An emerging theme in our current understanding of human oncogenesis is that cancers arise as mutations and epigenetic alterations accumulate in individual cells. The ultimate consequence of such changes is to alter the expression profile of the genome. Knowledge of the identity and function of genes whose expression is altered in particular types of cancer, would enable the correlation of specific genes and pathways to unique cancer induced phenotypes. This information would help our understanding of cancer biology and would provide new biomarkers for cancer detection as well as novel gene targets for therapeutic strategies. Thus, a high priority of current cancer research is to reveal the molecular variations that distinguish cancer cells from wild type and to determine the function of the affected genes. Of the possible genes whose altered expression may mark the molecular signature of cancer, primary candidates include those that encode proteins that function to regulate the expression of the genome and catalyze its replication and repair, collectively referred to as nucleic acid binding proteins (NBPs). Maintaining the integrity of the genome and regulating its appropriate expression are important first tier intracellular processes that must be controlled. Since genetic diseases such as cancer can result from alterations in the genome which ultimately change the expression profile of genes that function in nucleic acid house keeping and regulatory functions, our first goal, in the R21 phase of this proposal, is to examine the feasibility of developing a functional genomics technology aimed at identifying human genes selected by their ability to encode proteins that bind to DNA and/or RNA. Several additional components of the technology will be addressed in the R33 expanded development phase of the proposal. One encompasses a novel sorting phase that will rapidly distinguish between different classes of NBPs according to their (encoded) binding properties for particular nucleic acids types and conformations. We will also develop bioinformatic tools that can be used in both virtual and microarray based expression profiling to sample whether the expression of selected genes or gene clusters is altered in normal versus specific cancer cells. When developed, this new technology will enable the functional identification, categorization and expression profiling of genes that act to maintain and regulate the genome. It will directly improve the quality of data in the Cancer Genome Anatomy Project (CGAP) and it will likely identify new genes that confer a predisposition for cancer when their relative expression within a cell is altered. Such technology does not presently exist.
