (STAR v2.6.1a). Base-calling accuracy scores (Phred quality score, Q30) were obtained from demultiplexer bcl2fastq v2.20.. Paired-end reads were aligned to the human reference transcriptome “Homo_sapiens.GRCh38.cdna.all.fa.gz” using Salmon 1.3.0. For mapping, we used salmon quant command with parameters like –gcBias, --useVBOpt, --seqBias, and –validateMappings, correcting specific biases in the sequenced reads and increasing the sensitivity and specificity of the mapping. After mapping, R (R version R version 4.0.2) packages tximport (version 1.14.0) and DESeq2 (version 1.26.0) were used to summarize transcript-level estimate to the gene-level estimates. Further, we used the raw gene-level abundance estimates from salmon to perform to identify differentially expressed genes.