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Despite remarkable innovations in proteomic methods and technologies in the last years, the integration of new proteomic technologies in clinical laboratories is slow due to the costs associated with acquisition of new instruments, evaluation of biomarker specificity and sensitivity, and obtaining information on clinical validity of biomarkers in large populations.

This process is further complicated by the need for training technical and highly educated personnel in novel techniques and interpretation of obtained complex results [22–24].

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Considering that, comprehensive analyses of human proteome from clinical samples, such as serum or plasma, urine, spinal fluid, and tissues, are conducted and publicly available databases as well as bioinformatics analyses relevant to cancer proteomic studies have been recently developed and established [18–21].

Information collected in these large databases enables integration of transcriptomic, metabolomics, and proteomic profiles, which could ultimately contribute to identifying molecular features associated with cancers [19].

Cancer molecular heterogeneity can be observed on several levels: (1) genetic heterogeneity—copy number variations, point mutations, and different levels of gene expression; (2) heterogeneity in the germline background, which promotes generation of different aberrations in tumour cells and surrounding tumour stroma in individual patients; (3) epigenetic heterogeneity; and (4) phenotypic heterogeneity [30].

These inter- and intratumour heterogeneities add an additional level of complexity.

Consequently, the researchers and healthcare personnel meet difficulties in interpreting the results and it is next to impossible to expect that two or more cancer patients could have the same alterations on the protein level.

In this review we first focus on proteomic approaches used in the discovery and validation of new cancer biomarkers.

A myriad of protein biomarkers is already in use in clinical diagnostics (Table 1); however, the methods used for their detection and evaluation are mostly well established techniques, which are decades old, such as serum protein electrophoresis, Western blot, enzyme-linked immunoassays (ELISAs), and a few other immuno-based assays, including methods relying on fluorescence microscopy and flow cytometry.

A few of the better equipped laboratories also routinely use liquid chromatography mass spectrometry (LC-MS/MS) for the detection of small molecules, which include amino acids and biogenic amines [2, 3].

However, although sensitive proteomic methods have been developed for detecting these changes, translating the diagnostic significance of modified human proteomes in clinical samples is immensely complex [19].

Additionally, modern in-depth analyses revealed evidence of evolutionary dynamics and selective pressures that govern tumour initiation and progression and promote cancer subclonal spatial and temporal heterogeneity [30, 31].

The interrogation of data on aberrant posttranslational modifications of proteins could reveal proteins, whose genetic information is intact, but pathogenic alterations render these proteins either nonfunctional, more stable, or more prone to degradation, or they could even obtain the ability to form new interactions with other cellular molecules such as proteins, nucleic acids, lipids, and cofactors, which are not their normal binding partners [4].

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