MiR-18a-3p improves cartilage matrix remodeling and inhibits inflammation in osteoarthritis by suppressing PDP1

Identification of shared gene signatures and pathways for diagnosing osteoporosis with sarcopenia through integrated bioinformatics analysis and machine learning

BACKGROUND

Prior studies have suggested a potential relationship between osteoporosis and sarcopenia, both of which can present symptoms of compromised mobility. Additionally, fractures among the elderly are often considered a common outcome of both conditions. There is a strong correlation between fractures in the elderly population, decreased muscle mass, weakened muscle strength, heightened risk of falls, and diminished bone density. This study aimed to pinpoint crucial diagnostic candidate genes for osteoporosis patients with concomitant sarcopenia.

METHODS

Two osteoporosis datasets and one sarcopenia dataset were obtained from the Gene Expression Omnibus (GEO). Differential expression genes (DEGs) and module genes were identified using Limma and Weighted Gene Co-expression Network Analysis (WGCNA), followed by functional enrichment analysis, construction of protein-protein interaction (PPI) networks, and application of a machine learning algorithm (least absolute shrinkage and selection operator (LASSO) regression) to determine candidate hub genes for diagnosing osteoporosis combined with sarcopenia. Receiver operating characteristic (ROC) curves and column line plots were generated.

RESULTS

The merged osteoporosis dataset comprised 2067 DEGs, with 424 module genes filtered in sarcopenia. The intersection of DEGs between osteoporosis and sarcopenia module genes consisted of 60 genes, primarily enriched in viral infection. Through construction of the PPI network, 30 node genes were filtered, and after machine learning, 7 candidate hub genes were selected for column line plot construction and diagnostic value assessment. Both the column line plots and all 7 candidate hub genes exhibited high diagnostic value (area under the curve ranging from 1.00 to 0.93).

CONCLUSION

We identified 7 candidate hub genes (PDP1, ALS2CL, VLDLR, PLEKHA6, PPP1CB, MOSPD2, METTL9) and constructed column line plots for osteoporosis combined with sarcopenia. This study provides reference for potential peripheral blood diagnostic candidate genes for sarcopenia in osteoporosis patients.

PDP1 promotes the progression of breast cancer through STAT3 pathway

This study aimed to investigate the expression pattern and mechanisms of Pyruvate Dehydrogenase Phosphatase Catalytic Subunit 1 (PDP1) in the progression of breast cancer (BC). PDP1, known for its involvement in cell energy metabolism, was found to be overexpressed in BC tissues. Notably, low PDP1 expression aligns with improved overall survival (OS) in BC patients. In this study, we found that PDP1 was overexpressed among BC tissues and low PDP1 expression showed a better prognosis for the patients with BC. PDP1 knockdown suppressed cell amplification and migration and triggered cell apoptosis in BC cells. In vivo assessments through a xenograft model unveiled the pivotal role and underlying mechanisms of PDP1 knockdown. RNA sequencing and kyoto encyclopedia of genes and genomes analysis of RNAs from PDP1 knockdown and normal MCF7 cells revealed 1440 differentially expressed genes, spotlighting the involvement of the JAK/STAT3 signaling pathway in BC progression. Western blot results implied that PDP1 knockdown led to a loss of p-STAT3, whereas overexpression of PDP1 induced the p-STAT3 expression. Cell counting kit-8 assay showed that PDP1 overexpression significantly raised MDA-MB-231 and MCF7 cell viability while STAT3 inhibitor S3I-201 recovered the cell growth to normal level. To summarize, PDP1 promotes the progression of BC through STAT3 pathway by regulating p-STAT3. The findings contribute to understanding the molecular mechanisms underlying BC progression, and opening avenues for targeted therapeutic approaches.

MicroRNAs in idiopathic inflammatory myopathies: state-of-the-art and future perspectives

PURPOSE OF REVIEW

Idiopathic inflammatory myopathies (IIMs) are a group of rare autoimmune disorders characterized by muscle weakness and inflammation. MicroRNAs (miRNAs) are the main class of small noncoding RNAs regulating a wide range of physiological and pathological processes and play a role in mediating autoimmunity and inflammation. In this review, we summarize the latest knowledge on the role of miRNAs in systemic autoimmune diseases with particular focus on IIMs.

RECENT FINDINGS

Study on miRNA expression in IIMs is helping in understanding the pathogenetic basis of the disease at a tissue and systemic level. Several miRNAs, even with a muscle-specific expression (myomiRs), have been shown to be involved in immune and nonimmune mechanisms of myofiber damage. MiRNAs modulate and orchestrate the local inflammatory infiltrate and could be used as potential biomarkers as they correlate with disease activity and response to therapy.

SUMMARY

IIMs comprise different clinical phenotypes and still little is known about the molecular signature of each subset. Further research about miRNA profiling will provide additional insights in the disease characterization with an expected impact on the therapeutic strategies.

