A quantised cyclin-based cell cycle model

Computational modelling is an important research tool, helping predict the outcome of proposed treatment plans or to illuminate the mechanics of tumour growth. In silico modelling has been used in every aspect of cancer research from DNA damage and repair, tumour growth, drug/tumour interactions, and mutational status. Indeed, modelling even holds potential in understanding the interactions between individual proteins on a single cell basis. Here, we present a computational model of the cell cycle network of the cyclin family of proteins (cyclin A, B, D and E). This model has been quantised using western blot and flow cytometry data from a synchronised HUVEC line to enable the determination of the absolute number of cyclin protein molecules per cell. This quantification allows the model to have stringent controls over the thresholds between transitions. The results show that the peak values obtained for the four cyclins are similar with cyclin B having a peak values of 5×106 to 9×106 molecules per cell. Comparing this value with the number of actin proteins, 5E8, shows that despite their importance, the level of cyclin family proteins are approximately 2 orders of magnitude lower. The efficiency of the model presented would also allow for its use as an internal component in more complex models such as a tumour growth model, in which each individual cell would have its own cell cycle calculated independently from neighbouring cells. Additionally, the model can also be used to help understand the impact of novel therapeutic interventions on cell cycle progression.Author SummaryProtein and gene networks control every physiological behaviour of cells, with the cell cycle being controlled by the network of genes that promote the cyclin family of proteins. These networks hold the key to creating accurate and relevant biological models. Normally these models are presented with relative protein concentrations without any real world counterpart to their outputs. The model presented within shows and advancement of this approach by calculating the absolute concentration of each cyclin protein in one cell as it progresses through the cell cycle. This model employs Boolean variables to represent the genetic network, either the gene is active or not, and continuous variables to represent the concentrations of the proteins. This hybridised approach allows for rapid calculations of the protein concentrations and of the cell cycle progression allowing for a model that could be easily incorporated into larger tumour models, allowing for the tracking of discrete cells within the tumour.

Abnormal Platelet miRNA Profile Associated with Endometriosis

Endometriosis (EM) is a condition characterized by the growth of functional endometrium in areas other than the uterus. In this study, microRNAs (miRNAs) were extracted from peripheral blood platelets from patients diagnosed with EM and from healthy controls for high-throughput sequencing; differential expression of miR-542-3p and miR-618 was identified via database comparisons. Dual pathway enrichment analysis revealed that both miRNAs may target the cyclin protein, G1/S-specific cyclin-D2 (CCND2). CCND2 was verified as a target gene of both miR-542-3p and miR-618 via experiments carried out in vivo. Taken together, these results reveal that CCND2 may serve as a functional biomarker for the diagnosis of EM.

CDKs family -a glimpse into the past and present: from cell cycle control to current biological functions

Cyclin-dependent kinases (CDKs) are the catalytic subunits or protein kinases characterized by separate subunit “cyclin” that are essential for their enzymatic activity. CDKs play important roles in the control of cell cycle progression, cell division, neuronal function, epigenetic regulation, metabolism, stem cell renewal and transcription. However, they can accomplish some of these tasks independently, without binding with cyclin protein or kinase activity. Thus, so far, twenty different CDKs and cyclins have been reported in mammalian cells. The evolutionary expansion of the CDK family in mammals led to the division of CDKs into three cell-cycle-related subfamilies (Cdk1, Cdk4 and Cdk5) and five transcriptional subfamilies (Cdk7, Cdk8, Cdk9, Cdk11 and Cdk20). In this review, we summarizes that how CDKs are traditionally involve their latest revelations, their functional diversity beyond cell cycle regulation and their impact on development of disease in mammals.

Use of Serum Circulating Ccnb2 in Cancer Surveillance

Cyclin B2 (CCNB2), a member of the cyclin protein family, has been found to be up-regulated in human cancers. To evaluate the potential use of circulating CCNB2 in serum in cancer surveillance, we examined relative expression levels of serum circulating CCNB2 mRNA in 103 cancer patients, 19 normal controls, and 40 benign disease patients using real-time quantitative reverse transcriptase polymerase chain reaction. We found that the relative expression level of circulating CCNB2 mRNA in cancer patients was significantly higher (p<0.0001) than that in normal controls and benign diseases group. Circulating CCNB2 mRNA level was significantly (p<0.001) correlated with cancer stage and metastasis status. Receiver operating characteristic (ROC) analysis showed an area under the curve (AUC) of 0.87 and 0.83 (p<0.05) in identifying cancer patients' metastasis status in lung and digestive tract cancer, respectively. Moreover, we observed that expression levels of circulating CCNB2 mRNA in cancer patients significantly decreased (p=0.0084) after their therapeutic treatments. These data suggest that detection of serum circulating CCNB2 mRNA may have potential clinical applications in screening and monitoring of metastasis and therapeutic treatments.