Kreeger:Research

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===Signaling Network Cross-Talk in Ovarian Cancer===
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'''Signaling Network Cross-Talk in Ovarian Cancer'''
Ovarian cancer is the 5th leading cause of cancer death in women. The high mortality rate is primarily due to the late stage at which ovarian cancer is typically found.  Patients accumulate different mutations in their tumors during disease progression, making it impossible to define a blanket treatment for everyone.  We are working to characterize a panel of ovarian cancer cell lines to capture this diversity and determine how cells respond to current drugs. By delineating molecular signatures that correspond to drug sensitivities we hope to better match patients to drugs and improve prognosis.  Additionally, our models will attempt to reconstruct the cross-talk between various pathways in the cell.  These models will be examined to determine signals that are most responsible for controlling proliferation, providing potential drug targets.
Ovarian cancer is the 5th leading cause of cancer death in women. The high mortality rate is primarily due to the late stage at which ovarian cancer is typically found.  Patients accumulate different mutations in their tumors during disease progression, making it impossible to define a blanket treatment for everyone.  We are working to characterize a panel of ovarian cancer cell lines to capture this diversity and determine how cells respond to current drugs. By delineating molecular signatures that correspond to drug sensitivities we hope to better match patients to drugs and improve prognosis.  Additionally, our models will attempt to reconstruct the cross-talk between various pathways in the cell.  These models will be examined to determine signals that are most responsible for controlling proliferation, providing potential drug targets.

Revision as of 11:47, 9 April 2009

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Signaling Network Cross-Talk in Ovarian Cancer

Ovarian cancer is the 5th leading cause of cancer death in women. The high mortality rate is primarily due to the late stage at which ovarian cancer is typically found. Patients accumulate different mutations in their tumors during disease progression, making it impossible to define a blanket treatment for everyone. We are working to characterize a panel of ovarian cancer cell lines to capture this diversity and determine how cells respond to current drugs. By delineating molecular signatures that correspond to drug sensitivities we hope to better match patients to drugs and improve prognosis. Additionally, our models will attempt to reconstruct the cross-talk between various pathways in the cell. These models will be examined to determine signals that are most responsible for controlling proliferation, providing potential drug targets.
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