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New species from old data

hers in the journal, Lancet. That study reported dramatic results using mass spectrometry to search for a pattern of proteins in blood. In several sets of blinded samples, the test detected all patients who had ovarian cancer and only misdiagnosed three healthy individuals.

But among others who subsequently tested the study’s data for reproducibility were Baggerly and his colleagues (Kevin Coombes, Ph.D., and Jeffrey Morris, Ph.D., from M. D. Anderson Cancer Center, and Sarah Edmonson, M.D., from Baylor College of Medicine). They say the issue centers on how the mass spectrometer data were analyzed.

A mass spectrometer is an instrument that can quantitatively measure the concentration of hundreds of proteins from a single sample. In short, it does this by using an electric current to propel ionized proteins toward a detector. The number of ions hitting the detector at each mass-to-charge ratio (also known as m/z ratio) is recorded to produce a protein spectrum. A peak in the graph of the spectrum represents a protein (the identity of which is often unknown).

The goal is to find a pattern of peaks that will distinguish between patients with cancer and those who are cancer-free. The authors of the Lancet study have reported different proteomic patterns in three separate data sets. Researchers at the State University of New York, Stony Brook, reanalyzed the data to look for reproducible patterns. In 2003, they reported finding a single pattern involving 18 peaks (or unidentified proteins) that could diagnose ovarian cancer across two of these data sets.

The M. D. Anderson researchers examined the quality of the data sets and concluded that this systematic protein pattern “is biologically implausible.?Baggerly explains that discriminatory peaks appear to be spread across the entire m/z spectrum in the second data set, but “changes in protein expression associated with cancer should affect only a few specific peaks, not the entire spectrum
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