Epigenetic Abnormalities in Chondrosarcoma

In recent years, our understanding of the epigenetic mechanisms involved in tumor pathology has improved greatly. DNA and histone modifications, such as methylation, demethylation, acetylation, and deacetylation, can lead to the up-regulation of oncogenic genes, as well as the suppression of tumor suppressor genes. Gene expression can also be modified on a post-transcriptional level by microRNAs that contribute to carcinogenesis. The role of these modifications has been already described in many tumors, e.g., colorectal, breast, and prostate cancers. These mechanisms have also begun to be investigated in less common tumors, such as sarcomas. Chondrosarcoma (CS) is a rare type of tumor that belongs to sarcomas and is the second most common malignant bone tumor after osteosarcoma. Due to unknown pathogenesis and resistance to chemo- and radiotherapies of these tumors, there is a need to develop new potential therapies against CS. In this review, we summarize current knowledge on the influence of epigenetic alterations in the pathogenesis of CS by discussing potential candidates for future therapies. We also emphasize ongoing clinical trials that use drugs targeting epigenetic modifications in CS treatment.

Quantitative label-free mass spectrometry analysis of formalin-fixed, paraffin-embedded tissue representing the invasive cutaneous malignant melanoma proteome

Understanding the events at a protein level that govern the progression from melanoma in situ to invasive melanoma are important areas of current research to be developed. Recent advances in the analysis of formalin-fixed, paraffin-embedded tissue by proteomics, particularly using the filter-aided sample preparation protocol, has opened up the possibility of studying vast archives of clinical material and associated medical records. In the present study, quantitative protein profiling was performed using tandem mass spectrometry, and the proteome differences between melanoma in situ and invasive melanoma were compared. Biological pathway analyses revealed several signalling pathways differing between melanoma in situ and invasive melanoma, including metabolic pathways and the phosphoinositide 3-kinase-Akt signalling pathway. Selected proteins of interest (14–3-3ε and fatty acid synthase) were subsequently investigated using immunohistochemical analysis of tissue microarrays. Identifying the key proteins that play significant roles in the establishment of a more invasive phenotype in melanoma may ultimately aid diagnosis and treatment decisions.

Third-Kind Encounters in Biomedicine: Immunology Meets Mathematics and Informatics to Become Quantitative and Predictive

The understanding of the immune response is right now at the center of biomedical research. There are growing expectations that immune-based interventions will in the midterm provide new, personalized, and targeted therapeutic options for many severe and highly prevalent diseases, from aggressive cancers to infectious and autoimmune diseases. To this end, immunology should surpass its current descriptive and phenomenological nature, and become quantitative, and thereby predictive.Immunology is an ideal field for deploying the tools, methodologies, and philosophy of systems biology, an approach that combines quantitative experimental data, computational biology, and mathematical modeling. This is because, from an organism-wide perspective, the immunity is a biological system of systems, a paradigmatic instance of a multi-scale system. At the molecular scale, the critical phenotypic responses of immune cells are governed by large biochemical networks, enriched in nested regulatory motifs such as feedback and feedforward loops. This network complexity confers them the ability of highly nonlinear behavior, including remarkable examples of homeostasis, ultra-sensitivity, hysteresis, and bistability. Moving from the cellular level, different immune cell populations communicate with each other by direct physical contact or receiving and secreting signaling molecules such as cytokines. Moreover, the interaction of the immune system with its potential targets (e.g., pathogens or tumor cells) is far from simple, as it involves a number of attack and counterattack mechanisms that ultimately constitute a tightly regulated multi-feedback loop system. From a more practical perspective, this leads to the consequence that today's immunologists are facing an ever-increasing challenge of integrating massive quantities from multi-platforms.In this chapter, we support the idea that the analysis of the immune system demands the use of systems-level approaches to ensure the success in the search for more effective and personalized immune-based therapies.

The Association of Ala133Ser Polymorphism and Methylation in Ras Association Domain Family 1A Gene With Unfavorable Prognosis of Hepatocellular Carcinoma

BACKGROUND

The functional and prognostic significance of Ras association domain family 1A gene (RASSF1A) on hepatocellular carcinoma (HCC) has not been well characterized.

OBJECTIVES

This study aimed to investigate the association between Ala133Ser polymorphism or promoter methylation in RASSF1A and the prognosis of HCC in Nantong City, one of the areas with the highest incidence of cancer in China.

PATIENTS AND METHODS

Using peripheral blood plasma, the incidence rate of RASSF1A Ala133Ser in 235 controls and subjects with 260 HCC was analyzed by the polymerase chain reaction and sequencing. We further investigated the RASSF1A methylation status in HCC and corresponding peri-tumorous normal tissues using the methylation-specific polymerase chain reaction approach.

