Quantifying cell cycle-dependent drug sensitivities in cancer using a high throughput synchronisation and screening approach

Reversible and effective cell cycle synchronization method for studying stage-specific investigations

The cell cycle is a crucial process for cell proliferation, differentiation, and development. Numerous genes and proteins play pivotal roles at specific cell cycle stages to regulate these events precisely. Studying the stage-specific functions of the cell cycle requires accumulating cell populations at the desired cell cycle stage. Cell synchronization, achieved through the use of cell cycle kinase and protein inhibitors, is often employed for this purpose. However, suboptimal concentrations of these inhibitors can result in reduced efficiency, irreversibility, and undesirable cell cycle defects. In this study, we have optimized effective and reversible techniques to synchronize the cell cycle at each stage in human RPE1 cells, utilizing both fixed high-precision cell cycle identification methods and high-temporal live-cell imaging. These reproducible synchronization methods are invaluable for investigating the regulatory mechanisms specific to each cell cycle stage.

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Senescent cell heterogeneity and responses to senolytic treatment are related to cell cycle status during cell growth arrest

Cellular senescence has been strongly linked to aging and age-related diseases. It is well established that the phenotype of senescent cells is highly heterogeneous and influenced by their cell type and senescence-inducing stimulus. Recent single-cell RNA-sequencing studies identified heterogeneity within senescent cell populations. However, proof of functional differences between such subpopulations is lacking. To identify functionally distinct senescent cell subpopulations, we employed high-content image analysis to measure senescence marker expression in primary human endothelial cells and fibroblasts. We found that G2-arrested senescent cells feature higher senescence marker expression than G1-arrested senescent cells. To investigate functional differences, we compared IL-6 secretion and response to ABT263 senolytic treatment in G1 and G2 senescent cells. We determined that G2-arrested senescent cells secrete more IL-6 and are more sensitive to ABT263 than G1-arrested cells. We hypothesize that cell cycle dependent DNA content is a key contributor to the heterogeneity within senescent cell populations. This study demonstrates the existence of functionally distinct senescent subpopulations even in culture. This data provides the first evidence of selective cell response to senolytic treatment among senescent cell subpopulations. Overall, this study emphasizes the importance of considering the senescent cell heterogeneity in the development of future senolytic therapies.

An exploratory study on the effect of kynurenine metabolites on sEnd-2 endothelioma cells

Cancer is the second leading cause of mortality worldwide. The development of anticancer therapy plays a crucial role in mitigating tumour progression and metastasis. Epithelioid hemangioendothelioma is a very rare cancer, however, with a high systemic involvement. Kynurenine metabolites which include l-kynurenine, 3-hydroxykynurenine, 3-hydroxyanthranilic acid and quinolinic acid have been shown to inhibit T-cell proliferation resulting in a decrease in cell growth of natural killer cells and T cells. Furthermore, metabolites such as  l-kynurenine have been shown to inhibit proliferation of melanoma cells in vitro. Considering these metabolite properties, the present study aimed to explore the in vitro effects of  l-kynurenine, quinolinic acid and kynurenic acid on endothelioma sEnd-2 cells and on endothelial (EA. hy926 cells) (control cell line). The in vitro effect at 24, 48, and 72 h exposure to a range of 1-4 mM of the respective kynurenine metabolites on the two cell lines in terms of cell morphology, cell cycle progression and induction of apoptosis was assessed. The half inhibitory concentration (IC50), as determined using nonlinear regression, for  l-kynurenine, quinolinic acid and kynurenic acid was 9.17, 15.56, and 535.40 mM, respectively. Optical transmitted light differential interference contrast and hematoxylin and eosin staining revealed cells blocked in metaphase, formation of apoptotic bodies and compromised cell density in  l-kynurenine-treated cells. A statistically significant increase in the number of cells present in the sub-G1 phase was observed in  l-kynurenine-treated sample. To our knowledge, this was the first in vitro study conducted to investigate the mechanism of action of kynurenine metabolites on endothelioma sEnd-2 cells. It can be concluded that  l-kynurenine exerts an antiproliferative effect on the endothelioma sEnd-2 cell line by decreasing cell growth and proliferation as well as a metaphase block. These hallmarks suggest cell death via apoptosis. Further research will be conducted on  l-kynurenine to assess the effect on cell adhesion in vitro and in vivo as cell-cell adhesion has been shown to increase metastasis to distant organs therefore, the inhibition of adhesion may lead to a decrease in metastasis.

