Lihong Fan

Background: Sustained pulmonary inflammation contributes significantly to lung carcinogenesis. Macrophages play a pivotal role in perpetuating inflammatory responses, undergoing a metabolic shift from oxidative phosphorylation (OXPHOS) to glycolysis upon activation. The interplay between metabolic reprogramming and macrophage polarization remains poorly defined. The objective of this study is to examines the anti‐inflammatory mechanism of lipoic acid (LA), focusing on its ability to modulate immunometabolism in activated macrophages. Methods: We utilized lipopolysaccharide (LPS)‐stimulated RAW264.7 macrophages and a murine acute lung injury (ALI) model to evaluate the anti‐inflammatory effects of LA. Inflammatory cytokine expression was assessed by qPCR, ELISA, and Western blot. Metabolic profiling was performed using Seahorse XF technology to measure oxygen consumption rate (OCR) and extracellular acidification rate (ECAR), evaluating glycolytic and oxidative metabolic functions. Results: This study systematically elucidates the molecular mechanism by which LA modulates macrophage inflammatory responses through targeting the HIF1α/glycolysis axis. The main findings are as follows: (1) In LPS‐induced RAW264.7 macrophages, LA treatment significantly inhibited the expression of M1 macrophage markers (iNOS, CD86) and the secretion of proinflammatory cytokines (IL‐1β, IL‐6, etc.). (2) LA effectively reduced the expression of GSDMD, the key executor of pyroptosis, demonstrating its inhibitory effect on macrophage pyroptosis. (3) Metabolic analysis revealed that LA reversed LPS‐induced metabolic reprogramming by decreasing the ECAR and increasing the OCR, thereby suppressing glycolysis. (4) Mechanistic studies showed that siRNA‐mediated knockdown of HIF1α replicated both the anti‐inflammatory and metabolic regulatory effects of LA, confirming HIF1α as the key target in this pathway. (5) In an ALI mouse model, LA treatment significantly reduced HIF1α expression in lung tissues and effectively alleviated inflammatory responses, further validating the proposed mechanism. Conclusion: LA exerts potent anti‐inflammatory effects by targeting HIF1α‐mediated metabolic reprogramming in macrophages. Our results highlight the therapeutic potential of targeting immunometabolic pathways in inflammatory lung diseases, providing new insights into the mechanism by which LA ameliorates pulmonary inflammation.

Protein arginine methylation was a common post‐translational modification, playing a key role in many biological processes and disease. But the regulatory mechanisms of protein arginine methyltransferases (PRMTs) in cancer were not well understood. This study aimed to examine the influence of PRMTs across various cancers and identify potential PRMTs‐related prognostic biomarkers. Three machine learning algorithms were employed to identify potential PRMTs biomarkers across cancers. Additionally, drug prediction and molecular docking studies were carried out to discover new therapeutic targets. Functional studies, including Transwell and wound‐healing assays, were performed to investigate the role of PRMT3 in tumor regulation. Through three machine learning algorithms, significant PRMTs prognosis‐related biomarkers were identified across most cancers. The immune regulatory functions of PRMTs in pan‐cancer were further examined. Daporinad, dinaciclib, and sepantronium bromide were predicted as potential drugs for the majority of cancer types. Functionally, the absence of PRMT3 notably inhibited metastasis in pancreatic cancer. Ten distinct cell types were identified from single‐cell RNA sequencing data of pancreatic cancer. PRMT3 might serve as a promising prognostic biomarker for pancreatic cancer. These findings contributed to a deeper understanding of the regulatory mechanisms of PRMTs in cancer progression. Potential biomarkers had been identified that may predict responses to immunotherapy and improve survival outcomes for cancer patients. This study provided a detailed overview of the functional roles, genetic and epigenetic alterations, and prognostic significance of PRMTs in pan‐cancer.

Tumor cells undergo metabolic reprogramming to adapt to rapid proliferation and harsh microenvironments, as evidenced by aerobic glycolysis. Mitochondria serve as key coordinators of this process. Under internal and environmental stress in tumors, mitochondria reprogram metabolism by balancing energy dynamics, redirecting metabolic routes, communicating via metabolites, and preserving the quality of mitochondria, thus supporting tumor cell survival. Traditional Chinese medicine (TCM) has a key role in modulating mitochondrial reprogramming in tumor cells, possibly disrupting metabolic pathways that are necessary for survival and proliferation. However, the underlying molecular signaling and cellular biological mechanisms need to be elucidated. In this review, we focused on the Key functions of mitochondria in adapting to tumor metabolic reprogramming are the focus of this review and recent advances in and regulatory mechanisms of TCM and nano-pharmaceutical formulations in maintaining mitochondrial homeostasis are discussed. These insights may help understand the role of mitochondria in the pathogenesis of metabolic diseases, such as cancer, and identify therapeutic targets.

Objective: Lung cancer is the leading cause of cancer-related deaths worldwide. Chemotherapy is associated with side effects, such as damage to myeloid cells and a reduction in the number of immune cells in patients. In addition, tumor cells hijack the mitochondria of immune cells through tunnel nanotubes, thereby weakening immune ability. Methods: In this study the effects of direct mitochondria transplantation on cancer cell proliferation and chemotherapeutic sensitivity were determined, as well as anti-tumor immunity in in vitro and in vivo lung cancer models. Results: A combination of mitochondrial transplantation and cisplatin chemotherapy was shown for the first time to significantly improve immune infiltration of advanced non-small cell lung cancer (NSCLC) and overcome the shortcomings of cisplatin chemotherapy, including damage to myeloid cells and a reduction in the number of immune cells. Conclusions: The findings of the current study provide valuable recommendations for enhancing immune infiltration and augmenting anti-tumor efficacy during chemotherapy in advanced NSCLC. In addition, the findings support “mitochondrial transfer” as a novel paradigm in tumor treatment.

The therapeutic efficacy of lung adenocarcinoma (LUAD), the most prevalent histological subtype of primary lung cancer, remains inadequate, with accurate prognostic assessment posing significant challenges. This study sought to elucidate the prognostic significance of mitochondrial-related genes in LUAD through an integrative multi-omics approach, aimed at developing personalized therapeutic strategies. Utilizing transcriptomic and single-cell RNA sequencing (scRNA-seq) data, alongside clinical information from publicly available databases, we first applied dimensionality reduction and clustering techniques to the LUAD single-cell dataset, focusing on the subclassification of fibroblasts, epithelial cells, and T cells. Mitochondrial-related prognostic genes were subsequently identified using TCGA-LUAD data, and LUAD cases were stratified into distinct molecular subtypes through consensus clustering, allowing for the exploration of gene expression profiles and clinical feature distributions across subtypes. By leveraging an ensemble of machine learning algorithms, we developed an Artificial Intelligence-Derived Prognostic Signature (AIDPS) model based on mitochondrial-related genes and validated its prognostic accuracy across multiple independent datasets. The AIDPS model demonstrated robust predictive power for LUAD patient outcomes, revealing significant differences in responses to immunotherapy and chemotherapy, as well as survival outcomes between risk groups. Furthermore, we conducted comprehensive analyses of tumor mutation burden (TMB), immune microenvironment characteristics, and genome-wide association study (GWAS) data, providing additional insights into the mechanistic roles of mitochondrial-related genes in LUAD pathogenesis. This study not only offers a novel approach to improving prognostic assessments in LUAD but also establishes a strong foundation for the development of personalized therapeutic interventions.