← BioTransfer GEO Dataset Finder
GEO series

Evolution of transcriptomic profiles in relapsed inv(16) acute myeloid leukemia

GSE254098 Homo sapiens Expression profiling by high throughput sequencing 13 samples 2026/06/30 GPL24676
Summary
Acute myeloid leukemia (AML) with inv(16) is typically associated to a favourable prognosis. However, up to 40% of patients will eventually experience disease relapse. Herein, we dissected the transcriptomic profile of AML with inv(16) to identify potential prognostic markers and devise novel therapeutic vulnerabilities. Sequencing data from 222 diagnostic samples, including 44 relapse/refractory patients, revealed the presence of a median of 1 concomitant additional mutation, cooperating with inv(16) in leukemogenesis. Notably, the mutational landscape at diagnosis did not significantly differ between patients experiencing primary induction failure or relapse when compared to the rest of the cohort, except for an increase in the mutational burden in the relapse/refractory group. RNA-Seq of unpaired diagnostic and relapse) samples allowed the identification of oxidative phosphorylation (OXPHOS) as one of the most significantly downregulated pathways at relapse. Considering that OXPHOS could be targeted by Venetoclax/Azacitidine combination, we explored its biological effects on ME-1 inv(16) cell-line, but there was no additional advantage in terms of proliferation suppression over Azacitidine alone. To enhance Venetoclax efficacy, we tested the in vitro effects of Metformin as a potential drug able to enhance chemosensitivity of AML cells by inhibiting the mitochondrial transfer. By challenging ME-1 with this combination, we observed a significant synergistic interaction at least similar to that of Venetoclax/Azacitidine. In conclusion, the study of transcriptomic features of inv(16) at relapse unveiled OXPHOS as a potential target in this subset. The use of specific metabolic-oriented and synthetic lethal approaches (e.g., Venetoclax/Metformin) provided a rationale for its future clinical use.
Download
NCBI GEO page ↗ {# 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.