Researchers at Lawrence Berkeley National Laboratory have identified gene expression signatures that could serve as biomarkers to predict how individuals will respond to the breast cancer drugs lapatinib and CI-1040.
Their findings could help in individualizing treatments for women, and their methodologies could aid in identifying similar biomarkers for responses to other drugs and for other types of cancer.
“Individuals respond differently to different therapeutics because there are substantial differences in the spectrum of genetic, biological and epigenetic characteristics between breast cancers, although some recurrent abnormality patterns are emerging that define breast cancer subtypes” said Joe W. Gray, Ph.D., staff scientist and director of the Life Sciences Division at Lawrence Berkeley National Laboratory. “We need better ways to identify how we can best tailor existing therapies to individuals and how to target experimental agents.”
Gray and his colleagues have developed a system to evaluate drug response comprised of a panel of 50 breast cancer cell lines. Each of these cell lines represents a single variant among the different genomic abnormalities found among breast cancers. They measured molecular profiles of each cell line and used these to identify subsets of cell lines that represent the subtypes observed in analyses of primary tumors.
By correlating the responses of these cells to targeted therapeutic drugs, the researchers were able to identify the molecular characteristics of cells that were most sensitive to the drugs. They tested their approach by analyzing responses of the cell line panel to lapatinib, a duel inhibitor of EGFR and ErbB2 and CI-1040, a MEK enzyme inhibitor. These studies defined molecular signatures that predicted individual responses among the cell lines to the drugs. For Lapatinib, the strongest correlate of response was amplification and over expression of ErBB2, consistent with clinical experience. For CI-1040, changes in the MEK pathway were most strongly associated with response. Predictors based on combinations of molecular correlates of response were able to quantitatively predict individual cell line responses.
“The concordance of our markers of response to lapatinib with those observed clinically suggests that the molecular markers identified in the cell line collection can be used to guide the use and testing of other approved and experimental drugs,” Gray said. “This is important since it is logistically and financially impossible to test all of the experimental medicines in each cancer subtype. This ?systems? approach suggests a way to prioritize drugs for use in patients and for initial clinical tests.”
According to Gray, a large of number of emerging therapeutic agents should be prioritized for testing in the subtypes of breast cancer along with other cancers and their subtypes. When therapies are ineffective, they may produce harmful side effects and decrease a patient?s quality of life.