Analysis of Hub Genes Involved in Distinction Between Aged and Fetal Bone Marrow Mesenchymal Stem Cells by Robust Rank Aggregation and Multiple Functional Annotation Methods

The dark side of adipose-derived mesenchymal stromal cells in cutaneous oncology: roles, expectations, and potential pitfalls

Adipose-derived stromal cells (ADSCs) have well-established regenerative and immunomodulatory properties. For such reasons, ADSCs are currently under investigation for their use in the setting of both regenerative medicine and autoimmune diseases. As per dermatological disorders, MSC-based strategies represent potential therapeutic tools not only for chronic ulcers and wound healing, but also for immune-mediated dermatoses. However, a growing body of research has been focusing on the role of MSCs in human cancers, due to the potential oncological risk of using MSC-based strategies linked to their anti-apoptotic, pro-angiogenic and immunosuppressive properties. In the dermatological setting, ADSCs have shown not only to promote melanoma growth and invasiveness, but also to induce drug-resistance. On the other hand, genetically modified ADSCs have been demonstrated to efficiently target therapies at tumor sites, due to their migratory properties and their peculiar tropism for cancer microenvironment. The present review briefly summarizes the findings published so far on the use of ADSCs in the dermato-oncological setting, with the majority of data being available for melanoma.

Immunomodulating Profile of Dental Mesenchymal Stromal Cells: A Comprehensive Overview

Dental mesenchymal stromal cells (MSCs) are multipotent cells present in dental tissues, characterized by plastic adherence in culture and specific surface markers (CD105, CD73, CD90, STRO-1, CD106, and CD146), common to all other MSC subtypes. Dental pulp, periodontal ligament, apical papilla, human exfoliated deciduous teeth, alveolar bone, dental follicle, tooth germ, and gingiva are all different sources for isolation and expansion of MSCs. Dental MSCs have regenerative and immunomodulatory properties; they are scarcely immunogenic but actively modulate T cell reactivity. in vitro studies and animal models of autoimmune diseases have provided evidence for the suppressive effects of dental MSCs on peripheral blood mononuclear cell proliferation, clearance of apoptotic cells, and promotion of a shift in the Treg/Th17 cell ratio. Appropriately stimulated MSCs produce anti-inflammatory mediators, such as transforming growth factor-β (TGF-β), prostaglandin E2, and interleukin (IL)-10. A particular mechanism through which MSCs exert their immunomodulatory action is via the production of extracellular vesicles containing such anti-inflammatory mediators. Recent studies demonstrated MSC-mediated inhibitory effects both on monocytes and activated macrophages, promoting their polarization to an anti-inflammatory M2-phenotype. A growing number of trials focusing on MSCs to treat autoimmune and inflammatory conditions are ongoing, but very few use dental tissue as a cellular source. Recent results suggest that dental MSCs are a promising therapeutic tool for immune-mediated disorders. However, the exact mechanisms responsible for dental MSC-mediated immunosuppression remain to be clarified, and impairment of dental MSCs immunosuppressive function in inflammatory conditions and aging must be assessed before considering autologous MSCs or their secreted vesicles for therapeutic purposes.

An Robust Rank Aggregation and Least Absolute Shrinkage and Selection Operator Analysis of Novel Gene Signatures in Dilated Cardiomyopathy

Objective: Dilated cardiomyopathy (DCM) is a heart disease with high mortality characterized by progressive cardiac dilation and myocardial contractility reduction. The molecular signature of dilated cardiomyopathy remains to be defined. Hence, seeking potential biomarkers and therapeutic of DCM is urgent and necessary.

Methods: In this study, we utilized the Robust Rank Aggregation (RRA) method to integrate four eligible DCM microarray datasets from the GEO and identified a set of significant differentially expressed genes (DEGs) between dilated cardiomyopathy and non-heart failure. Moreover, LASSO analysis was carried out to clarify the diagnostic and DCM clinical features of these genes and identify dilated cardiomyopathy derived diagnostic signatures (DCMDDS).

Results: A total of 117 DEGs were identified across the four microarrays. Furthermore, GO analysis demonstrated that these DEGs were mainly enriched in the regulation of inflammatory response, the humoral immune response, the regulation of blood pressure and collagen–containing extracellular matrix. In addition, KEGG analysis revealed that DEGs were mainly enriched in diverse infected signaling pathways. Moreover, Gene set enrichment analysis revealed that immune and inflammatory biological processes such as adaptive immune response, cellular response to interferon and cardiac muscle contraction, dilated cardiomyopathy are significantly enriched in DCM. Moreover, Least absolute shrinkage and selection operator (LASSO) analyses of the 18 DCM-related genes developed a 7-gene signature predictive of DCM. This signature included ANKRD1, COL1A1, MYH6, PERELP, PRKACA, CDKN1A, and OMD. Interestingly, five of these seven genes have a correlation with left ventricular ejection fraction (LVEF) in DCM patients.

Conclusion: Our present study demonstrated that the signatures could be robust tools for predicting DCM in clinical practice. And may also be potential treatment targets for clinical implication in the future.

A Five-Gene-Based Prognostic Signature for Hepatocellular Carcinoma

Objective: This study intends to identify potential prognostic marker genes associated with the prognosis of patients suffering from hepatocellular carcinoma (HCC) based on TCGA and GEO analysis.

Methods: TCGA-LIHC cohort was downloaded and the data related to HCC were extracted from The Cancer Genome Atlas (TCGA) database and subjected to differential analysis. HCC-related gene expression datasets were retrieved from the GEO database, followed by differential analysis. After intersection of the results of TCGA and GEO databases, gene interaction analysis was performed to obtain the core genes. To identify the genes related to the prognosis of HCC patients, we conducted univariate and multivariate Cox analyses.

Results: Based on differential analysis of TCGA database, 854 genes were differentially expressed in HCC, any of which might link to the occurrence and progression of HCC. Meanwhile, joint analysis of HCC-related gene expression datasets in the GEO database screened 214 genes. Five core genes CDC20, TOP2A, RRM2, UBE2C and AOX1 were significantly associated with the prognosis of HCC patients and the risk model based on these five genes effectively predicted the prognosis of HCC patients.

Conclusion: Collectively, our data suggest that CDC20, TOP2A, RRM2, UBE2C and AOX1 may be the key genes affecting the prognosis of patients with HCC. The five-gene signature could accurately predict the prognosis of HCC patients.