Defining the gene regulatory networks that control the cellular behavior under genetic perturbations underlying cancer not only provides a better understanding of the cancer biology but has the potential to provide new targets for cancer therapy as well as candidates for cancer biomarker discovery. Transcription factors are the end receivers of the environmental signals carried through signal transduction pathways, and the initial core of interactive networks that regulate the expression of genes (the nodes). Hence, accurate understanding of transcription regulation in cancer cells is an essential step towards building biological models that define the cancer system. Transcription factors regulate the gene expression individually or with other proteins in an assembly called a regulatory complex. These complexes are dynamic structures that change constantly in response to environmental stimuli. The limitations hindering the elucidation of transcription regulation are twofold: 1) detecting low abundance transcription factors and 2) determining the dynamic stoichiometry of regulatory complexes that require quantification of the low abundance transcription factors.
SRM mass spectrometry has improved our ability to detect and quantify low abundance proteins significantly and has the potential to transform proteomics into an ideal data acquisition platform for systems biology. The advantages of SRM stem from its continuous, selective scanning mode that provides supreme sensitivity and selectivity. The quantitative nature of SRM also guarantees accurate quantification of the low abundance proteins required for biological model building. The principle is to use a DNA probe to hybridize to a specific chromatin locus and isolate it together with all associated proteins, which are then identified by mass spectrometry. The bottleneck in this approach is the detection limit of shotgun mass spectrometry which we will overcome by using highly sensitive SRM technology.
Ubiquitination is a post-translational modification that plays an important role in many cellular processes. Proteins can be both mono- or poly-ubiquitinated. Polyubiquitin chains vary in the number of ubiquitin monomers and the way they are connected. Different polyubiquitin structures are thought to specify different fates for the target protein but the correlation between polyubiquitin structures and their specific cellular function(s) is not well understood. The ubiquitin-proteasome pathway plays a crucial role in the degradation of short-lived and regulatory proteins involved in various cellular processes such as regulation of the cell cycle, modulation of cell surface receptors and ion channels, and antigen presentation. The pathway involves an enzymatic cascade through which multiple ubiquitin molecules are covalently attached to the protein substrate, which is then degraded by the 26S proteasome complex. The pathway has been implicated in several forms of malignancy. There are other ubiquitin-dependent mechanisms that play a role in tumor progression. Increased rate of protein synthesis is often required to support the transforming events that contribute to tumor progression. The role that ubiquitin plays in ribosome biogenesis and ribosome stress response is another example of the involvement of ubiquitin related processes in cancer biology.
The first step towards gaining a comprehensive view of the role that ubiquitin plays in cancer biology is defining the ubiquitinome referred to as the subset of proteins ubiquitinated in cell. Only then one can begin to look for changes in ubiquitination pattern that is diagnostic of cancer or can provide novel targets for cancer therapy. The previous attempts in defining the ubiquitinome have been futile due to lack of specificity and high rate of false positives. These attempts that are all mainly based on shotgun identification of immunopurified proteins have failed due to their lack of ability to detect the sites of ubiquitination that would confirm the ubiquitination status of detected proteins. The first step in this project is to generate a confident list of ubiquitinated proteins isolated from cell lines using advanced separation and mass spectrometry techniques such as SRM. The next aim of this project is to identify the substrates targeted by specific E3 ubiquitin ligases. The E3 ligases provide substrate selectivity. Functional relationship between the Cullin family of proteins, the largest family of E3 ligases, and neoplastic growth has been shown. Identifying ligase specific substrates hence provides a list of potential targets for cancer therapy.