KDM6A Regulates Cell Plasticity and Pancreatic Cancer Progression by Non-Canonical Activin Pathway

BACKGROUND & AIMS: Inactivating mutations of KDM6A, a histone demethylase, were frequently found in pancreatic ductal adenocarcinoma (PDAC). We investigated the role of KDM6A in PDAC development. METHODS: We performed a pancreatic tissue microarray analysis of KDM6A protein levels. We used human PDAC cell lines for KDM6A knockout and knockdown experiments. We performed Bru-seq analysis to elucidate the effects of KDM6A loss on global transcription. We performed studies with Ptf1a(Cre); LSL-Kras(G12D); Trp53(R172H/+); Kdm6a(fl/fl or fl/Y), Ptf1a(Cre); Kdm6a(fl/fl or fl/Y), and orthotopic xenograft mice to investigate the impacts of Kdm6a deficiency on pancreatic tumorigenesis and pancreatitis. RESULTS: Loss of KDM6A was associated with metastasis in PDAC patients. Bru-seq analysis revealed upregulation of the epithelial-mesenchymal transition pathway in PDAC cells deficient of KDM6A. Loss of KDM6A promoted mesenchymal morphology, migration, and invasion in PDAC cells in vitro. Mechanistically, activin A and subsequent p38 activation likely mediated the role of KDM6A loss. Inhibiting either activin A or p38 reversed the effect. Pancreas-specific Kdm6a-knockout mice pancreata demonstrated accelerated PDAC progression, developed a more aggressive undifferentiated type PDAC, and increased metastases in the background of Kras and p53 mutations. Kdm6a-deficient pancreata in a pancreatitis model had a delayed recovery with increased PDAC precursor lesions compared to wild-type pancreata. CONCLUSIONS: Loss of KDM6A accelerates PDAC progression and metastasis, most likely by a non-canonical p38-dependant activin A pathway. KDM6A also promotes pancreatic tissue recovery from pancreatitis. Activin A might be utilized as a therapeutic target for KDM6A-deficient PDACs

Abnormal RNA Stability in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) share key features, including accumulation of the RNA-binding protein TDP-43. TDP-43 regulates RNA homeostasis, but it remains unclear whether RNA stability is affected in these disorders. We use Bru-seq and BruChase-seq to assess genome-wide RNA stability in ALS patient-derived cells, demonstrating profound destabilization of ribosomal and mitochondrial transcripts. This pattern is recapitulated by TDP-43 overexpression, suggesting a primary role for TDP-43 in RNA destabilization, and in postmortem samples from ALS and FTD patients. Proteomics and functional studies illustrate corresponding reductions in mitochondrial components and compensatory increases in protein synthesis. Collectively, these observations suggest that TDP-43 deposition leads to targeted RNA instability in ALS and FTD, and may ultimately cause cell death by disrupting energy production and protein synthesis pathways

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Validating ocean general circulation models via Lagrangian particle simulation and data from drifting buoys

International Conference on Computational Science (ICCS) (19.2019.Faro,Portugal). In Computational Science – ICCS 2019. Lecture Notes in Computer Science, vol 11539. ISBN 978-3-030-22747-0; 978-3-030-22746-3Drifting Fish Aggregating Devices (dFADs) are small drifting platforms with an attached solar powered buoy that report their position with daily frequency via GPS. We use data of 9,440 drifting objects provided by a buoys manufacturing company, to test the predictions of surface current velocity provided by two of the main models: the NEMO model used by Copernicus Marine Environment Monitoring Service (CMEMS) and the HYCOM model used by the Global Ocean Forecast System (GOFS).Depto. de Física TeóricaFac. de Ciencias FísicasTRUEpu

Capturing the dynamic nascent transcriptome during acute cellular responses: The serum response

