The Networks Regulating Cell Division
Cytokinesis is a key event in the cell cycle requiring tight coordination of mitotic spindle assembly, actomyosin contractility and membrane dynamics, but the mechanisms that regulate cytokinesis are poorly understood. If chromosomes are not accurately segregated during division, and daughter cells lose or gain genomic DNA, this can lead to aneuploidy. Aneuploidy is not only a hallmark of tumor cells but has a causal role in tumorigenesis.
Failures in chromosome segregation can occur if: the mitotic spindle is not properly assembled; cytokinesis is not completed; the spindle assembly checkpoint is inappropriately bypassed; or the timing of late mitotic events is disrupted.
In fact altered expression or mutation of genes that encode proteins regulating the progression of late mitotic events and cytokinesis, such as Aurora-A, Eg5, BubR1, Mad2, or Polo-like kinase (PLK), has been detected in a number of cancers including breast, colorectal, ovarian and lung cancer. Mutations in these genes may override checkpoints that would limit the proliferation of genetically abnormal tumor cells.
Because of the role of aneuploidy in oncogenesis, gaining a systems-levels understanding of the signaling networks that act to ensure the fidelity of chromosome segregation is warranted. Moreover, as a number of anti-mitotic therapies are being devised for cancer therapy it is essential to gain insight in the basis of why these compounds are effective.
In nearly all metazoan cells, the RhoGAP MgcRacGAP and its binding partner the RhoGEF Ect2 are activated in late mitosis by a number of upstream kinases such as Aurora-B, Cdk1, and Plk1 to establish a localized zone of high RhoA GTPase activity at the presumptive cleavage furrow, which in turn promotes the formation of the contractile actomyosin cytokinetic ring and ultimately cytokinesis.
Recruitment of both MgcRacGAP and Ect2 to the presumptive furrow is essential for cytokinesis to occur. Inhibition of the RhoGAP MgcRacGAP or RhoGEF Ect2 results in chromosome segregation defects in a wide variety of organisms.
Late mitotic kinases phosphorylate and activate MgcRacGAP and Ect2 to signal that spindle-chromosome attachment and chromosome segregation has occurred and that cytokinesis can proceed. Interestingly expression of Ect2 has been observed to be upregulated in many human tumors.
Using high-throughput single cell RNAi screens we have previously identified ~40 kinase and phosphatases which are putative regulators of MgcRacGAP and Ect2 during cytokinesis in Drosophila cells, the majority of which have been previously shown to be mutated or have altered expression in human tumor cells.
We hypothesize that these signaling molecules play a role in coordinating spindle assembly and mitotic checkpoint signaling with the initiation of cytokinesis. We will use quantitative multiplexed live cell imaging to determine the role of these kinases and phosphatases in controlling MgcRacGAP and Ect2 localization and activity.
The datasets generated in the course of these studies will then be used in mathematical modeling approaches to describe the dynamics of cytokinesis regulation.
Mathematical Modeling of the Cell Cycle
In order for multicellular organisms to develop and grow, their cells must divide. Even in adults, some cell division still occurs. For example, stem cells divide to replenish shed skin cells, or immune cells divide in response to infection.
This process of cell division must be strictly controlled so that cells only divide when and where new cells are needed. Uncontrolled cell division leads to a mass of cells, or tumor. The genes that regulate cell division are frequently mutated in cancer - which can enhance, diminish or completely change the function of that gene.
Therefore, an understanding of how cell division is normally controlled, and how this process can be corrupted, is of critical importance if we are to understand and combat cancer.
The cell division cycle of human cells is divided into four discrete and consecutive phases known as: G1, S (DNA synthesis), G2 and Mitosis. Arguably, the first transition of the cell cycle – from G1 into S-phase – is the most critical as this represents commitment to a new round of cell division.
A number of proteins have evolved which can stop or start the cell cycle depending on the conditions in- and outside the cell. If, for example, a cell has incurred DNA damage then these proteins will prevent that cell from progressing through the cell cycle.
These regulatory proteins form a complex biochemical network that must be robust to failure, i.e. the system must maintain its function in the face of perturbations. Robustness is a property of many engineered systems, for example the navigation systems of aeroplanes have a number of failsafe mechanisms built-in to ensure continuity of performance if one component fails.
The control networks that control the cell cycle are similarly robust to different types of failure, one example being the loss of function of a regulator protein due to genetic mutation. The robustness of the cell cycle control network, however, comes at a price: the network can also be “rewired” by genetic mutation to drive cell division even when the environment is not suitable – leading to cancer.
This also means that it is difficult to block cancer cell division using different types of drugs, as cells are able to circumvent a block placed on cell division by co-opting and adapting other intact signaling pathways. Despite decades of research, we still do not understand the properties of the control systems that mediate robustness in the cell cycle in normal cells and how these control mechanisms are changed in cancer cells.
Even though we know many of the genes that are important for cell division, we do not understand how they interact in biochemical networks and how these networks are rewired in cancer cells. We aim to quantify the signaling events occurring during progression from G1 into S-phase in human cells.
In collaboration with the laboratory of Michael Yaffe (Massachusetts Institute of Technology, Cambridge USA) we are using this data to computationally model the networks that control G1 progression in order to understand both why the G1 control network is robust to genetic perturbation and how this robustness is hijacked by oncogenic mutations that drive cancer progression.