Abstract Maturation of the secondary antibody repertoire requires class‐switch recombination (CSR), which switches IgM to other immunoglobulins (Igs), and somatic hypermutation, which promotes the production of high‐affinity antibodies. Following immune response or infection within the body, activation of T cell‐dependent and T cell‐independent antigens triggers the activation of activation‐induced cytidine deaminase, initiating the CSR process. CSR has the capacity to modify the functional properties of antibodies, thereby contributing to the adaptive immune response in the organism. Ig CSR defects, characterized by an abnormal relative frequency of Ig isotypes, represent a rare form of primary immunodeficiency. Elucidating the molecular basis of Ig diversification is essential for a better understanding of diseases related to Ig CSR defects and could provide clues for clinical diagnosis and therapeutic approaches. Here, we review the most recent insights on the diversification of five Ig isotypes and choose several classic diseases, including hyper‐IgM syndrome, Waldenström macroglobulinemia, hyper‐IgD syndrome, selective IgA deficiency, hyper‐IgE syndrome, multiple myeloma, and Burkitt lymphoma, to illustrate the mechanism of Ig CSR deficiency. The investigation into the underlying mechanism of Ig CSR holds significant potential for the advancement of increasingly precise diagnostic and therapeutic approaches.
Abstract 1177: Introduction of the GA4GH Variation Representation Specification (VRS) and supporting tools for discovery and exchange of clinical genomic and cytogenomic knowledge in cancers
Abstract Precision oncology is the practice of interpreting the clinical significance of observed molecular changes in patient neoplasms, potentially impacting medical decision making and care. This process is labor-intensive and (among other challenges) involves accurately translating between variation representation conventions from one resource to the next. For example, differences in representations of Copy Number Variation (CNV) from genomic regions, cytogenomic bands, or gene features create challenges in knowledge matching due to lack of standards covering all of these modalities of observed variation.The Global Alliance for Genomics and Health (GA4GH; ga4gh.org) is an international collaborative of genomic data sharing initiatives (Driver Projects) developing genomic data sharing standards within a human rights framework. GA4GH recently published the Variation Representation Specification (VRS; pronounced “verse”), a standard for the computational representation of biomolecular variation. VRS is a terminology, schema, and associated conventions for creating uniquely identifiable and federatable representations of molecular variation. VRS has formal data classes well-suited to differentiating between variation on a single molecule (e.g. tandem duplications) from variation measured at a systemic level (e.g. genome-wide copy number variation). In addition to molecular sequence variation, VRS also supports variation on cytogenetic coordinate systems and genes, making it well-suited to representing variation associated with cancer biomarkers.We demonstrate the use of VRS to model reported gene-associated CNVs from the AACR Project GENIE cohort, to aid in the computational discovery of evidence from clinico-genomic knowledgebases with genomic or cytogenomic CNV representations. We highlight the use case of knowledge matching to the Atlas of Genetics and Cytogenetics in Oncology and Haematology (“the Atlas”; atlasgeneticsoncology.org), a cytogenetics resource historically driven by user website navigation. Using VRS search tools we developed for the Variant Interpretation for Cancer Consortium (VICC; cancervariants.org) GA4GH Driver Project, we found that 64% of GENIE samples with reported CNVs matched clinically relevant knowledge in the Atlas. This work was enabled by programmatic search tools leveraging standard VRS object structures, demonstrating how VRS enables collection of real-world evidence across more resources without manual interpretation or custom normalization methods. We conclude with a survey of open-source tools supporting this analysis as well as search of other clinico-genomic knowledgebases with VRS, including CIViC (civicdb.org), BRCA Exchange (brcaexchange.org), and the Molecular Oncology Almanac (moalmanac.org). Citation Format: Matthew Cannon, Kori Kuzma, James Stevenson, Jiachen Liu, Colin O'Sullivan, Bimal P. Chaudhari, Matthew Brush, Robert R. Freimuth, Tristan Nelson, Michael Baudis, Obi L. Griffith, Malachi Griffith, Lawrence Babb, Melissa S. Cline, Xuelu Liu, Brian Walsh, Alex H. Wagner. Introduction of the GA4GH Variation Representation Specification (VRS) and supporting tools for discovery and exchange of clinical genomic and cytogenomic knowledge in cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1177.