Intercellular interactions between mast cells and stromal fibroblasts obtained from canine cutaneous mast cell tumours

Mast cell tumours (MCTs) are the most frequent malignant skin neoplasm in dogs. Due to the difficulty in purifying large numbers of canine neoplastic mast cells, relatively little is known about their properties. A reproducible in vitro model is needed to increase the understanding about the phenotype and functional properties of neoplastic mast cells. In the present study, we describe the establishment of primary cocultures of neoplastic mast cells from canine cutaneous MCTs and cancer-associated fibroblasts. We confirmed the inability of canine neoplastic mast cells to remain viable for long periods in vitro without the addition of growth factors or in vivo passages in mice. Using a transwell system, we observed that mast cell viability was significantly higher when there is cell-to-cell contact in comparison to non-physical contact conditions and that mast cell viability was significantly higher in high-grade than in low-grade derived primary cultures. Moreover, the use of conditioned medium from co-cultured cells led to a significantly higher tumoral mast cell viability when in monoculture. Signalling mechanisms involved in these interactions might be attractive therapeutic targets to block canine MCT progression and deserve more in-depth investigations

Proteomic analysis identifies FNDC1, A1BG, and antigen processing proteins associated with tumor heterogeneity and malignancy in a canine model of breast cancer

Simple Summary Comparative oncology is centered around the study of naturally occurring tumors in animals as a parallel and complementary model for human cancer research. Canine mammary tumors pose as excellent models since they share similarities in their spontaneous nature, histological subtypes, genetic background, and clinical course, which would be impossible to reproduce in murine models. Our study aimed to investigate cancer heterogeneity in primary tumors and metastasis, by applying bottom-up proteomics and mass spectrometry imaging to identify potential disease-state markers. We have demonstrated that the malignant phenotype may have arisen as a consequence of alterations in the expression of proteins involved in immune evasion facilitating metastatic events. To our knowledge, this is the first study to use mass spectrometry imaging in a dog model of breast cancer, that have demonstrated that poorly described proteins might play important roles in cancer spreading and should be further validated as potential early-stage tumor biomarkers. New insights into the underlying biological processes of breast cancer are needed for the development of improved markers and treatments. The complex nature of mammary cancer in dogs makes it a great model to study cancer biology since they present a high degree of tumor heterogeneity. In search of disease-state biomarkers candidates, we applied proteomic mass spectrometry imaging in order to simultaneously detect histopathological and molecular alterations whilst preserving morphological integrity, comparing peptide expression between intratumor populations in distinct levels of differentiation. Peptides assigned to FNDC1, A1BG, and double-matching keratins 18 and 19 presented a higher intensity in poorly differentiated regions. In contrast, we observed a lower intensity of peptides matching calnexin, PDIA3, and HSPA5 in poorly differentiated cells, which enriched for protein folding in the endoplasmic reticulum and antigen processing, assembly, and loading of class I MHC. Over-representation of collagen metabolism, coagulation cascade, extracellular matrix components, cadherin-binding and cell adhesion pathways also distinguished cell populations. Finally, an independent validation showed FNDC1, A1BG, PDIA3, HSPA5, and calnexin as significant prognostic markers for human breast cancer patients. Thus, through a spatially correlated characterization of spontaneous carcinomas, we described key proteins which can be further validated as potential prognostic biomarkers.Proteomic

Liver transcriptomic networks reveal main biological processes associated with feed efficiency in beef cattle

Abstract\ud \ud Background\ud The selection of beef cattle for feed efficiency (FE) traits is very important not only for productive and economic efficiency but also for reduced environmental impact of livestock. Considering that FE is multifactorial and expensive to measure, the aim of this study was to identify biological functions and regulatory genes associated with this phenotype.\ud \ud \ud Results\ud Eight genes were differentially expressed between high and low feed efficient animals (HFE and LFE, respectively). Co-expression analyses identified 34 gene modules of which 4 were strongly associated with FE traits. They were mainly enriched for inflammatory response or inflammation-related terms. We also identified 463 differentially co-expressed genes which were functionally enriched for immune response and lipid metabolism. A total of 8 key regulators of gene expression profiles affecting FE were found. The LFE animals had higher feed intake and increased subcutaneous and visceral fat deposition. In addition, LFE animals showed higher levels of serum cholesterol and liver injury biomarker GGT. Histopathology of the liver showed higher percentage of periportal inflammation with mononuclear infiltrate.\ud \ud \ud Conclusion\ud Liver transcriptomic network analysis coupled with other results demonstrated that LFE animals present altered lipid metabolism and increased hepatic periportal lesions associated with an inflammatory response composed mainly by mononuclear cells. We are now focusing to identify the causes of increased liver lesions in LFE animals.The authors thank Fundação de Apoio a Pesquisa do Estado de São Paulo\ud (FAPESP) for financial support (process. numbers: 2014/02493-7; 2014/07566-\ud 2) and scholarship for PA Alexandre (2012/14792-3; 2014/00307-1). HN\ud Kadarmideen thanks EU-FP7 Marie Curie Actions – Career Integration Grant\ud (CIG-293511) for partially funding his time spent on this research. The authors\ud thank Dr. JF Medrano for the technical advice on RNAseq and experimental\ud design

Differential gene expression associated with soybean oil level in the diet of pigs.

The aim of this study was to identify the differentially expressed genes (DEG) from the skeletal muscle and liver samples of animal models for metabolic diseases in humans. To perform the study, the fatty acid (FA) profile and RNA sequencing (RNA-Seq) data of 35 samples of liver tissue (SOY1.5, n = 17 and SOY3.0, n = 18) and 36 samples of skeletal muscle (SOY1.5, n = 18 and SOY3.0, n = 18) of Large White pigs were analyzed. The FA profile of the tissues was modified by the diet, mainly those related to monounsaturated (MUFA) and polyunsaturated (PUFA) FA. The skeletal muscle transcriptome analysis revealed 45 DEG (FDR 10%), and the functional enrichment analysis identified network maps related to inflammation, immune processes, and pathways associated with oxidative stress, type 2 diabetes, and metabolic dysfunction. For the liver tissue, the transcriptome profile analysis revealed 281 DEG, which participate in network maps related to neurodegenerative diseases. With this nutrigenomics study, we verified that different levels of soybean oil in the pig diet, an animal model for metabolic diseases in humans, affected the transcriptome profile of skeletal muscle and liver tissue. These findings may help to better understand the biological mechanisms that can be modulated by the diet