BACKGROUND: The @entity356 is one of the most common and mortal @entity5 worldwide. The initial asymptomatic development and further nonspecific symptoms result in diagnosis at the advanced stage with poor prognosis. Yet, no clinically useful biomarkers are available for this malignancy, and invasive @entity344 remains the only reliable option at the moment. Hence, there is a need for discovery of clinically useful noninvasive diagnostic and/or prognostic tool as an alternative (or complement) for current diagnostic tools. Here we aimed to search for serum proteins characteristic for local and invasive @entity356 . METHODS: Pre-treatment blood samples were collected from @entity1 with diagnosed @entity356 at the different stage of disease: 35 @entity1 with locally advanced @entity5 and 18 @entity1 with @entity5 ; 50 healthy donors were also included as a control group. The low-molecular-weight fraction of serum proteome (i.e., endogenous peptidome) was profiled by the MALDI-ToF mass spectrometry, and the whole proteome components were identified and quantified by the LC-MS/MS shotgun approach. RESULTS: Multicomponent peptidome signatures were revealed that allowed good discrimination between healthy controls and @entity5 @entity1 , as well as between @entity1 with locally advanced and @entity5 . Moreover, a LC-MS/MS approach revealed 49 serum proteins with different abundances between healthy donors and @entity5 @entity1 (predominantly proteins associated with @entity32 and acute phase response). Furthermore, 19 serum proteins with different abundances between @entity1 with locally advanced and @entity5 were identified (including proteins associated with cytokine/chemokine response and metabolism of nucleic acids). However, neither peptidome profiling nor shotgun proteomics approach allowed detecting serum components discriminating between two subgroups of @entity1 with @entity66 who either developed or did not develop @entity3 during follow-up. CONCLUSIONS: The molecular differences between locally advanced and metastatic @entity356 , as well as more obvious differences between healthy individuals and @entity5 @entity1 , have marked reflection at the level of serum proteome. However, we have no evidence that features of pre-treatment serum proteome could predict a risk of @entity5 in @entity1 treated due to @entity66 . Nevertheless, presented data confirmed potential applicability of a serum proteome signature-based biomarker in diagnostics of @entity356 .

Identification of serum proteome signatures of locally advanced and metastatic XXXX : a pilot study.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity32 :: ('MESH:D007249', 'Disease') :: ['inflammation'] @entity66 :: ('MESH:D004194', 'Disease') :: ['local disease'] @entity5 :: ('MESH:D009369', 'Disease') :: ['cancer dissemination', 'cancer', 'metastatic cancer'] @entity344 :: ('MESH:D005767', 'Disease') :: ['gastrointestinal endoscopy'] @entity3 :: ('MESH:D009362', 'Disease') :: ['metastases'] @entity356 :: ('MESH:D013274', 'Disease') :: ['gastric cancer', 'gastric adenocarcinoma']
@entity356 :: (MESH:D013274,Disease) :: ['gastric cancer']
