Molecular phenotyping of malignant canine mammary tumours: Detection of high-risk group and its relationship with clinicomolecular characteristics.

Canine mammary gland tumours (CMTs) constitute the most common cancer in female dogs and comprise approximately 50% of all canine cancers. With the advent of high-throughput technologies such as microarray and next-generation sequencing, the molecular phenotyping (classification) of various cancers has been extensively developed. The present study used a canine RNA-sequencing dataset, namely GSE119810, to classify 113 malignant CMTs and 64 matched normal samples via an unsupervised hierarchical algorithm with a view to evaluating the association between the resulting subtypes (clusters) (n = 4) and clinical and molecular characteristics. Finally, a molecular classifier was developed, and it detected 1 high-risk molecular subtype in the training dataset (GSE119810) and 2 independent validation datasets (GSE20718 and GSE22516). Our results revealed four molecular subtypes (C2-C5) in malignant CMTs. Furthermore, the normal samples constituted a distinct group in the clustering analysis. Marked significant associations were observed between the molecular subtypes (especially C5) and clinical/molecular features, including positive lymphatic invasion, high tumour grades, histopathology diagnoses, short survival and high TP53 mutation rates (ps <.05). The high-risk subtype (C5) was further characterized through the development of a cell cycle-based gene signature, which comprised 37 proliferation-related genes according to the support vector machine algorithm. This signature identified the high-risk group in both training and validation datasets (ps <.001). In the validation analysis, our potential classifier robustly predicted patients with positive lymphatic invasion, metastases and short survival.

Prognostic efficacy of the RTN1 gene in patients with diffuse large B-cell lymphoma.

Gene expression profiling has been vastly used to extract the genes that can predict the clinical outcome in patients with diverse cancers, including diffuse large B-cell lymphoma (DLBCL). With the aid of bioinformatics and computational analysis on gene expression data, various prognostic gene signatures for DLBCL have been recently developed. The major drawback of the previous signatures is their inability to correctly predict survival in external data sets. In other words, they are not reproducible in other datasets. Hence, in this study, we sought to determine the gene(s) that can reproducibly and robustly predict survival in patients with DLBCL. Gene expression data were extracted from 7 datasets containing 1636 patients (GSE10846 [n = 420], GSE31312 [n = 470], GSE11318 [n = 203], GSE32918 [n = 172], GSE4475 [n = 123], GSE69051 [n = 157], and GSE34171 [n = 91]). Genes significantly associated with overall survival were detected using the univariate Cox proportional hazards analysis with a P value < 0.001 and a false discovery rate (FDR) < 5%. Thereafter, significant genes common between all the datasets were extracted. Additionally, chromosomal aberrations in the corresponding region of the final common gene(s) were evaluated as copy number alterations using the single nucleotide polymorphism (SNP) data of 570 patients with DLBCL (GSE58718 [n = 242], GSE57277 [n = 148], and GSE34171 [n = 180]). Our results indicated that reticulon family gene 1 (RTN1) was the only gene that met our rigorous pipeline criteria and associated with a favorable clinical outcome in all the datasets (P < 0.001, FDR < 5%). In the multivariate Cox proportional hazards analysis, this gene remained independent of the routine international prognostic index components (i.e., age, stage, lactate dehydrogenase level, Eastern Cooperative Oncology Group [ECOG] performance status, and number of extranodal sites) (P < 0.0001). Furthermore, no significant chromosomal aberration was found in the RTN1 genomic region (14q23.1: Start 59,595,976/End 59,870,966).

Macrophage polarization by MSC-derived CXCL12 determines tumor growth.

