Survival analysis is central to clinical oncology. Modern cancer studies can now measure gene activity in single cells from a patient’s tumor and link this information to how long patients live. However, until now, there has not been a good way to use this detailed cell-level data to directly predict survival.

The study, published in Cancer Discovery, describes a method called scSurvival that uses single-cell genetic data to identify which cells inside a tumor are most strongly linked to patient survival.

Unlike traditional methods that average signals across an entire tumor, the new approach pinpoints harmful and helpful cell populations that can drive disease progression. The research team presented these findings today at the American Association for Cancer Research conference.