← BioTransfer GEO Dataset Finder
GEO series

Dual STAT3/STAT5 inhibition as a novel treatment strategy in T-prolymphocytic leukemia

GSE286270 Homo sapiens Expression profiling by high throughput sequencing 118 samples 2025/06/16 GPL24676
Summary
T-prolymphocytic leukemia (T-PLL) is a rare, aggressive T-cell malignancy with poor outcomes and an urgent need for new therapeutic approaches. Integrating genomic data and new transcriptomic profiling, we identified recurrent JAK/STAT mutations as a hallmark in T-PLL in an unprecedented cohort of 335 T-PLL cases, predominantly involving JAK3 and STAT5B. In line, transcriptomic and immunoblot analyses revealed constitutive JAK/STAT activation in virtually all samples. Building on these findings, we explored the therapeutic potential of dual STAT3/STAT5 non-PROTAC degraders in T-PLL treatment, with JPX-1244 as our lead substance. JPX-1244 efficiently and selectively induced cell death in primary T-PLL samples, including those resistant to conventional therapies, by blocking STAT3/STAT5 phosphorylation and inducing their degradation. The extent of STAT3/STAT5 degradation directly correlated with cytotoxicity. RNA-sequencing confirmed the downregulation of STAT5 target genes. While JAK/STAT mutations did not predict treatment responses, elevated TOX, PAK6, and SPINT1 expression was associated with drug sensitivity. In a subsequent combination screening, cladribine, venetoclax, and azacytidine emerged as most effective combination partners even in low-responding T-PLL samples, synergistically reducing STAT5 phosphorylation. These findings highlight dual STAT3/STAT5 inhibition, particularly in combination with hypomethylating agents, as a promising therapeutic approach in T-PLL, warranting further preclinical and clinical investigation.
Download
NCBI GEO page ↗ Paper (PMID 40234614) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.