Model design choices impact biological insight: Unpacking the broad landscape of spatial-temporal model development decisions

Computational models enable scientists to understand observed dynamics, uncover rules underlying behaviors, predict experimental outcomes, and generate new hypotheses. There are countless modeling approaches that can be used to characterize biological systems, further multiplied when accounting for the variety of model design choices. Many studies focus on the impact of model parameters on model output and performance; fewer studies investigate the impact of model design choices on biological insight. Here we demonstrate why model design choices should be deliberate and intentional in context of the specific research system and question. In this study, we analyze agnostic and broadly applicable modeling choices at three levels-system, cell, and environment-within the same agent-based modeling framework to interrogate their impact on temporal, spatial, and single-cell emergent dynamics. We identify key considerations when making these modeling choices, including the (i) differences between qualitative vs. quantitative results driven by choices in system representation, (ii) impact of cell-to-cell variability choices on cell-level and temporal trends, and (iii) relationship between emergent outcomes and choices of nutrient dynamics in the environment. This generalizable investigation can help guide the choices made when developing biological models that aim to characterize spatial-temporal dynamics.

Cyclohexene oxide CA, a derivative of zeylenone, exhibits anti-cancer activity in glioblastoma by inducing G0/G1 phase arrest through interference with EZH2

Introduction: Due to its highly aggressiveness and malignancy, glioblastoma (GBM) urgently requires a safe and effective treatment strategy. Zeylenone, a natural polyoxygenated cyclohexenes compound isolated from Uvaria grandiflora, has exhibited potential biological activities in various human diseases, including tumors. Methods: We designed and synthesized a series of (+)-Zeylenone analogues and evaluated their anti-GBM roles through structural-activity analysis. Cell Counting Kit-8, TUNEL, transwell and flow cytometry were employed for investigating the anticancer effects of CA on GBM cells. Western blotting, molecular docking, qRT-PCR and ChIP assays were performed to reveal the underlying mechanisms by which CA regulates the GBM cell cycle. The nude mouse xenograft model, HE staining, immunohistochemistry and was used to evaluate the anticancer effect of CA in vivo. Results: We identified CA ((1R, 2R, 3S)-3-p-fluorobenzoyl-zeylenone) as having the lowest IC50 value in GBM cells. CA treatment significantly inhibited the malignant behaviors of GBM cells and induced G0/G1 phase arrest in vitro. Furthermore, we validated the molecular mechanism by which CA interferes with EZH2, attenuating the down-regulation of cyclin-dependent kinase inhibitors p27 and p16 by the PRC2 complex. By establishing orthotopic nude mice models, we further validated the inhibitory role of CA on tumorigenesis of GBM cells in vivo and its potential values to synergistically potentiate the anti-tumor effects of EZH2 inhibitors. Conclusion: Overall, this paper elucidated the anti-GBM effects and potential mechanisms of CA, and may provide a therapeutic drug candidate for GBM treatment.

Cardiac glycoside ouabain efficiently targets leukemic stem cell apoptotic machinery independent of cell differentiation status

BACKGROUND

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy characterized by an accumulation of immature leukemic myeloblasts initiating from leukemic stem cells (LSCs)-the subpopulation that is also considered the root cause of chemotherapy resistance. Repurposing cardiac glycosides to treat cancers has gained increasing attention and supporting evidence, but how cardiac glycosides effectively target LSCs, e.g., whether it involves cell differentiation, remains largely unexplored.

