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A new computational tool called TargetScore, developed at MD Anderson Cancer Center, identified a promising drug combination that overcame treatment resistance in preclinical breast cancer models. By simultaneously blocking the PARP and SHP2 proteins, researchers significantly slowed tumor growth and improved survival — especially in tumors with DNA repair defects. The findings, published in Cancer Research, could reshape how scientists approach precision oncology.
Cancer cells are notoriously crafty — when one survival route gets blocked, they often find another. Researchers at MD Anderson Cancer Center tackled this problem head-on using a new computational algorithm called TargetScore, which maps how tumor cells rewire their internal signaling networks under therapeutic stress, rather than just looking at pre-existing genetic mutations.
The team applied TargetScore to breast cancer cells treated with an MCL1 inhibitor (a drug that pushes cancer cells toward programmed death). As cells adapted, TargetScore flagged two backup survival pathways — controlled by PARP and SHP2 proteins — as key escape routes. When researchers blocked both simultaneously, tumor growth slowed significantly and survival improved across multiple preclinical breast cancer models, outperforming either drug alone.
Key Takeaways:
Why it matters: Treatment resistance is one of the biggest barriers in oncology. TargetScore offers a smarter, more adaptive way to identify combination therapies — and could eventually be applied to other hard-to-treat cancers beyond breast cancer.
