Persistent, low-grade inflammation is now considered a hallmark feature of chronic kidney disease (CKD), being involved in the development of all-cause mortality of these patients. Although substantial improvements have been made in clinical care, CKD remains a major public health burden, affecting 10–15% of the population, and its prevalence is constantly growing. Due to its insidious nature, CKD is rarely diagnosed in early stages, and once developed, its progression is unfortunately irreversible. There are many factors that contribute to the setting of the inflammatory status in CKD, including increased production of proinflammatory cytokines, oxidative stress and acidosis, chronic and recurrent infections, altered metabolism of adipose tissue, and last but not least, gut microbiota dysbiosis, an underestimated source of microinflammation. In this scenario, a huge step forward was made by the increasing progression of omics approaches, specially designed for identification of biomarkers useful for early diagnostic and follow-up. Recent omics advances could provide novel insights in deciphering the disease pathophysiology; thus, identification of circulating biomarker panels using state-of-the-art proteomic technologies could improve CKD early diagnosis, monitoring, and prognostics. This review aims to summarize the recent knowledge regarding the relationship between inflammation and CKD, highlighting the current proteomic approaches, as well as the inflammasomes and gut microbiota dysbiosis involvement in the setting of CKD, culminating with the troubling bidirectional connection between CKD and renal malignancy, raised on the background of an inflammatory condition.

Inflammation represents the immune system response to external or internal aggressors such as injury or infection in certain tissues. The body's response to cancer has many parallels with inflammation and repair; the inflammatory cells and cytokines present in tumours are more likely to contribute to tumour growth, progression, and immunosuppression, rather than in building an effective antitumour defence. Using new proteomic technology, we have investigated serum profile of pro- (IL-1β, IL-6, IL-8, IL-12, GM-CSF, and TNF-α) and anti-inflammatory cytokines (IL-4, IL-10), along with angiogenic factors (VEGF, bFGF) in order to assess tumoural aggressiveness. Our results indicate significant dysregulation in serum levels of cytokines and angiogenic factors, with over threefold upregulation of IL-6, IL-1β, TNF-α, and IL-10 and up to twofold upregulation of VEGF, FGF-2, IL-8, IL-2, and GM-CSF. These molecules are involved in tumour progression and aggressiveness, and are also involved in a generation of disease associated pain.

Malignant gliomas are aggressive brain tumors with limited therapeutic options, possibly because of highly tumorigenic subpopulations of glioma stem cells. These cells require specific microenvironments to maintain their “stemness,” described as perivascular and hypoxic niches. Each of those niches induces particular signatures in glioma stem cells (e.g., activation of Notch signaling, secretion of VEGF, bFGF, SDF1 for the vascular niche, activation of HIF2α, and metabolic reprogramming for hypoxic niche). Recently, accumulated knowledge on tumor-associated macrophages, possibly delineating a third niche, has underlined the role of immune cells in glioma progression, via specific chemoattractant factors and cytokines, such as macrophage-colony stimulation factor (M-CSF). The local or myeloid origin of this new component of glioma stem cells niche is yet to be determined. Such niches are being increasingly recognized as key regulators involved in multiple stages of disease progression, therapy resistance, immune-escaping, and distant metastasis, thereby substantially impacting the future development of frontline interventions in clinical oncology. This review focuses on the microenvironment impact on the glioma stem cell biology, emphasizing GSCs cross talk with hypoxic, perivascular, and immune niches and their potential use as targeted therapy.

In this work, the affinity of common dietary phenols (gallic acid, caffeic acid, catechin, and rutin) for iron and copper ions was quantitatively investigated in neutral phosphate buffer as well as the reactivity of the complexes toward dioxygen. Contrasting behaviors were observed: because of the competing phosphate ions, Fe(III) binding is much slower than Fe(II) binding, which is rapidly followed by autoxidation of Fe(II) into Fe(III). With both ions, O2 consumption and H2O2 production are modest and the phenolic ligands are only slowly oxidized. By contrast, metal-phenol binding is fast with both Cu(I) and Cu(II). With Cu(I), O2 consumption and H2O2 production are very significant and the phenolic ligands are rapidly oxidized into a complex mixture of oligomers. The corresponding mechanism with Cu(II) is hampered by the preliminary rate-determining step of Cu(II) reduction by the phenols. The consequences of these findings for the stability and antioxidant activity of plant phenols are discussed.

