ABSTRACT Projects like The Cancer Genome Atlas (TCGA) have generated a tremendous amount of data characterizing the genomic events in cancer and highlighting the deep complexity and significant heterogeneity that can make precision medicine challenging. Molecular subtyping has helped to identify groups of samples with shared genomic characteristics that can be used for clinical decisions. RNA expression has played a strong role in molecular subtyping over the last twenty years. Integration of RNA expression data with other data types that are being generated as part of the Genome Data Analysis Network have improved our knowledge of tumorigenesis and separating driving events from passenger events. Our team has over a 20 year history of innovation in expression technologies, innovating across generations of assays and projects. We propose to apply our knowledge, experience, and methods to address the projects that will be addressed in this cooperative agreement including clinical trial samples from ALCHEMIST or the Clinical Trials Sequencing Program. We propose to address four specific areas of research including `expression/mRNA analysis', `Spatial genomics data analysis', `data integration', and “clinical outcomes.” We will provide 1) analysis of RNA sequencing and expression data, 2) normalization and analysis methods of spatial transcriptomics data, 3) integrative genomic approaches for cancer classification and characterization, and 4) analysis of biomarkers for association with clinical and other molecular features. We will provide our data to other GDACs and work collaboratively with them to integrate our analyses and generate data for sharing with the larger scientific community through the Genome Data Commons.