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.

Anti-Müllerian Hormone (AMH) is a 140 kDa homodimeric glycoprotein consisting of two identical subunits linked by disulphide bonds and is synthesised by the testes and ovaries. Its clinical applications are prediction of ovarian response and gonadotropin dose selection upon in vitro fertilization. In males, AMH is used to investigate sexual developmental disorders and gonadal function. AMH is commonly assayed by enzyme-linked immunosorbent assay or automated immunoassay formats that show variation between methods. This review applies fundamental chemical pathology concepts to explain the observed analytical variation of AMH measurement. We examine the lack of standardisation between AMH assays, the impact of antibody design on variable measurements, consider the analytical detection of AMH isoforms, review analytical interference in AMH measurement, and briefly assess systematic bias between AMH assays. The improved attempt at standardising AMH measurement by the recent approval of a WHO Reference Reagent offers promise for harmonising immunoassay results and establishing consensus medical cut-off points for AMH in disease. Standardisation, however, will need to redress the issue of poor commutability of standard reference material and further assign a standard reference procedure to quantify AMH standard reference material. The improvement of the analytical phase of AMH testing will support harmonised method development and patient care.

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 p < 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.

Preclinical studies show that the anticancer actions of vitamin D metabolites are mediated by apoptosis, inhibition of cell proliferation and induction of cell cycle arrest. Cervical cancer cells express an autocrine vitamin D metabolising system (VDMS) comprised of a vitamin D receptor, vitamin D catabolic enzyme (CYP24A1), and the activating enzyme of 25-hydroxycholecalciferol (25(OH)D3), CYP27B1. We assessed the anticancer effects of 25(OH)D3 at clinically relevant concentrations on a cervical squamous cell cancer cell line, SiHa. We evaluated cell health parameters (cell count, viability, and cell cycle), cell death modes (apoptosis, autophagic-dependent death, and necrosis by flow cytometry and transmission electron microscopy), and autocrine VDMS gene and protein expression by qPCR and Western blot, respectively. Our study demonstrates that physiological and supraphysiological doses of 25(OH)D3 inhibit cell growth and viability and induce biochemical and morphological apoptosis in SiHa cells. These growth effects are mediated by alteration in the VDMS gene and protein expression, with prominent negative feedback at supraphysiological treatment dose. These data identify promising therapeutic potential of 25(OH)D3 in cervical cancer, which warrants further clinical translational investigations.

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.