Circadian clock effects on cellular proliferation: Insights from theory and experiments

Time-of-day effects of cancer drugs revealed by high-throughput deep phenotyping

The circadian clock, a fundamental biological regulator, governs essential cellular processes in health and disease. Circadian-based therapeutic strategies are increasingly gaining recognition as promising avenues. Aligning drug administration with the circadian rhythm can enhance treatment efficacy and minimize side effects. Yet, uncovering the optimal treatment timings remains challenging, limiting their widespread adoption. In this work, we introduce a high-throughput approach integrating live-imaging and data analysis techniques to deep-phenotype cancer cell models, evaluating their circadian rhythms, growth, and drug responses. We devise a streamlined process for profiling drug sensitivities across different times of the day, identifying optimal treatment windows and responsive cell types and drug combinations. Finally, we implement multiple computational tools to uncover cellular and genetic factors shaping time-of-day drug sensitivity. Our versatile approach is adaptable to various biological models, facilitating its broad application and relevance. Ultimately, this research leverages circadian rhythms to optimize anti-cancer drug treatments, promising improved outcomes and transformative treatment strategies.

Link between circadian rhythm and benign prostatic hyperplasia (BPH)/lower urinary tract symptoms (LUTS)

BACKGROUND

Benign prostatic hyperplasia (BPH) is the most common urologic disease in aging males, affecting 50% of men over 50 and up to 80% of men over 80 years old. Its negative impact on health-related quality of life implores further investigation into its risk factors and strategies for effective management. Although the exact molecular mechanisms underlying pathophysiological onset of BPH are poorly defined, the current hypothesized contributors to BPH and lower urinary tract symptoms (LUTS) include aging, inflammation, metabolic syndrome, and hormonal changes. These processes are indirectly influenced by circadian rhythm disruption. In this article, we review the recent evidence on the potential association of light changes/circadian rhythm disruption and the onset of BPH and impact on treatment.

METHODS

A narrative literature review was conducted using PubMed and Google Scholar to identify supporting evidence. The articles referenced ranged from 1975 to 2023.

RESULTS

A clear relationship between BPH/LUTS and circadian rhythm disruption is yet to be established. However, common mediators influence both diseases, including proinflammatory states, metabolic syndrome, and hormonal regulation that can be asserted to circadian disruption. Some studies have identified a possible relationship between general LUTS and sleep disturbance, but little research has been done on the medical management of these diseases and how circadian rhythm disruption further affects treatment outcomes.

CONCLUSIONS

There is evidence to implicate a relationship between BPH/LUTS and circadian rhythm disruptions. However, there is scarce literature on potential specific link in medical management of the disease and treatment outcomes with circadian rhythm disruption. Further study is warranted to provide BPH patients with insights into circadian rhythm directed appropriate interventions.

N-methyl-D-aspartate receptor regulates the circadian clock in megakaryocytic cells and impacts cell proliferation through BMAL1

Peripheral circadian clocks control cell proliferation and survival, but little is known about their role and regulation in megakaryocytic cells. N-methyl-D-aspartate receptor (NMDAR) regulates the central clock in the brain. The purpose of this study was to determine whether NMDAR regulates the megakaryocytic cell clock and whether the megakaryocytic clock regulates cell proliferation and cell death. We found that both the Meg-01 megakaryocytic cell line and native murine megakaryocytes expressed circadian clock genes. Megakaryocyte-directed deletion of Grin1 in mice caused significant disruption of the circadian rhythm pathway at the transcriptional level and increased expression of BMAL1 at the protein level. Similarly, both pharmacological (MK-801) and genetic (GRIN-/-) inhibition of NMDAR in Meg-01 cells in vitro resulted in widespread changes in clock gene expression including increased expression of BMAL1, the core clock transcription factor. BMAL1 overexpression reduced Meg-01 cell proliferation and altered the time-dependent expression of the cell cycle regulators MYC and WEE1, whereas BMAL1 knockdown led to increased cell death in Meg-01-GRIN1-/- cells. Our results demonstrate that NMDAR regulates the circadian clock in megakaryocytic cells and that the circadian clock component BMAL1 contributes to the control of Meg-01 cell proliferation and survival.

