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Fulltext Selection of phage-displayed human antibody fragments specific for CD1b presenting the Mycobacterium tuberculosis glycolipid Ac2SGL

Camacho F, Sarmiento ME, Reyes F, Kim L, Huggett J, Lepore M, et al.

Int J Mycobacteriol, 2016 06;5(2):120-7.
PMID: 27242221 DOI: 10.1016/j.ijmyco.2015.12.002

OBJECTIVE/BACKGROUND: The development of new tools capable of targeting Mycobacterium tuberculosis (Mtb)-infected cells have potential applications in diagnosis, treatment, and prevention of tuberculosis. In Mtb-infected cells, CD1b molecules present Mtb lipids to the immune system (Mtb lipid-CD1b complexes). Because of the lack of CD1b polymorphism, specific Mtb lipid-CD1b complexes could be considered as universal Mtb infection markers. 2-Stearoyl-3-hydroxyphthioceranoyl-2'-sulfate-α-α'-d-trehalose (Ac2SGL) is specific for Mtb, and is not present in other mycobacterial species. The CD1b-Ac2SGL complexes are expressed on the surface of human cells infected with Mtb. The aim of this study was to generate ligands capable of binding these CD1b-Ac2SGL complexes.
METHODS: A synthetic human scFv phage antibody library was used to select phage-displayed antibody fragments that recognized CD1b-Ac2SGL using CD1b-transfected THP-1 cells loaded with Ac2SGL.
RESULTS: One clone, D11-a single, light-variable domain (kappa) antibody (dAbκ11)-showed high relative binding to the Ac2SGL-CD1b complex.
CONCLUSION: A ligand recognizing the Ac2SGL-CD1b complex was obtained, which is a potential candidate to be further tested for diagnostic and therapeutic applications.
Fulltext Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Parsons MT, Tudini E, Li H, Hahnen E, Wappenschmidt B, Feliubadaló L, et al.

Hum Mutat, 2019 Sep;40(9):1557-1578.
PMID: 31131967 DOI: 10.1002/humu.23818

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.

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