sick,^58 but the genome gives the information for further, targeted biomarker investi-
gation. However, particular caution is recommended. Some diseases like cancer
and particular injuries also cause inflammation of surrounding tissues, and change
of concentration of corresponding proteins in body fluids (most frequently plasma
or serum) can result in their (false) identification as disease biomarkers.^59 In order
to avoid this bias, a more critical data analysis is necessary.
Unfortunately, the cost factor is the main reason that the above-discussed
strategy cannot be applied for the treatment of diseases, such as malaria (and now
ebola), that are prevalent in the Third World. However, all the above-discussed
omics methods can be also used for the targeted development of new vaccines and
therapies for disease treatment.^60
4 Posttranslational Modifications as Potential Theranostic
Biomarkers
Protein phosphorylation is the posttranslational modification (PTM) that is con-
trolled by different protein kinases, and it is the mechanism for downstream
signaling pathways that control cellular functions such as cell proliferation, apo-
ptosis, motility, and cellular metabolism.^61 This signaling mechanism is frequently
deregulated in cancers^62 (see also above) and important for investigation of
intratumorheterogeneity,^63 identification of the genomic instability of particular
metastatic tumors,^64 , determination of the origin of cancer of unknown primary
site^65 and also in personalized investigation of other diseases,^66 such as heart
failure^67 or neurodegenerative disease.^68 As discussed above, targeted inhibition
of protein phosphorylation by use of small, specially designed molecules in combi-
nation with monoclonal antibodies against cell surface molecules that alternate the
signaling process in malignant cells is already a recognized method that is used for
personalized cancer treatment.^69 The role of other types of PTMs, except glyco-
sylation, is only rarely investigated at the “omic” level. However, the level of
(^58) Silvestri et al. ( 2013 ), pp. 309–316.
(^59) Boschetti et al. ( 2012 ), pp. 22–41; Poste ( 2011 ), pp. 156–157; Breen et al. ( 2012 ), pp. S89–S100.
(^60) Josic et al. ( 2008 ), pp. 116–112.
(^61) Stehle et al. ( 2014 ), pp. 909–916.
(^62) Hanahan and Weinberg ( 2011 ), pp. 646–674.
(^63) Al-Lazikani et al. ( 2012 ), pp. 679–691.
(^64) Erben et al. ( 2008 ), pp. 1544–1550.
(^65) Varadchachary and Raber ( 2014 ), pp. 757–765.
(^66) Mauvoisin et al. ( 2014 ).
(^67) Shah and Mann ( 2011 ), pp. 704–712.
(^68) Goldknopf ( 2008 ), pp. 1–8.
(^69) Chen et al. ( 2012 ), pp. 1293–1307.
The Role of Proteomics in Personalized Medicine 191