Serum Pro-Inflammatory Cytokines and Leptin as Potential Biomarkers for Treatment Response and Toxicity in Locally Advanced Squamous Cell Carcinoma of the Head and Neck.

Squamous cell carcinoma of the head and neck (HNSCC) is a globally prevalent form of cancer with significant morbidity and mortality rates. The present study examines the relationship of serum pro-inflammatory cytokines and leptin levels with the effectiveness of therapy in individuals with HNSCC and their potential role as biomarkers for treatment response and toxicity. Induction chemotherapy and concomitant chemoradiotherapy were evaluated for efficacy and safety in 52 individuals with HNSCC. Both response and toxicity were evaluated, and serum levels of pro-inflammatory cytokines Interlukin-1 beta (IL-1ß), Interlukin-2 (IL-2), Interlukin-6 (IL-6), and Tumor Necrosis Factor-Alpha (TNF-α) and leptin were measured using enzyme-linked immunoassay before and after treatment. Before treatment, these measurements were made in comparison with a control group with 50 healthy people. The results showed that serum cytokines and leptin levels varied depending on the response to treatment, with patients who had a complete or partial response (PR) showing significant decreases in IL-1 ß, IL-6, and TNF-α levels and significant increases in IL-2 and leptin levels after treatment, with an improvement in cachexia. These results imply that variations in serum pro-inflammatory cytokines and leptin levels are likely related to the therapeutic effectiveness in HNSCC and may act as biomarkers for treatment response.

Delineated 3-1-BenCarMethInYlPro-Phosphonic Acid's Adroit Activity against Lung Cancer through Multitargeted Docking, MM\GBSA, QM-DFT and Multiscale Simulations.

Lung cancer is a pervasive and challenging disease with limited treatment options, with global health challenges often present with complex molecular profiles necessitating the exploration of innovative therapeutic strategies. Single-target drugs have shown limited success due to the heterogeneity of this disease. Multitargeted drug designing is imperative to combat this complexity by simultaneously targeting multiple target proteins and pathways, which can enhance treatment efficacy and overcome resistance by addressing the dynamic nature of the disease and stopping tumour growth and spread. In this study, we performed the molecular docking studies of Drug Bank compounds with a multitargeted approach against crucial proteins of lung cancer such as heat shock protein 5 (BIP/GRP78) ATPase, myosin 9B RhoGAP, EYA2 phosphatase inhibitor, RSK4 N-terminal kinase, and collapsin response mediator protein-1 (CRMP-1) using HTVS, SP with XP algorithms, and poses were filtered using MM\GBSA which identified [3-(1-Benzyl-3-Carbamoylmethyl-2-Methyl-1h-Indol-5-Yloxy)-Propyl-]-Phosphonic Acid (3-1-BenCarMethIn YlPro-Phosphonic Acid) (DB02504) as multitargeted drug candidate with docking and MM\GBSA score ranges from -5.83 to -10.66 and -7.56 to -50.14 Kcal/mol, respectively. Further, the pharmacokinetic and QM-based DFT studies have shown complete acceptance results, and interaction fingerprinting reveals that ILE, GLY, VAL, TYR, LEU, and GLN were among the most interacting residues. The 100 ns MD simulation in the SPC water model with NPT ensemble showed stable performance with deviation and fluctuations <2 Å with huge interactions, making it a promising multitargeted drug candidate; however, experimental studies are needed before use.

Targeting Cathepsin L in Cancer Management: Leveraging Machine Learning, Structure-Based Virtual Screening, and Molecular Dynamics Studies.

Cathepsin L (CTSL) expression is dysregulated in a variety of cancers. Extensive empirical evidence indicates their direct participation in cancer growth, angiogenic processes, metastatic dissemination, and the development of treatment resistance. Currently, no natural CTSL inhibitors are approved for clinical use. Consequently, the development of novel CTSL inhibition strategies is an urgent necessity. In this study, a combined machine learning (ML) and structure-based virtual screening strategy was employed to identify potential natural CTSL inhibitors. The random forest ML model was trained on IC50 values. The accuracy of the trained model was over 90%. Furthermore, we used this ML model to screen the Biopurify and Targetmol natural compound libraries, yielding 149 hits with prediction scores >0.6. These hits were subsequently selected for virtual screening using a structure-based approach, yielding 13 hits with higher binding affinity compared to the positive control (AZ12878478). Two of these hits, ZINC4097985 and ZINC4098355, have been shown to strongly bind CTSL proteins. In addition to drug-like properties, both compounds demonstrated high affinity, ligand efficiency, and specificity for the CTSL binding pocket. Furthermore, in molecular dynamics simulations spanning 200 ns, these compounds formed stable protein-ligand complexes. ZINC4097985 and ZINC4098355 can be considered promising candidates for CTSL inhibition after experimental validation, with the potential to provide therapeutic benefits in cancer management.

Evaluation of TET Family Gene Expression and 5-Hydroxymethylcytosine as Potential Epigenetic Markers in Non-small Cell Lung Cancer.

BACKGROUND/AIM: DNA methylation is the most studied epigenetic modification in cancer. Ten-eleven translocation enzymes (TET) catalyze the oxidation of 5-methylcytosine (5-mC) to 5-hydroxymethylcytosine (5-hmC) in the DNA. In the current research, we aimed to evaluate the role of 5-hmC and TET enzymes in non-small cell lung cancer (NSCLC) patients and their possible association with outcomes. PATIENTS AND METHODS: ELISA was used to measure the 5-hmC levels in genomic DNA and qRT-PCR was used to evaluate TET1, TET2, and TET3 mRNAs expression levels in NSCLC tissues and their paired normal controls. RESULTS: The levels of 5-hmC were significantly lower in NSCLC tissues than in normal tissues, with a mean ±SD of 0.28±0.37 vs. 1.84±0.58, respectively (t=22.77, p<0.0001), and this reduction was correlated with adverse clinical features. In addition, all TET genes were significantly down-regulated in NSCLC tissues in comparison to their matched normal tissues. The mean±SD level of TET1-mRNA was 38.48±16.38 in NSCLC vs. 80.65±11.25 in normal tissues (t=21.33, p<0.0001), TET2-mRNA level in NSCLC was 5.25±2.78 vs. 9.52±1.01 in normal tissues (t=14.48, p<0.0001), and TET3-mRNA level in NSCLC was 5.21±2.8 vs. 9.51±0.86 in normal tissues (t=14.75, p<0.0001). Downregulation of TET genes was correlated with poor clinical features. CONCLUSION: 5-HmC levels as well as TET1, TET2, and TET3 mRNA levels were reduced in NSCLC tissues. The reduced levels of 5-hmC and TET mRNAs were associated with adverse clinical features, suggesting that the level of 5-hmC may serve as a valuable prognostic biomarker for NSCLC.