MLGNAPDec 30, 2013

Identification of structural features in chemicals associated with cancer drug response: A systematic data-driven analysis

arXiv:1312.7734v242 citations
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This work addresses the need for integrated analysis of drug structure and biological response in cancer research, though it is incremental as it extends an existing method (Group Factor Analysis) to a new dataset.

The study tackled the problem of linking drug chemical structures to genome-wide gene expression responses across multiple cancer cell lines, identifying 11 components that connect structural descriptors with specific gene expression patterns and uncovering novel associations such as similarities between 15-delta prostaglandin J2 and HSP90 inhibitors.

Motivation: Analysis of relationships of drug structure to biological response is key to understanding off-target and unexpected drug effects, and for developing hypotheses on how to tailor drug thera-pies. New methods are required for integrated analyses of a large number of chemical features of drugs against the corresponding genome-wide responses of multiple cell models. Results: In this paper, we present the first comprehensive multi-set analysis on how the chemical structure of drugs impacts on ge-nome-wide gene expression across several cancer cell lines (CMap database). The task is formulated as searching for drug response components across multiple cancers to reveal shared effects of drugs and the chemical features that may be responsible. The com-ponents can be computed with an extension of a very recent ap-proach called Group Factor Analysis (GFA). We identify 11 compo-nents that link the structural descriptors of drugs with specific gene expression responses observed in the three cell lines, and identify structural groups that may be responsible for the responses. Our method quantitatively outperforms the limited earlier studies on CMap and identifies both the previously reported associations and several interesting novel findings, by taking into account multiple cell lines and advanced 3D structural descriptors. The novel observations include: previously unknown similarities in the effects induced by 15-delta prostaglandin J2 and HSP90 inhibitors, which are linked to the 3D descriptors of the drugs; and the induction by simvastatin of leukemia-specific anti-inflammatory response, resem-bling the effects of corticosteroids.

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