{"doi":"10.1289/ehp12677","title":"Quantitative Integration of Mode of Action Information in Dose–Response Modeling and POD Estimation for Nonmutagenic Carcinogens: A Case Study of TCDD","abstract":"BACKGROUND: Traditional dose-response assessment applies different low-dose extrapolation methods for cancer and noncancer effects and assumes that all carcinogens are mutagenic unless strong evidence suggests otherwise. Additionally, primarily focusing on one critical effect, dose-response modeling utilizes limited mode of action (MOA) data to inform low-dose risk. OBJECTIVE: We aimed to build a dose-response modeling framework that continuously extends the curve into the low-dose region via a quantitative integration of MOA information and to estimate MOA-based points of departure (PODs) for nonmutagenic carcinogens. METHODS: ) characterizing pathway dose-response relationship for MOA-based POD estimation. RESULTS: We identified and extracted six KQEs and corresponding essential events composing the MOA of TCDD-induced liver tumors. With the essential doses estimated from the BMD method using various settings, three link functions were applied to model the pathway dose-response relationship. Given a toxicologically plausible definition of adversity, an MOA-based POD was derived from the pathway dose-response curve. The estimated MOA-based PODs were generally comparable with traditional PODs and can be further used to calculate reference doses (RfDs). CONCLUSIONS: The proposed framework quantitatively integrated mechanistic information in the modeling process and provided a promising strategy to harmonize cancer and noncancer dose-response assessment through pathway dose-response modeling. However, the framework can also be limited by data availability and the understanding of the underlying mechanism. https://doi.org/10.1289/EHP12677.","journal":"Environmental Health Perspectives","year":2023,"id":371963,"datarank":0.3543529580001183,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"self_citation_contribution":0.29188652235829704,"citation_network_contribution":0.06246643564182123,"self_endowment_contribution":0.29188652235829704,"citer_contribution":0.06246643564182123,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":6,"citers_with_citation_signal":4,"citers_with_endowment":4,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.935,"is_data_producer":true,"deposit_databanks":{"GEO":["GSE9838"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1080566,"name":"Yun Zhou","orcid":"0000-0003-1945-5876","position":1,"is_corresponding":false},{"id":1005191,"name":"Chao Ji","orcid":"0000-0002-7422-650X","position":2,"is_corresponding":false},{"id":411425,"name":"James E. Klaunig","orcid":"0000-0002-4736-2223","position":3,"is_corresponding":false},{"id":378417,"name":"Kan Shao","orcid":"0000-0002-5512-2377","position":4,"is_corresponding":false},{"id":1016489,"name":"Qiran Chen","orcid":"0000-0002-0883-9789","position":0,"is_corresponding":true}],"reference_count":31,"raw_metadata":null,"created_at":"2026-07-19T01:15:49.453761Z","pmid":"38157272","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}