TY - JOUR T1 - Abstract 775: Combinatorial compound stratification based on integration of LINCS, TCGA and PubChem data JF - Cancer Research JO - Cancer Res SP - 775 LP - 775 DO - 10.1158/1538-7445.AM2016-775 VL - 76 IS - 14 Supplement AU - Stathias, Vasileios AU - Allen, Bryce AU - Clarke, Jennifer AU - Ayad, Nagi G. AU - Schürer, Stephan Y1 - 2016/07/15 UR - http://cancerres.aacrjournals.org/content/76/14_Supplement/775.abstract N2 - Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LAThe purpose of this study is to leverage the large number of perturbation signatures from the NIH Library of Integrative Network-based Cellular Signatures (LINCS) and integrate them with patient data from The Cancer Genome Atlas (TCGA) and PubChem bioactivity data in an effort to prioritize compounds based on their synergistic effect in cancer treatment.From the large number of LINCS L1000 transcriptional data capturing cellular responses after chemical or genetic perturbations, we extracted gene expression signatures that were indicative of specific LINCS compounds. Moreover, we compared the L1000 transcriptional profiles with ones from TCGA in order to identify characteristic signatures of major cancer types and prioritized small molecule compounds with discordant expression profiles to those cancer types. We then linked the above compounds to protein target annotations and therefore produced a compound-specific protein target profile. For this, we utilized biochemical data produced by the LINCS KinomeScan and KiNative assays and also biochemical data obtained through PubChem. Using the above information, we obtained pairs of compounds that would inhibit unlinked gene sub-networks that were produced through processing of the TCGA transcriptional data.The above process can be used as a means to suggest compound combinations towards specific cancer types and to prioritize the development of compounds with targeted polypharmacology.Citation Format: Vasileios Stathias, Bryce Allen, Jennifer Clarke, Nagi G. Ayad, Stephan Schürer. Combinatorial compound stratification based on integration of LINCS, TCGA and PubChem data. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 775. ER -