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Biology subjects

Poisson, L.

Publications and source records attributed to Poisson, L..

7 recordsLinked to original sources

Impact of genomic background and developmental state on signaling pathways and response to therapy in Glioblastoma patient-derived cells

Glioblastoma (GBM) tumors represents diverse genomic epigenomic, and transcriptional landscapes, with significant intratumoral heterogeneity that challenges standard of care treatments involving radiation (RT) and the DNA-alkylating agent temozolomide (TMZ). In this study, we employed targeted proteomics to assess the response of a genomically-diverse panel of GBM patient-derived cancer stem cells (CSCs) to astrocytic differentiation, growth factor withdrawal and traditional high fetal bovine serum culture. Our findings revealed a complex crosstalk and co-activation of key oncogenic signaling in CSCs and diverse patterns of response to these external stimuli. Using RNA sequencing and DNA methylation, we observed common adaptations in response to astrocytic differentiation of CSCs across genomically distinct models, including BMP-Smad pathway activation, reduced cholesterol biosynthesis, and upregulation of extracellular matrix components. Notably, we observed that these differentiated CSC progenies retained a subset of stemness genes and the activation of cell survival pathways. We also examined the impact of differentiation state and genomic background on GBM cell sensitivity and transcriptional response to TMZ and RT. Differentiation of CSCs increased resistance to TMZ but not to RT. While transcriptional responses to these treatments were predominantly regulated by p53 in wild-type p53 GBM cells, its transcriptional activity was modulated by the differentiation status and treatment modality. Both mutant and wild-type p53 models exhibited significant activation of a DNA-damage associated interferon response in CSCs and differentiated cells, suggesting this pathway may play a wider role in GBM response to TMZ and RT. Our integrative analysis of the impact of GBM cell developmental states, in the context of genomic and molecular diversity of patient-derived models, provides valuable insights for pre-clinical studies aimed at optimizing treatment strategies.

cancer biology↗

Utility of an untargeted metabolomics approach using a 2D GC-GC-MS platform to distinguish relapsing and progressive multiple sclerosis

IntroductionMultiple sclerosis (MS) is the most common inflammatory neurodegenerative disease of the central nervous system (CNS) in young adults and results in progressive neurological defects. The relapsing-remitting phenotype (RRMS) is the most common disease course in MS and may progress to the progressive form (PPMS). ObjectivesThere is a gap in knowledge regarding whether the relapsing form can be distinguished from the progressive course or healthy subjects (HS) based on an altered serum metabolite profile. In this study, we performed global untargeted metabolomics with the 2D GCxGC-MS platform to identify altered metabolites between RRMS, PPMS, and HS. MethodsWe profiled 235 metabolites in the serum of patients with RRMS (n=41), PPMS (n=31), and HS (n=91). A comparison of RRMS and HS patients revealed 22 significantly altered metabolites at p<0.05 (false discovery rate [FDR]=0.3). The PPMS and HS comparisons revealed 28 altered metabolites at p<0.05 (FDR=0.2). ResultsPathway analysis using MetaboAnalyst revealed enrichment of four metabolic pathways in both RRMS and PPMS (hypergeometric test p<0.05): 1) galactose metabolism; 2) amino sugar and nucleotide sugar metabolism; 3) phenylalanine, tyrosine, and tryptophan biosynthesis; and 4) aminoacyl-tRNA biosynthesis. The Qiagen IPA enrichment test identified the sulfatase 2 (SULF2) (p=0.0033) and integrin subunit beta 1 binding protein 1 (ITGB1BP1) (p=0.0067) genes as upstream regulators of altered metabolites in the RRMS vs. HS groups. However, in the PPMS vs. HS comparison, valine was enriched in the neurodegeneration of brain cells (p=0.05), and heptadecanoic acid, alpha-ketoisocaproic acid, and glycerol participated in inflammation in the CNS (p=0.03). ConclusionOverall, our study suggested that RRMS and PPMS may contribute metabolic fingerprints in the form of unique altered metabolites for discriminating MS disease from HS, with the potential for constructing a metabolite panel for progressive autoimmune diseases such as MS.

