discoveries magazine

Prostate Lines

Predicting the most aggressive cases of cancer, even when initial signs confuse

Illustration: Ivan Canu

One out of every seven men eventually will be diagnosed with prostate cancer, the second-leading cause of cancer deaths among men in the United States. Researchers at Cedars-Sinai are working on game-changing, lifesaving diagnostics for prostate cancer patients. While most prostate tumors grow slowly and are not life-threatening, some spread to other organs — with fatal results. Michael Freeman, PhD, and Sungyong You, PhD, are finding ways to identify which patients are likely to develop aggressive types of the disease even if their tumors at first appear to be lower risk.

"Once we figure out how genes are activated in the individual tumor, we can determine the best treatment," says You, an assistant professor in the departments of Surgery and Biomedical Sciences. "We’ll be able to start treatment earlier for the 40 percent of patients who face aggressive tumors."

The new approach divides prostate tumors into three subtypes, each associated with different levels of disease progression. "The findings could help us solve one of the biggest problems we face: reliably predicting who will develop the most dangerous forms of the disease," says Freeman, director of Cancer Biology and Therapeutics Research in the Cedars-Sinai Department of Biomedical Sciences, the Ben Maltz Chair in Cancer Therapeutics, and the study’s principal investigator.

Today, physicians rely heavily on the Gleason grading system, which ranks cancer cells on a 10-point scale based on how closely they resemble normal prostate cells. The lower the score, the lower the risk of an aggressive tumor. That system is imperfect, however. For example, patients with low-grade tumors often receive no treatment and instead are closely monitored under a strategy known as active surveillance. While this works well in many cases and avoids interventions such as radiation or surgery when unnecessary, the new study suggests that some patients require more assertive treatment.

"Correctly predicting each patient’s individual needs will lead to ever better outcomes and make these challenges a thing of the past," says Freeman. "And that’s something we can all celebrate."