Peritoneal dissemination is the primary metastatic route of ovarian cancer (OvCa), and is often accompanied by the accumulation of ascitic fluid. The peritoneal cavity is lined by mesothelial cells (MCs), which can be converted into carcinoma‐associated fibroblasts (CAFs) through mesothelial‐to‐mesenchymal transition (MMT). Here, we demonstrate that MCs isolated from ascitic fluid (AFMCs) of OvCa patients with peritoneal implants also undergo MMT and promote subcutaneous tumour growth in mice. RNA sequencing of AFMCs revealed that MMT‐related pathways – including transforming growth factor (TGF)‐β signalling – are differentially regulated, and a gene signature was verified in peritoneal implants from OvCa patients. In a mouse model, pre‐induction of MMT resulted in increased peritoneal tumour growth, whereas interfering with the TGF‐β receptor reduced metastasis. MC‐derived CAFs showed activation of Smad‐dependent TGF‐β signalling, which was disrupted in OvCa cells, despite their elevated TGF‐β production. Accordingly, targeting Smad‐dependent signalling in the peritoneal pre‐metastatic niche in mice reduced tumour colonization, suggesting that Smad‐dependent MMT could be crucial in peritoneal carcinomatosis. Together, these results indicate that bidirectional communication between OvCa cells and MC‐derived CAFs, via TGF‐β‐mediated MMT, seems to be crucial to form a suitable metastatic niche. We suggest MMT as a possible target for therapeutic intervention and a potential source of biomarkers for improving OvCa diagnosis and/or prognosis. © 2017 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Herein, by studying a stepwise phase transformation of 23 nm FeO-Fe3O4 core-shell nanocubes into Fe3O4, we identify a composition at which the magnetic heating performance of the nanocubes is not affected by the medium viscosity and aggregation. Structural and magnetic characterizations reveal the transformation of the FeO-Fe3O4 nanocubes from having stoichiometric phase compositions into Fe 2+ deficient Fe3O4 phases. The resultant nanocubes contain tiny compressed and randomly distributed FeO sub-domains as well as structural defects. This phase transformation causes a tenfold increase in the magnetic losses of the nanocubes, which remains exceptionally insensitive to the medium viscosity as well as aggregation unlike similarly sized single-phase magnetite nanocubes. We observe that the dominant relaxation mechanism switches from Néel in fresh core-shell nanocubes to Brownian in partially oxidized nanocubes and once again to Néel in completely treated nanocubes. The Fe 2+ deficiencies and structural defects appear to reduce the magnetic energy barrier and anisotropy field, thereby driving the overall relaxation into Néel process. The magnetic losses of the particles remain unchanged through a progressive internalization/association to ovarian cancer cells. Moreover, the particles induce a significant cell death after being exposed to hyperthermia treatment. Here, we present the largest heating performance that has been reported to date for 23 nm iron oxide nanoparticles under cellular and intracellular conditions. Our findings clearly demonstrate the positive impacts of the Fe 2+ deficiencies and structural defects in the Fe3O4 structure on the heating performance under cellular and intracellular conditions.

The immune system regulates itself to establish an appropriate immune response to potentially harmful pathogens while tolerating harmless environmental antigens and self-antigens. A central role in this balance is played by regulatory T cells (Tregs) through various ways of actions. By means of molecule secretion and cell-cell contact mechanisms, Tregs may have the capacity to modulate effector T cells and suppress the action of proinflammatory cytokines across a broad range of cell types. As a result, abnormal regulatory T cell function has been pointed as a main cause in the development of allergic diseases, a major public health problem in industrialized countries, with a high socioeconomic impact. This prevalence and impact have created an international interest in improving the allergy diagnosis and therapy. Additionally, research has sought to gain a better understanding of the molecular mechanisms underlining this kind of disease, in order to a better management. At this respect, the role of Treg cells is one of the most promising areas of research, mainly because of their potential use as new immunotherapeutical approaches. Therefore, the aim of this review is to update the existing knowledge of the role of Tregs in this pathology deepening in their implication in allergen-specific therapy (AIT).

