Evidence map›Paper›PMID 41265413›Full record

ArticleEnvironmental analysis, health and toxicology2025

Development of an integrated testing strategy using in vitro models to predict lung carcinogenesis.

Min-Ju Kim, Cho Hee Park, Seung Min Oh

Abstract read
In one paragraph

Article in Environmental analysis, health and toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Four Decades of Environmental Analysis, Health and Toxicology.Environmental analysis, health and toxicology · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Min-Ju KimDepartment of Bio-application Toxicity, Hoseo University, Asan, Republic of Korea.
Cho Hee ParkNonclinical Research Institute, Orient Genia Incorporated, Seongnam, Republic of Korea.
Seung Min OhDepartment of Bio-application Toxicity, Hoseo University, Asan, Republic of Korea.

Funding

Korea Environmental Industry & Technology InstituteMinistry of Environment RS-2021-KE00142Ministry of Science and ICTNational Research Foundation of Korea 2020R1F1A1077028
6 · The paper itself

Abstract

Carcinogenicity testing has traditionally been conducted using long-term animal studies, as specified in OECD TG 451 and 453 guidelines. These studies typically use rats and last for two years, requiring significant time and resources. Consequently, there is a pressing need to develop alternative toxicity testing methods that can efficiently predict lung cancer risks caused by chronic chemical exposure. In this study, we designed integrated testing strategies (ITS) to assess carcinogenesis by focusing on cell survival, clonal growth, and metastasis using the BEAS-2B cell model. Non-tumorigenic BEAS-2B cells were exposed to Benzo(a)pyrene (B(a)P), Ethyl carbamate (EC), Epichlorohydrin (ECH), and chloromethyl methyl ether (CMME) for 4 months (#40 passages). After treatment, the BEAS-2B cells showed enhanced anchorage-dependent and anchorage-independent colony formation. Furthermore, cell migration and invasion assays using transwell chambers revealed a significant increase in these malignant characteristics in treated BEAS-2B cells. Collectively, our findings demonstrate that prolonged exposure of non-tumorigenic BEAS-2B cells to B(a)P, EC, ECH, and CMME can lead to the acquisition of metastatic potential and multiple malignant characteristics. These integrated testing strategies for assessing carcinogenic potential could serve as a valuable tool for identifying unknown carcinogens.

Indexed as

BEAS-2B cellscarcinogenesisIntegrated Testing Strategy (ITS)in vitro model

Identifiers

PMID41265413
PMCPMC12897477

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.