An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells

MOTIVATION

Detecting oscillations in time series remains a challenging problem even after decades of research. In chronobiology, rhythms (for instance in gene expression, eclosion, egg-laying, and feeding) tend to be low amplitude, display large variations amongst replicates, and often exhibit varying peak-to-peak distances (non-stationarity). Most currently available rhythm detection methods are not specifically designed to handle such datasets, and are also limited by their use of P-values in detecting oscillations.

RESULTS

We introduce a new method, ODeGP (Oscillation Detection using Gaussian Processes), which combines Gaussian Process regression and Bayesian inference to incorporate measurement errors, non-uniformly sampled data, and a recently developed non-stationary kernel to improve detection of oscillations. By using Bayes factors, ODeGP models both the null (non-rhythmic) and the alternative (rhythmic) hypotheses, thus providing an advantage over P-values. Using synthetic datasets, we first demonstrate that ODeGP almost always outperforms eight commonly used methods in detecting stationary as well as non-stationary symmetric oscillations. Next, by analyzing existing qPCR datasets, we demonstrate that our method is more sensitive compared to the existing methods at detecting weak and noisy oscillations. Finally, we generate new qPCR data on mouse embryonic stem cells. Surprisingly, we discover using ODeGP that increasing cell-density results in rapid generation of oscillations in the Bmal1 gene, thus highlighting our method's ability to discover unexpected and new patterns. In its current implementation, ODeGP is meant only for analyzing single or a few time-trajectories, not genome-wide datasets.

AVAILABILITY AND IMPLEMENTATION

ODeGP is available at https://github.com/Shaonlab/ODeGP.

Circadian Clock Regulation via Biomaterials for Nucleus Pulposus

Circadian clock disorder during tissue degeneration has been considered the potential pathogenesis for various chronic diseases, such as intervertebral disc degeneration (IVDD). In this study, circadian clock-regulating biomaterials (ClockMPs) that can effectively activate the intrinsic circadian clock of nucleus pulposus cells (NPCs) in IVDD and improve the physiological function of NPCs for disc regeneration are fabricated via air-microfluidic technique and the chemical cross-linking between polyvinyl alcohol and modified-phenylboronic acid. In vitro experiments verified that ClockMPs can scavenge reactive oxygen species to maintain a stable microenvironment for the circadian clock by promoting the binding of BMAL1 and CLOCK proteins. ClockMPs can regulate the expression of core circadian clock genes by activating the PI3K-AKT pathway in NPCs to remodel the intrinsic circadian clock and promote extracellular matrix synthesis. Furthermore, in vivo experiments of IVDD treated with ClockMPs proved that ClockMPs can promote disc regeneration by regulating the circadian clock of NPCs. In conclusion, ClockMPs provided a novel and promising strategy for circadian clock regulation during tissue regeneration.

CLOCK inhibits the proliferation of porcine ovarian granulosa cells by targeting ASB9

BACKGROUND

Clock circadian regulator (CLOCK) is a core factor of the mammalian biological clock system in regulating female fertility and ovarian physiology. However, CLOCK's specific function and molecular mechanism in porcine granulosa cells (GCs) remain unclear. In this study, we focused on CLOCK's effects on GC proliferation.

RESULTS

CLOCK significantly inhibited cell proliferation in porcine GCs. CLOCK decreased the expression of cell cycle-related genes, including CCNB1, CCNE1, and CDK4 at the mRNA and protein levels. CDKN1A levels were upregulated by CLOCK. ASB9 is a newly-identified target of CLOCK that inhibits GC proliferation; CLOCK binds to the E-box element in the ASB9 promoter.

CONCLUSIONS

These findings suggest that CLOCK inhibits the proliferation of porcine ovarian GCs by increasing ASB9 level.