Dynamic regulation of gene expression via signal transduction pathways is of fundamental importance during many biological processes such as cell state transitioning, cell cycle progression and stress responses. In this study we used serum stimulation as a cell response paradigm to apply the nascent RNA Bru-seq technique in order to capture early dynamic changes in the nascent transcriptome. Our data provides an unprecedented view of the dynamics of genome-wide transcription during the first two hours of serum stimulation in human fibroblasts. While some genes showed sustained induction or repression, other genes showed transient or delayed responses. Surprisingly, the dynamic patterns of induction and suppression of response genes showed a high degree of similarity, suggesting that these opposite outcomes are triggered by a common set of signals. As expected, early response genes such as those encoding components of the AP-1 transcription factor and those involved in the circadian clock were immediately but transiently induced. Surprisingly, transcription of important DNA damage response genes and histone genes were rapidly repressed. We also show that RNA polymerase II accelerates as it transcribes large genes and this was independent of whether the gene was induced or not. These results provide a unique genome-wide depiction of dynamic patterns of transcription of serum response genes and demonstrate the utility of Bru-seq to comprehensively capture rapid and dynamic changes of the nascent transcriptome

Gene length as a biological timer to establish temporal transcriptional regulation

<p>Transcriptional timing is inherently influenced by gene length, thus providing a mechanism for temporal regulation of gene expression. While gene size has been shown to be important for the expression timing of specific genes during early development, whether it plays a role in the timing of other global gene expression programs has not been extensively explored. Here, we investigate the role of gene length during the early transcriptional response of human fibroblasts to serum stimulation. Using the nascent sequencing techniques Bru-seq and BruUV-seq, we identified immediate genome-wide transcriptional changes following serum stimulation that were linked to rapid activation of enhancer elements. We identified 873 significantly induced and 209 significantly repressed genes. Variations in gene size allowed for a large group of genes to be simultaneously activated but produce full-length RNAs at different times. The median length of the group of serum-induced genes was significantly larger than the median length of all expressed genes, housekeeping genes, and serum-repressed genes. These gene length relationships were also observed in corresponding mouse orthologs, suggesting that relative gene size is evolutionarily conserved. The sizes of transcription factor and microRNA genes immediately induced after serum stimulation varied dramatically, setting up a cascade mechanism for temporal expression arising from a single activation event. The retention and expansion of large intronic sequences during evolution have likely played important roles in fine-tuning the temporal expression of target genes in various cellular response programs.</p

KDM6A Loss Recruits Tumor-Associated Neutrophils and Promotes Neutrophil Extracellular Trap Formation in Pancreatic Cancer

UNLABELLED: Lysine (K)-specific demethylase 6A (KDM6A) is a frequently mutated tumor suppressor gene in pancreatic ductal adenocarcinoma (PDAC). However, the impact of KDM6A loss on the PDAC tumor immune microenvironment is not known. This study used a genetically engineered, pancreas-specific Kdm6a knockout (KO) PDAC mouse model and human PDAC tissue samples to demonstrate that KDM6A loss correlates with increased tumor-associated neutrophils and neutrophil extracellular traps (NET) formation, which are known to contribute to PDAC progression. Genome-wide bromouridine sequencing analysis to evaluate nascent RNA synthesis showed that the expression of many chemotactic cytokines, especially CXC motif chemokine ligand 1 (CXCL1), was upregulated in KDM6A KO PDAC cells. KDM6A-deficient PDAC cells secreted higher levels of CXCL1 protein, which in turn recruited neutrophils. Furthermore, in a syngeneic orthotopic mouse model, treatment with a CXCL1 neutralizing antibody blocked the chemotactic and NET-promoting properties of KDM6A-deficient PDAC cells and suppressed tumor growth, confirming CXCL1 as a key mediator of chemotaxis and PDAC growth driven by KDM6A loss. These findings shed light on how KDM6A regulates the tumor immune microenvironment and PDAC progression and suggests that the CXCL1-CXCR2 axis may be a candidate target in PDAC with KDM6A loss. SIGNIFICANCE: KDM6A loss in pancreatic cancer cells alters the immune microenvironment by increasing CXCL1 secretion and neutrophil recruitment, providing a rationale for targeting the CXCL1-CXCR2 signaling axis in tumors with low KDM6A