Control of anterior GRadient 2 (AGR2) dimerization links endoplasmic reticulum proteostasis to inflammation

International audienceAnterior gradient 2 (AGR2) is a dimeric protein disulfide isomerase family member involved in the regulation of protein quality control in the endoplasmic reticulum (ER). Mouse AGR2 deletion increases intestinal inflammation and promotes the development of inflammatory bowel disease (IBD). Although these biological effects are well established, the underlying molecular mechanisms of AGR2 function toward inflammation remain poorly defined. Here, using a protein-protein interaction screen to identify cellular regulators of AGR2 dimerization, we unveiled specific enhancers, including TMED2, and inhibitors of AGR2 dimerization, that control AGR2 functions. We demonstrate that modulation of AGR2 dimer formation, whether enhancing or inhibiting the process, yields pro-inflammatory phenotypes, through either autophagy-dependent processes or secretion of AGR2, respectively. We also demonstrate that in IBD and specifically in Crohn's disease, the levels of AGR2 dimerization modulators are selectively deregulated, and this correlates with severity of disease. Our study demonstrates that AGR2 dimers act as sensors of ER homeostasis which are disrupted upon ER stress and promote the secretion of AGR2 monomers. The latter might represent systemic alarm signals for pro-inflammatory responses

Application of an Integrative Computational Framework in Trancriptomic Data of Atherosclerotic Mice Suggests Numerous Molecular Players

Atherosclerosis is a multifactorial disease involving a lot of genes and proteins recruited throughout its manifestation. The present study aims to exploit bioinformatic tools in order to analyze microarray data of atherosclerotic aortic lesions of ApoE knockout mice, a model widely used in atherosclerosis research. In particular, a dynamic analysis was performed among young and aged animals, resulting in a list of 852 significantly altered genes. Pathway analysis indicated alterations in critical cellular processes related to cell communication and signal transduction, immune response, lipid transport, and metabolism. Cluster analysis partitioned the significantly differentiated genes in three major clusters of similar expression profile. Promoter analysis applied to functional related groups of the same cluster revealed shared putative cis-elements potentially contributing to a common regulatory mechanism. Finally, by reverse engineering the functional relevance of differentially expressed genes with specific cellular pathways, putative genes acting as hubs, were identified, linking functionally disparate cellular processes in the context of traditional molecular description

Gene Expression Analysis of Fibroblasts from Patients with Bipolar Disorder

Bipolar disorder is a severe, lifelong psychiatric disease. The main underlying pathophysiology of the disease is still incomprehensible. Various studies have suggested that many genes of small impact in combination with environmental factors contribute to the expression of the disease. In this study comparative transcriptomic profiling to characterize skin fibroblasts’ gene expression of bipolar disorder patients compared to healthy controls has been performed. Skin fibroblast cells from bipolar disorder patients (n=10) and marched healthy controls (n=5) have been cultured. RNA was extracted and then hybridized onto Illumina Human HT-12 v4 Expression BeadChips. Differentially expressed genes between bipolar disorder samples and healthy controls were identified by performing unequal t-test on log 2 transformed expression values. The resulting gene list was obtained by setting the p-value threshold to 0.05 and by removing genes that presented a fold change ≥ |0.5| (in log 2 scale). We concluded to 457 differentially expressed genes. Among them 127 showed an upregulation and 330 were downregulated. Τhe expression alterations of selected genes were validated by quantitative real-time polymerase chain reaction. In order to derive better insight into the biological mechanisms related to the differentially expressed genes, the lists of significant genes were subjected to pathway analysis and target prioritization indicating various processes such as calcium ion homeostasis, positive regulation of apoptotic process and cellular response to retinoic acid

Integrative Bioinformatic Analysis of a Greek Epidemiological Cohort Provides Insight into the Pathogenesis of Primary Cutaneous Melanoma

Part 1: Medical Artificial Intelligence Modeling (MAIM)International audienceMelanoma is the most lethal type of skin cancer. In this study for the first time we analyze a Greek cohort of primary cutaneous melanoma biopsies, subjected to whole exome sequencing, in order to derive their mutational profile landscape. Moreover, in the context of big data analytical methodologies, we integrated the results of the exome sequencing analysis with transcriptomic data of cutaneous melanoma from GEO, in an attempt to perform a multi-layered analysis and infer a tentative disease network for primary melanoma pathogenesis. The purpose of this research is to incorporate different levels of molecular data, so as to expand our understanding of cutaneous melanoma and the broader molecular network implicated with this type of cancer. Overall, we showed that the results of the integrative analysis offer deeper insight in the underlying mechanisms affected by melanoma and could potentially contribute to the valuable effective epidemiological characterization of this disease