bioinformatics↗

Blood-based targeted metabolipidomics reveals altered omega fatty acid-derived lipid mediators in relapsing-remitting multiple sclerosis patients

Unresolved and uncontrolled inflammation is considered a hallmark of pathogenesis in chronic inflammatory diseases like multiple sclerosis (MS), suggesting a defective resolution process. Inflammatory resolution is an active process partially mediated by endogenous metabolites of dietary polyunsaturated fatty acids (PUFA), collectively termed specialized pro-resolving lipid mediators (SPMs). Altered levels of resolution mediators have been reported in several inflammatory diseases and may partly explain impaired inflammatory resolution. Performing LC-MS/MS-based targeted lipid mediator profiling, we observed distinct changes in fatty acid metabolites in serum from 30 relapsing-remitting MS (RRMS) patients relative to 30 matched healthy subjects (HS). Robust linear regression revealed 12 altered lipid mediators after adjusting for confounders (p <0.05). Of these, 15d-PGJ2, PGE3, and LTB5 were increased in MS while PGF2a, 8,9-DiHETrE, 5,6-DiHETrE, 20-HETE, 15-HETE, 12-HETE, 12-HEPE, 14-HDoHE, and DHEA were decreased in MS compared to HS. In addition, 12,13-DiHOME and 12,13-DiHODE were positively correlated with expanded disability status scale values (EDSS). Using Partial Least Squares, we identified several lipid mediators with high VIP scores (VIP > 1: 32% - 52%) of which POEA, PGE3, DHEA, LTB5, and 12-HETE were top predictors for distinguishing between RRMS and HS (AUC =0.75) based on the XGBoost Classifier algorithm. Collectively, these findings suggest an imbalance between inflammation and resolution. Altogether, lipid mediators appear to have potential as diagnostic and prognostic biomarkers for RRMS.

biochemistry↗

Intermittent Fasting induced ketogenesis inhibits mouse epithelial ovarian tumors by promoting anti-tumor T cell response.

Epithelial Ovarian Cancer (EOC) is the most lethal gynecologic cancer with limited genetic alterations identified that can be therapeutically targeted. In tumor bearing mice, short-term fasting, fasting mimicking diet and calorie restriction enhance the activity of antineoplastic treatment by modulating systemic metabolism and boosting anti-tumor immunity. We tested the outcome of sixteen-hour intermittent fasting (IF) on mouse EOC progression with focus on fasting driven antitumor immune responses. IF resulted in consistent decrease of tumor promoting metabolic growth factors and cytokines, recapitulating changes that creates a tumor antagonizing environment. Immune profiling revealed that IF profoundly reshapes anti-cancer immunity by inducing increase in CD4+ and CD8+ cells, paralleled by enhanced antitumor Th1 and cytotoxic responses, by enhancing their metabolic fitness. Metabolic studies revealed that IF generated bioactive metabolite BHB which can be a potential substitute for simulating the antitumor benefits of IF. However, in a direct comparison, IF surpassed exogenous BHB therapy in improving survival and activating anti-tumor immune response. Thus, our data provides strong evidence for IF and its metabolic mediator BHB for ameliorating EOC progression and as a viable approach in maintaining and sustaining an effective anti-tumor T cell response.

cancer biology↗

X-linked adrenoleukodystrophy patient fibroblast-iPSC-derived astrocytes reveal phenotype-specific metabolic, inflammatory, and microRNA alterations

