Functional analysis of STAT3 activating mutations in LGL leukemia reveals epigenetic reprograming and therapeutic vulnerabilities. Free

STAT3 activating mutations, present in 40-70% of large granular lymphocytic leukemia (LGLL) patients, are associated with worse prognosis and inferior response to standard therapies. Once activated, STAT3 forms dimers and enters the nucleus to function as a transcription factor, though its impact on chromatin architecture in LGLL remains unclear. To study if the STAT3 mutations seen in LGLL patients directly effects STAT3 binding to DNA, we performed STAT3 chromatin immunoprecipitation (ChIP), followed by sequencing (ChIP-seq), to indentify STAT3 bound DNA segements. Patient samples used for CHIP sequencing were sorted CD3+CD8+CD5-/dim cells from healthy donors (HD; N=2), LGLL patient samples with wildtype STAT3 (STAT3^WT; N=9), and mutated STAT3 (STAT3^MUT; N=14). Compared to HD, LGLL patients had a 2-fold increase in STAT3 bound peaks. Differential analysis between STAT3^WT and STAT3^MUT patients revealed significant differences between the cohorts. A significant increase in binding occurred in 206 genes in the STAT3^MUT group, including including GZMB, NLRC5, and ROCK1(adjusted p-values respectively: 0.001, 0.0042, and 0.0049). Furthermore, MEME-chip comprehensive motif analysis was performed to discover unique motifs in the STAT3^MUT group. These unique motifs were quered with the TOMTOM motif comparison tool to find transcription factors with similar motifs including but not limited to: CDX2 (p = 0.0039), RELB (p = 0.0009), and RARB (p = 0.0012). To study the functional impact of STAT3 mutations in LGLL, we used CRISPR/Cas9 to introduce specific endogenous knock-ins into the wildtype STAT3-expressing MOTN1 LGLL cell line. Using MOTN1 cells we established an isogenic model of 3 most prevalent mutations (Y640F, D661V, and D661Y). After transfection, we perfomed single cell cloning in 96-well plates by FACS sorting single cell/wells containing murine OP9 feeder cells. The expanded clones were confirmed for mutations via Sanger sequencing and STAT3 activation through immunoblotting. Our confirmation analysis shows that the isogenic lines (9 STAT3^MUT lines [4 STAT3^Y640F, 1 STAT3^D661V, 4 STAT3^D661Y] and 3 mock-transfected STAT3^WT clones) were generated for all further use. These clones with specific STAT3 mutations exhibited consistent STAT3 phosphorylation across all three mutations in comparison to STAT^WT lines that showed no detectable p-STAT3. Furthermore, nuclear fractions of STAT3^MUT lines were tested by STAT3 nuclear factor activity assay and showed higher STAT3 activity when compared to STAT3^WT. STAT3^Y640F showed the highest increase of activity compared to STAT3^WT (p= 0.0005), followed by STAT3^D661Y (p= 0.0077), and STAT3^D661V (p= 0.0407). Stimulation of these clones with IL-15 leads to an increase in STAT3 phosphorylation and longer retention of pSTAT3 in mutated LGLL which closely resembles the activity of patient samples with mutated STAT3. STAT3^MUT lines have significant increase in 5-methylcytosine levels (p < 0.001), showing higher global DNA methylation than STAT3^WT. GFP-luciferase was transduced into the isogenic lines to make a xenograft model in NSG mice. IVIS imaging revealed that STAT3^WT had higher tumor burden than the mice engrafted with STAT3^MUT. This phenotype was amplified in xenografts using NSG-tg(Hu IL-15) mice. Growth dynamics were assessed through in vitro and in vivo competition assays using differentially labeled STAT3^WT and STAT3^MUT cells. In vivo competition assays were done in NSG peritoneal cavities. Equal growth between STAT^WT and STAT^MUT were observed, with the exception of STAT3^Y640F which was significantly outgrown by the STAT3^WT line. Differential analysis of transcriptome using RNA-seq between STAT3^MUT and STAT3^WT revealed 38 differentially expressed genes that have the potential to worsen disease severity in patients like PDGFB (adjusted p-value = 0.002) and YAP1 (adjusted p-value < 0.001). The list of 38 genes was cross-reference to the Drug-Gene Interaction database (DGIdb) find potential drugs that could have differential effects on LGLL with and without STAT3 mutations. One of those drugs is the kinase inhibitor Sorafenib which decrease cell viability and proliferation in STAT3^Mut lines. These findings provide mechanistic insight into how STAT3 activating mutations alter transcriptional activity, epigenetic regulation, and tumor behavior in LGLL, while identifying potential therapeutic vulnerabilities that could guide precision treatment strategies.