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MITF controls the TCA cycle to modulate the melanoma hypoxia response

ABSTRACT: In response to the dynamic intra-tumor microenvironment, melanoma cells adopt different phenotypic states possessing distinct biological properties associated with differential expression of the microphthalmia-associated transcription factor (MITF). The response to hypoxia, a major microenvironmental cue, is underpinned by expression of hypoxia-inducible transcription factors (HIFs) that reprogram metabolism and promote pro-angiogenic VEGF expression. HIF1 indirectly represses MITF via the transcription factor bHLHE40/DEC1, and MITF can activate HIF1 expression. Although HIF and MITF share a highly related DNA-binding specificity, it is unclear whether they share a subset of target genes. Moreover, the genome-wide impact of hypoxia on melanoma, which genes are direct HIF targets, and whether melanoma cell lines representing different phenotypic states exhibit distinct hypoxic responses is unknown. Here we show, that three different melanoma cell lines exhibit widely different hypoxia responses with only a core 23 genes regulated in common after 12 h in hypoxia. Surprisingly, under hypoxia MITF is transiently up-regulated by HIF1 and co-regulates a subset of HIF targets including VEGFA. Significantly, we also show that MITF represses itself and also regulates SDHB to control the TCA cycle and suppress pseudo-hypoxia. Our results reveal a previously unsuspected role for MITF in metabolism and the network of factors underpinning the hypoxic response in melanoma.

ORGANISM(S): Homo sapiens

PROVIDER: GSE132624 | GEO | 2019/06/13

REPOSITORIES: GEO

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Project description:Alternative RNA splicing analysis in Hep3B cell cultured under 21% (N1,3,5) or 1.2% (H2,4,6) oxygen Hypoxia is a common characteristic of many solid tumors. The hypoxic microenvironment stabilizes hypoxia-inducible transcription factor 1? (HIF1?) and 2? (HIF2?) to activate gene transcription, which promotes tumor cell survival. 95% of human genes are alternatively spliced, producing RNA isoforms that code functionally distinct proteins. Thus, effective hypoxia response requires increased HIF target gene transcription as well as proper RNA splicing of these HIF target genes. However, it is unclear if and how hypoxia regulates RNA splicing of HIF target genes. This study determined the effects of hypoxia on alternative splicing (AS) of HIF and non-HIF target genes in Hep3B cells and characterized the role of HIF in regulating AS of HIF induced genes. The results indicated that hypoxia generally promotes exon inclusion for hypoxia-induced, but reduces exon inclusion for hypoxia reduced genes. Mechanistically, HIF activity, but not hypoxia per se is found to be necessary and sufficient to increase exon inclusion of several HIF target genes including pyruvate dehydrogenase kinase 1 (PDK1). PDK1 splicing reporters confirmed that transcriptional activation by HIF is sufficient to increase exon inclusion of PDK1 splicing reporter. In contrast, transcriptional activation of the PDK1 minigene by other transcription factor in the absence of endogenous HIF target gene activation fails to alter PDK1 RNA splicing, demonstrating a novel role of HIF target gene(s) in regulating RNA splicing of HIF target genes. Implications:This study demonstrates a novel function of HIF in regulating RNA splicing of HIF target genes. We analyzed total RNA from Hep3B cells cultured under 21% (N1,3,5) or 1.2% (H2,4,6) oxygen using the Affymetrix Human Exon 1.0 ST platform. Array data was processed by Altanalyze software version 2.0.7. Techinical replicates were performed for Nx and Hx treated Hep3B cells

Project description:This a model from the article: Hypoxia-dependent sequestration of an oxygen sensor by a widespread structural motif can shape the hypoxic response - a predictive kinetic model Bernhard Schmierer, Béla Novák1 and Christopher J Schofield BMC Systems Biology2010, 4:139 20955552, Abstract: Background The activity of the heterodimeric transcription factor hypoxia inducible factor (HIF) is regulated by the post-translational, oxygen-dependent hydroxylation of its α-subunit by members of the prolyl hydroxylase domain (PHD or EGLN)-family and by factor inhibiting HIF (FIH). PHD-dependent hydroxylation targets HIFα for rapid proteasomal degradation; FIH-catalysed asparaginyl-hydroxylation of the C-terminal transactivation domain (CAD) of HIFα suppresses the CAD-dependent subset of the extensive transcriptional responses induced by HIF. FIH can also hydroxylate ankyrin-repeat domain (ARD) proteins, a large group of proteins which are functionally unrelated but share common structural features. Competition by ARD proteins for FIH is hypothesised to affect FIH activity towards HIFα; however the extent of this competition and its effect on the HIF-dependent hypoxic response are unknown. Results To analyse if and in which way the FIH/ARD protein interaction affects HIF-activity, we created a rate equation model. Our model predicts that an oxygen-regulated sequestration of FIH by ARD proteins significantly shapes the input/output characteristics of the HIF system. The FIH/ARD protein interaction is predicted to create an oxygen threshold for HIFα CAD-hydroxylation and to significantly sharpen the signal/response curves, which not only focuses HIFα CAD-hydroxylation into a defined range of oxygen tensions, but also makes the response ultrasensitive to varying oxygen tensions. Our model further suggests that the hydroxylation status of the ARD protein pool can encode the strength and the duration of a hypoxic episode, which may allow cells to memorise these features for a certain time period after reoxygenation. Conclusions The FIH/ARD protein interaction has the potential to contribute to oxygen-range finding, can sensitise the response to changes in oxygen levels, and can provide a memory of the strength and the duration of a hypoxic episode. These emergent properties are predicted to significantly shape the characteristics of HIF activity in animal cells. We argue that the FIH/ARD interaction should be taken into account in studies of the effect of pharmacological inhibition of the HIF-hydroxylases and propose that the interaction of a signalling sensor with a large group of proteins might be a general mechanism for the regulation of signalling pathways. There are there models described in the paper. 1) Skeleton Model 1 (SKM1) - HIFα CAD-hydroxylation in the absence of the FIH/AR-interaction. 2) Skeleton Model 2 (SKM2) - FIG sequestration by ARD proteins and oxygen-dependent FIH-release. 3) Full Model (Fusion of SKM1 and SKM2) - the effects of the FIH/ARD proteins interaction on HIFα CAD-hydroxylation. This model corresponds to the "Full Model" described in the paper. The model reproduces figure 5 of the publication. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team. For more information see the terms of use. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

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MITF controls the TCA cycle to modulate the melanoma hypoxia response

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