An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells

Detecting oscillations in time series remains a challenging problem even after decades of research. In chronobiology, rhythms in time series (for instance gene expression, eclosion, egg-laying and feeding) datasets tend to be low amplitude, display large variations amongst replicates, and often exhibit varying peak-to-peak distances (non-stationarity). Most currently available rhythm detection methods are not specifically designed to handle such datasets. Here we introduce a new method, ODeGP ( O scillation De tection using G aussian P rocesses), which combines Gaussian Process (GP) regression with Bayesian inference to provide a flexible approach to the problem. Besides naturally incorporating measurement errors and non-uniformly sampled data, ODeGP uses a recently developed kernel to improve detection of non-stationary waveforms. An additional advantage is that by using Bayes factors instead of p-values, ODeGP models both the null (non-rhythmic) and the alternative (rhythmic) hypotheses. Using a variety of synthetic datasets we first demonstrate that ODeGP almost always outperforms eight commonly used methods in detecting stationary as well as non-stationary oscillations. Next, on analyzing existing qPCR datasets that exhibit low amplitude and noisy oscillations, we demonstrate that our method is more sensitive compared to the existing methods at detecting weak oscillations. Finally, we generate new qPCR time-series datasets on pluripotent mouse embryonic stem cells, which are expected to exhibit no oscillations of the core circadian clock genes. Surprisingly, we discover using ODeGP that increasing cell density can result in the rapid generation of oscillations in the Bmal1 gene, thus highlighting our method’s ability to discover unexpected patterns. In its current implementation, ODeGP (available as an R package) is meant only for analyzing single or a few time-trajectories, not genome-wide datasets.

Construction and verification of a novel circadian clock related long non-coding RNA model and prediction of treatment for survival prognosis in patients with hepatocellular carcinoma

Circadian clock genes are significant in the occurrence and development of HCC and long-non coding RNAs (lncRNAs) are closely related to HCC progression. In this study, we aimed to establish a prognostic risk model for HCC. Circadian clock-related lncRNAs expressed in HCC were extracted from The Cancer Genome Atlas. A nomogram was established to predict individual survival rate. Biological processes enriched for risk model transcripts were investigated by Gene Set Enrichment Analysis. Further, we evaluated the relationship between risk score and immune-checkpoint inhibitor-related gene expression level. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to assess the sensitivity of tumors in high- and low-risk score groups to different drugs. A total of 11 circadian clock-related lncRNAs were included in multi-Cox proportional hazards model analysis to establish a risk model. Univariate and multivariate Cox regression analysis showed that the risk model was an independent risk factor in HCC. The risk model was a significantly associated with the immune signature. Further GDSC analysis indicated that patients in each risk score group may be sensitive to different anti-cancer drugs. QRT-PCR analysis results showed that C012073.1, PRRT3-AS1, TMCC1-AS1, LINC01138, MKLN1-AS, KDM4A-AS1, AL031985.3, POLH-AS1, LINC01224, and AC099850.3 were more highly expressed in Huh-7 and HepG2, compared to LO2, while AC008549.1 were lower expressed. Our work established a prognostic model for HCC. Risk score analysis indicated that the model is significantly associated with modulation tumor immunity and could be used to guide more effective therapeutic strategies in the future.

Patterns of interdivision time correlations reveal hidden cell cycle factors

The time taken for cells to complete a round of cell division is a stochastic process controlled, in part, by intracellular factors. These factors can be inherited across cellular generations which gives rise to, often non-intuitive, correlation patterns in cell cycle timing between cells of different family relationships on lineage trees. Here, we formulate a framework of hidden inherited factors affecting the cell cycle that unifies known cell cycle control models and reveals three distinct interdivision time correlation patterns: aperiodic, alternator, and oscillator. We use Bayesian inference with single-cell datasets of cell division in bacteria, mammalian and cancer cells, to identify the inheritance motifs that underlie these datasets. From our inference, we find that interdivision time correlation patterns do not identify a single cell cycle model but generally admit a broad posterior distribution of possible mechanisms. Despite this unidentifiability, we observe that the inferred patterns reveal interpretable inheritance dynamics and hidden rhythmicity of cell cycle factors. This reveals that cell cycle factors are commonly driven by circadian rhythms, but their period may differ in cancer. Our quantitative analysis thus reveals that correlation patterns are an emergent phenomenon that impact cell proliferation and these patterns may be altered in disease.

