Molecular characteristics detected in prostate cancers can provide clues that help predict how the disease will progress, according to new research from investigators at Weill Cornell Medicine and NewYork-Presbyterian.

The study, which used machine learning models to identify patterns in biopsy samples from more than 8,000 patients, defines distinct subclasses of disease based on genomic and transcriptomic data derived from the tumors. The investigators say that if they are validated,...