Autonomous driving paper index
Host systemic metabolism and cancer metabolic vulnerabilities: mechanisms and therapeutic opportunities
One-line summary
An autonomous driving research paper: Host systemic metabolism and cancer metabolic vulnerabilities: mechanisms and therapeutic opportunities.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
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.
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