Abstract Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality with significantly heterogeneous features and drug responses. Recently, the international Colorectal Cancer Subtyping Consortium identified four robust consensus molecular subtypes of CRC (CMS1-4) using large-scale gene expression data. These findings may enable us to identify molecularly homogenous subsets of CRC patients and accelerate effective drug development strategies. To identify potential therapeutic targets and novel selective vulnerabilities in CRC molecular subtypes, we developed an in vivo loss-of-function genomic screen using CRC patient-derived xenografts (PDXs) for each molecular subtype. Our PDX-derived CRC models underwent comprehensive integrated molecular characterization of mRNA profiles, DNA mutations, and histochemical profiles upon confirmed serial retransplantation to determine whether characteristics of the subtypes are recapitulated in vivo. Because the original CMS classification algorithm was trained and validated using Affymetrix data, profiling the PDX-derived cell lines using this technology provided the most robust analysis of the CMS subtypes. In vivo pooled short hairpin RNA (shRNA) screens rely on specific elimination of individual shRNAs in a cell population and require that the infected tumor cell population is adequately endowed with engraftment capacity when implanted into recipient mice. Therefore, we determined the transduction efficiency of the PDX models, the frequency of tumor-initiating cells, and the maximum library complexity allowed by each model. To identify targets that represent selective vulnerabilities in specific CRC molecular subtypes, we screened each model in vivo with an shRNA library targeting about 200 genes specifically belonging to U.S. Food and Drug Administration-approved targeted therapies (FDAome; 10 shRNAs/gene ). We leveraged redundant shRNA activity analysis to evaluate “hits” (or top-scoring genes) emerging from our screening. We further applied ranking-based analytics in combination with integromic approaches (use of computational packages to unravel relationships between -omics) to inform on selective CMS specific top-scoring genes. One of the benefits of using an FDAome library is the direct correspondence of target genes with clinically available drugs. We therefore tested these drugs for validation in fully annotated PDXs. These efforts, in association with systematic profiling of the CMS subtypes at the patient level through adaptation of NanoString technology, may enable us to stratify CRC patients who will benefit from selective U.S. Food and Drug Administration-approved drugs and to rapidly design successful preclinical and clinical trials in CRC patients. Citation Format: Akira Inoue, Bahar Salimian Rizi, Alessandro Carugo, Sahil Seth, Christopher Bristow, Giannicola Genovese, Andrea Viale, David G. Menter, Scott Kopetz, Giulio F. Draetta. Identifying selective vulnerabilities in colorectal cancer molecular subtypes using in vivo functional genomic screens abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 414. doi:10.1158/1538-7445.AM2017-414