BACKGROUND: Phenotypic and functional heterogeneity of macrophages is known to be the main reason for their ability to regulate inflammation and promote tumorigenesis. Mesenchymal stem cells (MSCs) are one of the principal cells commonly found in the tumor stromal niche, with capability of macrophage phenotypic switching. The objective of this study was to evaluate the role of C-X-C motif chemokine ligand 12 (CXCL12) produced by marrow-derived MSCs in the phenotypic and functional pattern of bone marrow-derived macrophages (BMDMs). METHODS: First, the CRISPR/Cas9 system was used for the CXCL12 gene knock-out in MSCs. Then, coculture systems were used to investigate the role of MSCsCXCL12-/- and MSCsCXCL12+/+ in determination of macrophage phenotype. To further analyze the role of the MSC-derived CXCL12 niche, cocultures of 4T1 mammary tumor cells and macrophages primed with MSCsCXCL12-/- or MSCsCXCL12+/+ as well as in-vivo limiting dilution assays were performed. RESULTS: Our results revealed that the expression of IL-4, IL-10, TGF-ß and CD206 as M2 markers was significantly increased in macrophages co-cultured with MSCsCXCL12+/+ , whereas the expression of IL-6, TNF-α and iNOS was conversely decreased. The number and size of multicellular tumor spheroids were remarkably higher when 4T1 cells were cocultured with MSCCXCL12+/+-induced M2 macrophages. We also found that the occurrence of tumors was significantly higher in coinjection of 4T1 cells with MSCCXCL12+/+-primed macrophages. Tumor initiating cells were significantly decreased after coinjection of 4T1 cells with macrophages pretreated with MSCsCXCL12-/-. CONCLUSIONS: In conclusion, our findings shed new light on the role of MSC-derived CXCL12 in macrophage phenotypic switching to M2, affecting their function in tumorigenesis.

Development of an RNA sequencing-based prognostic gene signature in multiple myeloma.

Several prognostic gene signatures have been developed to predict the clinical outcome in patients with multiple myeloma (MM). The most salient disadvantage of the previous signatures is their non-reproducibility in external datasets. Given the disadvantages and the superiority of RNA sequencing over microarrays in transcriptome profiling to produce more reliable outputs, we sought to develop a reproducible RNA sequencing-based prognostic gene signature for MM. Genes significantly associated with survival were detected in The Cancer Genome Atlas (TCGA) MM RNA sequencing dataset (MMRF-CoMMpass) (n = 412) through a strict pipeline containing four rigid filters. The reproducibility of the selected genes was checked in an independent dataset (GSE24080), containing 559 newly diagnosed patients with MM. The RNA sequencing-based prognostic signature was reconstructed based on the final genes in the training dataset (MMRF-CoMMpass) and externally validated in five independent datasets (i.e. GSE2658, GSE13624, GSE9782, GSE6477 and GSE57317), containing 1461 MM cases. The RNA sequencing-based signature was reconstructed using finally five reproducible genes: CCT2, CKS1B, PRKDC, NONO and UBE2A. This signature was able to robustly discriminate between low- and high-risk patients in both training and validation datasets (Ps ≤ 0·001). Our signature was also independent of and more powerful than the routine MM prognostic factors (i.e. ß2-microglobulin, albumin, age and sex) (Ps ≤ 0·01). Treatment regimens had no effect on RNA sequencing-based signature insofar as this signature succeeded in predicting the clinical outcome in various treatment groups (Ps ≤ 0·001).

Comparative measurement of FeLV load in hemolymphatic tissues of cats with hematologic cytopenias.

BACKGROUND: Feline leukemia virus (FeLV) is a serious viral infection in cats. FeLV is found in some tissues, such as spleen, lymph nodes and epithelial tissues. However, there is controversy about the organ in which the virus can be reliably detected in infected cats. The purpose of this study was to determine the level of viral infection in hemolymphatic tissues, including blood, bone marrow and spleen by reverse-transcriptase quantitative polymerase chain reaction (RT-qPCR). RESULTS: A total of 31 cats with clinical signs of FeLV infection associated with at least a single lineage hematologic cytopenia were included in this study. Peripheral blood, bone marrow and spleen samples were obtained from each cat. Complete blood counts, biochemical tests, and a rapid test to detect FeLV p27 antigen in blood samples of cats were performed. Of 31 cats, 9 had anemia alone, 4 had thrombocytopenia alone, 2 had neutropenia alone, 9 had bicytopenia of anemia and thrombocytopenia, 3 had bicytopenia of anemia and neutropenia, and 4 had pancytopenia. FeLV RNA was then detected by RT-qPCR in the whole blood, bone marrow and spleen. Viral RNA copy numbers were detected in all cats by RT-qPCR whereas 24 out of 31 cats were positive for the serum FeLV antigen. We detected a significantly greater number of viral RNA in the spleen compared with the whole blood and bone marrow. CONCLUSION: Spleen is a site where FeLV is most frequently detected in cats with hematologic cytopenias.

