Erroneous Silencing of the Mitotic Checkpoint by Aberrant Spindle Pole-Kinetochore Coordination

Research progress on morphology and mechanism of programmed cell death

Programmed cell death (PCD) is a basic process of life that is closely related to the growth, development, aging and disease of organisms and is one of the hotspots of life science research today. PCD is a kind of genetic control, autonomous and orderly important cell death that involves the activation, expression, and regulation of a series of genes. In recent years, with the deepening of research in this field, new mechanisms of multiple PCD pathways have been revealed. This article reviews and summarizes the multiple PCD pathways that have been discovered, analyses and compares the morphological characteristics and biomarkers of different types of PCD, and briefly discusses the role of various types of PCD in the diagnosis and treatment of different diseases, especially malignant tumors.

Spindle Architectural Features Must Be Considered Along With Cell Size to Explain the Timing of Mitotic Checkpoint Silencing

Mitosis proceeds through a defined series of events that is largely conserved, but the amount of time needed for their completion can vary in different cells and organisms. In many systems, mitotic duration depends on the time required to satisfy and silence the spindle assembly checkpoint (SAC), also known as the mitotic checkpoint. Because SAC silencing involves trafficking SAC molecules among kinetochores, spindle, and cytoplasm, the size and geometry of the spindle relative to cell volume are expected to affect mitotic duration by influencing the timing of SAC silencing. However, the relationship between SAC silencing, cell size, and spindle dimensions is unclear. To investigate this issue, we used four DLD-1 tetraploid (4N) clones characterized by small or large nuclear and cell size. We found that the small 4N clones had longer mitotic durations than the parental DLD-1 cells and that this delay was due to differences in their metaphase duration. Leveraging a previous mathematical model for spatiotemporal regulation of SAC silencing, we show that the difference in metaphase duration, i.e., SAC silencing time, can be explained by the distinct spindle microtubule densities and sizes of the cell, spindle, and spindle poles in the 4N clones. Lastly, we demonstrate that manipulating spindle geometry can alter mitotic and metaphase duration, consistent with a model prediction. Our results suggest that spindle size does not always scale with cell size in mammalian cells and cell size is not sufficient to explain the differences in metaphase duration. Only when a number of spindle architectural features are considered along with cell size can the kinetics of SAC silencing, and hence mitotic duration, in the different clones be explained.

Identification and Integrated Analysis of Key Biomarkers for Diagnosis and Prognosis of Non-Small Cell Lung Cancer

Background

Non-small cell lung cancer (NSCLC) is the main histologic form of lung cancer that affects human health, but biomarkers for therapeutic diagnosis and prognosis of the disease are currently lacking.

Material/Methods

The gene expression profile GSE18842 was downloaded from the Gene Expression Omnibus database in this prospective study, which consisted of 46 tumors and 45 controls. After screening differentially expressed genes (DEGs), we conducted functional enrichment analysis and KEGG analysis with upregulated differentially expressed genes (uDEGs) and downregulated differentially expressed genes (dDEGs), respectively. Protein–protein interaction (PPI) networks among DEGs and corresponding coding protein complexes, constructed using the STRING database, were analyzed using Cytoscape. Kaplan-Meier method was used to verify survival associated with hub genes. The GEPIA webserver was used to plot the gene expression level heat map of hub genes between NSCLC and adjacent lung tissues in the TCGA database.

Results

We identified 368 DEGs (168 uDEGs and 200 dDEGs) in NSCLC samples relative to control samples after gene integration. We established a PPI network for the DEGs, which had 249 nodes and 1472 edges protein pairs. Ten undefined hub genes with the highest connectivity degree (CDK1, UBE2C, AURKA, CCNA2, CDC20, CCNB1, TOP2A, ASPM, MAD2L1, and KIF11) were verified by survival analysis, and 9 of them were associated with poorer overall survival in NSCLC. The expression reliability of hub genes was verified by use of the GEPIA web tool.

Conclusions

The results suggested that UBE2C, AURKA, CCNA2, CDC20, CCNB1, TOP2A, ASPM, MAD2L1, and KIF11 are inherent key biomarkers for diagnosis and prognosis, while KEGG analysis results showed the mitotic cell cycle pathway is a probable signaling pathway contributing to NSCLC progression. These genes could be promising biomarkers for diagnosis and provide a new approach for developing targeted therapeutic NSCLC drugs.

The frequency and consequences of multipolar mitoses in undifferentiated embryonic stem cells

Embryonic stem (ES) cells are pluripotent cells widely used in cell therapy and tissue engineering. However, the broader clinical applications of ES cells are limited by their genomic instability and karyotypic abnormalities. Thus, understanding the mechanisms underlying ES cell karyotypic abnormalities is critical to optimizing their clinical use. In this study, we focused on proliferating human and mouse ES cells undergoing multipolar divisions. Specifically, we analyzed the frequency and outcomes of such divisions using a combination of time-lapse microscopy and cell tracking. This revealed that cells resulting from multipolar divisions were not only viable, but they also frequently underwent subsequent cell divisions. Our novel data also showed that in human and mouse ES cells, multipolar spindles allowed more robust escape from chromosome segregation control mechanisms than bipolar spindles. Considering the frequency of multipolar divisions in proliferating ES cells, it is conceivable that cell division errors underlie ES cell karyotypic instability.

Spindle Size Scaling Contributes to Robust Silencing of Mitotic Spindle Assembly Checkpoint

Chromosome segregation during mitosis hinges on proper assembly of the microtubule spindle that establishes bipolar attachment to each chromosome. Experiments demonstrate allometry of mitotic spindles and a universal scaling relationship between spindle size and cell size across metazoans, which indicates a conserved principle of spindle assembly at play during evolution. However, the nature of this principle is currently unknown. Researchers have focused on deriving the mechanistic underpinning of the size scaling from the mechanical aspects of the spindle assembly process. In this work we take a different standpoint and ask: What is the size scaling for? We address this question from the functional perspectives of spindle assembly checkpoint (SAC). SAC is the critical surveillance mechanism that prevents premature chromosome segregation in the presence of unattached or misattached chromosomes. The SAC signal gets silenced after and only after the last chromosome-spindle attachment in mitosis. We previously established a model that explains the robustness of SAC silencing based on spindle-mediated spatiotemporal regulation of SAC proteins. Here, we refine the previous model, and find that robust and timely SAC silencing entails proper size scaling of mitotic spindle. This finding provides, to our knowledge, a novel, function-oriented angle toward understanding the observed spindle allometry, and the universal scaling relationship between spindle size and cell size in metazoans. In a broad sense, the functional requirement of robust SAC silencing could have helped shape the spindle assembly mechanism in evolution.

Dynamics robustness of cascading systems

A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade’s kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1) Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2) Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it will provide a general basis for how biological systems function dynamically.

Cells use signaling pathways to transmit information received on its membrane to DNA, and many important cellular processes are tied to signaling networks. Past experiments have shown that cells’ internal signaling networks are sophisticated enough to process and encode temporal information such as the length of time a ligand is bound to a receptor. However, little research has been done to verify whether information encoded onto temporal profiles can be made robust. We examined mathematical models of linear signaling networks and found that the relaxation of the response to a transient stimuli can be made robust to certain parameter fluctuations. Robustness is a key concept in biological systems—it would be disastrous if a cell could not operate if there was a slight change in its environment or physiology. Our research shows that such dynamics robustness is a property of linear signaling cascades, and we outline the design principles needed to generate such robustness. We discovered that two conditions regarding the speed of the internal chemical reactions and concentration levels are needed to generate dynamics robustness.