RESUMO
Glucocorticoids (GCs) are widely used for the treatment of inflammatory skin diseases despite significant adverse effects including skin atrophy. Effects of GCs are mediated by the glucocorticoid receptor (GR), a well-known transcription factor. Previously, we discovered that one of the GR target genes, REDD1, is causatively involved in skin atrophy. Here, we investigated its role in GR function using HaCaT REDD1 knockout (KO) keratinocytes. We found large differences in transcriptome of REDD1 KO and control Cas9 cells in response to glucocorticoid fluocinolone acetonide (FA): both the scope and amplitude of response were significantly decreased in REDD1 KO. The status of REDD1 did not affect GR stability/degradation during self-desensitization, and major steps in GR activation-its nuclear import and phosphorylation at activating Ser211. However, the amount of GR phosphorylated at Ser226 that may play negative role in GR signalling, was increased in the nuclei of REDD1 KO cells. GR nuclear import and transcriptional activity also depend on the composition of GR chaperone complex: exchange of chaperone FKBP51 (FK506-binding protein 5) for FKBP52 (FK506-binding protein 4) being a necessary step in GR activation. We found the increased expression and abnormal nuclear translocation of FKBP51 in both untreated and FA-treated REDD1 KO cells. Overall, our results suggest the existence of a feed-forward loop in GR signalling mediated by its target gene REDD1, which has translational potential for the development of safer GR-targeted therapies.
Assuntos
Queratinócitos , Receptores de Glucocorticoides , Fatores de Transcrição , Humanos , Atrofia , Dano ao DNA , Glucocorticoides/farmacologia , Queratinócitos/metabolismo , Receptores de Glucocorticoides/metabolismo , Células HaCaT , Fatores de Transcrição/genéticaRESUMO
BACKGROUND: The large unmet need of hidradenitis suppurativa/acne inversa (HS) therapy requires the elucidation of disease-driving mechanisms and tissue targeting. OBJECTIVE: Robust characterization of the underlying HS mechanisms and detection of the involved skin compartments. METHODS: Hidradenitis suppurativa/acne inversa molecular taxonomy and key signalling pathways were studied by whole transcriptome profiling. Dysregulated genes were detected by comparing lesional and non-lesional skin obtained from female HS patients and matched healthy controls using the Agilent array platform. The differential gene expression was confirmed by quantitative real-time PCR and targeted protein characterization via immunohistochemistry in another set of female patients. HS-involved skin compartments were also recognized by immunohistochemistry. RESULTS: Alterations to key regulatory pathways involving glucocorticoid receptor, atherosclerosis, HIF1α and IL17A signalling as well as inhibition of matrix metalloproteases were detected. From a functional standpoint, cellular assembly, maintenance and movement, haematological system development and function, immune cell trafficking and antimicrobial response were key processes probably being affected in HS. Sixteen genes were found to characterize HS from a molecular standpoint (DEFB4, MMP1, GJB2, PI3, KRT16, MMP9, SERPINB4, SERPINB3, SPRR3, S100A8, S100A9, S100A12, S100A7A (15), KRT6A, TCN1, TMPRSS11D). Among the proteins strongly expressed in HS, calgranulin-A, calgranulin-B and serpin-B4 were detected in the hair root sheath, koebnerisin and connexin-32 in stratum granulosum, transcobalamin-1 in stratum spinosum/hair root sheath, small prolin-rich protein-3 in apocrine sweat gland ducts/sebaceous glands-ducts and matrix metallopeptidase-9 in resident monocytes. CONCLUSION: Our findings highlight a panel of immune-related drivers in HS, which influence innate immunity and cell differentiation in follicular and epidermal keratinocytes as well as skin glands.
