Researchers at the School of Medicine recently found that computational biology can be used to determine the rate of how human lung tumors respond to initial treatment. Scientists discovered that the success of therapies targeting cancer-causing genes is due to their ability to slow the speed of tumor cell division. By targeting particular cancer genes, researchers are now able to respond with appropriate therapy. Oncogene addiction occurs when the presence of cancer is dependent on a single cancer-causing gene. Cancer tumors of this nature regress with oncogene-targeted treatment. Stanford researchers have shown that oncogene-targeted therapies eradicate the addicted tumors by reducing survival signals. A cell’s life is dependent on the balance of life or death signals. The survival signals allow the death signals to continue.

The equation developed correlates changes in death signals with tumor regression rates.  Based on the newly developed formula, a patient with an oncogene-addicted tumor will have a different rate of regression than a patient with a non-addicted tumor. The formula helped predict which patients had oncogene-addicted tumors based on the rate of tumor regression from therapy. This new formula can help determine what treatment will work best for particular cancer patients. While the focus of the research was on lung cancer, Stanford researchers hope to extend the formula’s predictive success to other forms of cancer.

—Marianne LeVine