Abstract 1260: Establishment of intratumor heterogeneity models using lung cancer cells

Abstract Intratumor heterogeneity has been shown to be associated with treatment resistance in multiple cancers, including lung cancer. Elucidating intratumor heterogeneity is an issue that must be resolved to improve the prognosis of patients. Previous studies of intratumor heterogeneity have mainly involved collecting and analyzing cancer cells from patients, classifying subpopulation with different properties, and conducting comparative analysis. However, there are few studies focusing on the early phase of intratumor heterogeneity. We exposed alectinib to a commercially available ALK-positive lung cancer cell line (H2228) and established alectinib resistant cells (H2228-AR1S). H2228-AR1S was observed two cells with different appearances. In this intratumor heterogeneity model, flow cytometry (FACS) showed that the cell surface CD47 of the parent line was unimodal, whereas that of H2228-AR1S was bimodal, indicating that there were differences in the properties of migration and tumor formation between subpopulation having the CD47 high expression and subpopulation having CD47 low expression. Next, We exposed molecular targeted drugs to patient-derived lung cancer cell lines and evaluated the expression of cell surface markers using FACS. KTOR83-Dab, a cancer cell line derived from a BRAF-positive lung cancer patient that was exposed to dabrafenib for one month, showed bimodal EpCAM expression. The subpopulation of EpCAM low expression had high migration ability and showed reduced epithelial gene expression and increased mesenchymal gene expression, suggesting EMT (epithelial-mesenchymal transition). It was suggested that KTOR83-Dab is a patient-derived intratumor heterogeneity model. Furthermore, experiments are being conducted using these intratumor heterogeneity models to elucidate the mechanism of intratumor heterogeneity. H2228-AR1S is a intratumor heterogeneity model established from commercially available monoclonal cells, and single-cell analysis is performed to extract genes whose expression changes during the process of homogeneous cells becoming heterogeneous. KTOR83-Dab is a patient-derived lung cancer cell line and is therefore polyclonal. We will clone KTOR83-Dab and examine whether there are any cells that become heterogeneous when administered dabrafenib. In addition, based on the results of single-cell analysis of H2228-AR1s, we will also analyze genes involved in heterogeneity in KTOR83-Dab. Citation Format: Tomoko Funazo, Hiroaki Ozasa, Takahiro Tsuji, Yusuke Shima, Keiichiro Suminaga, Kentaro Hashimoto, Hiroshi Yoshida, Kazutaka Hosoya, Hitomi Ajimizu, Takashi Nomizo, Hironori Yoshida, Toyohiro Hirai. Establishment of intratumor heterogeneity models using lung cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1260.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-1260
Primary Topic
Radiomics and Machine Learning in Medical Imaging
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article
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article

Abstract 1260: Establishment of intratumor heterogeneity models using lung cancer cells

Hitomi Ajimizu, Hironori Yoshida, Kazutaka Hosoya, Hiroshi Yoshida et al.
Cancer Research
Radiomics and Machine Learning in Medical Imaging
article

Abstract 1260: Establishment of intratumor heterogeneity models using lung cancer cells

Hitomi Ajimizu, Hironori Yoshida, Kazutaka Hosoya, Hiroshi Yoshida, Toyohiro Hirai, Takahiro Tsuji, Kentaro Hashimoto, Hiroaki Ozasa, Takashi Nomizo, Keiichiro Suminaga, Tomoko Funazo, Yusuke Shima
article en

Abstract

Abstract Intratumor heterogeneity has been shown to be associated with treatment resistance in multiple cancers, including lung cancer. Elucidating intratumor heterogeneity is an issue that must be resolved to improve the prognosis of patients. Previous studies of intratumor heterogeneity have mainly involved collecting and analyzing cancer cells from patients, classifying subpopulation with different properties, and conducting comparative analysis. However, there are few studies focusing on the early phase of intratumor heterogeneity. We exposed alectinib to a commercially available ALK-positive lung cancer cell line (H2228) and established alectinib resistant cells (H2228-AR1S). H2228-AR1S was observed two cells with different appearances. In this intratumor heterogeneity model, flow cytometry (FACS) showed that the cell surface CD47 of the parent line was unimodal, whereas that of H2228-AR1S was bimodal, indicating that there were differences in the properties of migration and tumor formation between subpopulation having the CD47 high expression and subpopulation having CD47 low expression. Next, We exposed molecular targeted drugs to patient-derived lung cancer cell lines and evaluated the expression of cell surface markers using FACS. KTOR83-Dab, a cancer cell line derived from a BRAF-positive lung cancer patient that was exposed to dabrafenib for one month, showed bimodal EpCAM expression. The subpopulation of EpCAM low expression had high migration ability and showed reduced epithelial gene expression and increased mesenchymal gene expression, suggesting EMT (epithelial-mesenchymal transition). It was suggested that KTOR83-Dab is a patient-derived intratumor heterogeneity model. Furthermore, experiments are being conducted using these intratumor heterogeneity models to elucidate the mechanism of intratumor heterogeneity. H2228-AR1S is a intratumor heterogeneity model established from commercially available monoclonal cells, and single-cell analysis is performed to extract genes whose expression changes during the process of homogeneous cells becoming heterogeneous. KTOR83-Dab is a patient-derived lung cancer cell line and is therefore polyclonal. We will clone KTOR83-Dab and examine whether there are any cells that become heterogeneous when administered dabrafenib. In addition, based on the results of single-cell analysis of H2228-AR1s, we will also analyze genes involved in heterogeneity in KTOR83-Dab. Citation Format: Tomoko Funazo, Hiroaki Ozasa, Takahiro Tsuji, Yusuke Shima, Keiichiro Suminaga, Kentaro Hashimoto, Hiroshi Yoshida, Kazutaka Hosoya, Hitomi Ajimizu, Takashi Nomizo, Hironori Yoshida, Toyohiro Hirai. Establishment of intratumor heterogeneity models using lung cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1260.

Cancer ResearchVol. 85(8_Supplement_1)
Kyoto University (JP), Fred Hutch Cancer Center (US)
Openalex Percentile: Top 88%
Radiomics and Machine Learning in Medical Imaging
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