Back

Condition Medium of Glioblastoma Cell Lines Decreases the Viability of Glioblastoma Cells by Modulating Gene Expression Profile

Yavuz, M.; Akgul, S.; Kaya, E.; Demircan, T.

2021-09-12 cancer biology
10.1101/2021.09.11.459916 bioRxiv
Show abstract

Grade IV neoplasm of the central nervous system, GBM, is associated with poor prognosis and relatively short overall survival. Due to the current limitations in treatment methods, GBM is characterized as an incurable disease, and research to advance therapeutic options is required. Conditioned medium is commonly used in in-vitro studies complementary to animal experiments to simulate tumor microenvironment and has the potential to challenge and expand our current understanding of secretome effect on tumor characteristics. This study aimed to investigate the effects of conditioned mediums of GBM cell lines on each other. Conditioned mediums cellular and molecular effects were evaluated using commonly employed techniques such as MTT assay, colony formation assay, wound healing assay, EdU labeling-based flow cytometry, and qRT-PCR. Our study demonstrated that conditioned medium harvested from U87 or LN229 cells at 48th h exhibited an anti-growth activity on each other by changing the gene expression pattern. Furthermore, the conditioned medium of LN229 decreased the migration capacity of U87 cells, and the conditioned medium of U87 cells significantly suppressed the LN229 proliferation. We believe that this initial work provides new insights for a better understanding of GBM cell lines secretome roles and highlights the necessity of further studies to unveil the secretome content. HighlightsO_LIConditioned medium harvested from GBM cells at different time points displayed various effects. C_LIO_LIConditioned medium of GBM cell lines harvested at 48th h decreased the viability of each other. C_LIO_LIThe expression level of anti-and pro-proliferative genes is altered upon condition medium treatment. C_LI

Matching journals

The top 13 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.