Search Results (27)

Background and Objectives: HER2-positive breast cancer accounts for approximately 20–30% of all breast cancer cases and is associated with aggressive tumor behavior. Trastuzumab emtansine (T-DM1), an antibody-drug conjugate targeting HER2, is a standard second-line therapy for patients with metastatic disease. However, the impact of HER2 immunohistochemistry (IHC) expression levels on T-DM1 efficacy remains unclear. Materials and Methods: This retrospective study examined 87 patients with HER2-positive metastatic breast cancer who received T-DM1 following trastuzumab-based therapy. Patients were divided into IHC 2+ and IHC 3+ groups. Progression-free survival (PFS) and overall survival (OS) were evaluated via Kaplan–Meier analysis, and group comparisons were conducted using the log-rank test. Results: The median progression-free survival (PFS) for the entire cohort was 7.3 months (95% CI: 5.277–9.323), with a numerically longer PFS in the IHC 3+ group (8.4 months, 95% CI: 5.915–10.952) compared to the IHC 2+ group (6.3 months, 95% CI: 4.178–8.422). However, this difference was insignificant (HR: 0.91, 95% CI: 0.61–1.35; p = 0.778). Similarly, the median overall survival (OS) was 23.3 months (95% CI: 18.039–28.495), with the IHC 3+ group exhibiting a slightly longer OS (24.5 months, 95% CI: 18.600–30.400) compared to the IHC 2+ group (23.2 months, 95% CI: 12.387–34.147). Again, this difference did not reach statistical significance (HR: 0.93, 95% CI: 0.63–1.42; p = 0.369). Conclusions: Although the association between HER2 IHC 3+ expression and longer PFS and OS is promising, the lack of statistical significance suggests that IHC-based HER2 stratification alone may not be sufficient to predict the response to T-DM1. The potential of conducting prospective studies with larger cohorts and comprehensive molecular profiling to refine predictive biomarkers for optimizing therapeutic outcomes in HER2-positive metastatic breast cancer is a beacon of hope and should be pursued with optimism. Full article

Background/Objectives: Diabetic encephalopathy (DE), a severe neurological complication of diabetes mellitus (DM), is characterized by cognitive dysfunction. 3-Methyladenine (3-MA), a methylated adenine derivative, acts as a biomarker for DNA methylation and exhibits hypoglycemic and neuroprotective properties. However, the pharmacological mechanisms underlying 3-MA’s therapeutic effects on diabetic microvascular complications remain incompletely understood, owing to the intricate and multifactorial pathogenesis of DE. Methods: This study employed network pharmacology and molecular docking techniques to predict potential targets and signaling pathways of 3-MA against DE, with subsequent validation through animal experiments to elucidate the molecular mechanisms of 3-MA in DE treatment. Results: Network pharmacological analysis identified two key targets of 3-MA in DE modulation: AKT and GSK3β. Molecular docking confirmed a strong binding affinity between 3-MA and AKT/GSK3β. In animal experiments, 3-MA significantly reduced blood glucose levels in diabetic mice, ameliorated learning and memory deficits, and preserved hippocampal neuronal integrity. Furthermore, we found that 3-MA inhibited apoptosis by regulating the expression of Bax and BCL-2. Notably, 3-MA also downregulated the expression of amyloid precursor protein (APP) and Tau while enhancing the expression of phosphorylated AKT and GSK-3β. Conclusions: Our findings may contribute to elucidating the therapeutic mechanisms of 3-MA in diabetic microangiopathy and provide potential therapeutic targets through activation of the AKT/GSK-3β pathway. Full article

Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance and dysregulation of glucose metabolism. MicroRNAs (miRNAs) such as miR-4428 and miR-185-5p play critical roles in post-transcriptional regulation of genes involved in these processes, but their specific contributions to T2DM pathogenesis remain unclear. Plasma samples from T2DM patients and non-diabetic controls were analyzed for miR-4428 and miR-185-5p expression using microarray and bioinformatics tools. Target genes were predicted, and pathway enrichment analysis was performed to explore biological roles. Differential expression analysis revealed a 2.3-fold upregulation of miR-4428 and a 14.4-fold downregulation of miR-185-5p in T2DM patients compared to controls. Predicted targets such as ADAR, KLF9, and SOGA1 were linked to glucose metabolism and insulin signaling pathways. Enrichment analysis highlighted associations with neuronal signaling, chromatin remodeling, and metabolic regulation pathways. miR-4428 and miR-185-5p regulate critical insulin sensitivity and glucose metabolism pathways, making them promising biomarkers and therapeutic targets for managing T2DM. Future studies should validate these findings experimentally to advance miRNA-based interventions for T2DM and its complications. Full article