Asthma is a complex and heterogeneous respiratory disorder characterized by chronic airway inflammation. It has generally been associated with allergic mechanisms related to type 2 airway inflammation. Nevertheless, between 10 and 33% of asthmatic individuals have nonallergic asthma (NA). Several targeted treatments are in clinical development for patients with Th2 immune response, but few biomarkers are been defined for low or non-Th2-mediated inflammation asthma. We have recently defined by gene expression a set of genes as potential biomarkers of NA, mainly associated with disease severity: IL10, MSR1, PHLDA1, SERPINB2, CHI3L1, IL8, and PI3. Here, we analyzed their protein expression and specificity using sera and isolated peripheral blood mononuclear cells (PBMCs). First, protein quantification was carried out using ELISA (in sera) or Western blot (proteins extracted from PBMCs by Trizol procedure), depending on the biomarker in 30 healthy controls (C) subjects and 30 NA patients. A receiver operating characteristic curve analysis was performed by using the R program to study the specificity and sensitivity of the candidate biomarkers at a gene- and protein expression level. Four kinds of comparisons were performed: total NA group vs C group, severe NA patients vs C, moderate–mild NA patients vs C, and severe NA patients vs moderate–mild NA patients. We found that all the single genes showed good sensitivity vs specificity for some phenotypic discrimination, with CHI3L1 and PI3 exhibiting the best results for C vs NA: CHI3L1 area under the curve (AUC) (CI 95%): 0.95 (0.84–1.00) and PI3 AUC: 0.99 (0.98–1.00); C vs severe NA: PI3 AUC: 1 (0.99–1.00); and C vs moderate–mild NA: CHI3L1 AUC: 1 (0.99–1.00) and PI3 AUC: 0.99 (0.96–1.00). However, the results for discriminating asthma disease and severity with protein expression were better when two or three biomarkers were combined. In conclusion, individual genes and combinations of proteins have been evaluated as reliable biomarkers for classifying NA subjects and their severity. These new panels could be good diagnostic tests.

Asthma is a complex disease comprising various phenotypes and endotypes, all of which still need solid biomarkers for accurate classification. In a previous study, we defined specific genes related to asthma and respiratory allergy by studying the expression of 94 genes in a population composed of 4 groups of subjects: healthy control, nonallergic asthmatic, asthmatic allergic, and nonasthmatic allergic patients. An analysis of differential gene expression between controls and patients revealed a set of statistically relevant genes mainly associated with disease severity, i.e., CHI3L1, IL-8, IL-10, MSR1, PHLDA1, PI3 , and SERPINB2 . Here, we analyzed whether these genes and their proteins could be potential asthma biomarkers to distinguish between nonallergic asthmatic and asthmatic allergic subjects. Protein quantification was determined by ELISA (in serum) or Western blot (in protein extracted from peripheral blood mononuclear cells or PBMCs). Statistical analyses were performed by unpaired t -test using the Graph-Pad program. The sensitivity and specificity of the gene and protein expression of several candidate biomarkers in differentiating the two groups (and the severity subgroups) was performed by receiver operating characteristic (ROC) curve analysis using the R program. The ROC curve analysis determined single genes with good sensitivity and specificity for discriminating some of the phenotypes. However, interesting combinations of two or three protein biomarkers were found to distinguish the asthma disease and disease severity between the different phenotypes of this pathology using reproducible techniques in easy-to-obtain samples. Gene and protein panels formed by single biomarkers and biomarker combinations have been defined in easily obtainable samples and by standardized techniques. These panels could be useful for characterizing phenotypes of asthma, specifically when differentiating asthma severity.

