Ovarian Stainology: Database of evidence-based immunohistochemical antigen expression in ovarian tumors

Immunohistochemical (IHC) profiling is essential for ovarian tumor subtyping, but comprehensive data on antigen and protein expression frequencies is fragmented across the literature. We developed a structured, harmonized database of IHC expression profiles in ovarian tumors extracted from published studies. The dataset was constructed using large language models to identify and extract relevant data from abstracts and tables from systematically retrieved publications. Screening of 5,961 studies identified 100,149 raw tumor-stain pairs, which were processed through a multi-step curation pipeline to filter, standardize, and harmonize the records. The final dataset comprises 12,212 tumor-stain frequency records derived from 1,450 studies, with all tumor nomenclature standardized to the 2020 WHO Classification of tumors. Records include details such as expression type, total sample counts, expression percentages, subcellular localization and expression distribution. The resource provides a consolidated, evidence-based reference to support research, analyses, and the development of computational models in diagnostic pathology.

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Publication Details

Journal
Scientific Data
Published
2026-06-30
DOI
https://doi.org/10.1038/s41597-026-07776-1
Primary Topic
Ovarian cancer diagnosis and treatment
Type
article
Field-Weighted Citation Impact
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article

Ovarian Stainology: Database of evidence-based immunohistochemical antigen expression in ovarian tumors

Emilian Małek, Patryk Kraiński, Jan Gruszczynski, Aleksander Gostyński-Glina et al.
Scientific Data
Ovarian cancer diagnosis and treatment
article

Ovarian Stainology: Database of evidence-based immunohistochemical antigen expression in ovarian tumors

Emilian Małek, Patryk Kraiński, Jan Gruszczynski, Aleksander Gostyński-Glina, Hanna Pelant, Kacper Trębacz, Miłosz Kadziński, Michał J. Dopierała
article en

Abstract

Immunohistochemical (IHC) profiling is essential for ovarian tumor subtyping, but comprehensive data on antigen and protein expression frequencies is fragmented across the literature. We developed a structured, harmonized database of IHC expression profiles in ovarian tumors extracted from published studies. The dataset was constructed using large language models to identify and extract relevant data from abstracts and tables from systematically retrieved publications. Screening of 5,961 studies identified 100,149 raw tumor-stain pairs, which were processed through a multi-step curation pipeline to filter, standardize, and harmonize the records. The final dataset comprises 12,212 tumor-stain frequency records derived from 1,450 studies, with all tumor nomenclature standardized to the 2020 WHO Classification of tumors. Records include details such as expression type, total sample counts, expression percentages, subcellular localization and expression distribution. The resource provides a consolidated, evidence-based reference to support research, analyses, and the development of computational models in diagnostic pathology.

Scientific Data
Warsaw University of Technology (PL), Poznan University of Medical Sciences (PL), Poznań University of Technology (PL)
Openalex Percentile: Top 7%
Ovarian cancer diagnosis and treatment
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