Person: Pochet, Nathalie
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Publication miR-135a-5p-mediated downregulation of protein tyrosine phosphatase receptor delta is a candidate driver of HCV-associated hepatocarcinogenesis
(BMJ Publishing Group, 2018) Van Renne, Nicolaas; Roca Suarez, Armando Andres; Duong, Francois H T; Gondeau, Claire; Calabrese, Diego; Fontaine, Nelly; Ababsa, Amina; Bandiera, Simonetta; Croonenborghs, Tom; Pochet, Nathalie; De Blasi, Vito; Pessaux, Patrick; Piardi, Tullio; Sommacale, Daniele; Ono, Atsushi; Chayama, Kazuaki; Fujita, Masashi; Nakagawa, Hidewaki; Hoshida, Yujin; Zeisel, Mirjam B; Heim, Markus H; Baumert, Thomas F; Lupberger, JoachimBackground and aims HCV infection is a leading risk factor of hepatocellular carcinoma (HCC). However, even after viral clearance, HCC risk remains elevated. HCV perturbs host cell signalling to maintain infection, and derailed signalling circuitry is a key driver of carcinogenesis. Since protein phosphatases are regulators of signalling events, we aimed to identify phosphatases that respond to HCV infection with relevance for hepatocarcinogenesis. Methods: We assessed mRNA and microRNA (miRNA) expression profiles in primary human hepatocytes, liver biopsies and resections of patients with HCC, and analysed microarray and RNA-seq data from paired liver biopsies of patients with HCC. We revealed changes in transcriptional networks through gene set enrichment analysis and correlated phosphatase expression levels to patient survival and tumour recurrence. Results: We demonstrate that tumour suppressor protein tyrosine phosphatase receptor delta (PTPRD) is impaired by HCV infection in vivo and in HCC lesions of paired liver biopsies independent from tissue inflammation or fibrosis. In liver tissue adjacent to tumour, high PTPRD levels are associated with a dampened transcriptional activity of STAT3, an increase of patient survival from HCC and reduced tumour recurrence after surgical resection. We identified miR-135a-5p as a mechanistic regulator of hepatic PTPRD expression in patients with HCV. Conclusions: We previously demonstrated that STAT3 is required for HCV infection. We conclude that HCV promotes a STAT3 transcriptional programme in the liver of patients by suppressing its regulator PTPRD via upregulation of miR-135a-5p. Our results show the existence of a perturbed PTPRD–STAT3 axis potentially driving malignant progression of HCV-associated liver disease.
Publication Transcriptional signature of human pro-inflammatory TH17 cells identifies reduced IL10 gene expression in multiple sclerosis
(Nature Publishing Group UK, 2017) Hu, Dan; Notarbartolo, Samuele; Croonenborghs, Tom; Patel, Bonny; Cialic, Ron; Yang, Tun-Hsiang; Aschenbrenner, Dominik; Andersson, Karin M.; Gattorno, Marco; Pham, Minh; Kivisakk, Pia; Pierre, Isabelle V.; Lee, Youjin; Kiani, Karun; Bokarewa, Maria; Tjon, Emily; Pochet, Nathalie; Sallusto, Federica; Kuchroo, Vijay; Weiner, HowardWe have previously reported the molecular signature of murine pathogenic TH17 cells that induce experimental autoimmune encephalomyelitis (EAE) in animals. Here we show that human peripheral blood IFN-γ+IL-17+ (TH1/17) and IFN-γ−IL-17+ (TH17) CD4+ T cells display distinct transcriptional profiles in high-throughput transcription analyses. Compared to TH17 cells, TH1/17 cells have gene signatures with marked similarity to mouse pathogenic TH17 cells. Assessing 15 representative signature genes in patients with multiple sclerosis, we find that TH1/17 cells have elevated expression of CXCR3 and reduced expression of IFNG, CCL3, CLL4, GZMB, and IL10 compared to healthy controls. Moreover, higher expression of IL10 in TH17 cells is found in clinically stable vs. active patients. Our results define the molecular signature of human pro-inflammatory TH17 cells, which can be used to both identify pathogenic TH17 cells and to measure the effect of treatment on TH17 cells in human autoimmune diseases.
Publication Module Analysis Captures Pancancer Genetically and Epigenetically Deregulated Cancer Driver Genes for Smoking and Antiviral Response
(Elsevier, 2017) Champion, Magali; Brennan, Kevin; Croonenborghs, Tom; Gentles, Andrew J.; Pochet, Nathalie; Gevaert, OlivierThe availability of increasing volumes of multi-omics profiles across many cancers promises to improve our understanding of the regulatory mechanisms underlying cancer. The main challenge is to integrate these multiple levels of omics profiles and especially to analyze them across many cancers. Here we present AMARETTO, an algorithm that addresses both challenges in three steps. First, AMARETTO identifies potential cancer driver genes through integration of copy number, DNA methylation and gene expression data. Then AMARETTO connects these driver genes with co-expressed target genes that they control, defined as regulatory modules. Thirdly, we connect AMARETTO modules identified from different cancer sites into a pancancer network to identify cancer driver genes. Here we applied AMARETTO in a pancancer study comprising eleven cancer sites and confirmed that AMARETTO captures hallmarks of cancer. We also demonstrated that AMARETTO enables the identification of novel pancancer driver genes. In particular, our analysis led to the identification of pancancer driver genes of smoking-induced cancers and ‘antiviral’ interferon-modulated innate immune response. Software availability AMARETTO is available as an R package at https://bitbucket.org/gevaertlab/pancanceramaretto