Background: The global prevalence of type 2 diabetes mellitus (T2DM) with liver fibrosis is rising, with T2DM identified as an independent risk factor and key prognostic factor for liver fibrosis. However, the underlying mechanisms remain unclear. Methods: To explore the shared pathogenesis of liver fibrosis and T2DM, we analyzed gene expression profiles from the GEO database. The co-differentially expressed genes (co-DEGs) were identified and subsequently analyzed through functional enrichment, protein–protein interaction (PPI) network construction, transcription factor prediction, and drug prediction. Machine learning algorithms were then applied to identify key genes. Results: A total of 175 co-DEGs were identified. Functional enrichment analysis indicated their involvement in extracellular matrix (ECM) remodeling, inflammation, and the PI3K/Akt signaling pathway. Through PPI network analysis and four algorithms, eight hub genes were identified, including SPARC, COL4A2, THBS1, LUM, TIMP3, COL3A1, IGFBP7, and FSTL1, with THBS1 being recognized as a key gene by machine learning. The upregulation of THBS1 was observed in both diseases, and it is closely related to the progression of liver fibrosis and T2DM. Transcription factor analysis detected 29 regulators of these hub genes. Drug prediction analysis suggested that retinoic acid may serve as a potential therapeutic agent. Conclusions: This study provides novel insights into the shared pathogenesis of liver fibrosis and T2DM and offer potential targets for clinical intervention. Full article

Diabetic cardiomyopathy (DCM), a critical complication of type 2 diabetes mellitus (T2DM), is marked by metabolic dysfunction, oxidative stress, and chronic inflammation, ultimately progressing to heart failure. This study investigated the synergistic therapeutic potential of Hippophae rhamnoides L. (sea buckthorn, SBU) extract and metformin in a mouse model of T2DM-induced DCM. T2DM was induced using a 45% high-fat-AGEs-enriched diet, followed by treatment with SBU, metformin, or their combination. Treatment effects were monitored through bioinformatic analysis, chemoinformatic prediction, behavioral testing, biochemical assays, histopathological evaluations and gene expression profiles. Based on bioinformatic analysis, we identified key hub genes involved in the diabetic cardiomyopathy including SERPINE1, NRG1, MYH11, PTH, NR4A2, NRF2, PGC1α, GPX4, ATF1, ASCL2, NOX1, NLRP3, CCK8, COX2, CCL2, PTGS2, EGFR, and oncostatin, which are pivotal in modulating the ferroptosis pathway. Furthermore, the expression of long non-coding RNAs (lncRNAs) NEAT1 and MALAT1, critical regulators of inflammation and cell death, was effectively downregulated, correlating with decreased levels of the pro-inflammatory marker oncostatin. The combined therapy significantly improved glucose regulation, reduced systemic inflammation and protected the heart from oxidative damage. Histopathological analysis revealed notable reductions in cardiac necrosis and fibrosis. Particularly, the combination therapy of SBU and metformin demonstrated a synergistic effect, surpassing the benefits of individual treatments in preventing cardiac damage. These findings highlight the potential of integrating SBU with metformin as a novel therapeutic strategy for managing DCM by targeting both metabolic and ferroptosis-related pathways. This dual intervention opens promising avenues for future clinical applications in diabetic heart disease management, offering a comprehensive approach to mitigating the progression of DCM. Full article