Development of a Reproducible Prognostic Gene Signature to Predict the Clinical Outcome in Patients with Diffuse Large B-Cell Lymphoma.

Alongside various clinical prognostic factors for diffuse large B-cell lymphoma (DLBCL) such as the international prognostic index (IPI) components (ie, age, tumor stage, performance status, serum lactate dehydrogenase concentration, and number of extranodal sites), prognostic gene signatures have recently shown promising efficacy. However, previously developed signatures for DLBCL suffer from many major inadequacies such as lack of reproducibility in external datasets, high number of members (genes) in a signature, and inconsistent association with the survival time in various datasets. Accordingly, we sought to find a reproducible prognostic gene signature with a minimal number of genes. Seven datasets-namely GSE10856 (420 samples), GSE31312 (470 samples), GSE69051 (157 samples), GSE32918 (172 samples), GSE4475 (123 samples), GSE11318 (203 samples), and GSE34171 (91 samples)-were employed. The datasets were randomly categorized into training (1219 samples comprising GSE10856, GSE31312, GSE69051, and GSE32918) and validation (417 samples consisting of GSE4475, GSE11318, and GSE34171) groups. Through the univariate Cox proportional hazards analysis, common genes associated with the overall survival time with a P value less than 0.001 and a false discovery rate less than 5% were identified in 1219 patients included in the 4 training datasets. Thereafter, the common genes were entered into a multivariate Cox proportional hazards analysis encompassing the common genes and the international prognostic index (IPI) factors as covariates, and then only common genes with a significant level of difference (P < 0.01 and z-score >2 or <-2) were selected to reconstruct the prognostic signature. After the analyses, a 7-gene prognostic signature was developed, which efficiently predicted the survival time in the training dataset (Ps < 0.0001). Subsequently, this signature was tested in 3 validation datasets. Our signature was able to strongly predict clinical outcomes in the validation datasets (Ps < 0.0001). In the multivariate Cox analysis, our outcome predictor was independent of the routine IPI components in both training datasets (Ps < 0.0001). Furthermore, our outcome predictor was the most powerful independent prognostic variable (Ps < 0.0001). We developed a potential reproducible prognostic gene signature which was able to robustly discriminate low-risk patients with DLBCL from high-risk ones.

The diagnostic performance of human urinary dipsticks to estimate urine pH, specific gravity (SpG), and protein in horses: are they reliable?

BACKGROUND: Urinalysis is a critical diagnostic test which is performed in routine veterinary medicine practice. In this diagnostic test, semiquantitative measurement of urine biochemical substances is carried out using urinary dipstick. In the current study, we evaluated the diagnostic performance of human urinary dipsticks to estimate pH, specific gravity (SpG), and protein in 80 urine specimens collected from horses. These parameters were measured using two commercial human dipsticks (KP and MN in abbreviation) and quantitative reference methods. The reference methods for pH, SpG, and protein were pH meter, handheld refractometer, and pyrogallol red method, respectively. The correlation between the semiquantitative dipstick analysis and quantitative reference methods was determined using Spearman's rank correlation coefficient. RESULTS: In general, our results revealed that the both human urinary dipsticks are unreliable tests for urinary pH, SpG, and protein content in horses. The analysis indicated that there was a poor correlation between the urine dipsticks and reference method (KP: rS = 0.534 and MN: rs = 0.485, Ps < 0.001) for protein. Additionally, there was a weak correlation between the results of pH measured using the urine dipsticks and reference method (KP: rS = 0.445 and MN: rs = 0.370, Ps < 0.001). Similar findings were obtained for SpG (KP: rS = 0.285, MN: rs = 0.338, Ps < 0.001). The estimation of proteinuria using the human dipsticks in horses lacked specificity, as many false positive protein results were obtained. CONCLUSION: We observed that the human commercial urinary dipsticks used in this study were not reliable to correctly estimate urine protein, SpG, and pH in horses.

