Mutations in IDH induce epigenetic and transcriptional reprogramming, differentiation bias, and susceptibility to mitochondrial inhibitors in cancer cells. Here, we first show that cell lines, PDXs, and patients with acute myeloid leukemia (AML) harboring an IDH mutation displayed an enhanced mitochondrial oxidative metabolism. Along with an increase in TCA cycle intermediates, this AML-specific metabolic behavior mechanistically occurred through the increase in electron transport chain complex I activity, mitochondrial respiration, and methylation-driven CEBPα-induced fatty acid β-oxidation of IDH1 mutant cells. While IDH1 mutant inhibitor reduced 2-HG oncometabolite and CEBPα methylation, it failed to reverse FAO and OxPHOS. These mitochondrial activities were maintained through the inhibition of Akt and enhanced activation of peroxisome proliferator-activated receptor-γ coactivator-1 PGC1α upon IDH1 mutant inhibitor. Accordingly, OxPHOS inhibitors improved anti-AML efficacy of IDH mutant inhibitors in vivo. This work provides a scientific rationale for combinatory mitochondrial-targeted therapies to treat IDH mutant AML patients, especially those unresponsive to or relapsing from IDH mutant inhibitors.

One of the main current challenges in computational biology is to make sense of the huge amounts of multidimensional experimental data that are being produced. For instance, large cohorts of patients are often screened using different high-throughput technologies, effectively producing multiple patient-specific molecular profiles for hundreds or thousands of patients. We propose and implement a network-based method that integrates such patient omics data into Patient Similarity Networks. Topological features derived from these networks were then used to predict relevant clinical features. As part of the 2017 CAMDA challenge, we have successfully applied this strategy to a neuroblastoma dataset, consisting of genomic and transcriptomic data. In particular, we observe that models built on our network-based approach perform at least as well as state of the art models. We furthermore explore the effectiveness of various topological features and observe, for instance, that redundant centrality metrics can be combined to build more powerful models. We demonstrate that the networks inferred from omics data contain clinically relevant information and that patient clinical outcomes can be predicted using only network topological data. This article was reviewed by Yang-Yu Liu, Tomislav Smuc and Isabel Nepomuceno.

By generating protein diversity, alternative splicing provides an important oncogenic pathway. Isocitrate dehydrogenase (IDH) 1 and 2 mutations and 1p/19q co-deletion have become crucial for the novel molecular classification of diffuse gliomas, which also incorporates DNA methylation profiling. In this study, we have carried out a bioinformatics analysis to examine the impact of the IDH mutation, as well as the 1p/19q co-deletion and the glioma CpG island methylator phenotype (G-CIMP) status on alternative splicing in a cohort of 662 diffuse gliomas from The Cancer Genome Atlas (TCGA). We identify the biological processes and molecular functions affected by alternative splicing in the various glioma subgroups and provide evidence supporting the important contribution of alternative splicing in modulating epigenetic regulation in diffuse gliomas. Targeting the genes and pathways affected by alternative splicing might provide novel therapeutic opportunities against gliomas.

Glioblastoma (GBM), the most frequent and aggressive malignant primary brain tumor, is characterized by a highly invasive growth. In our previous study we showed that overexpression of Carboxypeptidase E (CPE) mitigated glioma cell migration. In the present study we aimed at deciphering the regulatory mechanisms of the secreted form of CPE (sCPE). By transcriptome analysis and inhibition of signaling pathways involved in the regulation of cell growth and motility, we discovered that overexpression of sCPE was accompanied by differential regulation of mRNAs connected to the motility-associated networks, among others FAK, PAK, Cdc42, integrin, STAT3 as well as TGF-β. Especially SLUG was downregulated in sCPE-overexpressing glioma cells, paralleled by reduced expression of matrix-metalloproteinases (MMP) and, in consequence, by decreased cell migration. Expression of SLUG was regulated by ERK since inhibition of ERK reverted sCPE-mediated SLUG downregulation and enhanced cell motility. In a mouse glioma model, overexpression of sCPE significantly prolonged survival. Our results implicate a novel role for sCPE that mainly affects the expression of motility-associated genes via several signal pathways.

The introduction of novel frontline agents in multiple myeloma (MM), like immunomodulatory drugs and proteasome inhibitors, has improved the overall survival of patients. Yet, MM is still not curable, and drug resistance (DR) remains the main challenge. To improve the understanding of DR in MM, we established a resistant cell line (MOLP8/R). The exploration of DR mechanisms yielded an overexpression of HIF1α, due to impaired proteasome activity of MOLP8/R. We show that MOLP8/R, like other tumor cells, overexpressing HIF1α, have an increased resistance to the immune system. By exploring the main target genes regulated by HIF1α, we could not show an overexpression of these targets in MOLP8/R. We, however, show that MOLP8/R cells display a very high overexpression of LCP1 gene (l-Plastin) controlled by HIF1α, and that this overexpression also exists in MM patient samples. The l-Plastin activity is controlled by its phosphorylation in Ser5. We further show that the inhibition of l-Plastin phosphorylation restores the sensitivity of MOLP8/R to immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs). Our results reveal a new target gene of DR, controlled by HIF1α.

Early-life adversity covers a range of physical, social and environmental stressors. Acute viral infections in early life are a major source of such adversity and have been associated with a broad spectrum of later-life effects outside the immune system or “off-target”. These include an altered hypothalamus–pituitary–adrenal (HPA) axis and metabolic reactions. Here, we used a murine post-natal day 14 (PND 14) Influenza A (H1N1) infection model and applied a semi-holistic approach including phenotypic measurements, gene expression arrays and diffusion neuroimaging techniques to investigate HPA axis dysregulation, energy metabolism and brain connectivity. By PND 56 the H1N1 infection had been resolved, and there was no residual gene expression signature of immune cell infiltration into the liver, adrenal gland or brain tissues examined nor of immune-related signalling. A resolved early-life H1N1 infection had sex-specific effects. We observed retarded growth of males and altered pre-stress (baseline) blood glucose and corticosterone levels at PND42 after the infection was resolved. Cerebral MRI scans identified reduced connectivity in the cortex, midbrain and cerebellum that were accompanied by tissue-specific gene expression signatures. Gene set enrichment analysis confirmed that these were tissue-specific changes with few common pathways. Early-life infection independently affected each of the systems and this was independent of HPA axis or immune perturbations.