Transcriptomics

Dataset Information

0

Loss of UTX/KDM6A and the activation of FGFR3 converge to regulate differentiation gene expression programs in bladder cancer [RNA-seq]


ABSTRACT: Bladder cancer prognosis is closely linked to the underlying differentiation state of the tumor, ranging from the less aggressive and most differentiated luminal tumors to the more aggressive and least differentiated basal tumors. Sequencing of bladder cancer has revealed that loss-of-function mutations in chromatin regulators and mutations that activate receptor tyrosine kinase (RTK) signaling frequently occur in bladder cancer. However, little is known as to whether and how these two types of mutations functionally interact or cooperate to regulate tumor growth and differentiation state. Here, we focus on loss of the histone demethylase UTX (also known as KDM6A) and activation of the RTK FGFR3, two events that commonly co-occur in muscle invasive bladder tumors. We show that UTX loss and FGFR3 activation cooperate to disrupt the balance of luminal and basal gene expression in bladder cells. UTX localized to enhancers surrounding many genes that are important for luminal cell fate, and supported the transcription of these genes in a catalytic-independent manner. In contrast to UTX, FGFR3 activation was associated with lower expression of luminal genes in tumors and FGFR inhibition increased transcription of these same genes in cell culture models. This suggests an antagonistic relationship between UTX and FGFR3. In support of this model, UTX loss-of-function potentiated FGFR3-dependent transcriptional effects and the presence of UTX blocked an FGFR3-mediated increase in the colony formation of bladder cells. Taken together, our study reveals how mutations in UTX and FGFR3 converge to disrupt bladder differentiation programs that could serve as a therapeutic target.

ORGANISM(S): Homo sapiens

PROVIDER: GSE157089 | GEO | 2020/09/15

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2020-09-15 | GSE157090 | GEO
2021-12-31 | GSE151888 | GEO
2014-09-12 | E-GEOD-61352 | biostudies-arrayexpress
2014-09-12 | GSE61352 | GEO
2023-10-10 | GSE244957 | GEO
2020-03-30 | GSE133192 | GEO
2013-11-19 | E-GEOD-52452 | biostudies-arrayexpress
2012-11-07 | E-GEOD-41035 | biostudies-arrayexpress
2015-06-19 | E-GEOD-64572 | biostudies-arrayexpress
2015-06-19 | E-GEOD-64279 | biostudies-arrayexpress