Identification of pathway-based prognostic gene signatures in patients with multiple myeloma.

Molecular profiling is used to extract prognostic gene signatures in different cancers such as multiple myeloma (MM), which is the second most common hematological malignancy. In this study, we utilized gene expression profiles to find biological pathways that could efficiently predict survival time in patients with MM. Four data sets-namely GSE2658 (559 samples), GSE9782 (264 samples), GSE6477 (147 samples), and GSE57317 (55 samples)-were employed. GSE2658 was used as a training data set and the others as validation data sets. The genes significantly associated with survival were identified using the univariate Cox proportional hazards analysis, and their roles in the biological pathways were explored using the Gene-Set Enrichment Analysis (GSEA) in the training data set. Next, the significant genes and their corresponding pathways were used to reconstruct pathway-based prognostic signatures. Thereafter, the significant gene signatures were externally validated in 3 independent cohorts-namely GSE9782, GSE6477, and GSE57317. Our results revealed that 9 pathway-based prognostic signatures were able to efficiently predict survival time in the training data set (Ps < 0.01). The testing of these signatures in the validation data sets demonstrated that 3 signatures-namely MYC targets, spliceosome, and metabolism of RNA-were able to strongly predict the clinical outcome in the 3 cohorts at P values < 0.01. In addition, in the multivariate Cox analysis, the 3 gene signatures remained as independent prognostic factors compared with the routine prognostic variables in MM-namely serum albumin, serum ß2-microglobulin, and age. These signatures were by far the most powerful independent prognostic factors (MYC targets: P = 0.009, spliceosome: P = 0.024, and metabolism of RNA: P < 0.001).

Endothelial Progenitor Cell Mobilization in Preterm Infants With Sepsis Is Associated With Improved Survival.

Microvascular dysfunction plays a key role in the pathology of sepsis, leading to multi-organ failure, and death. Circulating endothelial progenitor cells (cEPCs) are critically involved in the maintenance of the vascular homeostasis in both physiological and pathological contexts. In this study, concentration of cEPCs in preterm infants with sepsis was determined to recognize whether the EPC mobilization would affect the clinical outcome of infantile sepsis. One hundred and thirty-three preterm infants (81 with sepsis and 52 without sepsis) were enrolled in this study. The release of EPCs in circulation was first quantified. Thereafter, these cells were cultivated and biological features of these cells such as, proliferation and colony forming efficiency were analyzed. The levels of chemoattractant cytokines were also measured in infants. In mouse models of sepsis, effects of VEGF and SDF-1 as well as anti-VEGF and anti-SDF-1 were evaluated in order to shed light upon the role which the EPC mobilization plays in the overall survival of septic animals. Circulating EPCs were significantly higher in preterm infants with sepsis than in the non-sepsis group. Serum levels of VEGF, SDF-1, and Angiopoietin-2 were also higher in preterm infants with sepsis than in control non-sepsis. In the animal experiments, injection of VEGF and SDF-1 prompted the mobilization of EPCs, leading to an improvement in survival whereas injection of anti-VEGF and anti-SDF-1 was associated with significant deterioration of survival. Overall, our results demonstrated the beneficial effects of EPC release in preterm infants with sepsis, with increased mobilization of these cells was associated with improved survival. J. Cell. Biochem. 118: 3299-3307, 2017. © 2017 Wiley Periodicals, Inc.

Prognostic efficacy of the human B-cell lymphoma prognostic genes in predicting disease-free survival (DFS) in the canine counterpart.

