Journal of advanced research最新文献

Introduction: The eukaryotic translation initiation factor 4E (eIF4E) has emerged as a compelling target for cancer therapeutics due to its pivotal role in regulating cap-dependent translation of oncogenic mRNAs and its implication in various malignancies. However, the clinical potential of current eIF4E inhibitors is limited by suboptimal potency and binding affinity.

Objectives: Based on an analysis of the eIF4E/eIF4G binding pocket and structural features of existing inhibitors, 75 compounds were designed, synthesized, and screened. The binding affinity, molecular mechanism and antitumor activity of the most potent compound b14 were evaluated in vitro and in vivo.

Methods: Through structure-activity relationship analysis, 75 thiazole derivatives were synthesized and screened for binding affinity using fluorescence polarization (FP) and surface plasmon resonance (SPR). Hit compounds were evaluated for antitumor activity using the SRB assay. The most promising compound, b14, was further investigated for its antitumor activity and molecular mechanism via Western blotting (WB), quantitative real-time PCR (qRT-PCR), immunofluorescence, co-immunoprecipitation, and proteomics. The in vivo antitumor activity and safety of b14 were assessed using HeLa xenograft models and acute/subacute toxicity models, respectively.

Results: Compound b14 emerged as a lead molecule, exhibiting a 10-fold higher binding affinity to eIF4E than the reference inhibitor 4EGI-1. Mechanistic studies revealed that b14 disrupts eIF4F complex formation by inhibiting AKT-mTOR-4EBP1 and ERK-eIF4E phosphorylation, subsequently triggering mitochondrial dysfunction and apoptosis in tumor cells, with relatively low IC₅₀ values. Moreover, proteomics analysis further demonstrated that b14 suppresses oncogenic lipogenesis by downregulating key enzymes involved in lipid metabolism. Finally, oral administration of b14 significantly inhibits HeLa xenograft growth in vivo without measurable side effects.

Conclusions: Together, our results demonstrate that b14 is an excellent novel small-molecule inhibitor of eIF4E for future cancer therapy.

Aims: Cardiac muscle wasting is a significant complication observed in lung cancer patients receiving radiotherapy. Radiotherapy, a commonly used anticancer treatment, is known to cause cardiovascular complications; however, the mechanisms linking tumor irradiation to cardiac wasting remain poorly understood.

Methods: Lewis lung carcinoma (LLC) and CT26 tumor-bearing mice received localized tumor irradiation. Conditioned medium or EVs from irradiated tumor cells were collected and used to treat cardiomyocytes. Autophagy, protein synthesis, and atrophy were assessed. The roles of tumor Thbs1 and cardiac PERK signaling were determined via shRNA-mediated knockdown and PERK mutation in vitro and in vivo.

Results: We demonstrated that localized tumor irradiation induces cardiac muscle wasting in mice, which is associated with PERK-eIF2α-Atf4 pathway activation and increased Thbs1 protein-but not mRNA-levels in cardiomyocytes. Mechanistically, Thbs1 is delivered via extracellular vesicles (EVs) derived from irradiated tumors. Tumor-derived Thbs1⁺ EVs are necessary and sufficient to trigger autophagy, suppress protein synthesis, and cause atrophy in cardiomyocytes, which is dependent on the Thbs1-PERK interaction and downstream signaling.

Conclusion: These results indicate that radiotherapy promotes the release of Thbs1⁺ EVs, which drive cardiac muscle wasting via PERK-eIF2α-Atf4 signaling, revealing a novel mechanism underlying cancer-associated cardiac damage.

Introduction: Disruption of the circadian rhythm (CR) and autophagy in intervertebral discs contributes to intervertebral disc degeneration (IDD) progression. However, the circadian regulation of autophagy requires further investigation.

Objectives: We observed the expression of circadian proteins and autophagic markers of nucleus pulposus (NP) cells followed a diurnal rhythmic pattern in vivo and in vitro.

Methods: NP tissues were collected from light/dark cycle-shifted rats and IDD patients of varying severity. CR and ECM-related proteins were analyzed by immunohistochemistry and western blotting. Primary rat NP cells were treated with hypoxia or CoCl₂, followed by western blotting for CR proteins, HIF-1α, and autophagy markers. siRNA knockdown of PER2 or HIF-1α was performed to assess their roles in regulating autophagy, ECM, and CR-associated proteins.

