flow-cytometric-analysis-apoptotic-biomarkers-actinomycin-d-treated

Flow Cytometric Analysis of Apoptotic Biomarkers in Actinomycin D-Treated SiHa Cervical Cancer Cells

Apoptosis biomarkers were investigated in actinomycin D-treated SiHa cervical cancer cells using a benchtop flow cytometer. Early biomarkers (Annexin V ...

University of Pretoria

National Health Laboratory Service

2-Methoxyestradiol (2ME) is a promising anti-cancer agent that disrupts the integrity and dynamics of the spindle network. In order to overcome the pharmacokinetic constraints of this compound, a panel of sulphamoylated estradiol analogues were in silico-designed by our laboratory. In this study, we analysed the potential of each analogue to induce cell death on a panel of cancer cell lines. Moreover, the mechanism of action of the most effective compounds was determined.

Novel in silico-designed estradiol analogues are cytotoxic to a multidrug-resistant cell line at nanomolar concentrations.

Vitamin D has displayed anti-cancer actions in numerous in vitro studies. Here, we investigated the anti-cancer actions of cholecalciferol, a vitamin D precursor, on a metastatic cervical cancer cell line, namely, CaSki. Experimental cultures were incubated for 72 h and treated with cholecalciferol (10-1000 ng/mL). In the present study, cell count, viability, proliferation and cell cycle were analyzed by a crystal violet assay, trypan blue assay, Ki67 proliferation, and a cell cycle assay, respectively. Biomarkers of apoptosis, necrosis, and autophagic cell death were measured by the Caspase 3/7 and Annexin V/7-AAD Muse™ assays, a LC3-II assay, and a lactate dehydrogenase release assay, respectively. The ultrastructural features of cell death were assessed by transmission electron microscopy. A statistical analysis was performed using a one-way ANOVA and Bonferroni's post-hoc analysis test, and  < 0.05 is considered statistically significant here. The results identify statistical decreases in cell count and viability at high-dose treatments (100 and 1000 ng/mL). In addition, significant increases in apoptotic biochemical markers and apoptotic ultrastructure are shown to be present at high-dose treatments. In conclusion, high-dose cholecalciferol treatments inhibit cell count and viability, which are both mediated by apoptotic induction in the CaSki cell line.

Cholecalciferol Inhibits Cell Growth and Induces Apoptosis in the CaSki Cell Line.

Vitamin D is a steroid hormone crucial for bone mineral metabolism. In addition, vitamin D has pleiotropic actions in the body, including anti-cancer actions. These anti-cancer properties observed within in vitro studies frequently report the reduction of cell proliferation by interruption of the cell cycle by the direct alteration of cell cycle regulators which induce cell cycle arrest. The most recurrent reported mode of cell cycle arrest by vitamin D is at the G1/G0 phase of the cell cycle. This arrest is mediated by p21 and p27 upregulation, which results in suppression of cyclin D and E activity which leads to G1/G0 arrest. In addition, vitamin D treatments within in vitro cell lines have observed a reduced C-MYC expression and increased retinoblastoma protein levels that also result in G1/G0 arrest. In contrast, G2/M arrest is reported rarely within in vitro studies, and the mechanisms of this arrest are poorly described. Although the relationship of epigenetics on vitamin D metabolism is acknowledged, studies exploring a direct relationship to cell cycle perturbation is limited. In this review, we examine in vitro evidence of vitamin D and vitamin D metabolites directly influencing cell cycle regulators and inducing cell cycle arrest in cancer cell lines.

Policing Cancer: Vitamin D Arrests the Cell Cycle.

Machine learning (ML) is an area of artificial intelligence that provides computer programmes with the capacity to autodidact and learn new skills from experience, without continued human programming. ML algorithms can analyse large data sets quickly and accurately, by supervised and unsupervised learning techniques, to provide classification and prediction value outputs. The application of ML to chemical pathology can potentially enhance efficiency at all phases of the laboratory's total testing process. Our review will broadly discuss the theoretical foundation of ML in laboratory medicine. Furthermore, we will explore the current applications of ML to diverse chemical pathology laboratory processes, for example, clinical decision support, error detection in the preanalytical phase, and ML applications in gel-based image analysis and biomarker discovery. ML currently demonstrates exploratory applications in chemical pathology with promising advancements, which have the potential to improve all phases of the chemical pathology total testing pathway.

Rivak Punchoo

Department of Chemical Pathology,
Faculty of Health Sciences,
Department of Chemical Pathology, Faculty of Health Sciences

University of Pretoria

Flow Cytometric Analysis of Apoptotic Biomarkers in Actinomycin D-Treated SiHa Cervical Cancer Cells

Rivak Punchoo

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Chemical Pathology,Faculty of Health Sciences,Department of Chemical Pathology, Faculty of Health Sciences

University of Pretoria

Flow Cytometric Analysis of Apoptotic Biomarkers in Actinomycin D-Treated SiHa Cervical Cancer Cells

Department of Chemical Pathology,
Faculty of Health Sciences,
Department of Chemical Pathology, Faculty of Health Sciences