Combination therapy overcomes treatment resistance in breast cancer models
A combination approach successfully overcame treatment resistance and led to durable responses in preclinical models of advanced breast cancer, according to researchers at The University of Texas MD Anderson Cancer Center. The targets at the center of this approach were identified by a new computational biology algorithm developed at UT MD Anderson called TargetScore, suggesting this tool could…
Researchers at The University of Texas MD Anderson Cancer Center have developed a computational biology algorithm called TargetScore, which successfully overcame treatment resistance in preclinical models of advanced breast cancer. TargetScore evaluates networks of proteins and molecular signatures that work together inside tumor cells while under therapeutic stress, identifying potential backup routes that cancer cells use to survive despite initial targeted therapies.
By targeting both PARP and SHP2 proteins simultaneously, the combination therapy significantly slowed cancer growth and improved survival in multiple preclinical models of breast cancer, particularly in cells with defects in DNA repair that had already developed resistance to therapy. This study highlights the potential of TargetScore to identify more effective drug combinations to improve patient outcomes, although further validation in clinical trials is needed.
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