COXEN Version 1.0

Category Genomics>Gene Expression Analysis/Profiling/Tools

Abstract COXEN (COeXpression ExtrapolatioN) is an in silico algorithm that computationally predicts the effectiveness of chemotherapeutic agents for individual cancer cells or tumor samples, based on their genomic expression profiling information (see Note 1).

This website (software service) allows a registered researcher to obtain COXEN chemo-sensitivity prediction results for either cancer cells or patient tumor samples for most FDA-approved anti-cancer compounds.

What COXEN does -- COXEN provides the prediction probabilities on which chemotherapeutic agents should be effective for the treatment of individual cancerous tumors, based on gene expression profiles of the tumor samples.

The manufacturer provides a prediction value for each chip, which will eventually bring individualized chemotherapy one step forward.

The current COXEN prediction on most compounds, however, is a suggestive guideline ONLY for testing on experimental systems such as cancer cell lines and animal models.

How COXEN works -- Using statistical techniques, the manufacturer examines gene expression intensity values for the NCI-60 cancer cell lines, for which drug response information, in the form of GI50 data, is available, to determine which genes are associated with drug sensitivity.

Next, the manufacturer determines which of these genes are co- expressed in a set of cancer samples generating a probability of response.

The COXEN algorithm is composed of six (6) distinct steps (see below). The end result is what the manufacturer terms the "COXEN score", which reflects the predicted sensitivity of a particular cell line or human tumor to the specific drug being evaluated by the algorithm.

Generically, the steps for prediction of a drug's activity in cells belonging to some set 2 on the basis of its activity pattern in different cells of some set 1 are as follows:

Step 1) Experimentally determine the drug's pattern of activity in cells of set 1.

Step 2) Experimentally measure molecular characteristics of the cells in set 1.

Step 3) Select a subset of these molecular characteristics that most accurately predicts the drug's activity in cell set 1 ("chemo-sensitivity signature" selection).

Step 4) Experimentally measure the same molecular characteristics of the cells in set 2.

Step 5) Among the molecular characteristics selected in step 3, identify a subset that allows a strong pattern of co-expression extrapolation between cell sets 1 and 2.

Step 6) Use a 'multivariate algorithm' to predict the drug's activity in set 2 cells on the basis of the drug's activity pattern in set 1 and the molecular characteristics of set 2 selected in step 5. The output of the multivariate analysis is a COXEN score.

Note 1: More detailed information is available in the article by Lee et al., "A strategy for predicting the chemo-sensitivity of human cancers and its application to drug discovery", PNAS August 7, 2007 vol. 104 no. 32 13086-13091 located here.

What drugs COXEN provides predictions for -- The manufacturer can generate predictions for many compounds (contact the manufacturer via their web-site for a current list of these compounds). This ability is based on the robust availability of NCI-60 panel dose response information on these compounds.

Many other interesting compounds (i.e. Imatinib Mesylate / Gleevec) do Not have such information available to the manufacturer and thus canNot be predicted.

However, the manufacturer has the ability to use and provide predictions from any cell line panel, thus, if investigators have dose response data for their compound of interest on their own cell panel, the manufacturer would be glad to work with them and provide COXEN predictions for their agents.

What cancer types COXEN provides predictions for -- Currently, breast and bladder cancer, but the manufacturer plans on expanding this shortly.

As this service depends on the public availability of microarray data sets for different cancer types, the manufacturer strongly encourages users to make their cancer-related microarray datasets publicly available by contributing them to Gene Expression Omnibus (GEO) (see G6G Abstract Number 20013) or to other public databases.

In the meantime, if you would like to analyze microarray data from a different type of cancer, you may simply define them as breast or bladder cancer.

The prediction results for some compounds may hold for certain types of cancer since they may share common chemo-sensitivity with bladder and breast cancer.

However, the manufacturer warns that the fidelity of such COXEN predictions can be significantly lower without the correct designation of cancer type.

Note 2: COXEN algorithm results are provided at No cost for use in non- profit research only. This site and results made available through it are to be used only for 'in vitro research' or for retrospective studies.

"Retrospective" means that the genomic and chemotherapy outcomes data you use must be in existence at the time of the protocol submission to your IRB. You should consult your institutional IRB if you plan to use COXEN prediction results in research.

COXEN prediction results must Not be used prospectively to determine the choice of drugs to treat human patients.

System Requirements

Contact manufacturer.

Manufacturer

Manufacturer Web Site COXEN

Price COXEN algorithm results are provided at No cost for use in non-profit research only. This site and results made available through it are to be used only for in vitro research or for retrospective studies.

G6G Abstract Number 20223

G6G Manufacturer Number 102861