High expression of SDF-1 and VEGF is associated with poor prognosis in patients with synovial sarcomas

Next-Generation Biomarkers in Multiple Myeloma: Understanding the Molecular Basis for Potential Use in Diagnosis and Prognosis

Multiple myeloma (MM) is considered to be the second most common blood malignancy and it is characterized by abnormal proliferation and an accumulation of malignant plasma cells in the bone marrow. Although the currently utilized markers in the diagnosis and assessment of MM are showing promising results, the incidence and mortality rate of the disease are still high. Therefore, exploring and developing better diagnostic or prognostic biomarkers have drawn global interest. In the present review, we highlight some of the recently reported and investigated novel biomarkers that have great potentials as diagnostic and/or prognostic tools in MM. These biomarkers include angiogenic markers, miRNAs as well as proteomic and immunological biomarkers. Moreover, we present some of the advanced methodologies that could be utilized in the early and competent diagnosis of MM. The present review also focuses on understanding the molecular concepts and pathways involved in these biomarkers in order to validate and efficiently utilize them. The present review may also help in identifying areas of improvement for better diagnosis and superior outcomes of MM.

Molecular mechanisms underpinning sarcomas and implications for current and future therapy

Sarcomas are complex mesenchymal neoplasms with a poor prognosis. Their clinical management is highly challenging due to their heterogeneity and insensitivity to current treatments. Although there have been advances in understanding specific genomic alterations and genetic mutations driving sarcomagenesis, the underlying molecular mechanisms, which are likely to be unique for each sarcoma subtype, are not fully understood. This is in part due to a lack of consensus on the cells of origin, but there is now mounting evidence that they originate from mesenchymal stromal/stem cells (MSCs). To identify novel treatment strategies for sarcomas, research in recent years has adopted a mechanism-based search for molecular markers for targeted therapy which has included recapitulating sarcomagenesis using in vitro and in vivo MSC models. This review provides a comprehensive up to date overview of the molecular mechanisms that underpin sarcomagenesis, the contribution of MSCs to modelling sarcomagenesis in vivo, as well as novel topics such as the role of epithelial-to-mesenchymal-transition (EMT)/mesenchymal-to-epithelial-transition (MET) plasticity, exosomes, and microRNAs in sarcomagenesis. It also reviews current therapeutic options including ongoing pre-clinical and clinical studies for targeted sarcoma therapy and discusses new therapeutic avenues such as targeting recently identified molecular pathways and key transcription factors.

Stromal Cell-Derived Factor 1α (SDF-1α) in Invasive Breast Cancer: Associations with Vasculo-Angiogenic Factors and Prognostic Significance

(1) Background: Tumour angiogenesis is critical for the progression of neoplasms. A prospective study was designed to examine the utility of stromal cell-derived factor 1α (SDF-1α) and selected vasculo-angiogenic parameters for estimating the probability of disease relapse in 84 primary, operable invasive breast cancer (IBrC) patients (40 (48%) with stage IA and 44 (52%) with stage IIA and IIB). (2) Methods: We explored the prognostic value of the plasma levels of SDF-1α, vascular endothelial growth factor A (VEGF-A), the soluble forms of VEGF receptors type 1 and 2, and the number of circulating endothelial progenitor cells (circulating EPCs) in breast cancer patients. The median follow-up duration was 58 months, with complete follow-up for the first event. (3) Results: According to ROC curve analysis, the optimal cut-off point for SDF-1α (for discriminating between patients at high and low risk of relapse) was 42 pg/mL, providing 57% sensitivity and 75% specificity. Kaplan-Meier curves for disease-free survival (DFS) showed that concentrations of SDF-1α lower than 42 pg/dL together with a VEGFR1 lower than 29.86 pg/mL were significantly associated with shorter DFS in IBrC patients (p = 0.0381). Patients with both SDF-1α lower than 42 pg/dL and a number of circulating EPCs lower than 9.68 cells/µL had significantly shorter DFS (p = 0.0138). (4) Conclusions: Our results imply the clinical usefulness of SDF-1α, sVEGFR1 and the number of circulating EPCs as prognostic markers for breast cancer in clinical settings.