METHODS

Digoxin, a user-designed digitoxigenin-α-L-rhamnoside (D6-MA), and ouabain were tested against various human AML-derived cells with different maturation phenotypes. Herein, we established two study models to specifically determine the effects of cardiac glycosides on LSC death and differentiation-one allowed change in dynamics of LSCs and leukemic progenitor cells (LPCs), while another maintained their undifferentiated status. Regulatory mechanisms underlying cardiac glycoside-induced cytotoxicity were investigated and linked to cell cycle distribution and apoptotic machinery.

RESULTS

Primitive AML cells containing CD34+ LSCs/LPCs were very responsive to nanomolar concentrations of cardiac glycosides, with ouabain showing the greatest efficiency. Ouabain preferentially induces caspase-dependent apoptosis in LSCs, independent of its cell differentiation status, as evidenced by (i) the tremendous induction of apoptosis by ouabain in AML cells that acquired less than 15% differentiation and (ii) the higher rate of apoptosis in enriched LSCs than in LPCs. We sorted LSCs and LPCs according to their cell cycle distribution into G0/G1, S, and G2/M cells and revealed that G0/G1 cells in LSCs, which was its major subpopulation, were the top ouabain responders, indicating that the difference in ouabain sensitivity between LSCs and LPCs involved both distinct cell cycle distribution and intrinsic apoptosis regulatory mechanisms. Further, Mcl-1 and c-Myc, which were differentially expressed in LSCs and LPCs, were found to be the key apoptosis mediators that determined ouabain sensitivity in AML cells. Ouabain induces a more rapid loss of Mcl-1 and c-Myc in LSCs than in LPCs via the mechanisms that in part involve an inhibition of Mcl-1 protein synthesis and an induction of c-Myc degradation.

CONCLUSIONS

Our data provide new insight for repurposing cardiac glycosides for the treatment of relapsed/refractory AML through targeting LSCs via distinct cell cycle and apoptosis machinery. Video Abstract.

An autonomous mathematical model for the mammalian cell cycle

A mathematical model for the mammalian cell cycle is developed as a system of 13 coupled nonlinear ordinary differential equations. The variables and interactions included in the model are based on detailed consideration of available experimental data. A novel feature of the model is inclusion of cycle tasks such as origin licensing and initiation, nuclear envelope breakdown and kinetochore attachment, and their interactions with controllers (molecular complexes involved in cycle control). Other key features are that the model is autonomous, except for a dependence on external growth factors; the variables are continuous in time, without instantaneous resets at phase boundaries; mechanisms to prevent rereplication are included; and cycle progression is independent of cell size. Eight variables represent cell cycle controllers: the Cyclin D1-Cdk4/6 complex, APC^Cdh1, SCF^βTrCP, Cdc25A, MPF, NuMA, the securin-separase complex, and separase. Five variables represent task completion, with four for the status of origins and one for kinetochore attachment. The model predicts distinct behaviors corresponding to the main phases of the cell cycle, showing that the principal features of the mammalian cell cycle, including restriction point behavior, can be accounted for in a quantitative mechanistic way based on known interactions among cycle controllers and their coupling to tasks. The model is robust to parameter changes, in that cycling is maintained over at least a five-fold range of each parameter when varied individually. The model is suitable for exploring how extracellular factors affect cell cycle progression, including responses to metabolic conditions and to anti-cancer therapies.

Identification of novel piperazine-tethered phthalazines as selective CDK1 inhibitors endowed with in vitro anticancer activity toward the pancreatic cancer

