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Available Technologies: Medical and Biotechnology
Diagnostics & Assays
COXEN- In Silico Prediction of Chemotherapeutic Response
Dan Theodorescu and Jae Lee
COXEN is a novel methodology to predict the efficacy of a chemotherapeutic agent. The technique can be utilized for drug discovery or in diagnostic applications.
The use of large gene expression arrays has enabled scientists to define cells on their molecular signature. The grouping of cells according to these signatures is often referred to as clustering. The power of the COXEN methodology eliminates irrelevant similarities between samples, and enables clustering of samples (tumor biopsies, cell lines) according to their predicted response to a certain drug rather than other characteristics such as organ of origin. COXEN enables studies made on one tumor type to be extrapolated to all other tumor types and enables the prediction of clinical outcome based on in vitro data.
To demonstrate the power of the COXEN methodology in drug discovery applications specific sensitivity markers were identified for a large set of drugs to a panel of 60 cell lines (the NCI-60 public data set). There are no bladder tumors on that data set. By comparing bladder carcinoma expression profiles, and drug sensitivity profiles, a drug candidate with high potency against bladder carcinoma cells was identified. Through the elimination of irrelevant clustering between the NCI-60 cell lines the identification of the different drugs sensitivity profile was enabled. For one drug, this profile was highly prevalent in bladder cancer cell lines. Initial in vitro data indicates that this particular compound has a better response rate on bladder cancer cells than any other drug currently in use, including Cisplatin. At the same time the drug showed poor overall performance on the NCI-60 data set, and none of the nine tumor types represented in the NCI-60 panel responded as well as the bladder tumor cell lines. To enable the extrapolation of one tumor specific study to other tumor types could prove to be extremely valuable for drug development efforts.
COXEN can also be used to extrapolate in vitro generated toxicity data to predict patient outcome, given the expression profile of the patient’s tumor is known. As these profiles are rather small (4-7 genes) diagnostics could potentially be streamlined. The use of COXEN as a diagnostic tool has been convincingly demonstrated on two clinical studies.
The same inventors have recently developed a related methodology that accurately predicts the combinatorial effectiveness of two or more unrelated drugs from in vitro single drug sensitivity experiments. That methodology have been published in Molecular Cancer Therapeutics in February (6(2):578-86) with the title “Prediction of drug combination chemosensitivity in human bladder cancer” and is also currently available for world wide licensing.
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