Diagnostic signature, subtype classification, and immune infiltration of key m6A regulators in osteomyelitis patients

The Role of mRNA Modifications in Bone Diseases

As a type of epigenetic modifications, mRNA modifications regulate the metabolism of mRNAs, thereby influencing gene expression. Previous studies have indicated that dysregulation of mRNA modifications is closely associated with the occurrence and progression of bone diseases (BDs). In this study, we first introduced the dynamic regulatory processes of five major mRNA modifications and their effects on the nucleus export, stability, and translation of mRNAs. We then summarized the mechanisms of mRNA modifications involved in the development of osteoporosis, osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, fractures, osteomyelitis, and osteosarcoma. Finally, we reviewed therapeutic strategies for BDs based on the above mechanisms, focusing on regulating osteoblast and osteoclast differentiation, inhibiting cellular senescence and injury, and alleviating inflammation. This review identified mRNA modifications as potential targets for treating BDs and proposes perspectives on the diversity, targetability, and safety of mRNA-modifying therapies.

METTL3 accelerates staphylococcal protein A (SpA)-induced osteomyelitis progression by regulating m6A methylation-modified miR-320a

Osteomyelitis (OM) is an inflammatory disease of bone infection and destruction characterized by dysregulation of bone homeostasis. Staphylococcus aureus (SA) has been reported to be the most common pathogen causing infectious OM. Recent studies have demonstrated that N6-methyladenosine (m6A) regulators are associated with the development of OM. However, the molecular mechanism of m6A modifications in OM remains unclear. Here, we investigated the function of methyltransferase-like 3 (METTL3)-mediated m6A modification in OM development. In this study, human bone mesenchymal stem cells (hBMSCs) were treated with staphylococcal protein A (SpA), a vital virulence factor of SA, to construct cell models of OM. Firstly, we found that METTL3 was upregulated in OM patients and SpA-induced hBMSCs, and SpA treatment suppressed osteogenic differentiation and induced oxidative stress and inflammatory injury in hBMSCs. Functional experiments showed that METTL3 knockdown alleviated the inhibition of osteogenic differentiation and the promotion of oxidative stress and inflammation in SpA-treated hBMSCs. Furthermore, METTL3-mediated m6A modification upregulated miR-320a expression by promoting pri-miR-320a maturation, and the mitigating effects of METTL3 knockdown on SpA-mediated osteogenic differentiation, oxidative stress and inflammatory responses can be reversed by miR-320 mimic. In addition, we demonstrated that phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) was a downstream target of miR-320a, upregulation of PIK3CA alleviated miR-320a-induced inhibition of osteogenic differentiation, and upregulation of oxidative stress and inflammatory responses during SpA infection. Finally, we found that silencing METTL3 alleviated OM development by regulating the miR-320a/PIK3CA axis. Taken together, our data demonstrated that the METTL3/m6A/miR-320a/PIK3CA axis regulated SpA-mediated osteogenic differentiation, oxidative stress, and inflammatory responses in OM, which may provide a new therapeutic strategy for OM patients.

Integrated single-cell and bulk RNA sequencing analysis reveal immune-related biomarkers in postmenopausal osteoporosis

Background

Postmenopausal osteoporosis (PMOP) represents as a significant health concern, particularly as the population ages. Currently, there is a paucity of comprehensive descriptions regarding the immunoregulatory mechanisms and early diagnostic biomarkers associated with PMOP. This study aims to examine immune-related differentially expressed genes (IR-DEGs) in the peripheral blood mononuclear cells of PMOP patients to identify immunological patterns and diagnostic biomarkers.

Methods

The GSE56815 dataset from the Gene Expression Omnibus (GEO) database was used as the training group, while the GSE2208 dataset served as the validation group. Initially, differential expression analysis was conducted after data integration to identify IR-DEGs in the peripheral blood mononuclear cells of PMOP. Subsequently, feature selection of these IR-DEGs was performed using RF, SVM-RFE, and LASSO regression models. Additionally, the expression of IR-DEGs in distinct bone marrow cell subtypes was analyzed using single-cell RNA sequencing (scRNA-seq) datasets, allowing the identification of cellular communication patterns within various cell subgroups. Finally, molecular subtypes and diagnostic models for PMOP were constructed based on these selected IR-DEGs. Furthermore, the expression levels of characteristic IR-DEGs were examined in rat osteoporosis (OP) models.

