Naseh A. Algehainy

Host systemic metabolism and cancer metabolic vulnerabilities: mechanisms and therapeutic opportunities

Background Central molecular mediators—including hypoxia-inducible factors (HIF-1α/HIF-2α), MYC, wild-type and mutant p53, NF-κB, STAT3, SREBPs, NRF2, and KRAS—orchestrate these pathways by linking nutrient availability to oncogenic signalling, epigenetic reprogramming, and immune-metabolic crosstalk within the tumour microenvironment. Key metabolic enzymes including HK2, PKM2, LDH-A, IDH1/2, GLS1, and FASN serve as direct effectors and therapeutic targets. Mitochondrial dynamics—biogenesis (PGC-1α), fission (DRP1), fusion (MFN1/2, OPA1), and mitophagy (PINK1-Parkin)—constitute a critical regulatory layer. The bidirectional epigenetic-metabolic axis, mediated by acetyl-CoA, SAM, α-ketoglutarate, 2-hydroxyglutarate, and lysine lactylation, amplifies oncogenic transcriptional programs and locks cells into malignant states. Central to this review is the thesis that metabolic plasticity—the capacity of cancer cells to dynamically switch between and co-opt multiple metabolic programs—is the primary driver of tumour progression, immune evasion, and resistance to therapy. Understanding and targeting this plasticity represents the central translational challenge of cancer metabolic oncology. Methods A comprehensive narrative literature review was conducted across PubMed, Scopus, and Web of Science (2015–2025) using terms including metabolic reprogramming, Warburg effect, oncometabolites, mitochondrial dynamics, epigenetic metabolism, immunometabolism, and metabolic therapeutics. Peer-reviewed primary research and comprehensive reviews were evaluated. Limitations include restriction to English-language literature (2015–2025), potential publication bias toward high-impact journals, and the rapidly evolving nature of the field. Conclusion Metabolic reprogramming is governed by an interconnected network of transcription factors, signalling cascades, epigenetic regulators, mitochondrial dynamics, and TME-immune crosstalk. FDA-validated targets include IDH1/2 (ivosidenib, enasidenib, vorasidenib—August 2024), HIF-2α (belzutifan), and mTOR (everolimus). An expanding clinical pipeline encompasses GLS1, MCT1, OXPHOS Complex I, FASN, and metabolic immune checkpoints. Future advances require single-cell/spatial metabolomics, AI-driven patient stratification, and rational combination strategies that preempt adaptive metabolic escape. Future advances require AI-driven genome-scale metabolic modelling for patient stratification, single-cell and spatial metabolomics to resolve intra-tumoral metabolic heterogeneity, and rational combination strategies targeting multiple metabolic nodes simultaneously to preempt adaptive resistance. Integration of circadian pharmacology, host metabolic comorbidity management (obesity, diabetes, gut microbiome modulation), and TME metabolic normalisation into cancer treatment frameworks will drive the next generation of precision metabolic oncology.

Mechanistic Insights into Honey-Mediated Antibacterial Activity Against Enterobacteriaceae: A Multifaceted Approach Targeting Membrane Integrity, Protein Synthesis, and Quorum Sensing Inhibition.

Identification of novel and known variants in GAA, MYH6, NEXN, ATA3A, RHBDF1, and ACTA1 genes in coronary artery disease patients by Whole-exome sequencing.

Background The etiology of CAD is multifactorial, involving a complex interplay of genetic, environmental, and lifestyle factors, and CAD markedly increases the likelihood of impaired quality of life. Aim To identify potentially impactful genetic variants in patients with CAD that may influence the risk, severity, and clinical outcomes of the condition, we performed whole exome sequencing (WES) in 28 patients. Diverse risk factors such as gender and clinical conditions, including hypertension, hyperlipidemia, obesity, and T2DM, which are known contributors to cardiovascular adversities, have been found to be present in a significant proportion of the patients. Results Our study identified 13,289 variants in 108 genes across the cohort, with a median of 545 per patient. The most frequently mutated genes were TTN, followed by GAA, SVIL, NRAP, and DMD, all of which are related to sarcomere structural and functional integrity and cardiomyopathies. Analysis of VEP impact identified 341 variants in 58 genes with 122 novel variants (36%) not previously reported in public databases. The variants were classified as missense (66%), followed by frameshifts (25%) and in-frame indels (5%), with a minor proportion (4%) of nonsense, splice-site, and other protein-altering variants. Among these 58 genes, TTN emerged as the most frequently mutated gene, present in 96% of patient samples, while the other substantially mutated genes in patients included FLNC (29%), AGL (25%), ALPK3 (21%), and DSP (21%). A comprehensive analysis of candidate variants identified 21 variants classified as either pathogenic (3) or likely pathogenic (18), which may play a significant role in the development of cardiovascular disease. These variants met the American College of Medical Genetics and Genomics (ACMG) criteria for PM2 classification, indicating a very low (<1%) or absent frequency in population databases. Among these, eight variants were novel and classified as likely pathogenic, reported in genes GAA, MYH6, NEXN, ATA3A, RHBDF1, and ACTA1. Most gene variants have functional significance in cardiovascular pathologies, as demonstrated by gene ontology and human phenotype ontology enrichment analyses reported in this study. Conclusion The study has utilized whole exome sequencing to identify both known and novel gene variants that may contribute to disease risk, facilitating a deeper understanding of the genetic landscape of CAD. This high-resolution approach allows the detection of pathogenic and likely pathogenic variants in critical genes associated with cardiovascular health and provides evidence of functional significance, thereby elucidating complex interactions between genetic factors and enhancing understanding of disease mechanisms.