For a while it looked as if proteomics' next frontier was the clinic, if one was to believe the hype surrounding a 2002 study from US Food and Drug Administration scientist Emanuel Petricoin III and National Cancer Institute scientist Lance Liotta. The pair and their team used mass spectrometry and pattern-recognition software to probe serum samples for ovarian cancer biomarkers. Their findings suggested that proteomic patterns – series of peaks in mass spectra representing unidentified peptides or low molecular-weight protein fragments – could be used to diagnose early ovarian cancer with surprising accuracy.