Results

Using machine learning, six IR-DEGs (JUN, HMOX1, CYSLTR2, TNFSF8, IL1R2, and SSTR5) were identified. Subsequently, two molecular subtypes of PMOP (subtype 1 and subtype 2) were established, with subtype 1 exhibiting a higher proportion of M1 macrophage infiltration. Analysis of the scRNA-seq dataset revealed 11 distinct cell clusters. It was noted that JUN was significantly overexpressed in M1 macrophages, while HMOX1 showed a marked elevation in endothelial cells and M2 macrophages. Cell communication results suggested that the PMOP microenvironment features increased interactions among M2 macrophages, CD8+ T cells, Tregs, and fibroblasts. The diagnostic model based on these six IR-DEGs demonstrated excellent diagnostic performance (AUC = 0.927). In the OP rat model, the expression of IL1R2 and TNFSF8 were significantly elevated.

Conclusion

JUN, HMOX1, CYSLTR2, TNFSF8, IL1R2, and SSTR5 may serve as promising molecular targets for diagnosing and subtyping patients with PMOP. These results offer novel perspectives on the early diagnosis of PMOP and the advancement of personalized immune-based therapies.

Integrative gene expression analysis and animal model reveal immune- and autophagy-related biomarkers in osteomyelitis

BACKGROUND

Osteomyelitis (OM) is recognized as a significant challenge in orthopedics due to its complex immune and inflammatory responses. The prognosis heavily depends on timely diagnosis, accurate classification, and assessment of severity. Thus, the identification of diagnostic and classification-related genes from an immunological standpoint is crucial for the early detection and tailored treatment of OM.

METHODS

Transcriptomic data for OM was sourced from the Gene Expression Omnibus (GEO) database, leading to the identification of autophagy- and immune-related differentially expressed genes (AIR-DEGs) through differential expression analysis. Diagnostic and classification models were subsequently developed. The CIBERSORT algorithm was utilized to examine immune cell infiltration in OM, and the relationship between OM clusters and various immune cells was explored. Key AIR-DEGs were further validated through the creation of OM animal models.

RESULTS

Analysis of the transcriptomic data revealed three AIR-DEGs that played a significant role in immune responses and pathways. Nomogram and receiver operating characteristic curve analyses were performed, demonstrating excellent diagnostic capability for differentiating between OM patients and healthy individuals, with an area under the curve of 0.814. An unsupervised clustering analysis discerned two unique patterns of autophagy- and immune-related genes, as well as gene patterns. Further exploration into immune infiltration exhibited notable variances across different subtypes, especially between OM cluster 1 and gene cluster A, highlighting their potential role in mitigating inflammatory responses by regulating immune activities. Moreover, the mRNA and protein expression levels of three AIR-DEGs in the animal model were aligned with those in the training and validation data sets.

CONCLUSIONS

From an immunological perspective, a diagnostic model was successfully developed, and two distinct clustering patterns were identified. These contributions offer a significant resource for the early detection and personalized immunotherapy of patients with OM.

Targeting leucine-rich PPR motif-containing protein/LRPPRC by 5,7,4'-trimethoxyflavone suppresses esophageal squamous cell carcinoma progression

