PubMed HealthSearch

SEARCH · PubMed Health

Results for “NFATc1”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

2 recordsLinked to original sources

NFATc1 drives Orai3 transcription and proteolysis by harnessing epigenome differences in the MARCH8 promoter.

Several autonomous mechanisms regulate protein expression, such as transcription, translation, post-translational modifications, and epigenetic changes. Rarely, these processes are controlled by the same molecular player with overlapping roles. Here, we reveal that transcription factor NFATc1 regulates both transcription and degradation of the Ca2+ channel Orai3 in a context-dependent manner. We demonstrate that NFATc1 drives Orai3 transcription in non-metastatic pancreatic cancer cells. In invasive and metastatic pancreatic cancer cells, NFATc1 induces Orai3 lysosomal degradation by transcriptionally enhancing MARCH8 E3-ubiquitin ligase. We show that MARCH8 physically interacts with Orai3 intracellular loop eventually resulting in its ubiquitination at the N-terminal. Mechanistically, the dichotomy in the regulation of Orai3 expression emerges from the differences in MARCH8 epigenetic landscape. We uncover that MARCH8 promoter is hyper-methylated in non-metastatic cells. Importantly, we demonstrate that MARCH8 restricts pancreatic cancer metastasis by targeting Orai3 degradation, thereby highlighting the pathophysiological importance of this signaling module. Taken together, we report a unique and clinically relevant scenario wherein the same transcription factor both enhances and curtails the expression of a target protein in cancer.

Humans

Bayesian identification of differentially expressed isoforms using a novel joint model of RNA-seq data.

We develop a Bayesian approach, BayesIso, to identify differentially expressed isoforms from RNA-seq data. The approach features a novel joint model of the sample variability and the deferential state of isoforms. Specifically, the within-sample variability and the between-sample variability of each isoform are modeled by a Poisson-Lognormal model and a Gamma-Gamma model, respectively. Using a Bayesian framework, the differential state of each isoform and the model parameters are jointly estimated by a Markov Chain Monte Carlo (MCMC) method. Extensive studies using simulation and real data demonstrate that BayesIso can effectively detect isoforms of less differentially expressed and differential transcripts for genes with multiple isoforms. We applied the approach to breast cancer RNA-seq data and uncovered a unique set of isoforms that form key pathways associated with breast cancer recurrence. First, PI3K/AKT/mTOR signaling and PTEN signaling pathways are identified as being involved in breast cancer development. Further integrated with protein-protein interaction data, pathways of Jak-STAT, mTOR, MAPK and Wnt signaling are revealed in association with breast cancer recurrence. Finally, several pathways are activated in the early recurrence of breast cancer. In tumors that occur early, members of pathways of cellular metabolism and cell cycle (such as CD36 and TOP2A) are upregulated, while immune response genes such as NFATC1 are downregulated.

Humans