A day and night difference in the response of the hepatic transcriptome to cyclophosphamide treatment.

Application of omics-based technologies is a widely used approach in research aiming to improve testing strategies for human health risk assessment. In most of these studies, however, temporal variations in gene expression caused by the circadian clock are a commonly neglected pitfall. In the present study, we investigated the impact of the circadian clock on the response of the hepatic transcriptome after exposure of mice to the chemotherapeutic agent cyclophosphamide (CP). Analysis of the data without considering clock progression revealed common responses in terms of regulated pathways between light and dark phase exposure, including DNA damage, oxidative stress, and a general immune response. The overall response, however, was stronger in mice exposed during the day. Use of time-matched controls, thereby eliminating non-CP-responsive circadian clock-controlled genes, showed that this difference in response was actually even more pronounced: CP-related responses were only identified in mice exposed during the day. Only minor differences were found in acute toxicity pathways, namely lymphocyte counts and kidney weights, indicating that gene expression is subject to time of day effects. This study is the first to highlight the impact of the circadian clock on the identification of toxic responses by omics approaches.

Impact of Simulated Rotating Shift Work on Mammary Tumor Development in the p53R270H©/+WAPCre Mouse Model for Breast Cancer.

Epidemiological studies associate night shift work with increased breast cancer risk. However, the underlying mechanisms are not clearly understood. To better understand these mechanisms, animal models that mimic the human situation of different aspects of shift work are needed. In this study, we used "timed sleep restriction" (TSR) cages to simulate clockwise and counterclockwise rotating shift work schedules and investigated predicted sleep patterns and mammary tumor development in breast tumor-prone female p53R270H©/+WAPCre mice. We show that TSR cages are effective in disturbing normal activity and estimated sleep patterns. Although circadian rhythms were not shifted, we observed effects of the rotating schedules on sleep timing and sleep duration. Sleep loss during a simulated shift was partly compensated after the shift and also partly during the free days. No effects were observed on body weight gain and latency time of breast cancer development. In summary, our study shows that the TSR cages can be used to model shift work in mice and affect patterns of activity and sleep. The effect of disturbing sleep patterns on carcinogenesis needs to be further investigated.

Biomarker discovery using a comparative omics approach in a mouse model developing heterogeneous mammary cancer subtypes.

Identification of biomarkers for early breast cancer detection in blood is a challenging task, since breast cancer is a heterogeneous disease with a wide range of tumor subtypes. This is envisioned to result in differences in serum protein levels. The p53(R270H/+) WAPCre mouse model is unique in that these mice spontaneously develop both ER- and ER+ tumors, in proportions comparable to humans. Therefore, these mice provide a well-suited model system to identify human relevant biomarkers for early breast cancer detection that are additionally specific for different tumor subtypes. Mammary gland tumors were obtained from p53(R270H/+) WAPCre mice and cellular origin, ER, and HER2 status were characterized. We compared gene expression profiles for tumors with different characteristics versus control tissue, and determined genes differentially expressed across tumor subtypes. By using literature data (Gene Ontology, UniProt, and Human Plasma Proteome), we further identified protein candidate biomarkers for blood-based detection of breast cancer. Functional overrepresentation analysis (using Gene Ontology, MSigDB, BioGPS, Cancer GeneSigDB, and proteomics literature data) showed enrichment for several processes relevant for human breast cancer. Finally, Human Protein Atlas data were used to obtain a prioritized list of 16 potential biomarkers that should facilitate further studies on blood-based breast cancer detection in humans.

Chronically Alternating Light Cycles Increase Breast Cancer Risk in Mice.

