What are the potential benefits of the Mapping Cancer Markers project?
The project has three goals:
Identify sets of markers that may be able to predict if a person is at high risk of developing a particular cancer and increase the possibility of early detection.
Identify combinations of markers, which may predict a patient’s response to specific treatments. This would help make the treatment more personalized and could guide the development of customized therapeutic treatments for that patient.
Develop more efficient computational methods for discovering relevant patterns of markers.
Is the Mapping Cancer Markers project similar to the Help Conquer Cancer project?
Although both projects relate to cancer research, the Help Conquer Cancer project (run on World Community Grid from 2007-2013) focused on basic science - discovering principles of protein crystallization and helping to determine 3D structure of over 15,000 proteins. Knowing the protein structure helps scientists to understand their function and design drugs that may provide novel treatment options for multiple complex diseases, such as cancer.
The Mapping Cancer Markers project focuses on clinical application - discovering specific groups of markers that can be used to improve detection, diagnosis, prognosis and treatment of cancer. As a second goal, the comprehensive analysis of existing molecular profiles of cancer samples will lead to unraveling characteristics of such groups of markers - and in turn improving our understanding how to find them more efficiently.
What kinds of cancers are being studied in the Mapping Cancer Markers project?
Initially, we will focus on lung and ovarian cancer, followed by prostate, pancreatic and breast cancers. However, the project has been designed to accommodate other, less well-studied cancers if sufficient patient data exists.
What will happen with the data generated by all these calculations?
After the scientists have received all of the computed results for the project, they will analyze the data and publish their findings. The raw data and algorithms will be made publicly available at that time.
Some Mapping Cancer Markers jobs take longer to run than others. Why?
Each Mapping Cancer Markers task performs a search of multiple combinations of potential cancer biomarkers, representing a piece of a larger search strategy. It is difficult to split this extensive search into perfectly uniform pieces. Additionally, the machine-learning algorithms used to evaluate each combination of markers can take a variable amount of computing time to arrive at an answer. Together, these two factors make the run times of Mapping Cancer Markers tasks variable.
The researchers will publish an open-access database of the protein sequence comparisons computed on World Community Grid.
We expect that this information will help scientists discover new enzymatic functions, find how organisms interact with each other and the environment, document the current baseline microbial diversity, and better understand and model complex microbial systems.