Pharmacologic inhibition of the oncogenic protein kinases using small molecules is a promising strategy to combat several human malignancies. CDK1 is an example of such a valuable target for the management of pancreatic ductal adenocarcinomas (PDAC); its overexpression in PDAC positively correlates with the size, histological grade and tumor aggressiveness. Here we report the identification of novel series of 1-piperazinyl-4-benzylphthalazine derivatives (8a-g, 10a-i and 12a-d) as promising anticancer agents with CDK1 inhibitory activity. The anti-proliferative activity of these agents was first screened on a panel of 11 cell lines representing 5 cancers (pancreas, melanoma, leukemia, colon and breast), and then confirmed on two CDK1-overexpressing PDAC cell lines (MDA-PATC53 and PL45 cells). Phthalazines 8g, 10d and 10h displayed potent activity against MDA-PATC53 (IC₅₀ = 0.51, 0.88 and 0.73 μM, respectively) and PL45 (IC₅₀ = 0.74, 1.14 and 1.00 μM, respectively) cell lines. Furthermore, compounds 8g, 10d and 10h exhibited potent and selective inhibitory activity toward CDK1 with IC₅₀ spanning in the range 36.80-44.52 nM, whereas they exerted weak inhibitory effect on CDK2, CDK5, AXL, PTK2B, FGFR, JAK1, IGF1R and BRAF kinases. Western blotting of CDK1 in MDA-PATC53 cells confirmed the ability of target phthalazines to diminish the CDK1 levels, and cell cycle analyses revealed their ability to arrest the cell cycle at G2/M phase. In conclusion, a panel of potent and selective CDK1 inhibitors were identified which can serve as lead compounds for designing further CDK1 inhibitors.

A lineage tree-based hidden Markov model quantifies cellular heterogeneity and plasticity

Individual cells can assume a variety of molecular and phenotypic states and recent studies indicate that cells can rapidly adapt in response to therapeutic stress. Such phenotypic plasticity may confer resistance, but also presents opportunities to identify molecular programs that could be targeted for therapeutic benefit. Approaches to quantify tumor-drug responses typically focus on snapshot, population-level measurements. While informative, these methods lack lineage and temporal information, which are particularly critical for understanding dynamic processes such as cell state switching. As new technologies have become available to measure lineage relationships, modeling approaches will be needed to identify the forms of cell-to-cell heterogeneity present in these data. Here we apply a lineage tree-based adaptation of a hidden Markov model that employs single cell lineages as input to learn the characteristic patterns of phenotypic heterogeneity and state transitions. In benchmarking studies, we demonstrated that the model successfully classifies cells within experimentally-tractable dataset sizes. As an application, we analyzed experimental measurements in cancer and non-cancer cell populations under various treatments. We find evidence of multiple phenotypically distinct states, with considerable heterogeneity and unique drug responses. In total, this framework allows for the flexible modeling of single cell heterogeneity across lineages to quantify, understand, and control cell state switching.

Magnetomechanical Stress-Induced Colon Cancer Cell Growth Inhibition

The application of magnetomechanical stress in cells using internalized magnetic nanoparticles (MNPs) actuated by low-frequency magnetic fields has been attracting considerable interest in the field of cancer research. Recent developments prove that magnetomechanical stress can inhibit cancer cells’ growth. However, the MNPs’ type and the magnetic field’s characteristics are crucial parameters. Their variability allows multiple combinations, which induce specific biological effects. We previously reported the antiproliferative effects induced in HT29 colon cancer cells by static-magnetic-field (200 mT)-actuated spherical MNPs (100 nm). Herein, we show that similar growth inhibitory effects are induced in other colon cancer cell lines. The effect of magnetomechanical stress was also examined in the growth rate of tumor spheroids. Moreover, we examined the biological mechanisms involved in the observed cell growth inhibition. Under the experimental conditions employed, no cell death was detected by PI (propidium iodide) staining analysis. Flow cytometry and Western blotting revealed that G2/M cell cycle arrest might mediate the antiproliferative effects. Furthermore, MNPs were found to locate in the lysosomes, and a decreased number of lysosomes was detected in cells that had undergone magnetomechanical stress, implying that the mechanical activation of the internalized MNPs could induce lysosome membrane disruption. Of note, the lysosomal acidic conditions were proven to affect the MNPs’ magnetic properties, evidenced by vibrating sample magnetometry (VSM) analysis. Further research on the combination of the described magnetomechanical stress with lysosome-targeting chemotherapeutic drugs could lay the groundwork for the development of novel anticancer combination treatment schemes.