Project Summary Mantle cell lymphoma (MCL) is a rare, incurable form of non Hodgkin lymphoma which is disposed to therapeutic resistance and relapse. Though rare, MCL is both clinically and genetically heterogenous and represented by multiple subtypes. It is presently unknown how various genomic features impact the clinical course of MCL and how these biological aspects contribute to treatment resistance and disease progression. It is difficult to study the molecular features of MCL due to its rarity and lack of representation in accessible databases like the cancer genome atlas (TCGA). Additionally, it is currently challenging to integrate -omics features in precision medicine initiatives due to the vast size of data from sequencing and unclear biological and clinical relevance of singular mutational and transcriptional features. It is also difficult to study these features in combination with demographic and other relevant individual features. In the F99 phase of the proposed dissertation research project, Holly Hill will employ novel analytical and computational methods to integrate multi-omics datasets in a pooled analysis of MCL patients. These analyses will include genomics, transcriptomics, epigenomics and features of the clinical exposome. Feature selection and variable reduction techniques will be used as appropriate. These sub-analyses will identify biological correlates and generate composite variables which will be used in univariate and multivariate models to examine clinical outcomes in MCL including drug response and survival. The KOO phase of the proposed activities will include further investigations into MCL and other cancers utilizing knowledge gained from the dissertation project (F99). Insights acquired during the F99 phase will also be used to develop targeted assays that simplify the mutational or transcriptional profiles of MCL into clinically useful and valid applications. Serial -omics measurements will be integrated into correlative genomics studies and precision medicine trials which will include sequencing from liquid biopsies or circulating tumor DNA (ctDNA). The proposed efforts will produce insights into condensing and translating data from -omics studies into the clinical space. It is hoped that the findings of this study will inform methods suitable for precision medicine trials and help achieve our long-term objective to personalize therapeutics for individual cancer patients.