Temporal multi-omic profiling reveals chemoradiotherapy-specific dualistic metabolic rewiring that supports glioblastoma tumor recurrence
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE253649 | GEO | 2025/07/02
REPOSITORIES: GEO
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Project description:Tumor recurrence afflicts over 95% of glioblastoma (GBM) patients, contributing to the disease's high fatality rates. To unravel the molecular mechanisms behind post-therapy recurrence, we employed a clinically-relevant chemoradiotherapy model, studying the temporal molecular metabolic evolution of patient-derived GBM samples in vitro and in vivo. Leveraging unbiased multi-omics methods, including single-cell and bulk transcriptomics, untargeted metabolomics, and stable isotope tracing, we revealed a dynamic metabolic rewiring favoring one-way anaplerotic pyruvate metabolism via carboxylation across GBM samples. This conserved adaptation, confirmed in independent datasets, resulted in reduced glucose-derived acetyl-coA production, hindering histone acetylation and silencing neural-differentiation genes NEUROD1 and DCX. Pharmacological intervention targeting this metabolic shift reduced recurrent GBM cell aggressiveness, prolonging survival in preclinical GBM xenograft tumors treated with chemoradiotherapy. These findings illuminate a potential metabolic therapeutic avenue to enhance current strategies, addressing disease recurrence and offering much-needed improvements in survival outcomes for GBM patients suffering from this dismal disease.
2025-07-02 | GSE253648 | GEO
Project description:Tumor recurrence afflicts over 95% of glioblastoma (GBM) patients, contributing to the disease's high fatality rates. To unravel the molecular mechanisms behind post-therapy recurrence, we employed a clinically-relevant chemoradiotherapy model, studying the temporal molecular metabolic evolution of patient-derived GBM samples in vitro and in vivo. Leveraging unbiased multi-omics methods, including single-cell and bulk transcriptomics, untargeted metabolomics, and stable isotope tracing, we revealed a dynamic metabolic rewiring favoring one-way anaplerotic pyruvate metabolism via carboxylation across GBM samples. This conserved adaptation, confirmed in independent datasets, resulted in reduced glucose-derived acetyl-coA production, hindering histone acetylation and silencing neural-differentiation genes NEUROD1 and DCX. Pharmacological intervention targeting this metabolic shift reduced recurrent GBM cell aggressiveness, prolonging survival in preclinical GBM xenograft tumors treated with chemoradiotherapy. These findings illuminate a potential metabolic therapeutic avenue to enhance current strategies, addressing disease recurrence and offering much-needed improvements in survival outcomes for GBM patients suffering from this dismal disease.
2025-07-02 | GSE253464 | GEO
Project description:Temporal multi-omic profiling reveals chemoradiotherapy-specific dualistic metabolic rewiring that supports glioblastoma tumor recurrence
| PRJNA1066399 | ENA
Project description:Temporal multi-omic profiling reveals chemoradiotherapy-specific dualistic metabolic rewiring that supports glioblastoma tumor recurrence (scRNA-Seq)
| PRJNA1066401 | ENA
Project description:Temporal multi-omic profiling reveals chemoradiotherapy-specific dualistic metabolic rewiring that supports glioblastoma tumor recurrence (Bulk RNA-Seq)
| PRJNA1065856 | ENA
Project description:Even though its development starts early in utero, neonatal skin is still immature at birth relative to adult and undergoes a maturation process extending to the first years of life. It is now established that the stratum corneum is thinner and dryer and that skin contains less natural moisturizing factors and lipids in newborns compared to children and adults. Moreover, it has been shown that skin surface area expansion is not linear throughout life and is peaking perinatally, suggesting that baby skin has a higher epidermal cellular turnover. Despite growing resources showing differences between adult and infant skin physiology, molecular and metabolic specificities of baby skin are still poorly understood. To address this critical knowledge gap, we performed an integrative transcriptomic and metabolomic study comparing human primary foreskin and abdominal keratinocytes from male babies and female adults, respectively. Based on state-of-the-art integrative frameworks, our analyses revealed a major shift in the global energetic metabolism in baby foreskin keratinocytes compared to adult abdominal keratinocytes, highlighting increased amino acid metabolism and mitochondrial oxidative phosphorylation in baby cells to fuel the citric acid cycle, while showing glycolysis as the major cell energy source in adult cells.
