The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023.

BACKGROUND: Next-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic data it generates can be challenging. To address this, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology have established guidelines for standardized variant interpretation. In this manuscript, we present the updated Hospital Israelita Albert Einstein Standards for Constitutional Sequence Variants Classification, incorporating modifications from leading genetics societies and the ClinGen initiative. RESULTS: First, we standardized the scientific publications, documents, and other reliable sources for this document to ensure an evidence-based approach. Next, we defined the databases that would provide variant information for the classification process, established the terminology for molecular findings, set standards for disease-gene associations, and determined the nomenclature for classification criteria. Subsequently, we defined the general rules for variant classification and the Bayesian statistical reasoning principles to enhance this process. We also defined bioinformatics standards for automated classification. Our workgroup adhered to gene-specific rules and workflows curated by the ClinGen Variant Curation Expert Panels whenever available. Additionally, a distinct set of specifications for criteria modulation was created for cancer genes, recognizing their unique characteristics. CONCLUSIONS: The development of an internal consensus and standards for constitutional sequence variant classification, specifically adapted to the Brazilian population, further contributes to the continuous refinement of variant classification practices. The aim of these efforts from the workgroup is to enhance the reliability and uniformity of variant classification.

Generation and functional characterization of a single-chain variable fragment (scFv) of the anti-FGF2 3F12E7 monoclonal antibody.

Single-chain variable fragments (scFvs) are small-sized artificial constructs composed of the immunoglobulin heavy and light chain variable regions connected by a peptide linker. We have previously described an anti-fibroblast growth factor 2 (FGF2) immunoglobulin G (IgG) monoclonal antibody (mAb), named 3F12E7, with notable antitumor potential revealed by preclinical assays. FGF2 is a known angiogenesis-associated molecule implicated in tumor progression. In this report, we describe a recombinant scFv format for the 3F12E7 mAb. The results demonstrate that the generated 3F12E7 scFv, although prone to aggregation, comprises an active anti-FGF2 product that contains monomers and small oligomers. Functionally, the 3F12E7 scFv preparations specifically recognize FGF2 and inhibit tumor growth similar to the corresponding full-length IgG counterpart in an experimental model. In silico molecular analysis provided insights into the aggregation propensity and the antigen-recognition by scFv units. Antigen-binding determinants were predicted outside the most aggregation-prone hotspots. Overall, our experimental and prediction dataset describes an scFv scaffold for the 3F12E7 mAb and also provides insights to further engineer non-aggregated anti-FGF2 scFv-based tools for therapeutic and research purposes.