Cell size homeostasis under the circadian regulation of cell division in cyanobacteria

Bacterial cells maintain their characteristic cell size over many generations. Several rod-shaped bacteria, such as Escherichia coli and the cyanobacteria Synechococcus elongatus, divide after adding a constant length to their length at birth. Through this division control known as the adder mechanism, perturbation in cell length due to physiological fluctuation decays over generations at a rate of 2^-1 per cell division. However, previous experiments have shown that the circadian clock in cyanobacteria reduces cell division frequency at a specific time of day under constant light. This circadian gating should modulate the division control by the adder mechanism, but its significance remains unknown. Here we address how the circadian gating affects cell length, doubling time, and cell length stability in cyanobacteria by using mathematical models. We show that a cell subject to circadian gating grows for a long time, and gives birth to elongated daughter cells. These elongated daughter cells grow faster than the previous generation, as elongation speed is proportional to cell length and divide in a short time before the next gating. Hence, the distributions of doubling time and cell length become bimodal, as observed in experimental data. Interestingly, the average doubling time over the population of cells is independent of gating because the extension of doubling time by gating is compensated by its reduction in the subsequent generation. On the other hand, average cell length is increased by gating, suggesting that the circadian clock controls cell length. We then show that the decay rate of perturbation in cell length depends on the ratio of delay in division by the gating τ_G to the average doubling time τ₀ as [Formula: see text] . We estimated τ_G≈2.5, τ₀≈13.6 hours, and τ_G/τ₀≈0.18 from experimental data, indicating that a long doubling time in cyanobacteria maintains the decay rate similar to that of the adder mechanism. Thus, our analysis suggests that the acquisition of the circadian clock during evolution did not impose a constraint on cell size homeostasis in cyanobacteria.

The PER1/HIF-1alpha negative feedback loop promotes ferroptosis and inhibits tumor progression in oral squamous cell carcinoma

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PER1 is negatively correlated with GPX4 and HIF-1α expression in OSCC tissue.

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PER1 promotes ferroptosis in OSCC cells in a HIF-1α-dependent manner.

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PER1 binds with HIF-1α to promote HIF-1α degradation.

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HIF-1α binds to the PER1 promoter to inhibit PER1 transcription.

Current studies have proven that the decreased expression of the core circadian clock gene Period 1 (PER1) is closely related to the occurrence and progression of multiple malignant tumors, including oral squamous cell carcinoma (OSCC). But the mechanism involved is largely unknown. In this study, we found that PER1 was negatively correlated with the expression of the key ferroptosis-regulated proteins glutathione peroxidase (GPX4) and hypoxia inducible factor-1alpha (HIF-1α) in OSCC tissues. The expression of the ferroptosis related proteins GPX4, solute carrier family 7 member 11 (SLC7A11) and transferrin receptor (TFRC) and the levels of glutathione (GSH), malondialdehyde (MDA), reactive oxygen species (ROS) and Fe²⁺ were detected in OSCC cells with overexpression or silencing of PER1. Mitochondrial morphology changes were observed. We found that PER1 promotes ferroptosis depending on HIF-1α in OSCC cells. In vivo tumorigenicity assays proved that PER1 overexpression inhibits HIF-1α, promotes ferroptosis and suppresses OSCC growth. Mechanistically, coimmunoprecipitation and cycloheximide tracking assays proved that PER1 binds to HIF-1α to promote HIF-1α protein degradation. ChIP and dual luciferase reporter assays proved that HIF-1α binds to the PER1 promoter leading to feedback inhibition of PER1 transcription. Our findings suggest that targeting the PER1/HIF-1α negative feedback loop may provide a new strategy for OSCC treatment.

A detailed map of coupled circadian clock and cell cycle with qualitative dynamics validation

Background

The temporal coordination of biological processes by the circadian clock is an important mechanism, and its disruption has negative health outcomes, including cancer. Experimental and theoretical evidence suggests that the oscillators driving the circadian clock and the cell cycle are coupled through phase locking.

Results

We present a detailed and documented map of known mechanisms related to the regulation of the circadian clock, and its coupling with an existing cell cycle map which includes main interactions of the mammalian cell cycle. The coherence of the merged map has been validated with a qualitative dynamics analysis. We verified that the coupled circadian clock and cell cycle maps reproduce the observed sequence of phase markers. Moreover, we predicted mutations that contribute to regulating checkpoints of the two oscillators.

Conclusions

Our approach underlined the potential key role of the core clock protein NR1D1 in regulating cell cycle progression. We predicted that its activity influences negatively the progression of the cell cycle from phase G2 to M. This is consistent with the earlier experimental finding that pharmacological activation of NR1D1 inhibits tumour cell proliferation and shows that our approach can identify biologically relevant species in the context of large and complex networks.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04158-9.

