Clinical and prognostic significance analysis of glycolysis-related genes in HNSCC.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) represents one of the most malignant cancers worldwide, with poor survival. Experimental evidence implies that glycolysis/hypoxia is associated with HNSCC. In this study, we aimed to construct a novel glycolysis-/hypoxia-related gene (GHRG) signature for survival prediction of HNSCC. METHODS: A multistage screening strategy was used to establish the GHRG prognostic model by univariate/least absolute shrinkage and selection operator (LASSO)/step multivariate Cox regressions from The Cancer Genome Atlas cohort. A nomogram was constructed to quantify the survival probability. Correlations between risk score and immune infiltration and chemotherapy sensitivity were explored. RESULTS: We established a 12-GHRG mRNA signature to predict the prognosis in HNSCC patients. Patients in the high-risk score group had a much worse prognosis. The predictive power of the model was validated by external HNSCC cohorts, and the model was identified as an independent factor for survival prediction. Immune infiltration analysis showed that the high-risk score group had an immunosuppressive microenvironment. Finally, the model was effective in predicting chemotherapeutic sensitivity. CONCLUSIONS: Our study demonstrated that the GHRG model is a robust prognostic tool for survival prediction of HNSCC. Findings of this work provide novel insights for immune infiltration and chemotherapy of HNSCC, and may be applied clinically to guide therapeutic strategies.

IR808@MnO nano-near infrared fluorescent dye's diagnostic value for malignant pleural effusion.

BACKGROUND: Malignant pleural effusion is mostly a complication of advanced malignant tumors. However, the cancer markers such as carbohydrate antigen 125 (CA 125), carbohydrate antigen 15-3 (CA 15-3), carbohydrate antigen 19-9 (CA 19-9), and cytokeratin fragment 21-1 (CYFRA 21-1) have low sensitivity and organ specificity for detecting malignant pleural effusion. RESEARCH QUESTION: Is IR808@MnO nano-near infrared fluorescent dye worthy for the diagnosis in differentiating benign and malignant pleural effusions. STUDY DESIGN AND METHODS: This experiment was carried out to design and characterize the materials for in vitro validation of the new dye in malignant tumor cells in the A549 cell line and in patients with adenocarcinoma pleural effusion. The dye was verified to possess tumor- specific targeting capabilities. Subsequently, a prospective hospital-based observational study was conducted, enrolling 106 patients and excluding 28 patients with unknown diagnoses. All patients underwent histopathological analysis of thoracoscopic biopsies, exfoliative cytological analysis of pleural fluid, and analysis involving the new dye. Statistical analyses were performed using Microsoft Excel, GraphPad Prism, and the R language. RESULTS: The size of IR808@MnO was 136.8 ± 2.9 nm, with peak emission at 808 nm, and it has near-infrared fluorescence properties. Notably, there was a significant difference in fluorescence values between benign and malignant cell lines (p < 0.0001). The malignant cell lines tested comprised CL1-5, A549, MDA-MB-468, U-87MG, MKN-7, and Hela, while benign cell lines were BEAS-2B, HUVEC, HSF, and VE. The most effective duration of action was identified as 30 min at a concentration of 5 µl. This optimal duration of action and concentration were consistent in patients with lung adenocarcinoma accompanied by pleural effusion and 5 µl. Of the 106 patients examined, 28 remained undiagnosed, 39 were diagnosed with malignant pleural effusions, and the remaining 39 with benign pleural effusions. Employing the new IR808@MnO staining method, the sensitivity stood at 74.4%, specificity at 79.5%, a positive predictive value of 69.2%, and a negative predictive value of 82.1%. The area under the ROC curve was recorded as 0.762 (95% CI: 0.652-0.872). The confusion matrix revealed a positive predictive value of 75.7%, a negative predictive value of 75.6%, a false positive rate of 22.5%, and a false negative rate of 26.3%. INTERPRETATION: The IR808@MnO fluorescent probe represents an efficient, sensitive, and user-friendly diagnostic tool for detecting malignant pleural fluid, underscoring its significant potential for clinical adoption.