JAK2/STAT3/MYC axis is dysregulated in nearly 70 % of human cancers, but targeting this pathway therapeutically remains a big challenge in cancer therapy. In this study, genes associated with JAK2, STAT3, and MYC were analyzed, and potential target genes were selected. Leucine-rich PPR motif-containing protein (LRPPRC) whose function and regulation are not fully understood, emerged as one of top 3 genes in terms of RNA epigenetic modification. Here, we demonstrate LRPPRC may be an independent prognostic indicator besides JAK2, STAT3, and MYC. Mechanistically, LRPPRC impairs N6-methyladenosine (m6A) modification of JAK2, STAT3, and MYC to facilitate nuclear mRNA export and expression. Meanwhile, excess LRPPRC act as a scaffold protein binding to JAK2 and STAT3 to enhance stability of JAK2-STAT3 complex, thereby facilitating JAK2/STAT3/MYC axis activation to promote esophageal squamous cell carcinoma (ESCC) progression. Furthermore, 5,7,4'-trimethoxyflavone was verified to bind to LRPPRC, STAT3, and CDK1, dissociating LRPPRC-JAK2-STAT3 and JAK2-STAT3-CDK1 interaction, leading to impaired tumorigenesis in 4-Nitroquinoline N-oxide induced ESCC mouse models and suppressed tumor growth in ESCC patient derived xenograft mouse models. In summary, this study suggests regulation of m6A modification by LRPPRC, and identifies a novel triplex target compound, suggesting that targeting LRPPRC-mediated JAK2/STAT3/MYC axis may overcome JAK2/STAT3/MYC dependent tumor therapeutic dilemma.

N6-Methyladenosine in Cell-Fate Determination of BMSCs: From Mechanism to Applications

The methylation of adenosine base at the nitrogen-6 position is referred to as "N6-methyladenosine (m6A)" and is one of the most prevalent epigenetic modifications in eukaryotic mRNA and noncoding RNA (ncRNA). Various m6A complex components known as "writers," "erasers," and "readers" are involved in the function of m6A. Numerous studies have demonstrated that m6A plays a crucial role in facilitating communication between different cell types, hence influencing the progression of diverse physiological and pathological phenomena. In recent years, a multitude of functions and molecular pathways linked to m6A have been identified in the osteogenic, adipogenic, and chondrogenic differentiation of bone mesenchymal stem cells (BMSCs). Nevertheless, a comprehensive summary of these findings has yet to be provided. In this review, we primarily examined the m6A alteration of transcripts associated with transcription factors (TFs), as well as other crucial genes and pathways that are involved in the differentiation of BMSCs. Meanwhile, the mutual interactive network between m6A modification, miRNAs, and lncRNAs was intensively elucidated. In the last section, given the beneficial effect of m6A modification in osteogenesis and chondrogenesis of BMSCs, we expounded upon the potential utility of m6A-related therapeutic interventions in the identification and management of human musculoskeletal disorders manifesting bone and cartilage destruction, such as osteoporosis, osteomyelitis, osteoarthritis, and bone defect.

Identification of molecular subgroups in osteomyelitis induced by staphylococcus aureus infection through gene expression profiles

BACKGROUND

Staphylococcus aureus (S. aureus) infection-induced osteomyelitis (OM) is an inflammatory bone disease accompanied by persistent bone destruction, and the treatment is challenging because of its tendency to recur. Present study was aimed to explore the molecular subgroups of S. aureus infection-induced OM and to deepen the mechanistic understanding for molecularly targeted treatment of OM.

METHODS

Integration of 164 OM samples and 60 healthy samples from three datasets of the Gene Expression Omnibus (GEO) database. OM patients were classified into different molecular subgroups based on unsupervised algorithms and correlations of clinical characteristics between subgroups were analyzed. Next, The CIBERSORT algorithm was used to evaluate the proportion of immune cell infiltration in different OM subgroups. Weighted gene co-expression analysis (WGCNA) was used to identify different gene modules and explore the relationship with clinical characteristics, and further annotated OM subgroups and gene modules by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

RESULTS

Two subgroups with excellent consistency were identified in this study, subgroup and hospital length of stay were independent predictors of OM. Compared with subgroup I, OM patients in subgroup II had longer hospital length of stay and more severe disease. Meanwhile, the infiltration proportions of monocytes and macrophages M0 were higher in patients of OM subgroup II. Finally, combined with the characteristics of the KEGG enrichment modules, the expression of osteoclast differentiation-related genes such as CTSK was upregulated in OM subgroup II, which may be closely associated with more severe OM patients.

CONCLUSION

The current study showed that OM subgroup II had longer hospital length of stay and more severe disease, the osteoclast differentiation pathway and the main target CTSK contribute to our deeper understanding for the molecular mechanisms associated with S. aureus infection-induced OM, and the construction of molecular subgroups suggested the necessity for different subgroups of patients to receive individualized treatment.