- StatEpigen - a novel biomedical resource on the molecular determinants of cancer development
- Microscopic models to simulate epigenetic mechanisms in cancer initiation
- Computational model of epigenetic mechanisms to identify the risk for gastric cancer
- Computational micro-model for epigenetic mechanisms
StatEpigen, a Novel Knowledge Management System on Genetic/Epigenetic Molecular Determinants of Cancer Development: epigenetic data annotation, data base and data-mining facilities
Postdoctoral Researcher: Dr. Ana BARAT, Intern Students: Jyoti PORWAL and Mathieu ANDRE, MSc Researcher: Kabita Shakya
In cooperation with EMBL-EBI, Hinxton, UK, Funding: IRCSET, UDRC Sci-Sym
To see Ana's poster presented at the XX Conference of Genetics in July 2008, and at Sci-Sym first meeting, please follow the link: Ana Barat POSTER 08.
Epigenetic modifications are modifications of the DNA which do not involve the DNA sequence, but rather its structure. The importance of epigenetic studies includes both understanding the intrinsic mechanisms involved, and their relation to other crucial events in the cell, such as abnormal gene expression and mutation. Abnormal epigenetic behaviour has been shown to correlate with diseases, such as cancers and neuropsychiatric disorders. As epigenetic research gains momentum, biologists need new ways to access and analyse information on epigenetic-genetic interactions and their quantitative characteristic indices. While a few databases on epigenetic phenomena exist, these do not support relation of molecular events to the dynamics of the respective pathologies in recognised data-mining formats.
A first specific aim of our work is thus improved database and data-mining provision, with a view to providing direct access to those data, required to facilitate development of models at the molecular level. A novel and highly specific resource – StatEpigen – concentrates on combining dispersed information, with particular focus on correlation of annotated epigenetic information for a number of different cancer phenotypes. StatEpigen is designed to serve as a model driver, permitting identification of unique profiles corresponding to different cancer development stages. By uniting information on epigenetic-genetic events in its records, PathEpigen capitalises on their individual strengths, producing a more powerful diagnostic tool. At this moment in type, we have fully annotated the epigenomics of colon cancer, and we keep an eye on the new references. The platform will soon be made available online. Nevertheless, we are keen to annotate other pathologies, and we are looking forward to enlarge our team in order to perform the work related to it.
Here we would like to acknowledge Ubaldo Colmenar, MEng, who has volunteered to work together with us on the development of our user interface.
To see StatEpigen: http://statepigen.sci-sym.dcu.ie
Microscopic models to simulate epigenetic mechanisms
Postdoctoral Researcher: Dr. Dimitri PERRIN, Intern Students: Francois GOASMAT and Jyoti PORWAL
To see Jyoti's poster presented at the XX Conference of Genetics in July 2008, please follow the link: Jyoti Porwal POSTER 08.
Project description: Epigenetics involve heritable changes in appearance (phenotypes) or gene expressions caused by mechanisms other than changes in the underlying DNA sequence i.e. epi - "in addition to" -genetics. These changes may remain through cell division for the remainder of the cell's life and may also last for multiple generations. It involves heritable alterations in chromatin structure, in turn regulating gene expression, but not involving changes in DNA sequence. These stable alterations in gene expression arise during development and cell proliferation and persist through cell division. There are a number of important mechanisms of epigenetic inheritance, but probably the best example of stable epigenetic phenomena is DNA methylation, with changes closely related to progress of cancer disease.
As part of our multi-approach work on epigenetic mechanisms, we focus, here, on a microscopic model at the cell and cell component level.
Model objectives include:
- implementation of the chromatin structures, (nucleosomes, histones, DNA strand, etc.), as C++ classes;
- dynamic nucleosome positioning along DNA strands;
- implementation of epigenetic changes at the microscopic level, and interactions between the changes;
- definition of gene expression as a "function" of the epigenetic status.
Data from PathEpigen will be used to calibrate and validate this model.
Computational model of epigenetic mechanisms to identify the risk for gastric cancer
Postdoctoral Researcher: Dr. Dimitri PERRIN
Project Description: As a proof of concept for computational models of epigenetics changes, we focus, in this project, on inflection-induced epigenetic perturbations. The model and target medical condition are the result of an ongoing collaboration with the National Cancer Center Research Institute (Tokyo, Japan).
The motivation is that epigenetic alterations in non-disease tissues can be used as markers for disease risk and past exposure to some disease-including factors. In particular, current focus is on detection of aberrant DNA methlation in non-cancerous gastric mucosae, as the presence of such patterns can be used as a marker for both the risk of gastric cancers and past exposure to Helicobacter pylori.
To investigate the dynamics of infection-induced aberrant methylation in gastric crypts, we implement an object-oriented model of the entities involved.
Normal cell dynamics and infection-induced perturbations are implemented, and permit investigation of the methylation dynamics (and susceptibility) of various cell-types.
Computational micro model for epigenetic mechanisms
PhD Researcher: Karthika Raghavan
Project Description: Characterization of the epigenetic profile of humans since the initial breakthrough on the human genome project has strongly established the key role of dynamic histone modifications and stable DNA methylation, which are known to determine the normal level of expression or methylation status of the constituent genes in the genome. Recently, considerable evidence has been put forward to demonstrate that environmental stress implicitly alters epigenetic patterns causing an abnormal landscape of interaction which can lead to cancer initiation. This chain of consequences has motivated attempts to computationally model the influence of histone modification and DNA methylation in Gene expression and investigate their intrinsic interdependency. Here, a prototype model with a novel framework which can stochastically investigate the mutual influence of such epigenetic elements (dynamic histone modifications and inherent DNA methylation patterns derived through signal processing methods) is presented.