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.
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.
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.
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.
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.
Markers are specific genes (DNA segments), RNAs or proteins with differential activity. These molecules may be found in blood or tissue samples, and specific combination of these markers may be involved in a given cancer.
Even under healthy conditions, these genes, RNAs and proteins are activated and deactivated to perform specific functions. Cancer is caused by alterations to these activities. The Mapping Cancer Markers project focuses on discovering abnormal marker combinations, which may relate to cancer initiation and progression. It does so by comparing and analyzing data from many cancer patients and healthy control patients.
Extensive data mining and statistical analysis is needed to discover the subtle combinations of activity related to a cancer, and differentiate such signals from normal variation. This is done by systematically testing whether any of these combinations of markers are significantly correlated with the presence of the cancer.
Because there are thousands of possible markers, the number of their combinations becomes astronomical. Testing every combination would be impossible, even with all of the resources of World Community Grid. Various mathematical methods will therefore be used to zero in on the most likely combinations to be examined on World Community Grid.
There are several markers in clinical use. Two particular markers for breast and ovarian cancer, BRCA1 and BRCA2 recently received global attention after actress Angelina Jolie used them to assess her risk of developing the disease. In this particular case, only one marker BRCA1, in combination with family history was able to define her situation and to aid her in choosing her course of treatment.
DNA (deoxyribonucleic acid) is a long, helix shaped molecule that forms a chromosome. It acts as the master blueprint in charge of encoding genetic instructions used to develop all cells for a given organism. Specific sections of the DNA are called genes. A gene usually encodes information about how to build a particular protein molecule. RNA (ribonucleic acid) molecules are similar to DNA molecules, but are constructed from DNA information, and are used more directly to regulate and direct the machinery (other molecules) which creates proteins. The range of functions performed by these molecules is very broad and complex, and is a major subject in molecular biology. Typically, genes on the DNA (master blueprint) are “transcribed” into RNA, a process which is explained in this video. Other machinery then reads the RNA instructions and makes proteins such as hemoglobin, which is used to transport oxygen and carbon dioxide in blood.
Enzymes are proteins that convert chemicals or act as catalysts. Certain enzymes in plants, for example, can assist in the absorption of carbon dioxide molecules and incorporate them into other cellular molecules.
Microorganisms represent the great unseen and under appreciated majority of life on our planet. They are everywhere in the environment and in larger, more complex organisms. They are important for a huge variety of natural processes, including human health, agriculture and food production. For almost any kind of organic molecule, there will be a microorganism that has evolved the capacity to decompose, change, or construct it.
While your computer carries out work for the Mapping Cancer Markers project, you may see the project’s graphics either on the World Community Grid screensaver, or within the World Community Grid software.
The graphics show a representation of the 23 pairs of human chromosomes in the right hand panel. Each chromosome is a DNA molecule containing genes and other information. The 23rd chromosome pair determines sex and comprises two “X” chromosomes for females or an “X” with a “Y” chromosomes for males. Genes are located at specific points along the length of these chromosomes. As your device analyzes certain combinations of genes, the approximate locations of those sets of genes within these chromosomes are highlighted in red.
This graphically shows the approximate percentage of how far along your device is in calculating the current task. When it reaches 100%, the computation is completed and the results will then be uploaded to the servers at World Community Grid before being packaged and sent back to the research team.