Results: The silencing of clock gene PER2 disrupted the rhythmic expression of autophagic markers, by contrast PER2 overexpression inhibited mTOR pathway and enhanced autophagic levels. Co-IP analysis demonstrated the PER2-mTOR interaction, linking CR and autophagy rhythm. The inflammatory stimulator dampened the CR and autophagy rhythm, however intermittent hypoxia and cobalt chloride (CoCl₂) re-synchronized the rhythm. Mechanistically, HIF-1α-mediated regulation of PER2 by hypoxia was involved in the re-synchronization, which was further demonstrated by the loss of CR and autophagy rhythm after silencing of PER2 or HIF-1α under hypoxia. Furthermore, the rhythm of oxygen level and HIF-1α was proved in living healthy NP tissue, confirming the hypoxia as a Zeitgeber. CR disruption and autophagy dysfunction led to catabolism of extracellular matrix (ECM), but the hypoxia, CoCl₂ and autophagic stimulator could promote the rebalance of ECM metabolism.

Conclusion: Our study demonstrates that hypoxia maintains the intrinsic CR and autophagy rhythm through the HIF-1α/PER2/mTOR pathway to prevent IDD.

Artificial intelligence (AI) has played an excellent supporting role in novel drug discovery and development. This study introduces a reinforcement learning (RL) model based on the Soft Actor-Critic (SAC) algorithm for AI-driven de novo molecular generation targeting tyrosinase. The model facilitates forward molecular generation design by integrating a chemical reaction template and a molecular building block library, concurrently performing molecular docking and assessing drug-likeness. Through sequential decision-making, signal feedback, and a dynamic learning process, the model generates molecules exhibiting potent target affinity, optimal drug-like properties, and good synthetic feasibility. The AI-generated molecules undergo rigorous manual screening, synthesis, and biological evaluation, culminating in the identification of a prioritized lead compound V. Subsequent structural optimization of compound V reveals a series of compounds with significantly enhanced activity, shifting inhibitory potency from the micromolar to the nanomolar range. The optimized compound, V-24, demonstrates low cytotoxicity and significant anti-melanogenic activity both in cell melanogenesis inhibition and zebrafish anti-pigmentation models. Notably, it effectively reduces melanin content in an ultraviolet light-induced human 3D skin pigmentation model, exhibiting the potential to serve as a promising tyrosinase inhibitor for the treatment of skin pigmentation. More importantly, this "AI de novo Molecular Generation + Expert-Guided Structural Optimization" work demonstrates that integrating an AI algorithm with traditional medicinal chemistry experience is a novel approach and efficiency-redefined strategy for drug discovery.

Introduction: Wound healing impairment is highly prevalent in diabetes and frequently progresses to serious complications, including refractory ulcers and necessitated amputations. RNA sequencing in methylglyoxal (MGO)-injured HaCaT cells implicated fructose-1,6-bisphosphatase 1 (FBP1) in suppressing keratinocyte proliferation and migration, identifying it as a potential therapeutic target.

Objectives: This study aimed to validate FBP1 as a therapeutic target for diabetic wounds and evaluate asiatic acid (AA) and its novel hydrogen sulfide (H₂S)-donor derivatives, designed to enhance efficacy, as FBP1-targeted interventions.

Methods: Target discovery was performed via transcriptomics in MGO-injured HaCaT cells, identifying FBP1 as a key regulator. Virtual screening of compound libraries was combined with experimental screening to discover AA as a potent FBP1 inhibitor. Based on AA's structure, novel H₂S-donor derivatives were rationally designed and synthesized to enhance therapeutic properties. A topical AA4 gel was formulated and tested for its therapeutic impact on diabetic wound repair in mouse models.

Results: AA was identified as a potent FBP1 inhibitor (IC₅₀ = 2.5 μM). AA4, a synthesized H₂S-donor derivative, exhibited dual mechanisms: direct FBP1 enzymatic inhibition and H₂S-mediated FBP1 downregulation. This synergistically restored proliferation pathways (AKT/mTOR/HIF-1α/uPAR) and reduced apoptosis (Bcl-2/Bax/Caspase-3). Topical AA4 gel markedly enhanced wound closure rates in diabetic mice, primarily through promoting epidermal regeneration and collagen deposition.

Conclusion: This study validates FBP1 targeting as a feasible strategy to address diabetic wound healing. It establishes AA-H₂S donor derivatives, particularly AA4 acting via dual FBP1 targeting, as an encouraging precision therapy for diabetic wound healing.

