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Growth of Deadly Brain Cancer Cell Can Be Slowed Down Chemically, New Study Reveals

Growth of Deadly Brain Cancer Cell Can Be Slowed Down Chemically, New Study Reveals
02/14/2021
news18.com

news18.com

Inhibiting a key enzyme that controls a large network of proteins important in cell division and growth leads the way for a new class of drugs that could stop a deadly brain cancer from growing, a new study suggests. The study, published in the journal Nature Communications, showed that chemically inhibiting the enzyme PRMT5 can suppress the growth of glioblastoma cells.

The inhibition of PRMT5 led to cell senescence, similar to what happens to cells during aging when cells lose the ability to divide and grow. Cellular senescence can also be a powerful tumor suppression mechanism, stopping the unrelenting division of cancer cells. "By inhibiting one protein, PRMT5, we were able to affect a cascade of proteins involved in cell division and growth," said researcher Cheryl Arrowsmith from the University of Toronto.

"The traditional way of stopping cell division has been to block one protein. This gives us a new premise for the future development of novel, more precise therapies," Arrowsmith added. For the study, the team tested a group of new experimental small molecules designed to specifically inhibit key cellular enzymes being developed and studied to see if any would stop the growth of glioblastoma brain tumor cells in the laboratory.

The brain tumor cells were isolated from patients' tumors and grown in the laboratory in a way that preserved the unique properties of cancer stem cells. They found that specific molecules precursors to actual therapeutic drugs --inhibited the same enzyme, PRMT5, stopping the growth of a large portion of these patient-derived cancer stem cells. But they also caution that actual treatments for patients are many years away, and require development and testing of clinically appropriate and safe versions of PRMT5 inhibitors that can access the brain.

The researchers also examined the molecular features of the patient-derived glioblastoma cells by comparing those that responded well to those that did not respond as well. They found a different molecular signature for the tumor cells that responded. In the future, this could lead to specific tumor biomarkers, which could help in identifying those patients who will respond best to this new class of drugs.

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