New Statistical Algorithms for the Analysis of Mass - FU Berlin, FB MI ...

4.3. STUDY RESULTS 89
� “Peptide Mass Fingerprinting” (Mann et al., 1993; James et al.,
1993; Clauser et al., 1999) that uses the mass(es) of the (full or
proteolytic) peptide as input to a database search of known proteins
or
� Using the Tandem MS (MS 2 , MS/MS) technique (Little et al., 1994;
Mrtz et al., 1996; Wells and McLuckey, 2005; Hernandez et al.,
2006) that generates collision-induced fragments of a peptide and
analyzes these fragments to infer the original molecule either by
searching a database for the resulting fragment pattern or by de
novo sequencing the molecule.
There a numerous sophisticated algorithms available for peptide identification
and we have integrated some of them into our framework (see
section 6.2.3.
(2) Analyze biochemical pathways where this molecule plays a role: this
and the next step require a sound expertise in the biological / medical
area to draw meaningful conclusions. This step lays the foundation to
understand the context this molecule works in. As (Villanueva, Shaffer,
Philip, Chaparro, Erdjument-Bromage, Olshen, Fleisher, Lilja, Brogi,
Boyd, Sanchez-Carbayo, Holland, Cordon-Cardo, Scher and Tempst,
2006) show, even small pathways such as protease activity can exhibit
interesting insights.
(3) Find the reason for the different occurrence frequency: This step is
certainly the most complex part of the analysis and can yield insights
of varying complexity. This ranges from basic findings such as men and
woman have different concentrations of sex specific hormones till very
complex statements such as cancer patients show a very specific activity
of some proteases that result in a quite complex peptide pattern of the
fragmented pieces.
These findings should of course always be validated and confirmed by
further biochemical tests and (eventually) clinical trials.
4.3.5 Medical Examples
The above paragraphs gave a very coarse grained overview of the steps necessary
to analyze the features or fingerprints that can be found with our proteomics.net
pipeline. The next two sections give an example of how this can
be used in clinical environment.