Background: Leukocytes in peripheral blood (PB) are prognostic biomarkers in head and neck squamous cell carcinoma cancer patients (HNSCC-CPs), but differences between HNSCC-CPs and healthy adults (HAs) are insufficiently described. Methods: 10-color flow cytometry (FCM) was used for in-depth immunophenotyping of PB samples of 963 HAs and 101 therapy-naïve HNSCC-CPs. Absolute (AbsCC) and relative cell counts (RelCC) of leukocyte subsets were determined. A training cohort (TC) of 43 HNSCC-CPs and 43 HAs, propensity score (PS)-matched according to age, sex, alcohol, and smoking, was used to develop a score consecutively approved in a validation cohort (VC). Results: Differences in AbsCC were detected in leukocyte subsets (p < 0.001), but had low power in discriminating HNSCC-CPs and HAs. Consequently, RelCC of nine leukocyte subsets in the TC were used to calculate 36 ratios; receiver operating characteristic (ROC) curves defined optimum cut-off values. Binary classified data were combined in a score based on four ratios: monocytes-to-granulocytes (MGR), classical monocytes-to-monocytes (clMMR), monocytes-to-lymphocytes (MLR), and monocytes-to-T-lymphocytes (MTLR); ≥3 points accurately discriminate HNSCC-CPs and HAs in the PS-matched TC (p = 2.97 × 10−17), the VC (p = 4.404 × 10−178), and both combined (p = 7.74 × 10−199). Conclusions: RelCC of leukocyte subsets in PB of HNSCC-CPs differ significantly from those of HAs. A score based on MGR, clMMR, MLR, and MTLR allows for accurate discrimination.

Proteomics is a set of analytical methods which enable qualitative and quantitative characterization of the proteome. Expression proteomics quantitatively compares proteomes of cells, tissues, body fluids or other biological materials to find differencies in protein expression and, based on these differencies, to describe the biological processes occuring in investigated organisms. An initial material for expression proteomic studies are complex mixtures containing thousands of proteins, which are analyzed using separation (electrophoretic and chromatographic) methods, and identified, possibly quantified using mass spectrometry. The aim of this Thesis is to demonstrate the application of the tools of expression proteomics in solving diverse challenges in biomedicine. We employed various proteomic approaches and tools for studying molecular mechanisms of human diseases using pacient biological samples, or a model organism and a cell culture. We were conducting three different research projects, namely: A quest for potencial molecular targets for selective elimination of TRAIL-resistant mantle cell lymphoma cells; Investigation of molecular mechanisms of heart failure using a rat model of the disease induced by volume overload; and Searching for diagnostically usable serum biomarkers of ovarian...