Dissecting the Mutational Landscape of Cutaneous Melanoma: An Omic Analysis Based on Patients from Greece

Melanoma is a lethal type of skin cancer, unless it is diagnosed early. Formalin-fixed, paraffin-embedded (FFPE) tissue is a valuable source for molecular assays after diagnostic examination, but isolated nucleic acids often suffer from degradation. Here, for the first time, we examine primary melanomas from Greek patients, using whole exome sequencing, so as to derive their mutational profile. Application of a bioinformatic framework revealed a total of 10,030 somatic mutations. Regarding the genes containing putative protein-altering mutations, 73 were common in at least three patients. Sixty-five of these 73 top common genes have been previously identified in melanoma cases. Biological processes related to melanoma were affected by varied genes in each patient, suggesting differences in the components of a pathway possibly contributing to pathogenesis. We performed a multi-level analysis highlighting a short list of candidate genes with a probable causative role in melanoma

Genomics of cutaneous melanoma: focus on next-generation sequencing approaches and bioinformatics

Cutaneous melanoma is caused by the uncontrolled growth of epidermal melanocytes. Melanoma continues to be a rare form of skin cancer but causes the majority of skin cancer related deaths. For many years the scientific community has focused on the investigation of the pathogenesis leading to melanoma, with the aim of better understanding its complexity and the potential advancement of therapeutic strategies. In this paper, the genomic features characterising the development of cutaneous melanoma are reviewed. Next-generation sequencing technologies and bioinformatics tools are currently state-of-the-art approaches in basic, applied and clinical cancer research. In this review, most of the available tools for revealing the mutational landscape are outlined

A Comparative Genomic Study in Schizophrenic and in Bipolar Disorder Patients, Based on Microarray Expression Profiling Meta-Analysis

Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%-5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO dataset

A transcriptomic computational analysis of mastic oil-treated Lewis lung carcinomas reveals molecular mechanisms targeting tumor cell growth and survival

Abstract Background Mastic oil from Pistacia lentiscus variation chia, a blend of bioactive terpenes with recognized medicinal properties, has been recently shown to exert anti-tumor growth activity through inhibition of cancer cell proliferation, survival, angiogenesis and inflammatory response. However, no studies have addressed its mechanisms of action at genome-wide gene expression level. Methods To investigate molecular mechanisms triggered by mastic oil, Lewis Lung Carcinoma cells were treated with mastic oil or DMSO and RNA was collected at five distinct time points (3-48 h). Microarray expression profiling was performed using Illumina mouse-6 v1 beadchips, followed by computational analysis. For a number of selected genes, RT-PCR validation was performed in LLC cells as well as in three human cancer cell lines of different origin (A549, HCT116, K562). PTEN specific inhibition by a bisperovanadium compound was applied to validate its contribution to mastic oil-mediated anti-tumor growth effects. Results In this work we demonstrated that exposure of Lewis lung carcinomas to mastic oil caused a time-dependent alteration in the expression of 925 genes. GO analysis associated expression profiles with several biological processes and functions. Among them, modifications on cell cycle/proliferation, survival and NF-κB cascade in conjunction with concomitant regulation of genes encoding for PTEN, E2F7, HMOX1 (up-regulation) and NOD1 (down-regulation) indicated some important mechanistic links underlying the anti-proliferative, pro-apoptotic and anti-inflammatory effects of mastic oil. The expression profiles of Hmox1, Pten and E2f7 genes were similarly altered by mastic oil in the majority of test cancer cell lines. Inhibition of PTEN partially reversed mastic oil effects on tumor cell growth, indicating a multi-target mechanism of action. Finally, k-means clustering, organized the significant gene list in eight clusters demonstrating a similar expression profile. Promoter analysis in a representative cluster revealed shared putative cis-elements suggesting a common regulatory transcription mechanism. Conclusions Present results provide novel evidence on the molecular basis of tumor growth inhibition mediated by mastic oil and set a rational basis for application of genomics and bioinformatic methodologies in the screening of natural compounds with potential cancer chemopreventive activities.</p