Project description:In this study, we conducted a histopathological-based analysis of 10x Genomics Visium spatial transcriptomics data on a human kidney sample corresponding as closely as possible to the reality of the interpretation of a kidney biopsy in a healthcare or research context.
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:To enable the implementation of precise genomics in a local healthcare system, we devised a pipeline for filtering and reporting of relevant genetic information to healthy individuals based on exome or genome data. In our analytical pipeline, the first tier of filtering is variant-centric, and it is based on the selection of annotated pathogenic, protective, risk factor, and drug response variants, and their one-by-one detailed evaluation. This is followed by a second-tier gene-centric deconstruction and filtering of virtual gene lists associated with diseases, and VUS-centric filtering according to ACMG pathogenicity criteria and pre-defined deleteriousness criteria. By applying this filtering protocol, we were able to provide valuable insights regarding the carrier status, pharmacogenetic profile, actionable cardiovascular and cancer predispositions, and potentially pathogenic variants of unknown significance to our patients. Our experience demonstrates that genomic profiling can be implemented into routine healthcare and provide information of medical significance.
Project description:The development of precision medicine strategies requires prior knowledge of the genetic background of the target population. However, despite the availability of data from admixed Americans within large reference population databases, we cannot use these data as a surrogate for that of the Brazilian population. This lack of transferability is mainly due to differences between ancestry proportions of Brazilian and other admixed American populations. To address the issue, a coalition of research centres created the Brazilian Initiative on Precision Medicine (BIPMed), an initiative of five Research Innovation and Dissemination Centers (RIDCs) supported by FAPESP.
