Project

Our First Aim is to apply network based systems learning approaches to derive biological and clinically relevant information from the CPTAC proteogenomic(PG) data. We will employ novel computational tools to construct a series of molecular networks to elucidate the regulatory relationships among proteins, their PTMs and genomics alterations. We will then examine how these molecular systems change between different disease states, tumor types, or other meaningful variations among disease phenotypes. Throughout these analyses, we will carefully account for the unique properties of LC-MS based proteomics data. We will also perform Pan-cancer analyses to derive a more integrated view of the commonalities and differences across multiple tumor types.

In the past decade, our team members have developed a large number of computational/software tools for network based systems learning for PG data. These tools will effectively fuel the proposed data analyses of the CPTAC data.


In our Second Aim, we will continue the momentum in the tool development arena by developing new computational/software/web tools for analyzing CPTAC data and for visualizing/interpreting our analysis results. These tools will be made broadly accessible to the research community.


Our Third Aim is to identify protein biomarkers and drug targets for further investigation by targeted proteomics assays. We will first utilize a prediction based scoring system to identify protein biomarkers that predict altered cancer pathways, network modules and individual oncogenes; disease outcome and drug resistance; and therapeutically distinct disease subtypes. For the protein signature sets identified in this manner, we will further resolve the regulatory relationships among the genes and proteins comprising those components and identify the key regulatory drivers of those sets. These key driver proteins will then play an important role in defining the overall function of the networks, and thus serve as good biomarker and drug target candidates. Our PGDAC will also work with the Protein Candidate Selection Subcommittee to refine the CPTAC-wide candidate list for protein assay development