The clinical and fundamental research in prostate cancer - the most common urological cancer in men - is currently entering the proteomic and genomic era. The focus has switched from one single marker (PSA) to panels of biomarkers (including proteins involved in ribosomal function and heat shock proteins). Novel genetic markers (such as Transmembrane protease serine 2 (TMPRSS2)-ERG fusion gene mRNA) or prostate cancer gene 3 (PCA3) had already entered the clinical practice, raising the question whether subsequent protein changes impact the evolution of the disease and the response to treatment. Proteomic technologies such as MALDI-MS, SELDI-MS, i-TRAQ allow a qualitative/quantitative analysis of the proteome variations, in both serum and tumor tissue. A new trend in prostate cancer research is proteomic analysis of prostasomes (prostate-specific exosomes), for the discovery of new biomarkers. This paper provides an update of novel clinical tests used in research and clinical diagnostic, as well as of potential tissue or fluid biomarkers provided by extensive proteomic research data.

Keratoconus is a progressive corneal ectasia that may lead to severe visual impairment due to the irregular astigmatism caused by corneal thinning. In addition to its association with atopy, eye rubbing, or genetic component, late reports suggest the involvement of inflammation in the pathogenesis of the disease. Our aim was to determine the concentration of IL-4, IL-6, IL-10, RANTES, IFN gamma, and TNF alpha in the tear film of patients with keratoconus and their first degree family members. We analyzed forty-eight participants in an observational cross-sectional study. The diagnosis of keratoconus had to be confirmed in addition to a minimum of 47 D corneal refractive power by corneal topography readings provided by a Placido-based topography system and analysis of the pattern: irregular astigmatism with an asymmetric “bow-tie.” As for the other groups, the most important diagnosis criteria were a normal topographic pattern with a regular astigmatism. 17 keratoconus patients, 16 relatives, and 15 controls were recruited after clinical assessment as part of the research. The cytokine's mean values were similar in the keratoconus group and the relatives' samples but significantly higher compared to the controls. Important differences were found in IL-4 levels between keratoconus patients and relatives and between relatives and controls (mean difference of 302.42, p < 0.0016 and 219.16, p < 0.033, Tukey's HSD procedure). In the keratoconus group, using the CORR procedure, we found statistically strong correlations of IL-6 lacrimal concentrations with the disease stage (r = 0.56, p < 0.01), keratometry (r = 0.55, p < 0.02), pachymetry (r = −0.64, p < 0.048), and corneal hysteresis (r = −0.53, p < 0.02). Cytokine overexpression may be relevant for the inflammatory etiology of keratoconus. In conclusion, in the case of some first degree family members, the elevated tear biomarkers may represent a supplementary risk factor.

High grade gliomas represent one of the most aggressive and treatment-resistant types of human cancer, with only 1–2 years median survival rate for patients with grade IV glioma. The treatment of glioblastoma is a considerable therapeutic challenge; combination therapy targeting multiple pathways is becoming a fast growing area of research. This review offers an up-to-date perspective of the literature about current molecular therapy targets in high grade glioma, that include angiogenic signals, tyrosine kinase receptors, nodal signaling proteins and cancer stem cells related approaches. Simultaneous identification of proteomic signatures could provide biomarker panels for diagnostic and personalized treatment of different subsets of glioblastoma. Personalized medicine is starting to gain importance in clinical care, already having recorded a series of successes in several types of cancer; nonetheless, in brain tumors it is still at an early stage.

BackgroundThe rapid progress of proteomics over the past years has allowed the discovery of a large number of potential biomarker candidates to improve early tumor diagnosis and therapeutic response, thus being further integrated into clinical environment. High grade gliomas represent one of the most aggressive and treatment-resistant types of human brain cancer, with approximately 9–12 months median survival rate for patients with grade IV glioma (glioblastoma). Using state-of-the-art proteomics technologies, we have investigated the proteome profile for glioblastoma patients in order to identify a novel protein biomarker panel that could discriminate glioblastoma patients from controls and increase diagnostic accuracy.ResultsIn this study, SELDI-ToF MS technology was used to screen potential protein patterns in glioblastoma patients serum; furthermore, LC-MS/MS technology was applied to identify the candidate biomarkers peaks. Through these proteomic approaches, three proteins S100A8, S100A9 and CXCL4 were selected as putative biomarkers and confirmed by ELISA. Next step was to validate the above mentioned molecules as biomarkers through identification of protein expression by Western blot in tumoral versus peritumoral tissue.ConclusionsProteomic technologies have been used to investigate the protein profile of glioblastoma patients and established several potential diagnostic biomarkers. While it is unlikely for a single biomarker to be highly effective for glioblastoma diagnostic, our data proposed an alternative and efficient approach by using a novel combination of multiple biomarkers.