PROJECT ABSTRACT Genetic information codes for life events including disease associated changes and hints for cancer treatments. A daunting task is to decode genetic information. A common approach is to investigate whether genetic changes in cancer are associated with tumorigenesis. Efforts have been devoted to identifying key gene amplification/deletion/fusion events and elucidating hot mutation-associated enzymatic changes and interactome changes. However, mutations on enzymes only account for a small portion of total mutational landscape and meanings of the majority of non-enzyme mutations remain unclear. To this end, we have developed an algorithm to mine the gain or loss of key enzyme substrate motifs targeting the understudied non-enzyme mutations from TCGA database, through which key enzyme functions can be altered. As a proof-of-principle study, using this approach we have identified 1,792 mutations in cancer that a new motif for the AGC kinases is lost. These mutations are more enriched in colon and esophageal carcinoma to more likely affect cellular signaling pathways. More importantly, we validated that one hit, BUD13, upon mutation can bypass its phosphorylation by one AGC kinase GRK6, through which these cancerous BUD13 mutations deficient in phosphorylation gain oncogenicity to promote colon cancer growth through elevating the mTORC1 signaling. In this proposal, we will systematically identify the first mutational landscape for all characterized enzyme motifs and further validate important hits using an experimental pipeline that we have expertise on. We will also examine new therapeutic directions associated with both WT- and mutant-BUD13 expressing colon cancer in both in vitro cell culture models and in vivo preclinical animal models. We hope that our study will provide novel insights for mutations cancer hijacks to promote tumorigenesis with the potential for patient stratification and cancer treatment.