Computer algorithms find tumors’ molecular weak spots


In 2016, doctors invited Eileen Kapotes to join a clinical trial for a drug that had never been used for her disease.

Kapotes, a first grade teacher in her 50s, was fighting an aggressive breast cancer that had spread through her body. She had endured grueling treatments over the previous 4 years, including whole-brain radiation therapy. She had also been taking the breast cancer medication Herceptin, but her tumors were still growing.

Now, she had a chance to try something radically different: a drug called ruxolitinib, originally designed to treat cancers affecting the blood and bone marrow.

Kapotes’s oncologist, Amy Tiersten at Mount Sinai Hospital, was stunned by how well her patient responded to the new drug. It kept her cancer at bay and she had almost no side effects. “I was amazed,” Tiersten says.

The ruxolitinib trial was the product of a decadelong quest by Andrea Califano, a systems biologist at Columbia University. Using sophisticated computing, he models the molecular networks that sustain cancer cells and pinpoints proteins called transcription factors that act as linchpins, controlling the behavior of many genes inside a cell.

Califano collaborated with cell biologist José Silva, then also at Columbia, to analyze breast cancer samples in a repository of tissues from other patients who had become resistant to Herceptin. Findings of the analysis suggested a transcription factor called STAT3 plays a critical role in those cancers. And ruxolitinib was known to inhibit STAT3.

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