Multiplex Analysis of Cerebrospinal Fluid and Serum Exosomes MicroRNAs of Untreated Relapsing Remitting Multiple Sclerosis (RRMS) and Proposing Noninvasive Diagnostic Biomarkers

Exosomal microRNAs (miRNAs) are emerging diagnostic biomarkers for neurodegenerative diseases. In this study, we aimed to detect relapsing-remitting multiple sclerosis (RRMS)-specific miRNAs in cerebrospinal fluid (CSF) and serum exosomes with diagnostic potential. One ml of CSF and serum sample were collected from each of the 30 untreated RRMS patients and healthy controls (HCs). A panel of 18 miRNAs affecting inflammatory responses was applied, and qRT-PCR was conducted to detect differentially expressed exosomal miRNAs in CSF and serum of RRMS patients. We identified that 17 out of 18 miRNAs displayed different patterns in RRMS patients compared to HCs. Let-7 g-5p, miR-18a-5p, miR-145-5p, and miR-374a-5p with dual pro-inflammatory and anti-inflammatory actions and miR-150-5p and miR-342-3p with anti-inflammatory action were significantly upregulated in both CSF and serum-derived exosomes of RRMS patients compared to corresponding HCs. Additionally, anti-inflammatory miR-132-5p and pro-inflammatory miR-320a-5p were significantly downregulated in both CSF and serum-derived exosomes of RRMS patients compared to HCs. Ten of 18 miRNAs were differentially expressed in CSF and serum exosomes of the patients. Furthermore, miR-15a-5p, miR-19b-3p, and miR-432-5p were upregulated, and miR-17-5p was downregulated only in CSF exosomes. Interestingly, U6 housekeeping gene was differentially expressed in CSF and serum exosomes, in both RRMS and HCs. As the first report describing CSF exosomal miRNAs expression profile compared to that of serum exosomes in untreated RRMS patients, we showed that CSF and serum exosomes are not identical in terms of biological compounds and display different patterns in miRNAs and U6 expression.

miR-17-92 cluster in osteoarthritis: Regulatory roles and clinical utility

Osteoarthritis (OA) is the most prevalent articular disease, especially in aged population. Caused by multi-factors (e.g., trauma, inflammation, and overloading), OA leads to pain and disability in affected joints, which decreases patients' quality of life and increases social burden. In pathophysiology, OA is mainly characterized by cartilage hypertrophy or defect, subchondral bone sclerosis, and synovitis. The homeostasis of cell-cell communication is disturbed as well in such pro-inflammatory microenvironment, which provides clues for the diagnosis and treatment of OA. MicoRNAs (miRNAs) are endogenous non-coding RNAs that regulate various processes via post-transcriptional mechanisms. The miR-17-92 cluster is an miRNA polycistron encoded by the host gene called MIR17HG. Mature miRNAs generated from MIR17HG participate in biological activities such as oncogenesis, neurogenesis, and modulation of the immune system. Accumulating evidence also indicates that the expression level of miRNAs in the miR-17-92 cluster is tightly related to the pathological processes of OA, such as chondrocyte apoptosis, extracellular matrix degradation, bone remodeling, and synovitis. In this review, we aim to summarize the roles of the miR-17-92 cluster in the underlying molecular mechanism during the development and progression of OA and shed light on the new avenue of the diagnosis and treatment of OA.

PDP1 Promotes Cell Malignant Behavior and Is Associated with Worse Clinical Features in Ovarian Cancer Patients: Evidence from Bioinformatics and In Vitro Level

PDP1 has been reported in multiple diseases. However, it has not been fully explored in ovarian cancer (OC). The public data was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed gene analysis was conducted out using the limma package. Prognosis analysis was performed using the survival package. Gene Set Enrichment Analysis (GSEA) was performed using the fgsea package. Immune infiltration analysis was performed based on the CIBERSORT algorithm. CCK8 assay was used to evaluate the cell proliferation ability of cancer cells. Transwell assay was used for the invasion and migration ability. Our result showed that PDP1 was overexpressed in OC tissue in RNA and protein level based on multiple databases (TCGA, GSE18520, GSE27651, and GSE54388). At the same time, we found PDP1 was correlated with poor prognosis and worse clinical parameters. In vitro experiment showed that PDP1 could significantly promote proliferation, invasion, and migration ability of OC cells. GSEA analysis showed that in the OC patients with high PDP1 expression, the pathway of IL6/JAK/STAT3 signaling, interferon-alpha response, apoptosis, adipogenesis, KRAS signaling, and IL2/STAT5 signaling was activated, which might be responsible for its oncogenic effect in OC. Immune infiltration analysis indicated that PDP1 was positively correlated with activated myeloid dendritic cells, resting CD4 memory T cells, neutrophil, and M1 and M2 macrophages, yet negatively correlated with M0 macrophages, plasma B cells, γδT cells, and activated CD4 memory T cells. Drug sensitivity analysis showed a negative correlation between PDP1 expression and the IC50 of bleomycin and gemcitabine, yet a positive correlation of cisplatin, indicating that the OC patients with high PDP1 expression might be more sensitive to bleomycin and gemcitabine and more resistant to cisplatin. PDP1 could facilitate OC progression and is associated with patient prognosis and chemosensitivity, making it an underlying biomarker of OC.