TY - JOUR
T1 - A strategy for predicting the chemosensitivity of human cancers and its application to drug discovery
AU - Lee, Jae K.
AU - Havaleshko, Dmytro M.
AU - Cho, Hyung Jun
AU - Weinstein, John N.
AU - Kaldjian, Eric P.
AU - Karpovich, John
AU - Grimshaw, Andrew
AU - Theodorescu, Dan
PY - 2007/8/7
Y1 - 2007/8/7
N2 - The U.S. National Cancer Institute has used a panel of 60 diverse human cancer cell lines (the NCI-60) to screen > 100,000 chemical compounds for anticancer activity. However, not all important cancer types are included in the panel, nor are drug responses of the panel predictive of clinical efficacy in patients. We asked, therefore, whether it would be possible to extrapolate from that rich database (or analogous ones from other drug screens) to predict activity in cell types not included or, for that matter, clinical responses in patients with tumors. We address that challenge by developing and applying an algorithm we term "coexpression extrapolation" (COXEN). COXEN uses expression microarray data as a Rosetta Stone for translating from drug activities in the NCI-60 to drug activities in any other cell panel or set of clinical tumors. Here, we show that COXEN can accurately predict drug sensitivity of bladder cancer cell lines and clinical responses of breast cancer patients treated with commonly used chemotherapeutic drugs. Furthermore, we used COXEN for in silico screening of 45,545 compounds and identify an agent with activity against human bladder cancer.
AB - The U.S. National Cancer Institute has used a panel of 60 diverse human cancer cell lines (the NCI-60) to screen > 100,000 chemical compounds for anticancer activity. However, not all important cancer types are included in the panel, nor are drug responses of the panel predictive of clinical efficacy in patients. We asked, therefore, whether it would be possible to extrapolate from that rich database (or analogous ones from other drug screens) to predict activity in cell types not included or, for that matter, clinical responses in patients with tumors. We address that challenge by developing and applying an algorithm we term "coexpression extrapolation" (COXEN). COXEN uses expression microarray data as a Rosetta Stone for translating from drug activities in the NCI-60 to drug activities in any other cell panel or set of clinical tumors. Here, we show that COXEN can accurately predict drug sensitivity of bladder cancer cell lines and clinical responses of breast cancer patients treated with commonly used chemotherapeutic drugs. Furthermore, we used COXEN for in silico screening of 45,545 compounds and identify an agent with activity against human bladder cancer.
KW - Bladder neoplasms
KW - Breast neoplasms
KW - Coexpression extrapolation
KW - Microarray expression profiling
KW - NCI-60 anticancer compound screening
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U2 - 10.1073/pnas.0610292104
DO - 10.1073/pnas.0610292104
M3 - Article
C2 - 17666531
AN - SCOPUS:34548799629
SN - 0027-8424
VL - 104
SP - 13086
EP - 13091
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 32
ER -