RESULTS

It was found that the frequency of the RASSF1A Ala133Ser T allele (Ala/Ser and Ser/Ser) genotype in HCC cases was observably higher than that of normal subjects (P < 0.001). In comparison to the Ala/Ala genotype, the T allele genotype improved the susceptibility to HCC. The study also found that RASSF1A methylation improves the risk of HCC. Furthermore, in contrast with the corresponding peri-tumorous normal tissues, we observed that the RASSF1A methylation status was markedly higher in HCC tissues (P < 0.001). The Kaplan-Meier and multivariate analyses suggested that the poor survival of HCC patients was closely connected with hepatocirrhosis, Barcelona Clinic Liver Cancer stage, Edmondson division, RASSF1A methylation and Ala133Ser polymorphism (P < 0.001).

CONCLUSIONS

The polymorphism and promoter methylation of RASSF1A may be a significant factor in HCC, and can be an indicator for poor prognosis in patients with HCC.

Bifurcation Analysis of a Model Accounting for the 14-3-3s Signalling Compartmentalisation

Bifurcation theory studies the qualitative changes in the phase portrait when we vary the parameters of the system. In this book chapter we adapt and extend a mathematical model accounting for the subcellular localisation of 14-3-3s, a protein involved in cell cycle arrest and the regulation of apoptosis. The model is analysed with analytical tools coming from Lyapunov-Andronov theory, and our analytical calculations predict that soft (reversible) loss of stability takes place.

Biochemical Systems Theory: A Review

Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools that facilitate the analysis of dynamic biological systems. This paper depicts major developments in BST up to the current state of the art in 2012. It discusses its rationale, describes the typical strategies and methods of designing, diagnosing, analyzing, and utilizing BST models, and reviews areas of application. The paper is intended as a guide for investigators entering the fascinating field of biological systems analysis and as a resource for practitioners and experts.

Computational analysis of target hub gene repression regulated by multiple and cooperative miRNAs

MicroRNA (miRNA) target hubs are genes that can be simultaneously targeted by a comparatively large number of miRNAs, a class of non-coding RNAs that mediate post-transcriptional gene repression. Although the details of target hub regulation remain poorly understood, recent experiments suggest that pairs of miRNAs can cooperate if their binding sites reside in close proximity. To test this and other hypotheses, we established a novel approach to investigate mechanisms of collective miRNA repression. The approach presented here combines miRNA target prediction and transcription factor prediction with data from the literature and databases to generate a regulatory map for a chosen target hub. We then show how a kinetic model can be derived from the regulatory map. To validate our approach, we present a case study for p21, one of the first experimentally proved miRNA target hubs. Our analysis indicates that distinctive expression patterns for miRNAs, some of which interact cooperatively, fine-tune the features of transient and long-term regulation of target genes. With respect to p21, our model successfully predicts its protein levels for nine different cellular functions. In addition, we find that high abundance of miRNAs, in combination with cooperativity, can enhance noise buffering for the transcription of target hubs.

Modeling miRNA regulation in cancer signaling systems: miR-34a regulation of the p53/Sirt1 signaling module

MicroRNAs (miRNAs) are a family of small regulatory RNAs whose function is to regulate the activity and stability of specific messenger RNA targets through posttranscriptional regulatory mechanisms. Most of the times signaling systems involving miRNA modulation are not linear pathways in which a certain transcription factor activate the expression of miRNAs that posttranscriptionally represses targeting proteins, but complex regulatory structures involving a variety of feedback-loop architectures.In this book chapter, we define, discuss, and apply a Systems Biology approach to investigate dynamical features of miRNA regulation, based on the integration of experimental evidences, hypotheses, and quantitative data through mathematical modeling. We further illustrate the approach using as case study the signaling module composed by the proteins p53, Sirt1, and the regulatory miRNA miR-34a. The model was used not only to investigate different possible designs of the silencing mechanism exerted by miR-34a on Sirt1 but also to simulate the dynamics of the system under conditions of (pathological) deregulation of its compounds.

Model-based investigation of the transcriptional activity of p53 and its feedback loop regulation via 14-3-3σ

Experiments have recently shown that p53 expression can display oscillations in response to certain stress signals. In this work, mathematical modelling and bifurcation analysis are combined to investigate under which conditions the oscillation of p53 could propagate to its direct downstream transcription targets. The authors' analysis suggests that oscillations of p53 will propagate only to proteins with medium-fast mRNA and protein turnover rates. The authors retrieved data concerning the half-life of mRNA and protein for a number of p53-promoted genes and found that, according to their model, most of them are not able to inherit the oscillation of p53 because of their slow turnover rates. However, their analysis indicates that p53 oscillation may actually fine-tune the expression pattern of a protein when it is integrated with a second oscillatory signal. The authors also consider the case of additional regulatory loops affecting p53 oscillations and involving proteins transcriptionally induced by p53. Their results for 14-3-3σ, a protein that targets the p53 inhibitor MDM2 for degradation, suggest that the addition of feedback-loop regulation may modulate basic properties of p53 oscillation and induce quick cessation of them under certain physiological conditions. Moreover, the interplay between DNA damage and 14-3-3σ may induce bistability in the oscillation of p53.

