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Database: The Journal of Biological Databases and Curation
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Mapping assays to the key characteristics of carcinogens to support decision-making

Authors: Gabrielle Rigutto; Cliona M McHale; Ettayapuram Ramaprasad Azhagiya Singam; Iemaan Rana; Luoping Zhang; Martyn T Smith;

Mapping assays to the key characteristics of carcinogens to support decision-making

Abstract

Abstract The key characteristics (KCs) of carcinogens are the properties common to known human carcinogens that can be used to search for, organize, and evaluate mechanistic data in support of hazard identification. A limiting factor in this approach is that relevant in vitro and in vivo assays, as well as corresponding biomarkers and endpoints, have been only partially documented for each of the 10 KCs (Smith MT, Guyton KZ, Kleinstreuer N et al. The key characteristics of carcinogens: relationship to the hallmarks of cancer, relevant biomarkers, and assays to measure them. Cancer Epidemiol Biomarkers Prev 2020;29:1887–903. https://doi.org/10.1158/1055-9965.EPI-19-1346). To address this limitation, a comprehensive database is described that catalogues these previously described methods and endpoints/biomarkers pertinent to the 10 KCs of carcinogens as well as those referenced as supporting evidence for each KC in the International Agency of Research on Cancer Monograph Volumes 112–131. Our comprehensive mapping of KCs to assays and endpoints can be used to facilitate mechanistic data searches, presents a useful tool for searching for assays and endpoints relevant to the 10 KCs, and can be used to create a roadmap for utilizing data to evaluate the strength of the evidence for each KC. The KC-Assay database is available to the public on the web at https://kcad.cchem.berkeley.edu and acts as a ‘living document’, with the ability to be updated and refined. Database URL: https://kcad.cchem.berkeley.edu

Keywords

Cancer (rcdc), Humans (mesh), Neoplasms (mesh), 3102 Bioinformatics and computational biology (for-2020), 31 Biological Sciences (for-2020), Databases, Factual, 3102 Bioinformatics and Computational Biology (for-2020), Decision Making, Decision Making (mesh), Cancer (hrcs-hc), 0804 Data Format (for), 0807 Library and Information Studies (for), 4605 Data management and data science (for-2020), Factual (mesh), Databases, Database Tool, Neoplasms, Carcinogens, Animals (mesh), Humans, Animals, Carcinogens (mesh)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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gold
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Cancer Research