Insights into the Interaction Mechanisms of Peptide and Non-Peptide Inhibitors with MDM2 Using Gaussian-Accelerated Molecular Dynamics Simulations and Deep Learning.

Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2', as well as the ß-strands and loops between α2 and α2'. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics-generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor-MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members.

Unveiling Conformational States of CDK6 Caused by Binding of Vcyclin Protein and Inhibitor by Combining Gaussian Accelerated Molecular Dynamics and Deep Learning.

CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy landscapes (FELs). DL finds that the binding pocket as well as the T-loop binding to the Vcyclin protein are involved in obvious differences of conformation contacts. This result suggests that the binding pocket of inhibitors (LQQ and AP9) and the binding interface of CDK6 to the Vcyclin protein play a key role in the function of CDK6. The analyses of FELs reveal that the binding pocket and the T-loop of CDK6 have disordered states. The results from principal component analysis (PCA) indicate that the binding of the Vcyclin protein affects the fluctuation behavior of the T-loop in CDK6. Our QM/MM-GBSA calculations suggest that the binding ability of LQQ to CDK6 is stronger than AP9 with or without the binding of the Vcyclin protein. Interaction networks of inhibitors with CDK6 were analyzed and the results reveal that LQQ contributes more hydrogen binding interactions (HBIs) and hot interaction spots with CDK6. In addition, the binding pocket endures flexibility changes from opening to closing states and the Vcyclin protein plays an important role in the stabilizing conformation of the T-loop. We anticipate that this work could provide useful information for further understanding the function of CDK6 and developing new promising inhibitors targeting CDK6.

Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.

Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calculations are integrated to probe the binding modes of three inhibitors (H1B, JQ1 and TVU) to BRD4 and BRD9. The MD trajectory-based DL successfully identify significant functional function domains, such as BC-loop and ZA-loop. The information from the post-processing analysis of MD simulations indicates that inhibitor binding highly influences the structural flexibility and dynamic behavior of BRD4 and BRD9. The results of the MM-GBSA calculations not only suggest that the binding ability of H1B, JQ1 and TVU to BRD9 are stronger than to BRD4, but they also verify that van der Walls interactions are the primary forces responsible for inhibitor binding. The hot spots of BRD4 and BRD9 revealed by residue-based free energy estimation provide target sites of drug design in regard to BRD4 and BRD9. This work is anticipated to provide useful theoretical aids for the development of selective inhibitors over BRD family members.

Unveiling Allosteric Regulation and Binding Mechanism of BRD9 through Molecular Dynamics Simulations and Markov Modeling.

Bromodomain-containing protein 9 (BRD9) is a key player in chromatin remodeling and gene expression regulation, and it is closely associated with the development of various diseases, including cancers. Recent studies have indicated that inhibition of BRD9 may have potential value in the treatment of certain cancers. Molecular dynamics (MD) simulations, Markov modeling and principal component analysis were performed to investigate the binding mechanisms of allosteric inhibitor POJ and orthosteric inhibitor 82I to BRD9 and its allosteric regulation. Our results indicate that binding of these two types of inhibitors induces significant structural changes in the protein, particularly in the formation and dissolution of α-helical regions. Markov flux analysis reveals notable changes occurring in the α-helicity near the ZA loop during the inhibitor binding process. Calculations of binding free energies reveal that the cooperation of orthosteric and allosteric inhibitors affects binding ability of inhibitors to BRD9 and modifies the active sites of orthosteric and allosteric positions. This research is expected to provide new insights into the inhibitory mechanism of 82I and POJ on BRD9 and offers a theoretical foundation for development of cancer treatment strategies targeting BRD9.

Molecular Mechanism of Phosphorylation-Mediated Impacts on the Conformation Dynamics of GTP-Bound KRAS Probed by GaMD Trajectory-Based Deep Learning.

