Identification of ferroptosis-associated biomarkers for the potential diagnosis and treatment of postmenopausal osteoporosis

Revealing the key role of cuproptosis in osteoporosis via the bioinformatic analysis and experimental validation of cuproptosis-related genes

The incidence of osteoporosis has rapidly increased owing to the ageing population. Cuproptosis, a novel mechanism that regulates cell death, may be a new therapeutic approach. However, the relevance of cuproptosis in the immune microenvironment and osteoporosis immunotherapy is still unknown. We intersected the differentially expressed genes from osteoporotic samples with 75 cuproptosis-related genes to identify 16 significantly expressed cuproptosis genes. We further explored the connection between the cuproptosis pattern, immune microenvironment, and immunotherapy. The weighted gene co-expression network analysis algorithm was used to identify cuproptosis phenotype-associated genes, and we used quantitative real-time PCR and immunohistochemistry in mouse femur tissues to verify hub gene (MAP2K2, FDX1, COX19, VEGFA, CDKN2A, and NFE2L2) expression. Six hub genes and 59 cuproptosis phenotype-associated genes involved in immunisation were identified among the osteoporosis and control groups, and the majority of these 59 genes were enriched in the inflammatory response, as well as in signal transducers, Janus kinase, and transcription pathway activators. In addition, two different clusters of cuproptosis were found, and immune infiltration analysis showed that gene Cluster 1 had a greater immune score and immune infiltration level. Further analysis revealed that three key genes (COX19, MAP2K2, and FDX1) were highly correlated with immune cell infiltration, and external experiments validated the association of these three genes with the prognosis of osteoporosis. We used the three key mRNAs COX19, MAP2K2, and FDX1 as a classification model that may systematically elucidate the complex connection between cuproptosis and the immune microenvironment of osteoporosis. New insights into osteoporosis pathogenesis and immunotherapy prospects may be gained from this study.

Ferroptosis defense mechanisms: The future and hope for treating osteosarcoma

Currently, challenges such as chemotherapy resistance, resulting from preoperative and postoperative chemotherapy, postoperative recurrence, and poor bone regeneration quality, are becoming increasingly prominent in osteosarcoma (OS) treatment. There is an urgent need to find more effective ways to address these issues. Ferroptosis is a novel form of iron-dependent programmed cell death, distinct from other forms of cell death. In this paper, we summarize how, through the three major defense systems of ferroptosis, not only can substances from traditional Chinese medicine, antitumor drugs, and nano-drug carriers induce ferroptosis in OS cells, but they can also be combined with immunotherapy, differentiation therapy, and other treatment modalities to significantly enhance chemotherapy sensitivity and inhibit tumor growth. Thus, ferroptosis holds great potential in treating OS, offering more choices and possibilities for future clinical interventions.

RNA sequencing-based approaches to identifying disulfidptosis-related diagnostic clusters and immune landscapes in osteoporosis

Disulfidptosis, a newly recognized cell death triggered by disulfide stress, has garnered attention for its potential role in osteoporosis (OP) pathogenesis. Although sulfide-related proteins are reported to regulate the balance of bone metabolism in OP, the precise involvement of disulfidptosis regulators remains elusive. Herein, leveraging the GSE56815 dataset, we conducted an analysis to delineate disulfidptosis-associated diagnostic clusters and immune landscapes in OP. Subsequently, vertebral bone tissues obtained from OP patients and controls were subjected to RNA sequencing (RNA-seq) for the validation of key disulfidptosis gene expression. Our analysis unveiled seven significant disulfidptosis regulators, including FLNA, ACTB, PRDX1, SLC7A11, NUBPL, OXSM, and RAC1, distinguishing OP samples from controls. Furthermore, employing a random forest model, we identified four diagnostic disulfidptosis regulators including FLNA, SLC7A11, NUBPL, and RAC1 potentially predictive of OP risk. A nomogram model integrating these four regulators was constructed and validated using the GSE35956 dataset, demonstrating promising utility in clinical decision-making, as affirmed by decision curve analysis. Subsequent consensus clustering analysis stratified OP samples into two different disulfidptosis subgroups (clusters A and B) using significant disulfidptosis regulators, with cluster B exhibiting higher disulfidptosis scores and implicating monocyte immunity, closely linked to osteoclastogenesis. Notably, RNA-seq analysis corroborated the expression patterns of two disulfidptosis modulators, PRDX1 and OXSM, consistent with bioinformatics predictions. Collectively, our study sheds light on disulfidptosis patterns, offering potential markers and immunotherapeutic avenues for future OP management.