Although epidemiological studies in shift workers and flight attendants have associated chronic circadian rhythm disturbance (CRD) with increased breast cancer risk, causal evidence for this association is lacking. Several scenarios have been proposed to contribute to the shift work-cancer connection: (1) internal desynchronization, (2) light at night (resulting in melatonin suppression), (3) sleep disruption, (4) lifestyle disturbances, and (5) decreased vitamin D levels due to lack of sunlight. The confounders inherent in human field studies are less problematic in animal studies, which are therefore a good approach to assess the causal relation between circadian disturbance and cancer. However, the experimental conditions of many of these animal studies were far from the reality of human shift workers. For example, some involved xenografts (addressing tumor growth rather than cancer initiation and/or progression), chemically induced tumor models, or continuous bright light exposure, which can lead to suppression of circadian rhythmicity. Here, we have exposed breast cancer-prone p53(R270H/+)WAPCre conditional mutant mice (in a FVB genetic background) to chronic CRD by subjecting them to a weekly alternating light-dark (LD) cycle throughout their life. Animals exposed to the weekly LD inversions showed a decrease in tumor suppression. In addition, these animals showed an increase in body weight. Importantly, this study provides the first experimental proof that CRD increases breast cancer development. Finally, our data suggest internal desynchronization and sleep disturbance as mechanisms linking shift work with cancer development and obesity.

Biomarkers for circadian rhythm disruption independent of time of day.

Frequent shift work causes disruption of the circadian rhythm and might on the long-term result in increased health risk. Current biomarkers evaluating the presence of circadian rhythm disturbance (CRD), including melatonin, cortisol and body temperature, require 24-hr ("around the clock") measurements, which is tedious. Therefore, these markers are not eligible to be used in large-scale (human) studies. The aim of the present study was to identify universal biomarkers for CRD independent of time of day using a transcriptomics approach. Female FVB mice were exposed to six shifts in a clockwise (CW) and counterclockwise (CCW) CRD protocol and sacrificed at baseline and after 1 shift, 6 shifts, 5 days recovery and 14 days recovery, respectively. At six time-points during the day, livers were collected for mRNA microarray analysis. Using a classification approach, we identified a set of biomarkers able to classify samples into either CRD or non-disrupted based on the hepatic gene expression. Furthermore, we identified differentially expressed genes 14 days after the last shift compared to baseline for both CRD protocols. Non-circadian genes differentially expressed upon both CW and CCW protocol were considered useful, universal markers for CRD. One candidate marker i.e. CD36 was evaluated in serum samples of the CRD animals versus controls. These biomarkers might be useful to measure CRD and can be used later on for monitoring the effectiveness of intervention strategies aiming to prevent or minimize chronic adverse health effects.

Diurnal Variation of Hormonal and Lipid Biomarkers in a Molecular Epidemiology-Like Setting.

INTRODUCTION: Many molecular epidemiology studies focusing on high prevalent diseases, such as metabolic disorders and cancer, investigate metabolic and hormonal markers. In general, sampling for these markers can occur at any time-point during the day or after an overnight fast. However, environmental factors, such as light exposure and food intake might affect the levels of these markers, since they provide input for the internal time-keeping system. When diurnal variation is larger than the inter-individual variation, time of day should be taken into account. Importantly, heterogeneity in diurnal variation and disturbance of circadian rhythms among a study population might increasingly occur as a result of our increasing 24/7 economy and related variation in exposure to environmental factors (such as light and food). AIM: The aim of the present study was to determine whether a set of often used biomarkers shows diurnal variation in a setting resembling large molecular epidemiology studies, i.e., non-fasted and limited control possibilities for other environmental influences. RESULTS: We show that markers for which diurnal variation is not an issue are adrenocorticotropic hormone, follicle stimulating hormone, estradiol and high-density lipoprotein. For all other tested markers diurnal variation was observed in at least one gender (cholesterol, cortisol, dehydroepiandrosterone sulfate, free fatty acids, low-density lipoprotein, luteinizing hormone, prolactin, progesterone, testosterone, triglycerides, total triiodothyronine and thyroid-stimulating hormone) or could not reliably be detected (human growth hormone). DISCUSSION: Thus, studies investigating these markers should take diurnal variation into account, for which we provide some options. Furthermore, our study indicates the need for investigating diurnal variation (in literature or experimentally) before setting up studies measuring markers in routine and controlled settings, especially since time-of-day likely matters for many more markers than the ones investigated in the present study.