The phosphorylation of different sites produces a significant effect on the conformational dynamics of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations were combined with deep learning (DL) to explore the molecular mechanism of the phosphorylation-mediated effect on conformational dynamics of the GTP-bound KRAS. The DL finds that the switch domains are involved in obvious differences in conformation contacts and suggests that the switch domains play a key role in the function of KRAS. The analyses of free energy landscapes (FELs) reveal that the phosphorylation of pY32, pY64, and pY137 leads to more disordered states of the switch domains than the wild-type (WT) KRAS and induces conformational transformations between the closed and open states. The results from principal component analysis (PCA) indicate that principal motions PC1 and PC2 are responsible for the closed and open states of the phosphorylated KRAS. Interaction networks were analyzed and the results verify that the phosphorylation alters interactions of GTP and magnesium ion Mg2+ with the switch domains. It is concluded that the phosphorylation pY32, pY64, and pY137 tune the activity of KRAS through changing conformational dynamics and interactions of the switch domains. We anticipated that this work could provide theoretical aids for deeply understanding the function of KRAS.

Current mRNA-based vaccine strategies for glioma treatment.

Gliomas are one of the most aggressive types of brain tumors and are associated with high morbidity and mortality rates. Currently, conventional treatments for gliomas such as surgical resection, radiotherapy, and chemotherapy have limited effectiveness, and new approaches are needed to improve patient outcomes. mRNA-based vaccines represent a promising therapeutic strategy for cancer treatment, including gliomas. Recent advances in immunotherapy using mRNA-based dendritic cell vaccines have shown great potential in preclinical and clinical trials. Dendritic cells are professional antigen-presenting cells that play a crucial role in initiating and regulating immune responses. In this review, we summarize the current progress of mRNA-based vaccines for gliomas, with a focus on recent advances in dendritic cell-based mRNA vaccines. We also discuss the feasibility and safety of mRNA-based clinical applications for gliomas.

A Diagnostic Nomogram for Predicting Hypercapnic Respiratory Failure in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

Purpose: To develop and validate a nomogram for assessing the risk of developing hypercapnic respiratory failure (HRF) in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Patients and Methods: From January 2019 to August 2023, a total of 334 AECOPD patients were enrolled in this research. We employed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression to determine independent predictors and develop a nomogram. This nomogram was appraised by the area under the receiver operating characteristic curve (AUC), calibration curve, Hosmer-Lemeshow goodness-of-fit test (HL test), decision curve analysis (DCA), and clinical impact curve (CIC). The enhanced bootstrap method was used for internal validation. Results: Sex, prognostic nutritional index (PNI), hematocrit (HCT), and activities of daily living (ADL) were independent predictors of HRF in AECOPD patients. The developed nomogram based on the above predictors showed good performance. The AUCs for the training, internal, and external validation cohorts were 0.841, 0.884, and 0.852, respectively. The calibration curves and HL test showed excellent concordance. The DCA and CIC showed excellent clinical usefulness. Finally, a dynamic nomogram was developed (https://a18895635453.shinyapps.io/dynnomapp/). Conclusion: This nomogram based on sex, PNI, HCT, and ADL demonstrated high accuracy and clinical value in predicting HRF. It is a less expensive and more accessible approach to assess the risk of developing HRF in AECOPD patients, which is more suitable for primary hospitals, especially in developing countries with high COPD-related morbidity and mortality.

Long-term effects of chronic exposure to electronic cigarette aerosol on the cardiovascular and pulmonary system in mice: A comparative study to cigarette smoke.

Electronic cigarettes (e-cigarettes) have rapidly gained popularity as alternatives to traditional combustible cigarettes. However, their long-term health impact remains uncertain. This study aimed to investigate the effects of chronic exposure to e-cigarette aerosol (ECA) in mice compared to conventional cigarette smoke (CS) exposure. The mice were exposed to air (control), low, medium, or high doses of ECA, or a reference CS dose orally and nasally for eight months. Various cardiovascular and pulmonary assessments have been conducted to determine the biological and prosthetic effects. Histopathological analysis was used to determine structural changes in the heart and lungs. Biological markers associated with fibrosis, inflammation, and oxidative stress were investigated. Cardiac proteomic analysis was applied to reveal the shared and unique protein expression changes in ECA and CS groups, which related to processes such as immune activation, lipid metabolism, and intracellular transport. Overall, chronic exposure to ECA led to adverse cardiovascular and pulmonary effects in mice, although they were less pronounced than those of CS exposure. This study provides evidence that e-cigarettes may be less harmful than combustible cigarettes for the long-term health of the cardiovascular and respiratory systems in mice. However, further human studies are needed to clarify the long-term health risks associated with e-cigarette use.