X-linked adrenoleukodystrophy (X-ALD) is an inherited progressive metabolic disorder caused by pathogenic variants in the ABCD1 gene, which leads to accumulation of very long chain fatty acids in body fluids and tissues including brain and spinal cord. In the absence of a clear genotype-phenotype correlation the molecular mechanisms of the severe cerebral adrenoleukodystrophy (cALD) and the milder adrenomyeloneuropathy (AMN) phenotypes remain unknown. Given our previous evidence of role of astrocytes in the neuroinflammatory response in X-ALD we investigated the metabolic and molecular profiles of astrocytes derived from induced pluripotent stem cells (iPSC). The iPSCs were in turn generated from skin fibroblasts from healthy controls and patients with AMN or cALD. AMN and cALD astrocytes exhibited lack of ABCD1 and accumulation of very long chain fatty acids, a hallmark of X-ALD disease. Further, cALD astrocytes harbor significantly higher phosphorylation of STAT3, increased Toll-like receptor expression and higher chemokine and cytokine expression. In this first report of miRNA sequencing in X-ALD astrocytes, we observed that miR-9 expression was associated with increasing disease severity phenotype. CRISPR-Cas9 knock-in of ABCD1ABCD1 gene expression differentially affected the expression of key molecular, metabolic and microRNA targets in AMN and cALD astrocytes. Extensive characterization of the AMN and cALD iPSC-derived astrocyte model demonstrates critical aspects of X-ALD inflammatory disease in response to ABCD1ABCD1 mutation and can be further utilized for exploring the contribution of astrocytes to differential inflammatory response in cALD.

neuroscience↗

Blood-based untargeted metabolomics in Relapsing-Remitting Multiple Sclerosis revealed the testable therapeutic target

Metabolic aberrations impact the pathogenesis of multiple sclerosis (MS) and possibly can provide clues for new treatment strategies. Using untargeted metabolomics, we measured serum metabolites from 35 relapsing-remitting patients and 14 healthy age-matched controls. Out of 632 known metabolites detected, 60 were significantly altered in relapsing-remitting MS (RRMS). Bioinformatics analysis identified an altered "metabotype" in RRMS patients, represented by 4 changed metabolic pathways of glycerophospholipid, citrate cycle, sphingolipid, and pyruvate metabolism. Interestingly, the common upstream metabolic pathway feeding these 4 pathways is the glycolysis pathway. Real-time bioenergetic analysis of the patient derived peripheral blood mononuclear cells, showed enhanced glycolysis, supporting the altered metabolic state of immune cells. Experimental autoimmune encephalomyelitis mice treated with the glycolytic inhibitor, 2-deoxy-D-glucose ameliorated the disease progression and inhibited the disease pathology significantly by promoting the anti-inflammatory phenotype of monocytes/macrophage in the central nervous system. Our study suggests that targeting glycolysis offers a potential target for MS.

neuroscience↗

Distinct epigenetic shift in a subset of Glioma CpG island methylator phenotype (G-CIMP) during tumor recurrence

Histomorphology and current grading schemes are unable to predict glioma relapse and malignant tumor progression. We reported that the IDH-mutant associated Glioma-CpG Island Methylator Phenotype (G-CIMP) can be further divided into two clinically distinct subtypes independent of histopathological grading (G-CIMP-high and -low) with evidence of correlation with tumor progression. Here we performed a comprehensive epigenomic analysis of 74 longitudinally collected glioma samples (grade II-IV) to understand malignant recurrence from G-CIMP-high to G-CIMP-low. G-CIMP-low recurrence appeared in 12% of all gliomas and resemble IDH-wildtype primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, stem cell-like epigenomic phenotype, and genomic instability. Finally, we defined a set of candidate biomarker signatures that predict recurrence of G-CIMP-low with clinically relevance on patient outcomes. Our study provides opportunity for refined clinical trial designs and therapeutic targets that limit progression to more aggressive G-CIMP-low phenotype.\n\nHIGHLIGHTSO_LIIndolent G-CIMP-high progresses to aggressive G-CIMP-low phenotype\nC_LIO_LIIncidence of G-CIMP-low recurrent tumors are 3 times greater than G-CIMP-low primary\nC_LIO_LIG-CIMP-low recurrent tumors share epigenomic features with IDH-wildtype primary GBM\nC_LIO_LIPredictive biomarkers of G-CIMP-low progression at primary diagnosis\nC_LI

cancer biology↗