The role of the circadian clock in cancer hallmark acquisition and immune-based cancer therapeutics

The circadian system temporally regulates physiology to maintain homeostasis. Co-opting and disrupting circadian signals appear to be distinct attributes that are functionally important for the development of a tumor and can enable or give rise to the hallmarks that tumors use to facilitate their initiation, growth and progression. Because circadian signals are also strong regulators of immune cell proliferation, trafficking and exhaustion states, they play a role in how tumors respond to immune-based cancer therapeutics. While immuno-oncology has heralded a paradigm shift in cancer therapeutics, greater accuracy is needed to increase our capability of predicting who will respond favorably to, or who is likely to experience the troubling adverse effects of, immunotherapy. Insights into circadian signals may further refine our understanding of biological determinants of response and help answer the fundamental question of whether certain perturbations in circadian signals interfere with the activity of immune checkpoint inhibitors. Here we review the body of literature highlighting circadian disruption as a cancer promoter and synthesize the burgeoning evidence suggesting circadian signals play a role in how tumors respond to immune-based anti-cancer therapeutics. The goal is to develop a framework to advance our understanding of the relationships between circadian markers, cancer biology, and immunotherapeutics. Bolstered by this new understanding, these relationships may then be pursued in future clinical studies to improve our ability to predict which patients will respond favorably to, and avoid the adverse effects of, traditional and immune-based cancer therapeutics.

Circadian clock: a regulator of the immunity in cancer

The circadian clock is an endogenous timekeeper system that controls and optimizes biological processes, which are consistent with a master circadian clock and peripheral clocks and are controlled by various genes. Notably, the disruption of circadian clock genes has been identified to affect a wide range of ailments, including cancers. The cancer-immunity cycle is composed of seven major steps, namely cancer cell antigen release and presentation, priming and activation of effector immunity cells, trafficking, and infiltration of immunity to tumors, and elimination of cancer cells. Existing evidence indicates that the circadian clock functions as a gate that govern many aspects of the cancer-immunity cycle. In this review, we highlight the importance of the circadian clock during tumorigenesis, and discuss the potential role of the circadian clock in the cancer-immunity cycle. A comprehensive understanding of the regulatory function of the circadian clock in the cancer-immunity cycle holds promise in developing new strategies for the treatment of cancer.

Identification of a circadian gene signature that predicts overall survival in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common subtypes of lung cancer which is the leading cause of death in cancer patients. Circadian clock disruption has been listed as a likely carcinogen. However, whether the expression of circadian genes affects overall survival (OS) in LUAD patients remains unknown. In this article, we identified a circadian gene signature to predict overall survival in LUAD.

METHODS

RNA sequencing (HTSeq-FPKM) data and clinical characteristics were obtained for a cohort of LUAD patients from The Cancer Genome Atlas (TCGA). A multigene signature based on differentially expressed circadian clock-related genes was generated for the prediction of OS using Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression analysis, and externally validated using the GSE72094 dataset from the GEO database.

RESULTS

Five differentially expressed genes (DEGs) were identified to be significantly associated with OS using univariate Cox proportional regression analysis (P < 0.05). Patients classified as high risk based on these five DEGs had significantly lower OS than those classified as low risk in both the TGCA cohort and GSE72094 dataset (P < 0.001). Multivariate Cox regression analysis revealed that the five-gene-signature based risk score was an independent predictor of OS (hazard ratio > 1, P < 0.001). Receiver operating characteristic (ROC) curves confirmed its prognostic value. Gene set enrichment analysis (GSEA) showed that Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to cell proliferation, gene damage repair, proteasomes, and immune and autoimmune diseases were significantly enriched.

CONCLUSION

A novel circadian gene signature for OS in LUAD was found to be predictive in both the derivation and validation cohorts. Targeting circadian genes is a potential therapeutic option in LUAD.

How Do Living Systems Create Meaning?

Meaning has traditionally been regarded as a problem for philosophers and psychologists. Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer science. Here, we review the notion of “meaning” as it applies to living systems, and argue that the question of how living systems create meaning unifies the biological and cognitive sciences across both organizational and temporal scales.