BACKGROUND: Canine B-cell lymphoma is deemed an ideal model of human non-Hodgkin's lymphoma where the lymphomas of both species share similar clinical features and biological behaviors. However there are some differences between tumor features in both species. In the current study, we sought to evaluate the prognostic efficacy of human B-cell lymphoma prognostic gene signatures in canine B-cell lymphoma. METHODS: The corresponding probe sets of 36 human B-cell lymphoma prognostic genes were retrieved from 2 canine B-cell lymphoma microarray datasets (GSE43664 and GSE39365) (76 samples), and prognostic probe sets were thereafter detected using the univariate and multivariate Cox proportional-hazard model and the Kaplan-Meier analysis. The two datasets were employed both as training sets and as external validation sets for each other. Results were confirmed using quantitative real-time PCR (qRT-PCR) analysis. RESULTS: In the univariate analysis, CCND1, CCND2, PAX5, CR2, LMO2, HLA-DQA1, P53, CD38, MYC-N, MYBL1, and BIRCS5 were associated with longer disease-free survival (DFS), while CD44, PLAU, and FN1 were allied to shorter DFS. However, the multivariate Cox proportional-hazard analysis confirmed CCND1 and BIRCS5 as prognostic genes for canine B-cell lymphoma. qRT-PCR used for verification of results indicated that expression level of CCND1 was significantly higher in B-cell lymphoma patients with the long DFS than ones with the short DFS, while expression level of BIRCS5 wasn't significantly different between two groups. CONCLUSION: Our results confirmed CCND1 as important gene that can be used as a potential predictor in this tumor type.

Predictive and prognostic value of TLR9 and NFKBIA gene expression as potential biomarkers for human glioma diagnosis.

BACKGROUND: Malignant gliomas are the most common form of primary intracranial tumors with the highest mortality rates. Various gene alterations are considered as prognostic markers in glioma. But, the relevant molecular mechanisms in this setting are not well-understood. OBJECTIVE: The aim of this study was to assess the association and prognostic value of TLR9 and NFKBIA with clinical significance and also their impact on patient survival in human glioma. METHODS: Expression of TLR9 and NFKBIA mRNA in the tissues was determined by immunohistochemistry and qRT-PCR methods. Kaplan-Meier curves and Cox proportional hazards regression model were used to assess the association of TLR9 and NFKBIA with clinical outcomes of patients. RESULTS: Quantitative real-time PCR analysis showed that TLR9 mRNAs is markedly expressed in glioma tissues than in non-neoplastic tissues (mean±SD: 3.26±0.40 vs. 0.71±0.36, P<0.001). There was also a significant difference between TLR9 mRNAs and high grade glioma (P<0.001).NFKBIA mRNAs was significantly identified in non-neoplastic tissues compared with glioma specimens (mean±SD: 2.76±0.30 vs. 0.94±0.35, P<0.001). Lower levels of NFKBIA mRNA were significantly related to advanced grade of gliomas (P<0.001). Furthermore, Immunoreactivity for high expression of TLR9 was detected in 65% of cases (26/40) that was associated with high grade glioma (P=0.001). No statistically significant correlation was found between TLR9 and other clinical parameters (P>0.05). Immunoreactivity for high expression of NFKBIA was observed in 32.5% (13/40) of cases and NFKBIA expression was decreased in patients with high grad glioma (P=0.014). There was no significant correlation between NFKBIA protein expression and age, sex, and relapse. The Kaplan-Meier analysis indicated that patients with high expression of TLR9 and low expression of NFKBIA are significantly related to poorer OS (P<0.001). In addition, the multivariate Cox regression model revealed that TLR9 and NFKBIA protein expressions (low/high) and tumor grade were potentially an independent predictor of survival in patients (hazard ratio, 2.132, 2.411, 2.13 [95% confidence interval, 1.825-3.782, 1.61-3.231, 1.542-3.92]; P=0.012,P=0.018, P=0.001). CONCLUSION: These data indicate that TLR9 and NFKBIA protein expressions act as independent predictor of survival for the diagnosis of glioma and a prognostic biomarker for those with a tumor at an advanced pathological grade.

