Using large-scale tissue microarray resources for the identification and evaluation of old, new, and novel targets for surgical pathology

Résumé fourni par la source

Immunohistochemistry (IHC) is essential in diagnostic pathology, but antibody reliability is often limited by insufficient validation and high variability between clones. Conventional validation approaches normally use only few tissues or cell lines which do not reflect tissue and cell type complexity. A high-throughput validation platform based on large-scale tissue microarrays (TMAs) was established to assess antibody specificity across 76 normal tissue types and to evaluate the diagnostic performance in > 15,000 tumours from > 130 entities. Comparative staining with independent antibodies on a full set of normal tissues enables robust detection of cross-reactivity. Comparative staining of critical tumour cohorts under different conditions enables protocol optimization to obtain the best possible sensitivity and specificity for the distinction of different tumour types. Large-scale tumour profiling studies on ≥ 15,000 cancers generated comprehensive datasets refining the diagnostic value of established markers (e.g., CK7/CK20, PLAP) and characterizing the impact of emerging diagnostic targets such as MTAP, CDH16, and CDH17. Furthermore, screening of over 6000 antibodies of previously unknown clinical significance identified various novel diagnostic markers, including CPA1, GAD2, and KDM6A, with high specificity for distinct tumour entities and/or neoplastic transformation. In conclusion, large-scale TMA-based validation improves antibody identification and characterization and provides a robust framework for integrating IHC into digital pathology solutions.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.