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A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Development of an integrated testing strategy using in vitro models to predict lung carcinogenesis
Min-Ju Kim1, Cho Hee Park2, Seung Min Oh1,3
1Department of Bio-application Toxicity, Hoseo University, Asan, Republic of Korea.
New integrated testing strategies (ITS) assess lung cancer risks from chemical exposure. BEAS-2B cells exposed to carcinogens developed metastatic potential, showing promise for identifying unknown carcinogens.
Area of Science:
- Toxicology
- Cancer Research
- Cell Biology
Background:
- Traditional carcinogenicity testing relies on lengthy, resource-intensive animal studies (OECD TG 451, 453).
- A need exists for efficient alternative methods to predict lung cancer risk from chronic chemical exposure.
Purpose of the Study:
- To develop and validate integrated testing strategies (ITS) for assessing carcinogenic potential.
- To evaluate the effects of specific chemicals on cellular characteristics related to metastasis and malignancy.
Main Methods:
- Utilized the non-tumorigenic BEAS-2B cell model for integrated testing strategies.
- Exposed BEAS-2B cells to Benzo(a)pyrene (B(a)P), Ethyl carbamate (EC), Epichlorohydrin (ECH), and chloromethyl methyl ether (CMME) for 4 months.
- Assessed cell survival, clonal growth, migration, and invasion post-exposure.
Main Results:
- Prolonged chemical exposure enhanced anchorage-dependent and anchorage-independent colony formation in BEAS-2B cells.
- Significant increases in cell migration and invasion were observed in treated BEAS-2B cells.
- Demonstrated acquisition of metastatic potential and multiple malignant characteristics.
Conclusions:
- Integrated testing strategies effectively identified malignant transformations in BEAS-2B cells.
- These ITS can serve as a valuable tool for predicting carcinogenic potential and identifying unknown carcinogens.
- The study highlights the utility of cellular models in alternative toxicity testing for carcinogenicity.
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