Assuntos
Hidradenite Supurativa/genética , Hidradenite Supurativa/imunologia , Imunidade Inata , Adulto , Diferenciação Celular/genética , Diferenciação Celular/imunologia , Feminino , Perfilação da Expressão Gênica , Humanos , Imuno-Histoquímica , Reação em Cadeia da Polimerase em Tempo Real , Pele/citologia , TranscriptomaRESUMO
Identification and characterization of molecular mechanisms that connect genetic risk factors to initiation and evolution of disease pathophysiology represent major goals and opportunities for improving therapeutic and diagnostic outcomes in Alzheimer's disease (AD). Integrative genomic analysis of the human AD brain transcriptome holds potential for revealing novel mechanisms of dysfunction that underlie the onset and/or progression of the disease. We performed an integrative genomic analysis of brain tissue-derived transcriptomes measured from two lines of mice expressing distinct mutant AD-related proteins. The first line expresses oligomerogenic mutant APP(E693Q) inside neurons, leading to the accumulation of amyloid beta (Aß) oligomers and behavioral impairment, but never develops parenchymal fibrillar amyloid deposits. The second line expresses APP(KM670/671NL)/PSEN1(Δexon9) in neurons and accumulates fibrillar Aß amyloid and amyloid plaques accompanied by neuritic dystrophy and behavioral impairment. We performed RNA sequencing analyses of the dentate gyrus and entorhinal cortex from each line and from wild-type mice. We then performed an integrative genomic analysis to identify dysregulated molecules and pathways, comparing transgenic mice with wild-type controls as well as to each other. We also compared these results with datasets derived from human AD brain. Differential gene and exon expression analysis revealed pervasive alterations in APP/Aß metabolism, epigenetic control of neurogenesis, cytoskeletal organization and extracellular matrix (ECM) regulation. Comparative molecular analysis converged on FMR1 (Fragile X Mental Retardation 1), an important negative regulator of APP translation and oligomerogenesis in the post-synaptic space. Integration of these transcriptomic results with human postmortem AD gene networks, differential expression and differential splicing signatures identified significant similarities in pathway dysregulation, including ECM regulation and neurogenesis, as well as strong overlap with AD-associated co-expression network structures. The strong overlap in molecular systems features supports the relevance of these findings from the AD mouse models to human AD.
Assuntos
Precursor de Proteína beta-Amiloide/genética , Precursor de Proteína beta-Amiloide/metabolismo , Presenilina-1/genética , Doença de Alzheimer/genética , Peptídeos beta-Amiloides/metabolismo , Animais , Encéfalo/metabolismo , Modelos Animais de Doenças , Colágenos Fibrilares , Proteína do X Frágil da Deficiência Intelectual/metabolismo , Humanos , Camundongos , Camundongos Transgênicos , Mutação , Neurogênese , Neurônios/metabolismo , Placa Amiloide/patologia , Fatores de Risco , Transcriptoma/genéticaRESUMO
Multiple myeloma (MM) is an incurable malignancy of bone marrow plasma cells characterized by wide clinical and molecular heterogeneity. In this study we applied an integrative network biology approach to molecular and clinical data measured from 450 patients with newly diagnosed MM from the MMRF (Multiple Myeloma Research Foundation) CoMMpass study. A novel network model of myeloma (MMNet) was constructed, revealing complex molecular disease patterns and novel associations between clinical traits and genomic markers. Genomic alterations and groups of coexpressed genes correlate with disease stage, tumor clonality and early progression. We validated CDC42BPA and CLEC11A as novel regulators and candidate therapeutic targets of MMSET-related myeloma. We then used MMNet to discover novel genes associated with high-risk myeloma and identified a novel four-gene prognostic signature. We identified new patient classes defined by network features and enriched for clinically relevant genetic events, pathways and deregulated genes. Finally, we demonstrated the ability of deep sequencing techniques to detect relevant structural rearrangements, providing evidence that encourages wider use of such technologies in clinical practice. An integrative network analysis of CoMMpass data identified new insights into multiple myeloma disease biology and provided improved molecular features for diagnosing and stratifying patients, as well as additional molecular targets for therapeutic alternatives.