Key Personnel:
Ramana V. Davuluri (PI)
Tim Huang (Co-PI)
Hao Sun, Research Scientist
Huaxia Qin, Post doctoral Researcher
Gregory Singer, Post doctoral Researcher
Sandya Liyanarachichi, Statistics Specialist
Francisco Agosto, Ph.D Student
The goals of this Integrated Cancer Biology Program (ICBP) are to 1) increase
our understanding of complex epigenetic alterations in neoplasms and 2)
use this high-end information for improved prognosis, intervention and treatment
of female cancers.
This project involves the integration of state-of-the-art computational
and statistical support for the maintenance and management of an interactive
database. Using JavaTM technology, we have developed Genome Data
Visualization Toolkit (GDVTK), which consists of a set of data structures
and core classes. We have utilized GDVTK as a sound framework for developing
web-based applications to present genomic annotations in visual form. We
will employ GDVTK to develop a robust, flexible data management system for
the storage and query of promoter CpG islands and the associated methylation
and genetic changes, histone modifications and chromatin status in cancer
cell lines, neoplastic epithelium, and tumor stroma.
We are also developing innovative Bayesian methods to predict outcomes of
epigenetic and genetic variables. Both supervised and unsupervised classification
methods are used for data mining of experimental results. A combination
of cross-validation and permutation testing methods will hopefully result
in the creation of robust statistical models. We also provide consultation
for the analysis and reporting of microarray data and provide methods to
address problems inherent in analyzing large, complex epigenomic data sets.
Our current foci include the characterization of genes regulated by the
ER-α and TGF-β
pathways. We use computational tools to identify putative target sequences
and determine their functional relationship with local chromatin structure.
A novel microarray-based ChIP-n-chip assay has been developed to experimentally
determine whether chromatin remodeling of the predicted promoters occur
in cancerous tissue.