Background: Lung adenocarcinoma (LUAD) is a common histopathological variant of non-small cell lung cancer. Individuals with type 2 diabetes (T2DM) face an elevated risk of developing LUAD. We examined the common genomic characteristics between LUAD and T2DM through bioinformatics analysis. Methods: We acquired the GSE40791, GSE25724, GSE10072, and GSE71416 datasets. Differentially expressed genes (DEGs) were identified through R software, particularly its version 4.1.3 and analyzed via gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Subsequently, we analyzed the relationship between immune cell infiltration and DEGs. we constructed a protein–protein interaction network using STRING and visualized it with Cytoscape. Moreover, gene modules were identified utilizing the MCODE plugin, and hub genes were selected through the CytoHubba plugin. Additionally, we evaluated the predictive significance of hub genes using receiver operating characteristic curves and identified the final central hub genes. Finally, we forecasted the regulatory networks of miRNA and transcription factors for the central hub genes. Results: A total of 748 DEGs were identified. Analysis of immune infiltration showed a notable accumulation of effector-memory CD8 T cells, T follicular helper cells, type 1 T helper cells, activated B cells, natural killer cells, macrophages, and neutrophils in both LUAD and T2DM. Moreover, these DEGs were predominantly enriched in immune-related pathways, including the positive regulation of I-κB kinase/NF-κB signaling, positive regulation of immunoglobulin production, cellular response to interleukin-7, and cellular response to interleukin-4. The TGF-β signaling pathway was significantly important among them. Additionally, seven hub genes were identified, including ATR, RFC4, MCM2, NUP155, NUP107, NUP85, and NUP37. Among them, ATR, RFC4, and MCM2 were identified as pivotal hub genes. Additionally, hsa-mir147a, hsa-mir16-5p, and hsa-mir-1-3p were associated with LUAD and T2DM. SP1 (specific protein 1) and KDM5A (lysine-specific demethylase 5A) regulated MCM2, ATR, and RFC4. Conclusions: Our study elucidates the common mechanisms of immune response, TGF-β signaling pathway, and natural killer cells in LUAD and T2DM, and identifies ATR, RFC4, and MCM2 as key potential biomarkers and therapeutic targets for the comorbidity of these two conditions. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continually undergoes mutation, leading to variants with altered pathogenicity and transmissibility. The Omicron variant (B.1.1.529), first identified in South Africa in 2021, has become the dominant strain worldwide. It harbors approximately 50 mutations compared to the original strain, with 15 located in the receptor-binding domain (RBD) of the spike protein that facilitates viral entry via binding to the human angiotensin-converting enzyme 2 (ACE2) receptor. How do these mutated residues modulate the intermolecular interactions and binding affinity between the RBD and ACE2? This is a question of great theoretical importance and practical implication. In this study, we employed quantum chemical calculations at the B2PLYP-D3/def2-TZVP level of theory to investigate the molecular determinants governing Omicron’s ACE2 interaction. Comparative analysis of the Omicron and wild-type RBD–ACE2 interfaces revealed that mutations including S477N, Q493R, Q498R, and N501Y enhance binding through the formation of bifurcated hydrogen bonds, π–π stacking, and cation–π interactions. These favorable interactions counterbalance such destabilizing mutations as K417N, G446S, G496S, and Y505H, which disrupt salt bridges and hydrogen bonds. Additionally, allosteric effects improve the contributions of non-mutated residues (notably A475, Y453, and F486) via structural realignment and novel hydrogen bonding with ACE2 residues such as S19, leading to an overall increase in the electrostatic and π-system interaction energy. In conclusion, our findings provide a mechanistic basis for Omicron’s increased infectivity and offer valuable insights for the development of targeted antiviral therapies. Moreover, from a methodological perspective, we directly calculated mutation-induced binding energy changes at the residue level using advanced quantum chemical methods rather than relying on the indirect decomposition schemes typical of molecular dynamics-based free energy analyses. The strong correlation between calculated energy differences and experimental deep mutational scanning (DMS) data underscores the robustness of the theoretical framework in predicting the effects of RBD mutations on ACE2 binding affinity. This demonstrates the potential of quantum chemical methods as predictive tools for studying mutation-induced changes in protein–protein interactions and guiding rational therapeutic design. Full article

Metabolic disorders, including type 2 diabetes mellitus (T2DM), obesity, and metabolic syndrome, are systemic conditions that profoundly impact the skin microbiota, a dynamic community of bacteria, fungi, viruses, and mites essential for cutaneous health. Dysbiosis caused by metabolic dysfunction contributes to skin barrier disruption, immune dysregulation, and increased susceptibility to inflammatory skin diseases, including psoriasis, atopic dermatitis, and acne. For instance, hyperglycemia in T2DM leads to the formation of advanced glycation end products (AGEs), which bind to the receptor for AGEs (RAGE) on keratinocytes and immune cells, promoting oxidative stress and inflammation while facilitating Staphylococcus aureus colonization in atopic dermatitis. Similarly, obesity-induced dysregulation of sebaceous lipid composition increases saturated fatty acids, favoring pathogenic strains of Cutibacterium acnes, which produce inflammatory metabolites that exacerbate acne. Advances in metabolomics and microbiome sequencing have unveiled critical biomarkers, such as short-chain fatty acids and microbial signatures, predictive of therapeutic outcomes. For example, elevated butyrate levels in psoriasis have been associated with reduced Th17-mediated inflammation, while the presence of specific Lactobacillus strains has shown potential to modulate immune tolerance in atopic dermatitis. Furthermore, machine learning models are increasingly used to integrate multi-omics data, enabling personalized interventions. Emerging therapies, such as probiotics and postbiotics, aim to restore microbial diversity, while phage therapy selectively targets pathogenic bacteria like Staphylococcus aureus without disrupting beneficial flora. Clinical trials have demonstrated significant reductions in inflammatory lesions and improved quality-of-life metrics in patients receiving these microbiota-targeted treatments. This review synthesizes current evidence on the bidirectional interplay between metabolic disorders and skin microbiota, highlighting therapeutic implications and future directions. By addressing systemic metabolic dysfunction and microbiota-mediated pathways, precision strategies are paving the way for improved patient outcomes in dermatologic care. Full article

