Project description:This clinical trial studies the effectiveness of a web-based cancer education tool called Helping Oncology Patients Explore Genomics (HOPE-Genomics) in improving patient knowledge of personal genomic testing results and cancer and genomics in general. HOPE-Genomics is a web-based education tool that teaches cancer/leukemia patients, and patients who may be at high-risk for developing cancer, about genomic testing and provide patients with information about their own genomic test results. The HOPE-Genomics tool may improve patient’s genomic knowledge and quality of patient-centered care. In addition, it may also improve education and care quality for future patients.
Project description:A diallel including reciprocals but not selfs experiment. Keywords: Agilent microarray, sexual dimorphism, genetical genomics, genetic variation
Project description:Genomic sequencing of many thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for proliferation or survival in hundreds of cancer cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, it is likely that there exist many undiscovered tumor specific genetic dependencies, such as prostate cancer specific drivers, that represent drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated publicly available pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data revealed two known prostate cancer specific driver genes, AR and HOXB13, as the top two hits and also nominated a number of unexpected genes. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome.
Project description:An overall goal of functional genomics has been to measure the impact of variants on molecular endophenotypes (e.g. gene expression levels or the degree of TF binding) and relate this to organismal traits and disease phenotypes. However, all the experiments to date have been described relative to a generic reference genome, significantly hobbling their interpretation. Here, we describe a strategy for finding significant relationships between disease variation and genomic annotation via personal functional genomics, by performing personal genome sequencing and paired functional genomics experiments, on the same individual.
