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Hematopoietic differentiation is driven by transcription factors, which orchestrate a finely tuned transcriptional network. At bipotential branching points lineage decisions are made, where key transcription factors initiate cell type-specific gene expression programs. These programs are stabilized by the epigenetic activity of recruited chromatin-modifying cofactors. An example is the association of the transcription factor RUNX1 with protein arginine methyltransferase 6 (PRMT6) at the megakaryocytic/erythroid bifurcation. However, little is known about the specific influence of PRMT6 on this important branching point. Here, we show that PRMT6 inhibits erythroid gene expression during megakaryopoiesis of primary human CD34+ progenitor cells. PRMT6 is recruited to erythroid genes, such as glycophorin A. Consequently, a repressive histone modification pattern with high H3R2me2a and low H3K4me3 is established. Importantly, inhibition of PRMT6 by shRNA or small molecule inhibitors leads to upregulation of erythroid genes and promotes erythropoiesis. Our data reveal that PRMT6 plays a role in the control of erythroid/megakaryocytic differentiation and open up the possibility that manipulation of PRMT6 activity could facilitate enhanced erythropoiesis for therapeutic use.
The transcription factor Tal1 is a critical activator or repressor of gene expression in hematopoiesis and leukaemia. The mechanism by which Tal1 differentially influences transcription of distinct genes is not fully understood. Here we show that Tal1 interacts with the peptidylarginine deiminase IV (PADI4). We demonstrate that PADI4 can act as an epigenetic coactivator through influencing H3R2me2a. At the Tal1/PADI4 target gene IL6ST the repressive H3R2me2a mark triggered by PRMT6 is counteracted by PADI4, which augments the active H3K4me3 mark and thus increases IL6ST expression. In contrast, at the CTCF promoter PADI4 acts as a repressor. We propose that the influence of PADI4 on IL6ST transcription plays a role in the control of IL6ST expression during lineage differentiation of hematopoietic stem/progenitor cells. These results open the possibility to pharmacologically influence Tal1 in leukaemia.
Toxicogenomic differentiation of functional responses to fipronil and imidacloprid in Daphnia magna
(2021)
Active substances of pesticides, biocides or pharmaceuticals can induce adverse side effects in the aquatic ecosystem, necessitating environmental hazard and risk assessment prior to substance registration. The freshwater crustacean Daphnia magna is a model organism for acute and chronic toxicity assessment representing aquatic invertebrates. However, standardized tests involving daphnia are restricted to the endpoints immobility and reproduction and thus provide only limited insights into the underlying modes-of-action. Here, we applied transcriptome profiling to a modified D. magna Acute Immobilization test to analyze and compare gene expression profiles induced by the GABA-gated chloride channel blocker fipronil and the nicotinic acetylcholine receptor (nAChR) agonist imidacloprid. Daphnids were expose to two low effect concentrations of each substance followed by RNA sequencing and functional classification of affected gene ontologies and pathways. For both insecticides, we observed a concentration-dependent increase in the number of differentially expressed genes, whose expression changes were highly significantly positively correlated when comparing both test concentrations. These gene expression fingerprints showed virtually no overlap between the test substances and they related well to previous data of diazepam and carbaryl, two substances targeting similar molecular key events. While, based on our results, fipronil predominantly interfered with molecular functions involved in ATPase-coupled transmembrane transport and transcription regulation, imidacloprid primarily affected oxidase and oxidoreductase activity. These findings provide evidence that systems biology approaches can be utilized to identify and differentiate modes-of-action of chemical stressors in D. magna as an invertebrate aquatic non-target organism. The mechanistic knowledge extracted from such data will in future contribute to the development of Adverse Outcome Pathways (AOPs) for read-across and prediction of population effects.
Purpose: Preoperative (neoadjuvant) chemoradiotherapy (CRT) and total mesorectal excision is the standard treatment for rectal cancer patients (UICC stage II/III). Up to one-third of patients treated with CRT achieve a pathological complete response (pCR). These patients could be spared from surgery and its associated morbidity and mortality, and assigned to a “watch and wait” strategy. However, reliably identifying pCR based on clinical or imaging parameters remains challenging.
Experimental design: We generated gene-expression profiles of 175 patients with locally advanced rectal cancer enrolled in the CAO/ARO/AIO-94 and -04 trials. One hundred and sixty-one samples were used for building, training and validating a predictor of pCR using a machine learning algorithm. The performance of the classifier was validated in three independent cohorts, comprising 76 patients from (i) the CAO/ARO/AIO-94 and -04 trials (n = 14), (ii) a publicly available dataset (n = 38) and (iii) in 24 prospectively collected samples from the TransValid A trial.
Results: A 21-transcript signature yielded the best classification of pCR in 161 patients (Sensitivity: 0.31; AUC: 0.81), when not allowing misclassification of non-complete-responders (False-positive rate = 0). The classifier remained robust when applied to three independent datasets (n = 76).
Conclusion: The classifier can identify >1/3 of rectal cancer patients with a pCR while never classifying patients with an incomplete response as having pCR. Importantly, we could validate this finding in three independent datasets, including a prospectively collected cohort. Therefore, this classifier could help select rectal cancer patients for a “watch and wait” strategy.
Translational relevance: Forgoing surgery with its associated side effects could be an option for rectal cancer patients if the prediction of a pathological complete response (pCR) after preoperative chemoradiotherapy would be possible. Based on gene-expression profiles of 161 patients a classifier was developed and validated in three independent datasets (n = 76), identifying over 1/3 of patients with pCR, while never misclassifying a non-complete-responder. Therefore, the classifier can identify patients suited for “watch and wait”.