Mitocytosis Mediated by an Enzyme-Activable Mitochondrion-Disturbing Polymer-Drug Conjugate Enhances Active Penetration in Glioblastoma Therapy.

The application of nanomedicines for glioblastoma (GBM) therapy is hampered by the blood-brain barrier (BBB) and the dense glioblastoma tissue. To achieve efficient BBB crossing and deep GBM penetration, this work demonstrates a strategy of active transcellular transport of a mitochondrion-disturbing nanomedicine, pGBEMA22-b-pSSPPT9 (GBEPPT), in the GBM tissue through mitocytosis. GBEPPT is computer-aided designed and prepared by self-assembling a conjugate of an amphiphilic block polymer and a drug podophyllotoxin (PPT). When GBEPPT is delivered to the tumor site, overexpressed γ-glutamyl transpeptidase (GGT) on the brain-blood endothelial cell, or the GBM cell triggered enzymatic hydrolysis of γ-glutamylamide on GBEPPT to reverse its negative charge to positive. Positively charged GBEPPT rapidly enter into the cell and target the mitochondria. These GBEPPT disturb the homeostasis of mitochondria, inducing mitocytosis-mediated extracellular transport of GBEPPT to the neighboring cells via mitosomes. This intracellular-to-intercellular delivery cycle allows GBEPPT to penetrate deeply into the GBM parenchyma, and exert sustainable action of PPT released from GBEPPT on the tumor cells along its penetration path at the tumor site, thus improving the anti-GBM effect. The process of mitocytosis mediated by the mitochondrion-disturbing nanomedicine may offer great potential in enhancing drug penetration through malignant tissues, especially poorly permeable solid tumors.

let-7b-5p suppresses the proliferation and migration of pulmonary artery smooth muscle cells via down-regulating IGF1

Abstract Objectives Some previous studies indicated that the excessive proliferation and migration of Pulmonary Artery Smooth Muscle Cells (PASMCs) could be observed in pulmonary artery intima after Pulmonary Embolism (PE) occurred. In addition, recent studies identified some miRNAs that are differentially expressed in the blood of PE patients, which might be used as a diagnostic biomarker for PE, including let-7a-5p, let-7b-5p, and miR-150-5p. Hence, the authors sought to explore the effects of let-7b-5p in PASMC proliferation and migration and the corresponding regulatory mechanism. Methods Platelet-Derived Growth Factor (PDGF) was utilized to induce the hyper-proliferation model in PASMCs. The mRNA and protein expression levels were detected by RT-qPCR and western blot, respectively. The proliferation of PASMCs was evaluated by the detection of PCNA expression, as well as CCK-8 and Edu assays. Wound healing and Transwell assays were exploited to assess the migration ability of PASMCs. The targets of let-7b-5p were predicted based on two bioinformatics online tools. Dual-luciferase and Ago2 pull-down assays were applied to confirm the interaction between let-7b-5p and IGF1. Results 40 ng/mL PDGF was selected as the optimal concentration to induce PASMCs. let-7b-5p mimics suppressed the proliferation and migration of PDGF-induced PASMCs, while let-7b-5p inhibitor led to the opposite result. In further mechanism exploration, IGF1 was predicted and confirmed as the direct target gene of let-7b-5p. The promotion role of IGF1 overexpression on the proliferation and migration of PDGF-induced PASMCs was dramatically countered by let-7b-5p mimics. Conclusion let-7b-5p prohibits the proliferation and migration of PDGF-induced PASMCs by modulating IGF1.