Long non-coding RNA HOTAIR promotes the progression of synovial sarcoma through microRNA-126/stromal cell-derived factor-1 regulation

The long non-coding RNA (lncRNA) HOTAIR is an oncogene, that has been reported to be aberrantly expressed in multiple types of malignant tumor tissues. However, its expression and association with synovial sarcoma (SS) remains unclear. The present study aimed to elucidate the expression level of HOTAIR in SS tissues and also identify its role. Reverse transcription-quantitative PCR was used to detect the expression level of HOTAIR and microRNA (miR)-126 in 54 tissue samples from patients with SS, in 10 tissue samples from synovium tissues of normal patients, and in SW982 cells. The protein expression level was measured using western blot analysis and cellular immunofluorescence. Cellular proliferation, invasion and migration were assessed using MTT, Transwell and wound healing assays, respectively. HOTAIR was expressed at high levels in SS tissues. In contrast, miR-126 was expressed at low levels in SS tissues, and was negatively correlated with HOTAIR expression. HOTAIR knockdown in SW982 cells inhibited cellular proliferation in vitro, but also significantly increased the ratio of cells in the G₁/G₀ phase of the cell cycle, and decreased the ratio of cells in the G₂/S phase. In addition, HOTAIR knockdown inhibited the invasion and migration of the SW982 cells, as observed in the Transwell and wound healing assays. Furthermore, HOTAIR knockdown increased miR-126 expression level and decreased the expression level of stromal cell-derived factor-1 (SDF-1) at the protein level. On the other hand, while miR-126-mimic decreased the protein expression level of SDF-1, miR-126-inhibitor increased its expression level in SW982 cells. Notably, HOTAIR knockdown or SDF-1 knockout significantly decreased the protein expression levels of CDK1, CDK2, cyclin D1, MMP-9, vimentin and N-cadherin, and significantly increased the protein expression levels of p21, p53 and E-cadherin in SW982 cells. HOTAIR was highly expressed in SS tissues, wherein it could promote the proliferation, invasion and migration of SS cells by increasing the expression of SDF-1 via miR-126 inhibition.

Identification of Metastasis-Associated Biomarkers in Synovial Sarcoma Using Bioinformatics Analysis

Synovial sarcoma (SS) is a highly aggressive soft tissue tumor with high risk of local recurrence and metastasis. However, the mechanisms underlying SS metastasis are still largely unclear. The purpose of this study is to screen metastasis-associated biomarkers in SS by integrated bioinformatics analysis. Two mRNA datasets (GSE40018 and GSE40021) were selected to analyze the differentially expressed genes (DEGs). Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), functional and pathway enrichment analyses were performed for DEGs. Then, the protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. The module analysis of the PPI network and hub genes validation were performed using Cytoscape software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the hub genes were performed using WEB-based GEne SeT AnaLysis Toolkit (WebGestalt). The expression levels and survival analysis of hub genes were further assessed through Gene Expression Profiling Interactive Analysis (GEPIA) and the Kaplan-Meier plotter database. In total, 213 overlapping DEGs were identified, of which 109 were upregulated and 104 were downregulated. GO analysis revealed that the DEGs were predominantly involved in mitosis and cell division. KEGG pathways analysis demonstrated that most DEGs were significantly enriched in cell cycle pathway. GSEA revealed that the DEGs were mainly enriched in oocyte meiosis, cell cycle and DNA replication pathways. A key module was identified and 10 hub genes (CENPF, KIF11, KIF23, TTK, MKI67, TOP2A, CDC45, MELK, AURKB, and BUB1) were screened out. The expression and survival analysis disclosed that the 10 hub genes were upregulated in SS patients and could result in significantly reduced survival. Our study identified a series of metastasis-associated biomarkers involved in the progression of SS, and may provide novel therapeutic targets for SS metastasis.