SIMBIOSYS PHENOSCOPE: A CLOUD-ENABLED, WEB-BASED PORTAL FOR RAW AND PROCESSED CANCER PHENOTYPE DATA SPANNING SCALES FROM GENOMES TO TISSUES

While genomic methods yield a plethora of information on the underlying cause and variety of cancers, genotype is only one factor contributing to the observed phenotype of a tumor. Heterogeneity among cancers and differences within individual tumors continue to challenge the efforts to develop effective therapies. A multitude of data such as single cell sequencing, digital pathology, and medical imaging are being generated that captures heterogeneity across multiple scales. However, data is siloed and connections between scales remains elusive. We propose the development of SimBioSys PhenoScope, a novel research tool to harmonize these disparate data types and provide connections between the genomic, cellular/pathway, microscopic tissue environment, and tissue scales. Combining state-of-the art machine learning, dimensionality reduction techniques, novel spatio-temporal simulation algorithms, and support for public data repositories, PhenoScope will provide a new means of assessing factors contributing to a cancer's phenotypical behavior. As an exploratory data platform, the tool will provide novel multi-scale visualizations by relying on the novel analyses between scales, that could be used by academic and pharmaceutical researchers alike to generate hypotheses for new drug targets, dosing regimens, and research targets. This technology enables researchers and clinicians to study cancer in a new light, and lead the way in to the upcoming phenomics era.