miR-877 inhibits the proliferation, migration, and invasion of osteosarcoma cells by targeting gamma-glutamylcyclotransferase

The GGCT and REST positive feedback loop promotes tumor growth in Glioma

BACKGROUND

γ-Glutamylcyclotransferase (GGCT), an enzyme crucial in glutathione metabolism, has emerged as a participant in tumorigenesis. The present study is designed to elucidate the biological role and molecular mechanisms underlying GGCT in glioma.

METHODS

Gene Expression Profiling Interactive Analysis (GEPIA), Chinese Glioma Genome Atlas (CGGA), and PrognoScan online databases were utilized to examine the expressions and clinical prognosis of GGCT and REST in glioma. Cell Counting Kit-8 (CCK-8), Transwell, Wound healing, and Flow cytometric assays, and RNA-sequencing analysis were employed to uncover the molecular role of GGCT and REST. Prediction of Differentially expressed microRNA (DE-miRNAs) and miRNAs targeting GGCT 3' Untranslated Region (UTR) was performed using miRanda online datasets. Finally, Real time-quantitative Polymerase Chain Reaction (RT-qPCR), western blot and dual luciferase reporter gene activity analysis were employed to confirm a positive feedback loop involving GGCT/REST/miR-34a-5p in glioma cells.

RESULTS

High expression of GGCT was correlated with poor prognosis in glioma. GGCT silencing demonstrated inhibitory effects on the proliferation, migration, and induction of apoptosis in T98G and U251 cells. Mechanistically, GGCT downregulated REST expression and modulated cancer-associated pathways in glioma cells. High expression of REST was associated with poor prognosis in glioma. In vitro and in vivo experiments showed that REST overexpression restored the repression of proliferation, invasion, migration, and xenograft tumor formation induced by GGCT knockdown. Furthermore, the study uncovered that REST inhibited miR-34a-5p mRNA expression, and miR-34a-5p suppressed GGCT expression by targeting its 3'UTR, forming a positive regulatory loop in glioma. Notably, the inhibitor of miR-34a-5p restored the role of REST silencing in decreasing GGCT expression in glioma cells.

CONCLUSIONS

GGCT/REST/miR-34a-5p axis holds promising potential as a therapeutic target, offering a potential breakthrough in the treatment of glioma.

Machine learning-based cell death marker for predicting prognosis and identifying tumor immune microenvironment in prostate cancer

Background

Prostate cancer (PCa) incidence and mortality rates are rising, necessitating precise prognostic tools to guide personalized treatment. Dysregulation of programmed cell death pathways in tumor suppression and cancer development has garnered increasing attention, providing a new research direction for identifying biomarkers and potential therapeutic targets.

Methods

Integrating multiple database resources, we constructed and optimized a prognostic signature based on the expression of programmed cell death-related genes (PCDRG) using ten machine learning algorithms. Model performance and prognostic effects were further evaluated. We analyzed the relationships between signature and clinicopathological features, somatic mutations, drug sensitivity, and the tumor immune microenvironment, and constructed a nomogram. The expression level of PCDRGs were evaluated and compared.

Results

Of 1560 PCDRGs, 149 were differentially expressed in PCa, with 34 associated with biochemical recurrence. The PCDRG-derived index (PCDI), constructed using the random forest algorithm, exhibited optimal prognostic performance, successfully stratifying PCa patients into two groups with significant prognostic differences. Patients with high PCDI scores exhibited poorer survival and lower immunotherapy benefit. PCDI was closely associated with the infiltration of specific immune cells, particularly positive correlations with macrophages and T helper cells, and negative correlations with neutrophils, suggesting that PCDI may influence the tumor immune microenvironment, thereby affecting patient prognosis and treatment response. PCDI was associated with age, pathological stage, somatic mutations, and drug sensitivity. The PCDI-based nomogram demonstrated excellent performance in predicting biochemical recurrence in PCa patients. Finally, the differential expression of these PCDRGs was verified based on cell lines and PCa patient expression profile data.

Conclusion

This study developed an effective prognostic indicator for prostate cancer, PCDI, using machine learning approaches. PCDI reflects the link between aberrant programmed cell death pathways and disease progression and treatment response.

Profiling of microRNAs by next-generation sequencing: Potential biomarkers for diffuse large B-cell lymphoma

Background

Lymphoma ranks fifth in prevalence among common cancer types worldwide. This lymphatic system cancer arises from T or B cells. Diffuse large B cell lymphomas (DLBCLs) are associated with most non-Hodgkin lymphomas. Non-coding microRNAs (miRNAs) greatly affect gene expression. A single miRNA can target numerous genes, thus largely influencing gene expression networks. MiRNAs can act as oncogenes or tumor suppressors in controlling DLBCL progression. This study investigated the roles of miRNAs in patients with DLBCL through next-generation sequencing, which was found to be sensitive, accurate, and robust.

Methods

The study involved seven patients with DLBCLs and three controls at a hematology-oncology clinic. MiRNA was extracted from existing formalin-fixed, paraffin-embedded (FFPE) tissue specimens. Illumina next-generation sequencing was used to sequence samples for miRNA profiling.

Results

Samples from patients showed expression of various hsa-mir miRNAs (1248, 3607, 21, 142, 1244, 182, 6516, 766, 1291, 4449, and 181a), whereas those from healthy individuals showed expression of hsa-mir 1248, 3607, 21, 142, and 877. Hsa-mir-877-3p is known to target multiple genes, and miRNAs such as hsa-mir-877-3p, hsa-mir-1291, and hsa-mir-181a-5p interact primarily with target genes.

Conclusions

MiRNA profiling in FFPE tissues from patients with DLBCL suggested that miRNA levels can distinguish patients with DLBCL from controls, and therefore may provide prognostic or diagnostic biomarkers for DLBCL. Altered genes and miRNAs may also be potential therapeutic targets.

BMSC-EV-derived lncRNA NORAD Facilitates Migration, Invasion, and Angiogenesis in Osteosarcoma Cells by Regulating CREBBP via Delivery of miR-877-3p

Bone marrow mesenchymal stem cells (BMSCs) can boost osteosarcoma (OS) cell proliferation and invasion, yet the function of extracellular vesicles (EVs) derived from BMSCs on OS is scarcely known. This study is aimed at examining the role of BMSC-EVs in OS cells. BMSCs and BMSC-EVs were isolated and identified. The effect of EVs and EVs-si-NORAD on OS cell proliferation, invasion, migration, and angiogenesis was determined. Expressions of NORAD, miR-877-3p, and CREBBP were detected. The binding relationship among NORAD, miR-877-3p, and CREBBP was verified. The miR-877-3p inhibitor or pc-CREBBP was delivered into OS cells treated with EVs-si-NORAD for in vitro analysis. The nude mouse model of the subcutaneous tumor xenograft was established for in vivo analysis. BMSC-EVs promoted OS cell proliferation, invasion, migration, and angiogenesis. BMSC-EVs carried NORAD into OS cells and upregulated CREBBP by sponging miR-877-3p. miR-877-3p downregulation or CREBBP overexpression partly inverted the inhibitory effect of EVs by silencing NORAD on OS cell proliferation, invasion, migration, and angiogenesis. In vivo experiments validated that BMSC-EV-derived NORAD facilitated tumor growth by upregulating CREBBP via miR-877-3p. To conclude, BMSC-EV-derived NORAD facilitated OS cell proliferation, invasion, migration, and angiogenesis by modulating CREBBP via miR-877-3p, which may offer new insights into OS treatment.