Network pharmacology-based investigation and experimental validation of the mechanism of metformin in the treatment of acute myeloid leukemia.

Metformin, a widely used anti-diabetic agent, has shown significant anti-cancer properties as reported in in various cancers, including acute myeloid leukemia. However, the detailed mechanisms by which metformin influences acute myeloid leukemia remain unrevealed. Employing a synergistic approach of network pharmacology and experimental validation, this study systematically identifies and analyzes potential metformin targets and AML-related genes. These findings are then cross-referenced with biomedical databases to construct a target-gene network, providing insights into metformin's pharmacodynamics in AML treatment. Protein-Protein Interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses are utilized. Results show metformin's effectiveness in inhibiting AML cell proliferation and inducing apoptosis through the AKT/HIF1A/PDK1 signaling pathway. This research provides insights into metformin's clinical application in AML treatment.

Bioinformatics analysis and experimental verification of TIGD1 in non-small cell lung cancer.

Introduction: Non-small cell lung cancer (NSCLC) is a prevalent respiratory system tumor. Triggered transposable element derivative 1 (TIGD1) exhibits significant overexpression in various tumor cells and tissues, suggesting its involvement in cancer progression. Methods: Clinical data and gene expression profiles of lung adenocarcinoma were collected from TCGA, UCSC XENA, and GEO databases. Computational techniques and empirical studies were employed to analyze the role of TIGD1 in NSCLC. Cellular experiments were conducted using the H1299 cell line, including RNA interference, cell viability assays, quantitative PCR, wound-healing assays, western blotting, and plate clone formation assays. Results: Bioinformatics analysis revealed TIGD1's potential as a biomarker for diagnosing and predicting lung cancer. It also indicated promise as a target for immune-related therapy and targeted drug therapy. Cellular studies confirmed TIGD1's involvement in cancer cell proliferation, invasion, and migration. Furthermore, an association between TIGD1 and the PI3K/AKT signaling pathway was suggested. Discussion: The findings suggest that TIGD1 plays a vital role in NSCLC progression, making it a potential diagnostic biomarker and therapeutic target. The association with the PI3K/AKT signaling pathway provides insights into the underlying molecular mechanisms. Integrating computational analysis with empirical studies enhances our understanding of TIGD1's significance in NSCLC and opens avenues for further research into targeted therapies.

Machine learning-identified stemness features and constructed stemness-related subtype with prognosis, chemotherapy, and immunotherapy responses for non-small cell lung cancer patients.

AIM: This study aimed to explore a novel subtype classification method based on the stemness characteristics of patients with non-small cell lung cancer (NSCLC). METHODS: Based on the Cancer Genome Atlas database to calculate the stemness index (mRNAsi) of NSCLC patients, an unsupervised consensus clustering method was used to classify patients into two subtypes and analyze the survival differences, somatic mutational load, copy number variation, and immune characteristics differences between them. Subsequently, four machine learning methods were used to construct and validate a stemness subtype classification model, and cell function experiments were performed to verify the effect of the signature gene ARTN on NSCLC. RESULTS: Patients with Stemness Subtype I had better PFS and a higher somatic mutational burden and copy number alteration than patients with Stemness Subtype II. In addition, the two stemness subtypes have different patterns of tumor immune microenvironment. The immune score and stromal score and overall score of Stemness Subtype II were higher than those of Stemness Subtype I, suggesting a relatively small benefit to immune checkpoints. Four machine learning methods constructed and validated classification model for stemness subtypes and obtained multiple logistic regression equations for 22 characteristic genes. The results of cell function experiments showed that ARTN can promote the proliferation, invasion, and migration of NSCLC and is closely related to cancer stem cell properties. CONCLUSION: This new classification method based on stemness characteristics can effectively distinguish patients' characteristics and thus provide possible directions for the selection and optimization of clinical treatment plans.

In vitroapplication of drug-loaded hydrogel combined with 3D-printed porous scaffolds.

Titanium mesh and three-dimensional titanium alloy scaffolds play a key role in addressing oral and maxillofacial bone defects, which can provide a specific environment and structure for bone growth and development. The two main causes of implant surgery failure are aseptic loosening and bacterial-induced implant-associated infections. To make bone defect implants effective for a long time, the ideal scaffold should take into account the two functions of osseointegration and anti-infection. Therefore, on the basis of the low-elastic-modulus Ti-10Ta-2Nb-2Zr (TTNZ) alloys developed by the research group in the early stage, this study intends to combine the vancomycin-loaded hydrogel with the 3D-printed through-hole porous titanium alloy scaffold to endow 3D-printed TTNZ scaffolds with antibacterial properties. The antibacterial properties of the complex were investigated by the zone of inhibition test and the adhesion/free antibacterial test. The effects of the composite system on osseointegration were investigated from the aspects of cell adhesion, cell proliferation and osteogenesis-related gene expression. The results showed that loading 2.5 wt.% and 5 wt.% vancomycin did not affect the structure of chitosan-hyaluronic acid hydrogel. The properties of the hydrogels were examined by scanning electron microscopy, Fourier-transform infrared, degradation experimentin vitroand vancomycin release experimentin vitro. When combined with porous scaffolds, the drug-loaded hydrogels exhibited slower drug release rates and longer release times. In addition,in vitrostudies found that the TTNZ scaffolds loaded with 5 wt.% vancomycin had a certain effect on the expression of osteogenesis-related genes in cells, but the antibacterial effect was the best. The porous scaffolds loaded with 2.5 wt.% vancomycin hydrogel TTNZ scaffolds did not inhibit cell proliferation, adhesion, alkaline phosphatase activity, and osteogenesis-related gene ex-pression, but the antibacterial effect on free bacteria was not as good as that of TTNZ scaffolds loaded with 5 wt.% vancomycin. This study, complementing the advantages of the two and controlling the local release rate of vancomycin, provides a new idea for future 3D printing of titanium alloy stents for anti-infection.