Uncovering the 'sphinx' of sphingosine 1-phosphate signalling: from cellular events to organ morphogenesis

Interplay of Sphingolipid Metabolism in Predicting Prognosis of GBM Patients: Towards Precision Immunotherapy

Background: In spite of numerous existing bio-surveillance systems for predicting glioma (GBM) prognosis, enhancing the efficacy of immunotherapy remains an ongoing conundrum. The continual scrutiny of the dynamic interplay between the sphingolipid metabolic pathway and tumor immunophenotypes has unveiled potential implications. However, the intricate orchestration of functional and regulatory mechanisms by long non-coding RNAs (lncRNAs) in GBM, particularly in the context of sphingolipid metabolism, remains cryptic. Methods: We harnessed established R packages to intersect gene expression profiles of GBM patients within the The Cancer Genome Atlas (TCGA) database with the compilation of sphingolipid metabolism genes from GeneCards. This enabled us to discern markedly distinct lncRNAs, which were subsequently deployed to construct a robust prognostic model utilizing Lasso-Cox regression analysis. We then scrutinized the immune microenvironment across various risk strata using the ssGSEA and CIBERSORT algorithms. To evaluate mutation patterns and drug resistance profiles within patient subgroups, we devised the "Prophytic" and "Maftools" packages, respectively. Results: Our investigation scrutinized lncRNAs linked to sphingolipid metabolism, utilizing glioma specimens from TCGA. We meticulously curated 1224 sphingolipid-associated genes gleaned from GeneCards and pinpointed 272 differentially expressed mRNAs via transcriptomic analysis. Enrichment analyses underscored their significance in sphingolipid processes. A prognostic model founded on 17 meticulously selected lncRNAs was systematically constructed and validated. This model adeptly stratified GBM patients into high- and low-risk categories, yielding highly precise prognostic insights. We also discerned correlations between immune cell infiltration and genetic mutation discrepancies, along with distinct therapeutic responses through drug sensitivity analysis. Notably, computational findings were corroborated through experimental validation by RT-PCR. Conclusion: In summation, our exhaustive inquiry underscores the multifaceted utility of the sphingolipid metabolic pathway as an autonomous diagnostic and prognostic indicator for glioma patients. Furthermore, we amalgamate a profusion of substantiated evidence concerning immune infiltration and gene mutations, thereby reinforcing the proposition that sphingolipid metabolism may function as a pivotal determinant in the panorama of immunotherapeutic interventions.

Next Generation, Modifiable Cardiometabolic Biomarkers: Mitochondrial Adaptation and Metabolic Resilience: A Scientific Statement From the American Heart Association

Cardiometabolic risk is increasing in prevalence across the life span with disproportionate ramifications for youth at socioeconomic disadvantage. Established risk factors and associated disease progression are harder to reverse as they become entrenched over time; if current trends are unchecked, the consequences for individual and societal wellness will become untenable. Interrelated root causes of ectopic adiposity and insulin resistance are understood but identified late in the trajectory of systemic metabolic dysregulation when traditional cardiometabolic risk factors cross current diagnostic thresholds of disease. Thus, children at cardiometabolic risk are often exposed to suboptimal metabolism over years before they present with clinical symptoms, at which point life-long reliance on pharmacotherapy may only mitigate but not reverse the risk. Leading-edge indicators are needed to detect the earliest departure from healthy metabolism, so that targeted, primordial, and primary prevention of cardiometabolic risk is possible. Better understanding of biomarkers that reflect the earliest transitions to dysmetabolism, beginning in utero, ideally biomarkers that are also mechanistic/causal and modifiable, is critically needed. This scientific statement explores emerging biomarkers of cardiometabolic risk across rapidly evolving and interrelated "omic" fields of research (the epigenome, microbiome, metabolome, lipidome, and inflammasome). Connections in each domain to mitochondrial function are identified that may mediate the favorable responses of each of the omic biomarkers featured to a heart-healthy lifestyle, notably to nutritional interventions. Fuller implementation of evidence-based nutrition must address environmental and socioeconomic disparities that can either facilitate or impede response to therapy.

Unlocking the secrets of the microbiome: exploring the dynamic microbial interplay with humans through metabolomics and their manipulation for synthetic biology applications

Metabolomics is a powerful research discovery tool with the potential to measure hundreds to low thousands of metabolites. In this review, we discuss the application of GC-MS and LC-MS in discovery-based metabolomics research, we define metabolomics workflows and we highlight considerations that need to be addressed in order to generate robust and reproducible data. We stress that metabolomics is now routinely applied across the biological sciences to study microbiomes from relatively simple microbial systems to their complex interactions within consortia in the host and the environment and highlight this in a range of biological species and mammalian systems including humans. However, challenges do still exist that need to be overcome to maximise the potential for metabolomics to help us understanding biological systems. To demonstrate the potential of the approach we discuss the application of metabolomics in two broad research areas: (1) synthetic biology to increase the production of high-value fine chemicals and reduction in secondary by-products and (2) gut microbial interaction with the human host. While burgeoning in importance, the latter is still in its infancy and will benefit from the development of tools to detangle host-gut-microbial interactions and their impact on human health and diseases.