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Updated: Sep 15, 2025

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy
Published on: October 4, 2019
Unique gene patterns lead to distinct functional phenotypes and chemosensitivity profiles among subclones obtained
Daxing Xu1,2, Yingdi Jiang1,2,3, Jie Li1,2
1Department of Laboratory Medicine, the Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi 214023, China.
Abstract:
One of the characteristics of malignant tumors is heterogeneity, which refers to the molecular or genetic differences among progeny cells during tumor growth. This heterogeneity contributes to variations in the tumor growth rate, invasive ability, drug sensitivity, and prognosis. To gain a deeper understanding of the molecular background underlying tumor heterogeneity, we construct monoclonal cell lines derived from the glioblastoma (GBM) cell line U87-MG by limiting dilution assays. The selected CF5 and G11 subclones exhibit completely different cell morphologies and, more importantly, distinct functional phenotypes. CF5 exhibits stronger proliferative properties and chemoresistance, whereas G11 shows greater motility and invasion. Transcriptomic sequencing reveals great differences in gene expression among the CF5, G11, and U87 cell lines, and downregulated genes in individual clones are significantly enriched in gene sets related to extracellular matrix function. ITGA11 and ITGA6, as research subjects, are demonstrated to exclusively regulate functional phenotypes and chemotherapy sensitivity in CF5 or G11 cells. In U87 cells, combined knockdown of these two genes significantly inhibits tumor growth and increases chemotherapy sensitivity, but knockdown of either gene alone does not. In summary, these data reveal that even under uniform growth conditions, the heterogeneity of tumor cells and their diverse genetic backgrounds remain significant and persistent. This finding is crucial for accurately identifying tumor-related genes and their functional phenotypes, and a thorough understanding of the genetic and molecular background underlying tumor heterogeneity is essential for comprehensive cancer treatment.
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