Cyclin dependent kinases (CDKs) are serine/threonine kinases that are proposed as promising candidate targets for cancer treatment. These proteins complexed with cyclins play a critical role in cell cycle progression. Most CDKs demonstrate substantially higher expression in cancer tissues compared with normal tissues and, according to the TCGA database, correlate with survival rate in multiple cancer types. Deregulation of CDK1 has been shown to be closely associated with tumorigenesis. CDK1 activation plays a critical role in a wide range of cancer types; and CDK1 phosphorylation of its many substrates greatly influences their function in tumorigenesis. Enrichment of CDK1 interacting proteins with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted to demonstrate that the associated proteins participate in multiple oncogenic pathways. This abundance of evidence clearly supports CDK1 as a promising target for cancer therapy. A number of small molecules targeting CDK1 or multiple CDKs have been developed and evaluated in preclinical studies. Notably, some of these small molecules have also been subjected to human clinical trials. This review evaluates the mechanisms and implications of targeting CDK1 in tumorigenesis and cancer therapy.

Because of profound effects observed in carcinogenesis, prostaglandins (PG), prostaglandin-endoperoxide synthases, and PG receptors are implicated in cancer development and progression. Understanding the molecular mechanisms of PG actions has potential clinical relevance for cancer prevention and therapy. This review focuses on the current status of PG signaling pathways in modulating cancer progression and aims to provide insights into the mechanistic actions of PGs and their receptors in influencing tumor progression. We also examine several small molecules identified as having anticancer activity that target prostaglandin receptors. The literature suggests that targeting PG pathways could provide opportunities for cancer prevention and therapy.

The immune checkpoint ligand PD-L1 has emerged as a molecular target for skin cancer therapy and might also hold promise for preventive intervention targeting solar UV light–induced skin damage. In this study, we have explored the role of PD-L1 in acute keratinocytic photodamage testing the effects of small-molecule pharmacological inhibition. Epidermal PD-L1 upregulation in response to chronic photodamage was established using immunohistochemical and proteomic analyses of a human skin cohort, consistent with earlier observations that PD-L1 is upregulated in cutaneous squamous cell carcinoma. Topical application of the small-molecule PD-L1 inhibitor BMS-202 significantly attenuated UV-induced activator protein-1 transcriptional activity in SKH-1 bioluminescent reporter mouse skin, also confirmed in human HaCaT reporter keratinocytes. RT-qPCR analysis revealed that BMS-202 antagonized UV induction of inflammatory gene expression. Likewise, UV-induced cleavage of procaspase-3, a hallmark of acute skin photodamage, was attenuated by topical BMS-202. NanoString nCounter transcriptomic analysis confirmed downregulation of cutaneous innate immunity- and inflammation-related responses, together with upregulation of immune response pathway gene expression. Further mechanistic analysis confirmed that BMS-202 antagonizes UV-induced PD-L1 expression both at the mRNA and protein levels in SKH-1 epidermis. These data suggest that topical pharmacological PD-L1 antagonism using BMS-202 shows promise for skin protection against photodamage.

In this study, eSRA is a novel optimization algorithm proposed to enhance machine learning model efficiency in large-scale problems with numerous dimensions and intricate patterns. For comparison purposes and to assess eSRA’s efficiency, it was compared with several popular methods for gene expression analysis of Wilms tumors (WT) using real-life medical datasets for gene expression classification, combining microarray (GSE66405, GSE73209, GSE2712, GSE11024) and RNA sequencing (TARGET-WT) with more than 260 samples of tumor and normal samples taken together from the kidneys. For this analysis, eSRA was used for gene set identification and hyperparameter tuning of the XGBoost classification algorithm, and eSRA was used alone. Experimental outcomes confirmed eSRA’s top rank for accuracy (0.9769), F 1 score (0.985), and ROC AUC (0.998) with superior performances compared with traditional and hybrid models. The model’s robustness and scalability were confirmed with unaltered performances regardless of population sizes and dimensions. SHAP value-based interpretation concluded genes like CALB1, CLDN8, NUP155, ALDH4A1, CYB5A, and GATA2 account for primary contributions to classifications related to tumors. Functional enrichment confirmed that these genes are involved in cell proliferation, embryonic kidney development, and vascular remodeling, processes central to WT biology. Overall, this work shows that eSRA is a powerful, efficient optimizer that enhances machine learning performance and provides biologically meaningful insights, making it a promising tool for biomedical data analysis and cancer genomics research.

Carcinogenesis, the process by which normal cells transform into cancer cells, is complex and multifaceted

Nonmelanoma skin cancers (NMSC) are the most common skin cancers, and about 5.4 million people are diagnosed each year in the United States. A newly developed T-lymphokine-activated killer cell-originated protein kinase (TOPK) inhibitor, HI-TOPK-032, is effective in suppressing colon cancer cell growth, inducing the apoptosis of colon cancer cells and ultraviolet (UV) light-induced squamous cell carcinoma (SCC). This study aimed to investigate the physicochemical properties, permeation behavior, and cytotoxicity potential of HI-TOPK-032 prior to the development of a suitable topical formulation for targeted skin drug delivery. Techniques such as scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) spectroscopy, differential scanning calorimetry (DSC), hot-stage microscopy (HSM), X-ray powder diffraction (XRPD), Karl Fisher (KF) coulometric titration, Raman spectrometry, confocal Raman microscopy (CRM), attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), and Fourier transform infrared microscopy were used to characterize HI-TOPK-032. The dose effect of HI-TOPK-032 on in vitro cell viability was evaluated using a 2D cell culture of the human skin keratinocyte cell line (HaCaT) and primary normal human epidermal keratinocytes (NHEKs). Transepithelial electrical resistance (TEER) at the air–liquid interface as a function of dose and time was measured on the HaCAT human skin cell line. The membrane permeation behavior of HI-TOPK-032 was tested using the Strat-M^® synthetic biomimetic membrane with an in vitro Franz cell diffusion system. The physicochemical evaluation results confirmed the amorphous nature of the drug and the homogeneity of the sample with all characteristic chemical peaks. The in vitro cell viability assay results confirmed 100% cell viability up to 10 µM of HI-TOPK-032. Further, a rapid, specific, precise, and validated reverse phase-high performance liquid chromatography (RP-HPLC) method for the quantitative estimation of HI-TOPK-032 was developed. This is the first systematic and comprehensive characterization of HI-TOPK-032 and a report of these findings.