By processing the data into effective fold profiles, with the expression levels factored by the average level over the experimental series and defined over a non redundant gene list, we can directly Wortmannin DNA-PK compare transcriptional profiles from arbitrary sources. The fundamental principal underly ing the utility of this approach is that biological effects can be compared through the corresponding transcriptional changes. This idea underlies the CMAP initiative for matching drug to phenotype by querying a database of drug induced transcriptional profiles with a profile defining the phenotype. We have extended this methodology to include potentially all available transcriptional data. In its current version SPIED contains transcriptional profiles for 106,101 arrays covering five platform architectures and three species.

This can be easily extended to include other platforms and species. The results largely confirm the hypothesis that high scoring correlations correspond to similar biological processes. We have presented SPIED results for drug perturbagen induced profile queries and queries derived from disease states. For brevity we focussed on three sets of drug treatment profiles corresponding to mTOR/PI3K, estrogen and HDAC inhibitors. SPIED searches with these queries showed correlations with other drug treatments belonging to the same classes and in the case of the mTOR antagonist rapamycin we found high anti correlations with the profile of a cancer inducing fusion transformation, suggesting a novel indication for rapamycin.

Also, for brevity of exposition we focussed on two completely unrelated classes of pathology cancer and neurodegeneration. In the case of leukaemia we show that a corticosteroid resistance signature derived from leukae mia cell cultures shows significant correlation with a lung cancer predisposition profile and a pancreatic cancer pro file. Thereby implicating glucocorticoid resistance in these two pathologies. To illustrate the application of SPIED to neurodegenerative pathology we constructed a severe stage AD profile from a published study. Interestingly, querying SPIED resulted in high correlations with other neuropatho logical conditions indicating a common feature of synaptic loss and mitochondrial dysfunction. Restricting our searches to the rodent subset of SPIED returned expression profiles from animal models of neurodegeneration and neuronal injury.

Combining the human and rodent signa tures we obtained a core signature that we probed against CMAP for neuroprotective agents. Remarkably, we found at least 9 neuroprotective agents in the top 22 anti corre lating CMAP hits. These results Anacetrapib motivate the extension of SPIED and the extension of the CMAP to include other cell types, for example a neuronal cell lineage will be more appropriate for generating drug profiles for neurological diseases.