Introduction: Berberine (BBR), the predominant isoquinoline alkaloid in Coptidis Rhizoma, exhibits remarkable anti- colorectal cancer (CRC) activity. However, whether BBR triggers CRC cell death through ferroptosis-associated disruption of energy metabolism remains to be elucidated.

Objective: To investigate if BBR induces mitochondrial energy metabolism disorder in CRC cells by regulating the ferroptosis signaling pathway.

Methods: BBR's effects on malignant phenotypes were evaluated in vitro (human cell line HCT116, murine cell line CT26 cells at 10, 20, 40 μM) and in vivo (80 mg/kg). Target engagement and mechanistic pathways were interrogated through RNA-sequence combined with convolutional neural network-based pathway prediction, corroborated by surface plasmon resonance, cellular thermal shift assay. Downstream validation mainly included quantification of Gli1, STAT3, GPX4, SLC7A11, and FTH1 expression via RT-qPCR, Western blot, immunofluorescence, and other molecular expression and functional confirmation experiments.

Results: BBR inhibited CRC cell proliferation with IC₅₀ value for HCT116 cells for 48 h at 19.86 ± 2.31 μM, and for CT26 cells for 48 h at 21.35 ± 2.63 μM. Concurrently, it elevated ferroptosis markers such as malondialdehyde, lactate dehydrogenase, Fe²⁺, and 4-hydroxynonenal, while suppressing ATP levels, superoxide dismutase activity, and energy metabolism-related enzymes. Graph convolutional network-based drug "on-target" pathway algorithm predicted Gli1 as top-9 target, and surface plasmon resonance confirmed direct BBR-Gli1 binding with KD value at 0.652 μM, cellular stability thermal assessment showed BBR stabilized Gli1 with thermal shift with ΔT = 2.3 °C. Mechanistically, BBR exerted its anti-CRC effects by inhibiting the Gli1/STAT3-ferroptosis negative regulation (Gli1/STAT3-FNR) axis, a novel regulatory pathway. Notably, BBR exhibited no significant organ or hematological toxicity in vivo at the experimental doses.

Conclusion: BBR triggers ferroptosis-mediated energy metabolism disorder by inhibiting Gli1/STAT3-FNR axis. This work provides a mechanistic support for BBR anti-CRC indications, and suggests an encouraging approach for treating CRC.

Introduction: Understanding of cerebral ischemic tolerance could provide important insight into viable neuroprotective strategies against ischemic stroke.

Objectives: To elucidate the function of superoxide dismutase 1 (SOD1) in cellular tolerance to ischemia and its underlying molecular mechanism.

Methods: Two-vessel occlusion of the carotid arteries and oxygen-glucose deprivation were used for modelling global ischemic preconditioning (IPC) and in vitro ischemic preconditioning models, respectively. Cleavage-Under-Targets-And-Tagmentation (CUT&Tag)-sequencing analysis was performed for mapping SOD1-whole genome-binding sites in cultured cortical neurons in the in vitro ischemic tolerance model. Cell fractionation and immunofluorescent staining were used for analyzing the subcellular localization of SOD1 in tissue and cultured neuronal cells.

Results: Here, we showed that cortex, striatum and thalamus, but not hippocampus, exhibited ischemic tolerance phenotypes after global IPC. Intriguingly, we found that SOD1 was accumulated in the cellular nucleus after IPC. Notably, cortex was the most responsive brain region in terms of neuronal SOD1 nuclear translocation in response to IPC. We further confirmed these observations in the cultured cortical neurons in the in vitro ischemic tolerance model. CUT&Tag-sequencing analysis revealed that SOD1 bound to promoter regions in cortical neurons, and its binding was significantly altered after IPC stimulus. Notably, SOD1 was most prominently accumulated at the gene promoter of CXCR4 after IPC, which was correlated with transcriptional activation of CXCR4. Furthermore, we found that upregulation of CXCR4 expression was accompanied by modulation of gene expression resulting in anti-apoptosis. Moreover, we showed that pharmacological manipulation of CXCR4 activity could regulate cell viability through STAT3 in cortical neurons. Finally, we found that SOD1 was required for CXCR4-STAT3-mediated apoptosis in the IPC-induced ischemic tolerance.

Conclusion: Therefore, these results demonstrate a non-canonical transcription-regulatory function of SOD1 which regulates CXCR4-STAT3 pathway to confer ischemic tolerance in cortical neurons.