This systematic review extensively investigated the role of the genetic and transcriptomic factors in late complications of type 2 diabetes mellitus (T2DM) and the current approaches targeting oxidative-stress-related pathways with antioxidant therapies. To cover our broad research area, we have conducted two systematic searches, the first focusing on genetic and transcriptomic factors affecting oxidative stress and the second one focusing on the antioxidant therapies in late complications of T2DM. The final review included 33 genetic and transcriptomic studies and 23 interventional randomized clinical trials. The conducted systematic review highlights the important role of oxidative stress in the development of late complications in T2DM patients. However, the current level of evidence does not support the use of genetic and transcriptomic factors as predictive and prognostic biomarkers for the development of T2DM late complications. Further studies are needed to elucidate the potential of targeting oxidative-stress-related pathways for novel preventative and therapeutic approaches. Additionally, antioxidants both in dietary and supplement form have been shown to improve different metabolic and biochemical parameters in T2DM patients with developed late complications. In recent years, studies have improved in methodological quality despite still mainly focusing on microvascular late complications of T2DM. Furthermore, the observed interventional studies suggest non-homogeneity in the duration of observation. As many studies do not provide post-intervention follow-up testing, it is difficult to assess the long-term health benefits of antioxidant supplementation. Full article

Inhibiting the activity of intestinal α-glucosidase is considered an effective approach for treating type II diabetes mellitus (T2DM). In this study, we employed an in vitro enzymatic synthesis approach to synthesize four derivatives of natural products (NPs) for the discovery of therapeutic drugs for T2DM. Network pharmacology analysis revealed that the betulinic acid derivative P3 exerted its effects in the treatment of T2DM through multiple targets. Neuroactive ligand–receptor interaction and the calcium signaling pathway were identified as key signaling pathways involved in the therapeutic action of compound P3 in T2DM. The results of molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations indicate that compound P3 exhibits a more stable binding interaction and lower binding energy (−41.237 kcal/mol) with α-glucosidase compared to acarbose. In addition, compound P3 demonstrates excellent characteristics in various pharmacokinetic prediction models. Therefore, P3 holds promise as a lead compound for the development of drugs for T2DM and warrants further exploration. Finally, we performed site-directed mutagenesis to achieve targeted synthesis of betulinic acid derivative. This work demonstrates a practical strategy of discovering novel anti-hyperglycemic drugs from derivatives of NPs synthesized through in vitro enzymatic synthesis technology, providing potential insights into compound P3 as a lead compound for anti-hyperglycemic drug development. Full article

The impact of yttrium 90 radioembolization (Y90-RE) in combination with immune checkpoint inhibitors (ICIs) has recently gained attention. However, it is unclear how sequencing and dosage affect therapeutic efficacy. The purpose of this study was to develop a mathematical model to simulate the synergistic effects of Y90-RE and ICI combination therapy and find the optimal treatment sequences and dosages. We generated a hypothetical patient cohort and conducted simulations to apply different treatments to the same patient. The compartment of models is described with ordinary differential equations (ODEs), which represent targeted tumors, non-targeted tumors, and lymphocytes. We considered Y90-RE as a local treatment and ICIs as a systemic treatment. The model simulations show that Y90-RE and ICIs administered simultaneously yield greater benefits than subsequent sequential therapy. In addition, applying Y90-RE before ICIs has more benefits than applying ICIs before Y90-RE. Moreover, we also observed that the median PFS increased up to 31~36 months, and the DM rates at 3 years decreased up to 36~48% as the dosage of the two drugs increased (p < 0.05). The proposed model predicts a significant benefit of Y90-RE with ICIs from the results of the reduced irradiated tumor burden and the associated immune activation and suppression. Our model is expected to help optimize complex strategies and predict the efficacy of clinical trials for HCC patients. Full article

Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance and/or defective insulin production in the human body. Although the antidiabetic action of corn silk (CS) is well-established, the understanding of the mechanism of action (MoA) behind this potential is lacking. Hence, this study aimed to elucidate the MoA in different samples (raw and three extracts: aqueous, hydro-ethanolic, and ethanolic) as a therapeutic agent for the management of T2DM using metabolomic profiling and computational techniques. Ultra-performance liquid chromatography-mass spectrometry (UP-LCMS), in silico techniques, and density functional theory were used for compound identification and to predict the MoA. A total of 110 out of the 128 identified secondary metabolites passed the Lipinski’s rule of five. The Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis revealed the cAMP pathway as the hub signaling pathway, in which ADORA1, HCAR2, and GABBR1 were identified as the key target genes implicated in the pathway. Since gallicynoic acid (−48.74 kcal/mol), dodecanedioc acid (−34.53 kcal/mol), and tetradecanedioc acid (−36.80 kcal/mol) interacted well with ADORA1, HCAR2, and GABBR1, respectively, and are thermodynamically stable in their formed compatible complexes, according to the post-molecular dynamics simulation results, they are suggested as potential drug candidates for T2DM therapy via the maintenance of normal glucose homeostasis and pancreatic β-cell function. Full article

Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), imposes a significant global burden with adverse clinical outcomes and escalating healthcare expenditures. Early identification of biomarkers can facilitate better screening, earlier diagnosis, and the prevention of diabetes. However, current clinical predictors often fail to detect abnormalities during the prediabetic state. Emerging studies have identified specific amino acids as potential biomarkers for predicting the onset and progression of diabetes. Understanding the underlying pathophysiological mechanisms can offer valuable insights into disease prevention and therapeutic interventions. This review provides a comprehensive summary of evidence supporting the use of amino acids and metabolites as clinical biomarkers for insulin resistance and diabetes. We discuss promising combinations of amino acids, including branched-chain amino acids, aromatic amino acids, glycine, asparagine and aspartate, in the prediction of T2DM. Furthermore, we delve into the mechanisms involving various signaling pathways and the metabolism underlying the role of amino acids in disease development. Finally, we highlight the potential of targeting predictive amino acids for preventive and therapeutic interventions, aiming to inspire further clinical investigations and mitigate the progression of T2DM, particularly in the prediabetic stage. Full article

Diabetes mellitus is a chronic multifaceted disease with multiple potential complications, the treatment of which can only delay and prolong the terminal stage of the disease, i.e., type 2 diabetes mellitus (T2DM). The World Health Organization predicts that diabetes will be the seventh leading cause of death by 2030. Although many antidiabetic medicines have been successfully developed in recent years, such as GLP-1 receptor agonists and SGLT-2 inhibitors, single-target drugs are gradually failing to meet the therapeutic requirements owing to the individual variability, diversity of pathogenesis, and organismal resistance. Therefore, there remains a need to investigate the pathogenesis of T2DM in more depth, identify multiple therapeutic targets, and provide improved glycemic control solutions. This review presents an overview of the mechanisms of action and the development of the latest therapeutic agents targeting T2DM in recent years. It also discusses emerging target-based therapies and new potential therapeutic targets that have emerged within the last three years. The aim of our review is to provide a theoretical basis for further advancement in targeted therapies for T2DM. Full article

The sigma 1 receptor (S1R) is a 223-amino-acid-long transmembrane endoplasmic reticulum (ER) protein. The S1R plays an important role in neuronal health and it is an established therapeutic target for neurodegenerative and neuropsychiatric disorders. Despite its importance in physiology and disease, the biological function of S1R is poorly understood. To gain insight into the biological and signaling functions of S1R, we took advantage of recently reported crystal structures of human and Xenopus S1Rs and performed structural modeling of S1R interactions with ligands and cholesterol in the presence of the membrane. By combining bioinformatics analysis of S1R sequence and structural modelling approaches, we proposed a model that suggests that S1R may exist in two distinct conformations—“dynamic monomer” (DM) and “anchored monomer” (AM). We further propose that equilibrium between AM and DM conformations of S1R is essential for its biological function in cells, with AM conformation facilitating the oligomerization of S1R and DM conformation facilitating deoligomerization. Consistent with experimental evidence, our hypothesis predicts that increased levels of membrane cholesterol and S1R antagonists should promote the oligomeric state of S1R, but S1R agonists and pathogenic mutations should promote its deoligomerization. Obtained results provide mechanistic insights into signaling functions of S1R in cells, and the proposed model may help to explain neuroprotective effects of S1R modulators. Full article