A new method reveals how medications cause cancer cell death

Cancer cells are wise when it comes to anti-cancer drugs, evolving and resisting even the strongest chemotherapies over time. To address this evasive behavior, researchers have devised a method of naming D₂Ramanometry O-probed CANcer Bias Test (D.₂O-CANST-R) to see, at the single-cell / organelle level, how drugs promote cancer cell death and how cancer cells change.

The research, conducted by the Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT) of the Chinese Academy of Sciences (CAS), was published on January 12 in Analytical chemistry, a journal of the Chemical Society of America.

Understanding the cell response mechanism to drugs and pharmacokinetics is critical to improving cancer treatment. ”

Xu Jian, Director, Single Cell Center, QIBEBT and Paper Author

He explained that cancer cells can resist chemotherapy by altering metabolic activity to change to drug weight, but how this happens is not well understood. “Approaches are needed to quickly clarify the specific effects of a drug on the metabolic activity of cancer cells. This is clinically important because precise and personalized administration of cancer chemotherapy is essential for saving the lives of cancer patients.”

Maryam Hekmatara, a PhD student at XU, and her staff married a powerful algorithm with Raman spectroscopy, which involves using a laser to stimulate photons in a sample to reveal structural information, including interactions. They studied how rapamycin, an anti-cancer drug, altered the metabolic activity in human cancer cell line and in yeast.

Their method revealed the small organelles changes within the cells that were made in energy use and consumption. With a solubility capacity of less than one micrometer – human hair width is typically 80 to 100 micrometers, for comparison – the procedure has the ability to show metabolism in a cancer cell with very fine detail.

“The method is able to quickly and accurately detect and differentiate changes in the lipid-blocking metabolic effect of rapamycin proteins,” said Hekmatara, noting that the method takes just days to compare. to traditional tests that may take much longer to see if individual patient cells respond favorably to a drug. “It’s also very precise, because it can differentiate cancer cell responses to drugs at the same cell and single organelle resolution, which is crucial for understanding why the drug is – or isn’t – effective.”

The researchers plan to further study how cells resist, as well as develop their approach as a personalized approach to determine the most effective anti-cancer drug for a patient.