Computer algorithm maps cancer resistance to drugs, therapy
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IMAGE: In vitro time course reflects clinical evolution of cetuximab response and evolution of acquired resistance. view more 

Credit: Johns Hopkins Kimmel Cancer Center

New methods of studying the evolution of treatment resistance in head and neck cancer are being developed by researchers at the Johns Hopkins Kimmel Cancer Center.

The scientists wanted to examine how cancers acquire resistance to treatment over time and whether those changes could be modeled computationally to determine patient-specific timelines of resistance.

The research was published by Genome Medicine on May 23, 2018.

The Coordinate Gene Activity in Pattern Sets algorithm (CoGAPS) was used to determine the molecular changes associated with resistance during the course of the development of the resistance. It required developing new methods of collecting data from in vitro cell models and developing a computational analysis approach to measure these observations that has not previously been done for cancer.

“The biggest novelty in this paper is considering time as a variable. We have to prove that it matters before putting that burden on patients,” said senior author Elana Fertig, Ph.D. “But we think it will result in better treatment.”

The study examined cetuximab treatment effects on cancer cells from head and

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