Researchers at the University of Oulu have created a new method to analyze how individual patient tumor samples respond to drugs.This new pipeline is a major step towardpersonalized medicine because it addresses the difficulty in identifying the right drug, or combination of drugs, for each patient.
This pipeline uses live-cell barcoding to screen 96 drug treatments at single-cell resolution simultaneously.In a study focusing on high-grade serous ovarian cancer (HGSOC), the pipeline revealed the complex transcriptional landscape of tumors treated with 45 different drugs, representing 13 classes of mechanism of action.
Traditional cell line models often oversimplify the biology of real tumors, making it challenging to predict how a patient will respond to therapy.Working with primary patient samples not only improves the accuracy of these predictions but also opens the door to building a large-scale, data-driven “omics” database of drug responses.Researchers are hopeful that a comprehensive drug response database will significantly enhance the ability to match patients with the therapies most likely to be effective, ultimately improving outcomes in personalized cancer treatment.
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