학술논문

Long-Term Simulation of Microgravity Induces Changes in Gene Expression in Breast Cancer Cells.
Document Type
Article
Source
International Journal of Molecular Sciences. Jan2023, Vol. 24 Issue 2, p1181. 23p.
Subject
*BRCA genes
*CANCER cells
*BREAST
*REDUCED gravity environments
*EXTRACELLULAR matrix
*GENOME-wide association studies
Language
ISSN
1661-6596
Abstract
Microgravity changes the gene expression pattern in various cell types. This study focuses on the breast cancer cell lines MCF-7 (less invasive) and MDA-MB-231 (triple-negative, highly invasive). The cells were cultured for 14 days under simulated microgravity (s-µg) conditions using a random positioning machine (RPM). We investigated cytoskeletal and extracellular matrix (ECM) factors as well as focal adhesion (FA) and the transmembrane proteins involved in different cellular signaling pathways (MAPK, PAM and VEGF). The mRNA expressions of 24 genes of interest (TUBB, ACTB, COL1A1, COL4A5, LAMA3, ITGB1, CD44, VEGF, FLK1, EGFR, SRC, FAK1, RAF1, AKT1, ERK1, MAPK14, MAP2K1, MTOR, RICTOR, VCL, PXN, CDKN1, CTNNA1 and CTNNB1) were determined by quantitative real-time PCR (qPCR) and studied using STRING interaction analysis. Histochemical staining was carried out to investigate the morphology of the adherent cells (ADs) and the multicellular spheroids (MCSs) after RPM exposure. To better understand this experimental model in the context of breast cancer patients, a weighted gene co-expression network analysis (WGCNA) was conducted to obtain the expression profiles of 35 breast cell lines from the HMS LINCS Database. The qPCR-verified genes were searched in the mammalian phenotype database and the human genome-wide association studies (GWAS) Catalog. The results demonstrated the positive association between the real metastatic microtumor environment and MCSs with respect to the extracellular matrix, cytoskeleton, morphology, different cellular signaling pathway key proteins and several other components. In summary, the microgravity-engineered three-dimensional MCS model can be utilized to study breast cancer cell behavior and to assess the therapeutic efficacies of drugs against breast cancer in the future. [ABSTRACT FROM AUTHOR]