Circadian rhythms are intrinsic, with roughly 24 h oscillations that coordinate many physiological functions and are increasingly recognized as key determinants of human health. When these rhythms become misaligned, there is an increased risk for neurodegenerative and psychiatric disorders, metabolic syndrome, sleep disturbances, and even certain cancers. The hormones, melatonin that rises in the evening and cortisol that peaks shortly after awakening, represent crucial biochemical markers of the circadian phase. This review systematically evaluates contemporary techniques for quantifying melatonin and cortisol, comparing biological matrices (blood, saliva, urine) alongside analytical platforms. Special focus is placed on two clinically informative markers: Dim Light Melatonin Onset (DLMO) and the Cortisol Awakening Response (CAR). We compared immunoassays with liquid chromatography tandem mass spectrometry (LC MS/MS), highlighting differences in sensitivity, specificity, and laboratory feasibility. Potential confounders, including ambient light, body posture, and exact sampling times—are discussed in detail, to show the capacity of providing the most reliable results. By emphasizing the need for standardized protocols and controlled sampling conditions, this review provides essential guidance for researchers and clinicians aiming to assess the circadian biomarkers melatonin and cortisol with precision since they can be used in clinical practice as diagnostic and prognostic tools for assessing numerous pathologies.

We developed a simple and robust liquid chromatographic/mass spectrometric method (LC-MS) for the quantitative analysis of 10 sterols from the late part of cholesterol synthesis (zymosterol, dehydrolathosterol, 7-dehydrodesmosterol, desmosterol, zymostenol, lathosterol, FFMAS, TMAS, lanosterol, and dihydrolanosterol) from cultured human hepatocytes in a single chromatographic run using a pentafluorophenyl (PFP) stationary phase. The method also avails on a minimized sample preparation procedure in order to obtain a relatively high sample throughput. The method was validated on 10 sterol standards that were detected in a single chromatographic LC-MS run without derivatization. Our developed method can be used in research or clinical applications for disease-related detection of accumulated cholesterol intermediates. Disorders in the late part of cholesterol synthesis lead to severe malformation in human patients. The developed method enables a simple, sensitive, and fast quantification of sterols, without the need of extended knowledge of the LC-MS technique, and represents a new analytical tool in the rising field of cholesterolomics.

While the role of cholesterol in liver carcinogenesis remains controversial, hepatocellular carcinoma generally prevails in males. Herein, we uncover pathways of female-prevalent progression to hepatocellular carcinoma due to chronic repression of cholesterogenic lanosterol 14α-demethylase (CYP51) in hepatocytes. Tumors develop in knock-out mice after year one, with 2:1 prevalence in females. Metabolic and transcription factor networks were deduced from the liver transcriptome data, combined by sterol metabolite and blood parameter analyses, and interpreted with relevance to humans. Female knock-outs show increased plasma cholesterol and HDL, dampened lipid-related transcription factors FXR, LXRα:RXRα, and importantly, crosstalk between reduced LXRα and activated TGF-β signalling, indicating a higher susceptibility to HCC in aging females. PI3K/Akt signalling and ECM-receptor interaction are common pathways that are disturbed by sex-specific altered genes. Additionally, transcription factors (SOX9)2 and PPARα were recognized as important for female hepatocarcinogenesis, while overexpressed Cd36, a target of nuclear receptor RORC, is a new male-related regulator of ECM-receptor signalling in hepatocarcinogenesis. In conclusion, we uncover the sex-dependent metabolic reprogramming of cholesterol-related pathways that predispose for hepatocarcinogenesis in aging females. This is important in light of increased incidence of liver cancers in post-menopausal women.

Sterols from cholesterol synthesis are crucial for cholesterol production, but also have individual roles difficult to assess in vivo due to essentiality of cholesterol. We developed HepG2 cell models with knockouts (KOs) for three enzymes of cholesterol synthesis, each accumulating specific sterols. Surprisingly, KOs of CYP51, DHCR24, and SC5D shared only 9% of differentially expressed genes. The most striking was the phenotype of CYP51 KO with highly elevated lanosterol and 24,25-dihydrolanosterol, significant increase in G2+M phase and enhanced cancer and cell cycle pathways. Comparisons with mouse liver Cyp51 KO data suggest 24,25-dihydrolanosterol activates similar cell proliferation pathways, possibly via elevated LEF1 and WNT/NFKB signaling. In contrast, SC5D and DHCR24 KO cells with elevated lathosterol or desmosterol proliferated slowly, with downregulated E2F, mitosis, and enriched HNF1A. These findings demonstrate that increase of lanosterol and 24,25-dihydrolanosterol, but not other sterols, promotes cell proliferation in hepatocytes.

Circadian rhythms are intrinsic, with roughly 24-hour oscillations that coordinate many physiological functions and are increasingly recognized as key determinants of human health. When these rhythms become misaligned, there is an increased risk for neuro-degenerative and psychiatric disorders, metabolic syndrome, sleep disturbances, and even certain cancers. The hormones, melatonin that rises in the evening and cortisol that peaks shortly after awakening, represent crucial biochemical markers of the circadian phase. This review systematically evaluates contemporary techniques for quantifying melatonin and cortisol, comparing biological matrices (blood, saliva, urine) alongside analytical platforms. Special focus is placed on two clinically informative markers: Dim Light Melatonin Onset (DLMO) and the Cortisol Awakening Response (CAR). We com-pared immunoassays with liquid chromatography tandem mass spectrometry (LC MS/MS), highlighting differences in sensitivity, specificity, and laboratory feasibility. Po-tential confounders, including ambient light, body posture, and exact sampling times—are discussed in detail, to show the capacity of providing the most reliable results. By emphasizing the need for standardized protocols and controlled sampling conditions, this review provides essential guidance for researchers and clinicians aiming to assess the circadian biomarkers melatonin and cortisol with precision since they can be used in clinical practice as diagnostic and prognostic tools for assessing numerous pathologies.

Background/Objectives: In recent years, interest in studying changes in cancer metabolites has resulted in significant advances in the metabolomics field. Glioblastoma remains the most aggressive and lethal brain malignancy, which presents with notable metabolic reprogramming. Methods: We performed literature research from the PubMed database and considered research articles focused on the key metabolic pathways altered in glioblastoma (e.g., glycolysis, lipid metabolism, TCA cycle), the role of oncometabolites and metabolic plasticity, and the differential expression of metabolites in glioblastoma. Currently used metabolomics approaches can be either targeted, focusing on specific metabolites and pathways, or untargeted, which involves data-driven exploration of the metabolome and also results in the identification of new metabolites. Data processing and analysis is of great importance and can be improved with the integration of machine learning approaches for metabolite identification. Results: Changes in α/β-glucose, lactate, choline, and 2-hydroxyglutarate were detected in glioblastoma compared with non-tumor tissues. Different metabolites such as fumarate, tyrosine, and leucine, as well as citric acid, isocitric acid, shikimate, and GABA were detected in blood and CSF, respectively. Conclusions: Although promising new technological and bioinformatic approaches help us understand glioblastoma better, challenges associated with biomarker availability, tumor heterogeneity, interpatient variability, standardization, and reproducibility still remain. Metabolomics research, either alone or combined with genomics or proteomics (i.e., multiomics) in glioblastoma, can lead to biomarker identification, tracking of metabolic therapy response, discovery of novel metabolites and pathways, and identification of potential therapeutic targets.