Embryonic stem cell gene expression signatures in the canine mammary tumor: a bioinformatics approach.

Canine breast cancer was considered as an ideal model of comparative oncology for the human breast cancer, as there is significant overlap between biological and clinical characteristics of the human and canine breast cancer. We attempt to clarify expression profile of the embryonic stem cell (ES) gene signatures in canine breast cancer. Using microarray datasets (GSE22516 and GSE20718), expression of the three major ES gene signatures (modules or gene-sets), including Myc, ESC-like, and PRC modules, was primarily analyzed through Gene-Set Enrichment Analysis (GSEA) method in tumor and healthy datasets. For confirmation of the primary results, an additional 13 ES gene-sets which were categorized into four groups including ES expressed (ES exp1 and ES exp2), NOS targets (Nanog targets, Oct4 targets, Sox2 targets, NOS targets, and NOS TFs), Polycomb targets (Suz12 targets, Eed targets, H3K27 bound, and PRC2 targets), and Myc targets (Myc targets1, and Myc targets2) were tested in the tumor and healthy datasets. Our results revealed that there is a valuable overlap between canine and human breast cancer ES gene-sets expression profile, where Myc and ESC-like modules were up-regulated and PRC module was down-regulated in metastatic canine mammary gland tumors. Further analysis of the secondary gene-sets indicated overexpression of the ES expressed, NOS targets (Nanog targets, Oct4 targets, Sox2 targets, and NOS targets), and Myc targets and underexpression of the Polycomb targets in metastatic canine breast cancer.

Detection of Critical Genes Associated with Overall Survival (OS) and Progression-Free Survival (PFS) in Reconstructed Canine B-Cell Lymphoma Gene Regulatory Network (GRN).

Canine B-cell lymphoma GRN was reconstructed from gene expression data in the STRING and MiMI databases. Critical genes of networks were identified and correlations of critical genes with overall survival (OS) and progression-free survival (PFS) were evaluated. Significant changes were detected in the expressions of GLUL, CD44, CD79A, ARF3, FOS, BLOC1S1, FYN, GZMB, GALNT3, IFI44, CD3G, GNG2, ESRP1, and CCND1 in the STRING network and of PECAM1, GLUL, CD44, GDI1, E2F4, TLE1, CD79A, UCP2, CCND1, FYN, RHOQ, BIN1, and A2M in the MiMI network. Final survival analysis highlighted CCND1 and FOS as genes with significant correlations with OS and PFS.

Relationship between microRNA genes incidence and cancer-associated genomic regions in canine tumors: a comprehensive bioinformatics study.

The role of microRNAs (miRNAs) in human cancer biology has been confirmed on a genome-wide scale through the high incidence of these genes in cancer-associated regions. We analyzed the association between canine miRNA genes and cancer-associated regions (deleted and amplified regions) using previously published array of comparative genomic hybridization data on 268 canine cancer samples-comprising osteosarcoma, breast cancer, leukemia, and colorectal cancer. We also assessed this relationship apropos the incidence of miRNA genes in the CpG islands of the canine genome assembly. The association was evaluated using the mixed-effects Poisson regression analysis. Our analyses revealed that 135 miRNA genes were exactly located in the aberrated regions: 77 (57 %) in the loss and 58 (43 %) in amplified regions. Our findings indicated that the miRNA genes were located more frequently in the deleted regions as well as in the CpG islands than in all other regions. Additionally, with the exception of leukemia, the amplified regions significantly contained higher numbers of miRNA genes than did all the other regions.

Serological proteome analysis of dogs with breast cancer unveils common serum biomarkers with human counterparts.