Allergic diseases are highly prevalent disorders, mainly in industrialized countries where they constitute a high global health problem. Allergy is defined as an immune response “shifted toward a type 2 inflammation” induced by the interaction between the antigen (allergen) and IgE antibodies bound to mast cells and basophils that induce the release of inflammatory mediators that cause the clinical symptoms. Currently, allergen-specific immunotherapy (AIT) is the only treatment able to change the course of these diseases, modifying the type 2 inflammatory response by an allergenic tolerance, where the implication of T regulatory (Treg) cells is considered essential. The pollen of the olive tree is one of the most prevalent causes of respiratory allergic diseases in Mediterranean countries, inducing mainly nasal and conjunctival symptoms, although, in areas with a high antigenic load, olive-tree pollen may cause asthma exacerbation. Classically, olive-pollen allergy treatment has been based on specific immunotherapy using whole-olive pollen extracts. Despite extracts standardization, the effectiveness of this strategy varies widely, therefore there is a need for more effective AIT approaches. One of the most attractive is the use of synthetic peptides representing the B- or T-cell epitopes of the main allergens. This review summarizes experimental evidence of several T-cell epitopes derived from the Ole e 1 sequence to modulate the response to olive pollen in vitro, associated with several possible mechanisms that these peptides could be inducing, showing their usefulness as a safe preventive tool for these complex diseases.

Background: Macrophage scavenger receptor 1 (MSR1) has mostly been described in macrophages, but we previously found a significant gene expression increase in peripheral blood mononuclear cells (PBMCs) of asthmatic patients. Objective: To confirm those results and to define its cellular origin in PBMCs. Methods: Four groups of subjects were studied: healthy controls (C), nonallergic asthmatic (NA), allergic asthmatic (AA), and chronic obstructive pulmonary disease (COPD) patients. RNA was extracted from PBMCs. MSR1 gene expression was analyzed by RT-qPCR. The presence of MSR1 on the cellular surface of PBMC cellular subtypes was analyzed by confocal microscopy and flow cytometry. Results: MSR1 gene expression was significantly increased in the three clinical conditions compared to the healthy control group, with substantial variations according to disease type and severity. MSR1 expression on T cells (CD4+ and CD8+), B cells, and monocytes was confirmed by confocal microscopy and flow cytometry. In all clinical groups, the four immune cell subtypes studied expressed MSR1, with a greater expression on B lymphocytes and monocytes, exhibiting differences according to disease and severity. Conclusions: This is the first description of MSR1’s presence on lymphocytes’ surfaces and reinforces the potential role of MSR1 as a player in asthma and COPD.

Highly prevalent respiratory diseases such as asthma and allergy remain a pressing health challenge. Currently, there is an unmet need for precise diagnostic tools capable of predicting the great heterogeneity of these illnesses. In a previous study of 94 asthma/respiratory allergy biomarker candidates, we defined a group of potential biomarkers to distinguish clinical phenotypes (i.e. nonallergic asthma, allergic asthma, respiratory allergy without asthma) and disease severity. Here, we analyze our experimental results using complex algorithmic approaches that establish holistic disease models (systems biology), combining these insights with information available in specialized databases developed worldwide. With this approach, we aim to prioritize the most relevant biomarkers according to their specificity and mechanistic implication with molecular motifs of the diseases. The Therapeutic Performance Mapping System (Anaxomics’ TPMS technology) was used to generate one mathematical model per disease: allergic asthma (AA), non-allergic asthma (NA), and respiratory allergy (RA), defining specific molecular motifs for each. The relationship of our molecular biomarker candidates and each disease was analyzed by artificial neural networks (ANNs) scores. These analyses prioritized molecular biomarkers specific to the diseases and to particular molecular motifs. As a first step, molecular characterization of the pathophysiological processes of AA defined 16 molecular motifs: 2 specific for AA, 2 shared with RA, and 12 shared with NA. Mechanistic analysis showed 17 proteins that were strongly related to AA. Eleven proteins were associated with RA and 16 proteins with NA. Specificity analysis showed that 12 proteins were specific to AA, 7 were specific to RA, and 2 to NA. Finally, a triggering analysis revealed a relevant role for AKT1, STAT1, and MAPK13 in all three conditions and for TLR4 in asthmatic diseases (AA and NA). In conclusion, this study has enabled us to prioritize biomarkers depending on the functionality associated with each disease and with specific molecular motifs, which could improve the definition and usefulness of new molecular biomarkers.