Dataset Information

Condensate-promoting ENL mutation induces tumorigenesis via chromatin remodeling [RNA-seq]

ABSTRACT: Gain-of-function mutations in the chromatin ‘reader’ ENL, identified in AML and Wilms tumor, have been shown to induce aberrant formation of transcriptional condensates in cellular systems. However, the precise role of these mutations and their condensate forming property in tumorigenesis remains unclear. By creating a conditional knock-in mouse model for the most prevalent ENL mutation, we establish ENL mutant as a bona fide oncogenic driver of acute myeloid leukemia in vivo. Heterozygous expression of ENL mutant perturbs the normal hematopoietic hierarchy and results in the aberrant expansion of myeloid progenitors with increased self-renewal property. Furthermore, the ENL mutant remodels histone modifications to alter differentiation processes and drive oncogenic gene expression during hematopoietic development. Importantly, targeted point mutagenesis to disrupt the condensate formation property completely abolishes ENL mutant’s oncogenic function in hematopoietic stem and progenitor cells (HSPCs). Lastly, short-term treatment with a small molecule inhibitor that blocks the acetyl-binding activity of ENL mutant reverts its impact on chromatin and significantly delays leukemia development in mice. Our studies reveal the crucial biological function of mutation-induced transcriptional condensates in chromatin regulation and cancer in vivo and provide proof-of-concept for targeting of pathogenic condensates as a promising therapy for certain cancers.

ORGANISM(S): Mus musculus

PROVIDER: GSE239469 | GEO | 2024/04/14

REPOSITORIES: GEO

ACCESS DATA

Shared Molecules

Only show the datasets with similarity scores above: 0.5

Threshold

0.5

Similar Datasets

Project description:Like tobacco smoking, habitual marijuana smoking causes numerous adverse pulmonary effects. However, the mechanisms of action involved, especially as compared to tobacco smoke, are still unclear. To uncover putative modes of action, this study employed a toxicogenomics approach to compare the toxicological pathways perturbed following exposure to marijuana and tobacco smoke condensate in vitro. Condensates of mainstream smoke from hand-rolled tobacco and marijuana cigarettes were similarly prepared using identical smoking conditions. Murine lung epithelial cells were exposed to low, medium and high concentrations of the smoke condensates for 6 hr. RNA was extracted immediately or after a 4-hr recovery period and hybridized to mouse whole genome microarrays. Tobacco smoke condensate (TSC) exposure was associated with changes in xenobiotic metabolism, oxidative stress, inflammation, and DNA damage response. These same pathways were also significantly affected following marijuana smoke condensate (MSC) exposure. Although the effects of the condensates were largely similar, dose-response analysis indicates that the MSC is substantially more potent than TSC. In addition, steroid biosynthesis, apoptosis, and inflammation pathways were more significantly affected following MSC exposure, whereas m-phase cell cycle pathways were more significantly affected following TSC exposure. MSC exposure also appeared to elicit more severe oxidative stress than TSC exposure, which may account for the greater cytotoxicity of MSC. This study shows that in general, MSC impacts many of the same molecular processes as TSC. However, subtle pathway differences can provide insight into the differential toxicities of the two complex mixtures. Murine epithelial lung cells were exposed to tobacco smoke condensates (0, 25, 50, 90 Î¼g/ml) or marijuana smoke condensates (0, 2.5, 5, 10 Î¼g/ml) in serum-free medium for a six hour period. Following the six-hour exposure, cells were either harvested immediately or washed with phosphate-buffered saline and incubated in fresh serum-free medium for a four hour recovery period. Total RNA was extracted from the cells and hybridized against Universal Mouse Reference RNA (Agilent Technologies Canada, Inc.) to Agilent whole mouse genome microarray slides containing 44,000 transcripts. A LOWESS normalization was applied to expression results, and statistically significant genes were identified using the R library MAANOVA. Microarray results were validated by real time RT-PCR.