Canine mammary tumor is being touted as a model for investigating the human breast cancer. Breast cancer of the both species has similar biological behavior, histopathologic characteristics, and metastatic pattern. In this study, we used the serological proteome analysis to detect autoantigens that elicit a humoral response in dogs with mammary tumor in order to identify serum biomarkers with potential usefulness as diagnostic markers and to better understand molecular mechanisms underlying canine breast cancer development. Protein extract from a cell line was subject to 2DE followed by Western blotting using sera from 15 dogs with mammary tumor and sera from 15 healthy control dogs. Immunoreactive autoantigens were subsequently identified by the MALDI-TOF MS. Four autoantigens, including manganese-superoxide dismutase, triose phosphate isomerase, alpha-enolase, and phosphoglycerate mutase1, with significantly higher immunoreactivity in the tumor samples than in the normal samples were identified as biomarker candidates. Immunohistochemistry and Western blotting revealed higher expression of these biomarkers in the malignant tumors than in the normal or benign tumors. The autoantigens found in this study have been reported to elicit autoantibody response in the human breast cancer, indicating the similarity of breast cancer proteome profile in dogs with that in human beings.

Isolation and characterization of a canine mammary cell line prepared for proteomics analysis.

Mammary cancer is the most common tumor in female dogs. Canine mammary tumor serves as an excellent model for human breast cancer biology. Cancer cell lines are routinely used as the source of protein for proteomics studies because antigen homogeneity is essential for protein profiling of tumors. In this study, we sought to isolate and characterize a canine mammary cell line that was subject to protein profiling analysis through 2-dimensional electrophoresis (2-DE) method. Mammary tumor was collected from a 6-year-old terrier dog. Tumor fragments were treated with collagenase, and dissociated cells were cultured. The cell line was subcultured over 50 times. Characterization profile included population doubling time, colony forming assay, spheroid formation/migration potency, immunocytochemistry for steroid receptors and intermediate filaments, karyotyping, RT-PCR for cytokeratins 8, 14, and 18, and 2-DE pattern. The cell line revealed three growth phases including normal, dormant, and immortal phase. Immunocytochemistry showed that the cell line was positive for estrogen receptor, pancytokeratin, cytokeratin-low and vimentin, and negative for progesterone receptor, cytokeratin-high. RT-PCR supported the immunocytochemistry results. 2-DE pattern and proteome analysis of the cell line revealed that protein composition was stable, indicating the cell line as an appropriate source of protein for canine mammary proteomics studies.

Juxtacrine and paracrine interactions of rat marrow-derived mesenchymal stem cells, muscle-derived satellite cells, and neonatal cardiomyocytes with endothelial cells in angiogenesis dynamics.

Research into angiogenesis has contributed to progress in the fast-moving field of regenerative medicine. Designing coculture systems is deemed a helpful method to understand the dynamic interaction of various cells involved in the angiogenesis process. We investigated the juxtacrine and paracrine interaction between 3 different cells, namely rat marrow-derived mesenchymal stem cells (rMSCs), rat muscle-derived satellite cells (rSCs), and rat neonatal cardiomyocytes (rCMs), and endothelial cells (ECs) during angiogenesis process. In vitro Matrigel angiogenesis assay was performed whereby ECs were monocultured or cocultured with rMSCs, rSCs, and rCMs or their conditioned media (CM). In addition, in vivo Matrigel plug assay for angiogenesis was conducted to assess the angiogenic potential of the rCM-, rMSC-, and rSC-derived CM. Our results demonstrated that the rMSCs, rSCs, and rCMs elongated along the EC tubules, whereas the rMSCs formed tube-like structures with sprouting tip cells, leading to improved angiogenesis in the coculture system. Moreover, the rMSC- and rSC-derived CM significantly improved angiogenesis tube formation on Matrigel, accelerated EC chemotaxis, and increased the arteriolar density, vascularization index, and vascularization flow index in the Matrigel plug in vivo. Western blotting showed that rMSCs secreted a high level of vascular endothelial growth factor, basic fibroblast growth factor, and stromal-derived factor-1-alpha. Tie2 is also shed from rMSCs. This study demonstrated that stem cells interact with ECs in the juxtacrine and paracrine manner during angiogenesis, and marrow MSCs have superior angiogenic properties.