Glycosylation Changes in Serum Proteins Identify Patients with Pancreatic Cancer

After more than a decade of biomarker discovery using advanced proteomic and genomic approaches, very few biomarkers have been involved in clinical diagnostics. Most candidate biomarkers are focused on the protein component. Targeting post-translational modifications (PTMs) in combination with protein sequences will provide superior diagnostic information with regards to sensitivity and specificity. Glycosylation is one of the most common and functionally important PTMs. It plays a central role in many biological processes, including protein folding, host–pathogen interactions, immune response, and inflammation. Cancer-associated aberrant glycosylation has been identified in various types of cancer. Expression of cancer-specific glycan epitopes represents an excellent opportunity for diagnostics and potentially specific detection of tumors. Here, we report four proteins (LIFR, CE350, VP13A, HPT) found in sera from pancreatic cancer patients carrying aberrant glycan structures as compared to those of controls

Advances in the Study of Aptamer–Protein Target Identification Using the Chromatographic Approach

Ever since the development of the process known as the systematic evolution of ligands by exponential enrichment (SELEX), aptamers have been widely used in a variety of studies, including the exploration of new diagnostic tools and the discovery of new treatment methods. Aptamers’ ability to bind to proteins with high affinity and specificity, often compared to that of antibodies, enables the search for potential cancer biomarkers and helps us understand the mechanisms of carcinogenesis. The blind spot of those investigations is usually the difficulty in the selective extraction of targets attached to the aptamer. There are many studies describing the cell SELEX for the prime choice of aptamers toward living cancer cells or even whole tumors in the animal models. However, a dilemma arises when a large number of proteins are being identified as potential targets, which is often the case. In this article, we present a new analytical approach designed to selectively target proteins bound to aptamers. During studies, we have focused on the unambiguous identification of the molecular targets of aptamers characterized by high specificity to the prostate cancer cells. We have compared four assay approaches using electrophoretic and chromatographic methods for “fishing out” aptamer protein targets followed by mass spectrometry identification. We have established a new methodology, based on the fluorescent-tagged oligonucleotides commonly used for flow-cytometry experiments or as optic aptasensors, that allowed the detection of specific aptamer–protein interactions by mass spectrometry. The use of atto488-labeled aptamers for the tracking of the formation of specific aptamer–target complexes provides the possibility of studying putative protein counterparts without needing to apply enrichment techniques. Significantly, changes in the hydrophobic properties of atto488-labeled aptamer–protein complexes facilitate their separation by reverse-phase chromatography combined with fluorescence detection followed by mass-spectrometry-based protein identification. These comparative results of several methodological approaches confirmed the universal applicability of this method to studying aptamer–protein interactions with high sensitivity, showing superior properties compared with pull-down techniques

Mixed model coefficients for correlation of perfusion parameters in NAWM with WM and atrophy measurements (all models adjusted for age, gender and time).

<p>Abbreviations: CBV = cerebral blood volume, CBF = cerebral blood flow, CI = confidence interval, T2-LV = T2 hyperintense lesion volume, T1-LV = T1 hypointense lesion volume, Gd-LV = contrast enhancing lesion volume, WMV = white matter volume, GMV = gray matter volume, EDSS = Expanded Disability Status Scale</p><p>Mixed model coefficients for correlation of perfusion parameters in NAWM with WM and atrophy measurements (all models adjusted for age, gender and time).</p

Temporal evolution of perfusion parameters in NAWM comparing high inflammatory with low inflammatory patients: a) CBV, b) CBF.

<p>Temporal evolution of perfusion parameters in NAWM comparing high inflammatory with low inflammatory patients: a) CBV, b) CBF.</p

Segmentation results of white matter CBV (a,b) and CBF (c,d) maps with excluded lesions (NAWM) in a single low inflammatory and high inflammatory patient.

<p>Exemplary regions of interest drawn in the left frontal white matter of each individual map show elevated mean CBV (9.61 ± 1.35 vs 7.22 ± 0.77 ml/100g) and CBF (46.47 ±6.93 vs. 39.42 ± 6.32 ml/100g/min) in high inflammatory patients.</p