Purpose: Currently, there are only a few software tools designed to assist physicians to translate molecular abnormalities in the cancer genome into potential treatment options. There is a pressing need to develop software to reliably identify known targeted therapies and experimental treatments for patients on the basis of the results of tumor DNA sequencing.
Methods: The TQuest platform includes a data layer, data acquisition layer, search engine, and user interface. It identifies associations between one or more molecular targets and therapeutic options. The data layer consists of indexed interventional clinical trials and an expert-curated database of clinically or experimentally validated associations between mutations and drug response. The data acquisition layer includes an information-harvesting module that keeps an up-to-date full-text index of clinical trials by crawling clinicaltrials.gov and combining it with US Food and Drug Administration label data. The user interface is a Web-based module that allows users to upload genomic variants, tumor morphology, and diagnosis. The search results are qualified and ranked by a relevance score.
Results: We have manually curated information for 368 distinct genomic variants of 162 gene targets corresponding to 863 drug and target interactions. The platform currently contains a full-text index of approximately 80,000 interventional clinical trials. We applied TQuest to molecular data from 73 metastatic breast cancers. TQuest identified a total of 276 drugs as potential therapeutic options, ranging from one to 103 per patient.
Conclusion: TQuest correctly identified all US Food and Drug Administration-approved drugs and routine indications for all cases and also identified many additional drugs that were used in the context of a given molecular abnormality in various clinical trials. The prototype Web application is available at www.tquest.us , and the source code is open and available on GitHub.