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The effects of cell-cell orientation in modeling the hallmarks of lung cancer in vitro

GSE241845 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2025/12/31 Platform GPL18573
Summary
To better understand and develop treatments for lung cancer, it is important to have reliable and physiologically relevant culture models. Traditional methods of growing lung cancer cells in two-dimensional monolayers have limitations in mimicking the complex architecture and microenvironment of lung tumors in vivo, limiting their value as reliably informative disease models. In this study, we introduce a new cell culture platform called "tumoroids," which involves growing HCC827 lung cancer cells in three-dimensional configurations for more accurately predicting how cell-cell orientation and signaling affects the cancer-driving properties of lung cancer. By comparing transcriptional profiles of HCC827 cells grown as tumoroids versus the same cells grown in two-dimensional monolayers, we investigate how cell-cell orientation and signaling impact the cancer-driving properties of lung cancer. We examine key features associated with cancer progression, such as epithelial mesenchymal transition, replicative ability, and induction of angiogenesis. Additionally, we assess the functional characteristics of the 3D tumoroid culture system by subjecting the cells to irradiation. Through comparing the gene expression profiles of the 3D tumoroid cultures with those of primary human lung adenocarcinoma, we find that the 3D tumoroid cultures closely resemble the characteristics of primary human lung cancer. This suggests that the 3D tumoroid culture platform can serve as a valuable in vitro model for studying lung cancer, offering greater clinical relevance compared to traditional 2D cultures. Overall, this study highlights the importance of using advanced culture models like 3D tumoroids to improve our understanding of lung cancer and facilitate the development of effective treatments.
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Direct links to NCBI, no account and no request form: the whole study as GSE241845_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1010229 and SRA study SRP457354. Searching any of these in the dataset finder brings you back here.

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