Cancers, one of the leading causes of death worldwide, come in many different types and forms in which uncontrolled cell growth can spread to other parts of the body. Unchecked and untreated, it can ultimately lead to death. The disease is caused by genetic or environmental changes that interfere with biological mechanisms that control cell growth. These changes, as well as normal cell activities, can be detected in tissue samples through the presence of their unique chemical indicators, such as DNA and proteins, which together are known as "markers." Specific combinations of these markers may be associated with a given type of cancer.
The pattern of markers can determine whether an individual is susceptible to developing a specific form of cancer, and may also predict the progression of the disease, helping to suggest the best treatment for a given individual. For example, two patients with the same form of cancer may have different outcomes and react differently to the same treatment due to a different genetic profile. While several markers are already known to be associated with certain cancers, there are many more to be discovered, as cancer is highly heterogeneous.
Mapping Cancer Markers
on World Community Grid aims to identify the markers associated with various types of cancer. The project is analyzing millions of data points collected from thousands of healthy and cancerous patient tissue samples. These include tissues with lung, ovarian, prostate, pancreatic and breast cancers. By comparing these different data points, researchers aim to identify patterns of markers for different cancers and correlate them with different outcomes, including responsiveness to various treatment options.
This knowledge can help researchers and physicians to:
Improve and personalize cancer treatment:
by making it possible to detect cancer earlier, identify high-risk patients, and to customize treatment based on a patient's personal genetic profile.
Accelerate cancer research and improve the overall process for identifying markers:
by refining the process of identifying markers, researchers can determine an individual patient's markers more easily, and future large sets of data can be analyzed more efficiently.