Data Sciences Core (Core C) Project Summary/Abstract The research proposed by the UT Lung Cancer SPORE encompasses a broad range of activities, including studies in clinically annotated patient tumor samples, tumor cell lines, xenografts, and mouse models, as well as human clinical trials. These studies generate multiple types of data, including clinical, histologic, genome-wide molecular (mutation, expression), proteomic, biochemical, immunohistochemical, drug and immune response phenotype, metabolomic, and tumor environmental. The Data Sciences Core provides comprehensive expertise to ensure the statistical integrity, data integrity, data sharing capability, and data analysis accuracy of the studies performed by the SPORE. The Core has a Director at each institution (Y. Xie, UTSW, and J. Wang, MDACC) and the flexibility to match personnel to the evolving needs of existing SPORE Projects, and Developmental Research and Career Enhancement Program (DRP, CEP) Projects. To ensure appropriate consideration of biostatistics and data management concerns throughout all SPORE work, members of this Core participate in monthly all-SPORE Project and Core meetings, and in the specific Data Sciences SPORE video/WebEx conferences linking researchers at UTSW and MDACC. The Data Sciences Core will perform the following: (a) develop and maintain systems for data storage, retrieval, analysis, and sharing; (b) provide an interface for all SPORE investigators to exchange data and information easily and freely; (c) provide analyses to allow investigators outside the UT Lung SPORE to have appropriate access to SPORE datasets, and to be able easily to independently reproduce and validate biostatistical and computational analyses. The Core services include innovative, unique, and occasionally customized approaches to solving the data analysis and interpretation challenges of the modern data-centric research laboratory. The Core Specific Aims are: Aim 1: Provide valid statistical designs for SPORE laboratory research, clinical trials and translational experiments. Aim 2: Oversee and conduct innovative statistical modeling, simulations, data analyses and data integration needed by the Projects, DRP and CEP, and Pathology Core to achieve their specific aims. Aim 3: Ensure that all complex molecular, biologic, and clinical datasets are protected for confidentiality, analyzed, shared among SPORE investigators and collaborators, and appropriately deposited into publically accessible databases as required, using valid and innovative bioinformatics methods. Aim 4: Develop and maintain a secure, web-accessible site for SPORE research data integration and storage linked to an extensive tissue repository of clinically and molecularly annotated archived patient samples, tumor grafts, tumor and normal cell lines, and relevant mouse models of lung cancer; we will also (a) develop and maintain centralized deposits from the literature of lung cancer-relevant datasets in a web site (“Lu...