and preliminary validation of biomarker candidates for the early detection of
cancer^101 and cancer metastasis^102 and for such as difficult task as investigation
of cancer of unknown primary side.^103 However, further development in the
direction of high-throughput methods and the reduction of sample amount that
enables highly reproducible analyses and statistical evaluation of large number of
samples is still a challenge.
5.2 Cardiovascular Diseases
Cardiovascular diseases (CVD) are a group of different pathophysiological changes
of the heart and blood vessels that as a result have problem in blood transport and as
a final consequence disturbed or interrupted oxygen supply to the target tissues.
Whether expressed as acute or chronic, they are a result of tissue changes, which
also may be interconnected with other diseases (e.g., diabetes mellitus type 2).
Proteomics technology was applied to study the mechanism of disease-analyzing
processes at protein level: during placentation in early,^104 after deletion, or
overexpression of individual genes in animal models,^105 in plasma after patient
treatment with different medicaments,^106 in different cellular compartments, for
example, mitochondria,^107 plasma membrane,^108 or extracellular compartments,^109
analyzing role of individual players such as platelets^110 or adipose tissue^111 or high
density lipoproteins.^112 Particularly important is the analysis of protein PTMs in
CVD that are not detectable by use of genomics technologies alone.^113 These
proteomic, phosphoproteomic, and glycoproteomics studies result in definition of
protein networks involved in CVD and help to identify proteins, most frequently
cell surface antigens or intracellular protein kinases as new potential drug targets
(see also^114 ). In the same time, proteomics has irreplaceable role in the discovery of
protein or peptide molecules as clinical cardiovascular biomarkers that will enable
(^101) Goh et al. ( 2007 ), pp. 8685–8690.
(^102) Brinton et al. ( 2012 ), pp. 345–356.
(^103) Varadchachary and Raber ( 2014 ), pp. 757–765.
(^104) Sharma et al. ( 2009 ), pp. 2650–2655.
(^105) Dai ( 2014 ), p. A15454.
(^106) Silvestri et al. ( 2013 ), pp. 309–316.
(^107) Agnetti et al. ( 2010 ), pp. 78–87.
(^108) Donoghue et al. ( 2008 ), pp. 3895–3905.
(^109) Barallobre-Barreiro et al. ( 2012 ), pp. 789–802.
(^110) Ve ́lez and Garcı ́a( 2014 ).
(^111) Chang et al. ( 2010 ), pp. 1067–1078.
(^112) Birner-Gruenberger et al. ( 2014 ), pp. 36–46.
(^113) Smith and White ( 2014 ), pp. 506–521.
(^114) Vidal et al. ( 2011 ), pp. 986–998; Fredolini et al. ( 2011 ), pp. 125–136.
The Role of Proteomics in Personalized Medicine 199