Introduction: Adipose tissue (AT) immune cells regulate metabolic functions in obesity through both inflammatory and non-inflammatory pathways. However, the specific roles and mechanisms of individual AT immune cell types in glycemic control remain poorly understood.

Objective: This study investigates the function of myeloid-derived Zbtb46⁺ cells, a major subset of peripheral dendritic cells (DCs), in established obesity.

Methods: Chimeric Zbtb46-DTR mice were generated by transplanting bone marrow from Zbtb46-DTR donors into wild-type recipients with distinct congenic markers. Obesity was induced with a high-fat diet (HFD; 60% kcal from fat), and myeloid-derived Zbtb46⁺ cells were selectively depleted in obese mice via diphtheria toxin (DT) injection. DC-specific Dpp4 knockout (DC-Dpp4KO) mice were generated using the Cre-loxP system and subsequently challenged with the HFD.

Results: Inducible depletion of myeloid-derived Zbtb46⁺ cells improves glucose homeostasis and reduces body weight in obese mice. Notably, these effects were observed even in weight-matched mice and under conditions of increased ATM accumulation, suggesting benefits independent of weight loss or AT inflammation. The improvement in glucose homeostasis was primarily mediated by elevated GLP-1 levels, which enhanced insulin secretion and decreased food intake. Increased GLP-1 was associated with decreased DPP4 activity, attributed to the depletion of ATDCs, a key contributor to circulating DPP4. Consistently, DC-specific Dpp4 deficiency confirmed that ATDC-derived DPP4 regulates GLP-1-induced insulin secretion in obesity.

Conclusions: These findings uncover a novel, non-inflammatory role for ATDCs in glucose regulation via the DPP4/GLP-1/GLP-1R axis, positioning them as promising therapeutic targets for obesity and related metabolic diseases.

Introduction: Optimal ovarian stimulation (OS) selection is critical for IVF success, but expert-based decisions often lack consistency in outcomes, cost-efficiency, and personalization, highlighting the need for more individualized and data-driven approaches.

Objectives: This study propose an artificial intelligence (AI) system that analyzes extensive IVF-ET cycles to uncover OS-pregnancy outcome relationships, enabling personalized treatment recommendations while improving success rates and minimizing unnecessary costs.

Methods: This study analyzed anonymized data from 17,791 patients undergoing OS and IVF/ICSI at Tongji Hospital between May 2015 and May 2019. An adaptive AI model was developed to predict key indicators-including progesterone (P), number of oocytes retrieved (NOR), estradiol (E2), and endometrial thickness (EMT) on the hCG day-by integrating personal characteristics, ovarian reserve, and etiological factors. This model facilitated personalized OS selection, pregnancy outcome grading, and the development of an AI-driven clinical decision support system (CDSS).

Results: The key indicators-progesterone (P), number of oocytes retrieved (NOR), estradiol (E2), and endometrial thickness (EMT) on the hCG day-were used to establish a pregnancy grading system. Pregnancy rates are stratified as follows: Level IV (Total Score 15-16), 0.55; Level III (Total Score 13-14), 0.44; Level II (Total Score 11-12), 0.24; and Level I (Total Score 4-10), 0.07. After OS optimization, 1,355 patients who were initially at level I were elevated to a better level. Of the 2,341 patients initially in level II, 2,290 improved, and of the 3,839 initially in level III, 1,448 improved. Patients elevated to level IV accounted for 80 percent of all cases. The CDSS prioritized a GnRH antagonist regimen for 54.64 % of patients, resulting in per-patient time savings of 15.39-33.48 days and cost reductions of ¥989-¥2,623 compared to non-optimal to antagonist. Scaled to China's > 1 million ART cycles annually, this corresponds to projected direct savings of approximately ¥0.54-1.43 billion per year. In the new evaluation datasets (n = 4,251), implementation of CDSS recommendations increased the clinical pregnancy rate from 0.452 to 0.512 (p < 0.001) and reduced mean per-cycle cost from ¥7,385 to ¥7,242 (p = 0.018), demonstarting cost-effectiveness dominance with ICER saving of ¥2,383 per additional clinical pregnancy.

Conclusion: This AI-assisted CDSS streamlines clinicians' decision-making by enabling efficient and accurate initial judgments on OS, standardizing and personalizing recommendations, and optimizing OS for effectiveness and cost-efficiency.