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Project description:Glioblastoma multiforme (GBM) has been recognized as the most lethal type of malignant brain tumor. Despite efforts of the medical and research community, patients' survival remains extremely low. Multi-omic profiles (including DNA sequence, methylation and gene expression) provide rich information about the tumor. These profiles are likely to reveal processes that may be predictive of patient survival. However, the integration of multi-omic profiles, which are high dimensional and heterogeneous in nature, poses great challenges. The goal of this work was to develop models for prediction of survival of GBM patients that can integrate clinical information and multi-omic profiles, using multi-layered Bayesian regressions. We apply the methodology to data from GBM patients from The Cancer Genome Atlas (TCGA, n = 501) to evaluate whether integrating multi-omic profiles (SNP-genotypes, methylation, copy number variants and gene expression) with clinical information (demographics as well as treatments) leads to an improved ability to predict patient survival. The proposed Bayesian models were used to estimate the proportion of variance explained by clinical covariates and omics and to evaluate prediction accuracy in cross validation (using the area under the Receiver Operating Characteristic curve, AUC). Among clinical and demographic covariates, age (AUC = 0.664) and the use of temozolomide (AUC = 0.606) were the most predictive of survival. Among omics, methylation (AUC = 0.623) and gene expression (AUC = 0.593) were more predictive than either SNP (AUC = 0.539) or CNV (AUC = 0.547). While there was a clear association between age and methylation, the integration of age, the use of temozolomide, and either gene expression or methylation led to a substantial increase in AUC in cross-validaton (AUC = 0.718). Finally, among the genes whose methylation was higher in aging brains, we observed a higher enrichment of these genes being also differentially methylated in cancer.
| S-EPMC6222579 | biostudies-other
Project description:Even though its development starts early in utero, neonatal skin is still immature at birth relative to adult and undergoes a maturation process extending to the first years of life. It is now established that stratum corneum is thinner and dryer, and that skin contains less natural moisturizing factors and lipids in newborns compared to children and adults. Moreover, it has been shown that skin surface area expansion is not linear throughout life and is peaking perinatally, suggesting that baby skin has a higher epidermal cellular turnover. Despite growing resources showing differences between adult and infant skin physiology, molecular and metabolic specificities of baby skin are still poorly understood. To address this critical knowledge gap, we performed an integrative transcriptomic and metabolomic study comparing human primary keratinocytes from babies and adults. Based on state-of-the-art integrative frameworks, our analyses revealed a major shift in the global energetic metabolism in baby keratinocytes compared to adults, highlighting increased amino acid metabolism and mitochondrial oxidative phosphorylation in baby cells to fuel TCA cycle, while showing glycolysis as the major cell energy source in adult cells.
2021-09-12 | GSE183891 | GEO
Project description:Glioblastoma (GBM) constitutes the most lethal primary brain tumor for which immunotherapy has provided limited benefit. The unique brain immune landscape is reflected in a complex tumor immune microenvironment (TIME) in GBM. Here, single-cell sequencing of the GBM TIME revealed that microglia were under severe oxidative stress, which induced nuclear receptor subfamily 4 group A member 2 (NR4A2)-dependent transcriptional activity in microglia. Heterozygous Nr4a2 (Nr4a2+/-) or CX3CR1+ myeloid cell-specific Nr4a2 (Nr4a2fl/flCx3cr1Cre) genetic targeting reshaped microglia plasticity in vivo by reducing alternatively activated microglia and enhancing antigen presentation capacity for CD8+ T cells in GBM. In microglia, NR4A2 activated squalene monooxygenase (SQLE) to dysregulate cholesterol homeostasis. Pharmacologic NR4A2 inhibition attenuated the protumorigenic TIME, and targeting the NR4A2 or SQLE enhanced the therapeutic efficacy of immune-checkpoint blockade in vivo. Collectively, oxidative stress promotes tumor growth through NR4A2-SQLE activity in microglia, informing novel immune therapy paradigms in brain cancer.SignificanceMetabolic reprogramming of microglia in GBM informs synergistic vulnerabilities for immune-checkpoint blockade therapy in this immunologically cold brain tumor. This article is highlighted in the In This Issue feature, p. 799.
| S-EPMC10073346 | biostudies-literature
Project description:Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.
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