Differential expression of 14-3-3 isoforms in human alcoholic brain

BACKGROUND

Neuropathological damage as a result of chronic alcohol abuse often results in the impairment of cognitive function. The damage is particularly marked in the frontal cortex. The 14-3-3 protein family consists of 7 proteins, β, γ, ε, ζ, η, θ, and σ, encoded by 7 distinct genes. They are highly conserved molecular chaperones with roles in the regulation of metabolism, signal transduction, cell-cycle control, protein trafficking, and apoptosis. They may also play an important role in neurodegeneration in chronic alcoholism.

METHODS

We used real-time PCR to measure the expression of 14-3-3 mRNA transcripts in both the dorsolateral prefrontal cortex and motor cortex of human brains obtained at autopsy.

RESULTS

We found significantly lower 14-3-3β, γ, and θ expression in both cortical areas of alcoholics, but no difference in 14-3-3η expression, and higher expression of 14-3-3σ in both areas. Levels of 14-3-3ζ and ε transcripts were significantly lower only in alcoholic motor cortex.

CONCLUSIONS

Altered 14-3-3 expression could contribute to synaptic dysfunction and altered neurotransmission in chronic alcohol misuse by human subjects.

Bioinformatics in aging research: a workshop report

Evidence is accumulating that the first genuine antiaging interventions (e.g., approved pharmaceutical, nutriceutical, and stem-cell-based therapies) will become available within the next decades. Model organism data, next-generation sequencing, and further advances call for sophisticated large-scale data analysis. To present the state-of-the art and to talk about upcoming tasks and challenges in the bioinformatics and systems biology of aging-related data, a workshop on Bioinformatics in Ageing Research convened leading experts from Europe on May 4-5, 2010, in Rostock/Warnemünde. This meeting report summarizes talks and gives some outlook into future developments.

Integrated computational model of cell cycle and checkpoint reveals different essential roles of Aurora-A and Plk1 in mitotic entry

Understanding the regulation of mitotic entry is one of the most important goals of modern cell biology, and computational modeling of mitotic entry has been a subject of several recent studies. However, there are still many regulation mechanisms that remain poorly characterized. Two crucial aspects are how mitotic entry is controlled by its upstream regulators Aurora-A and Plk1, and how mitotic entry is coordinated with other biological events, especially G2/M checkpoint. In this context, we reconstructed a comprehensive computational model that integrates the mitotic entry network and the G2/M checkpoint system. Computational simulation of this model and subsequent experimental verification revealed that Aurora-A and Plk1 are redundant to the activation of cyclin B/Cdk1 during normal mitotic entry, but become especially important for cyclin B/Cdk1 activation during G2/M checkpoint recovery. Further analysis indicated that, in response to DNA damage, Chk1-mediated network rewiring makes cyclin B/Cdk1 more sensitive to the down-regulation of Aurora-A and Plk1. In addition, we demonstrated that concurrently targeting Aurora-A and Plk1 during G2/M checkpoint recovery achieves a synergistic effect, which suggests the combinational use of Aurora-A and Plk1 inhibitors after chemotherapy or radiotherapy. Thus, the results presented here provide novel insights into the regulation mechanism of mitotic entry and have potential value in cancer therapy.

Investigating dynamics of inhibitory and feedback loops in ERK signalling using power-law models

The investigation of the structure and dynamics of signal transduction systems through data-based mathematical models in ordinary differential equations or other paradigms has proven to be a successful approach in recent times. Extending this concept, we here analysed the use of kinetic models based on power-law terms with non-integer kinetic orders in the validation of hypotheses concerning regulatory structures in signalling systems. We integrated pre-existent biological knowledge, hypotheses and experimental quantitative data into a power-law model to validate the existence of certain regulatory loops in the Ras/Raf-1/MEK/ERK pathway, a MAPK pathway involved in the transduction of mitogenic and differentiation signals. Towards this end, samples of a human mammary epithelial cell line (MCF-10A) were used to obtain time-series data, characterising the behaviour of the system after epidermal growth factor stimulation in different scenarios of expression for the critical players of the system regarding the investigated loops (e.g., the inhibitory protein RKIP). The mathematical model was calibrated using a computational procedure that included: analysis of structural identifiability, global ranking of parameters to detect the most sensitivity ones towards the experimental setup, model calibration using global optimization methods to find the parameter values that better fit the data, and practical identifiability analysis to estimate the confidence in the estimated values for the parameters. The obtained model was used to perform computational simulations concerning the role of the investigated regulatory loops in the time response of the signalling pathway. Our findings suggest that the special regularity in the structure of the power-law terms make them suitable for a data-based validation of regulatory loops in signalling pathways. The model-based analysis performed identified RKIP as an actual inhibitor of the activation of the ERK pathway, but also suggested the existence of an intense feedback-loop control of the pathway by the activated ERK that maybe responsible for the damped oscillations we saw in the fraction of activated MEK both in the experiments and simulations. In addition, the model analysis suggested that phosphorylation/deactivation of RKIP during the transient stimulation may have a significant effect on the signalling peaks of both MEK and ERK. This later result suggests that dynamic modulation of signal inhibitors during stimulation may be a regulatory mechanism in ERK signalling and other pathways.