Analysis and validation of biomarkers of immune cell-related genes in postmenopausal osteoporosis: An observational study

Postmenopausal osteoporosis (PMOP) is a common metabolic inflammatory disease. In conditions of estrogen deficiency, chronic activation of the immune system leads to a hypo-inflammatory phenotype and alterations in its cytokine and immune cell profile, although immune cells play an important role in the pathology of osteoporosis, studies on this have been rare. Therefore, it is important to investigate the role of immune cell-related genes in PMOP. PMOP-related datasets were downloaded from the Gene Expression Omnibus database. Immune cells scores between high bone mineral density (BMD) and low BMD samples were assessed based on the single sample gene set enrichment analysis method. Subsequently, weighted gene co-expression network analysis was performed to identify modules highly associated with immune cells and obtain module genes. Differential analysis between high BMD and low BMD was also performed to obtain differentially expressed genes. Module genes are intersected with differentially expressed genes to obtain candidate genes, and functional enrichment analysis was performed. Machine learning methods were used to filter out the signature genes. The receiver operating characteristic (ROC) curves of the signature genes and the nomogram were plotted to determine whether the signature genes can be used as a molecular marker. Gene set enrichment analysis was also performed to explore the potential mechanism of the signature genes. Finally, RNA expression of signature genes was validated in blood samples from PMOP patients and normal control by real-time quantitative polymerase chain reaction. Our study of PMOP patients identified differences in immune cells (activated dendritic cell, CD56 bright natural killer cell, Central memory CD4 T cell, Effector memory CD4 T cell, Mast cell, Natural killer T cell, T follicular helper cell, Type 1 T-helper cell, and Type 17 T-helper cell) between high and low BMD patients. We obtained a total of 73 candidate genes based on modular genes and differential genes, and obtained 5 signature genes by least absolute shrinkage and selection operator and random forest model screening. ROC, principal component analysis, and t-distributed stochastic neighbor embedding down scaling analysis revealed that the 5 signature genes had good discriminatory ability between high and low BMD samples. A logistic regression model was constructed based on 5 signature genes, and both ROC and column line plots indicated that the model accuracy and applicability were good. Five signature genes were found to be associated with proteasome, mitochondria, and lysosome by gene set enrichment analysis. The real-time quantitative polymerase chain reaction results showed that the expression of the signature genes was significantly different between the 2 groups. HIST1H2AG, PYGM, NCKAP1, POMP, and LYPLA1 might play key roles in PMOP and be served as the biomarkers of PMOP.

Advances in exosome modulation of ferroptosis for the treatment of orthopedic diseases

Current treatments for orthopaedic illnesses frequently result in poor prognosis, treatment failure, numerous relapses, and other unpleasant outcomes that have a significant impact on patients' quality of life. Cell-free therapy has emerged as one of the most promising options in recent decades for improving the status quo. As a result, using exosomes produced from various cells to modulate ferroptosis has been proposed as a therapeutic method for the condition. Exosomes are extracellular vesicles that secrete various bioactive chemicals that influence disease treatment and play a role in the genesis and progression of orthopaedic illnesses. Ferroptosis is a recently defined kind of controlled cell death typified by large iron ion buildup and lipid peroxidation. An increasing number of studies indicate that ferroptosis plays a significant role in orthopaedic illnesses. Exosomes, as intercellular information transfer channels, have been found to play a significant role in the regulation of ferroptosis processes. Furthermore, accumulating research suggests that exosomes can influence the course of many diseases by regulating ferroptosis in injured cells. In order to better understand the processes by which exosomes govern ferroptosis in the therapy of orthopaedic illnesses. This review discusses the biogenesis, secretion, and uptake of exosomes, as well as the mechanisms of ferroptosis and exosomes in the therapy of orthopaedic illnesses. It focuses on recent research advances and exosome mechanisms in regulating iron death for the therapy of orthopaedic illnesses. The present state of review conducted both domestically and internationally is elucidated and anticipated as a viable avenue for future therapy in the field of orthopaedics.

Th17 Cell-Related Gene Biomarkers in Osteoporosis: Comprehensive Bioinformatics Analysis and In Vivo Validation

The interaction between the bone and immune systems has a major role in osteoporosis regulation. However, the infiltration of T helper 17 (Th17) cells and their associated genes in osteoporosis remains unclear. The GSE35959 dataset was obtained from the Gene Expression Omnibus (GEO) database, and the Immune Cell Abundance Identifier (ImmuCellAI) program was used to evaluate the abundance of 24 immune cell types, including Th17 cells. Differential analysis and relevance analysis were performed to identify differentially expressed Th17 cell-related genes (DETh17RGs) in osteoporosis. The potential functions of DETh17RGs were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment. Hub DETh17RGs were obtained through comprehensive analysis using Weighted Gene Co-Expression Network Analysis (WGCNA) and the CytoHubba plug-in algorithm. The expression levels of hub genes were validated using additional osteoporosis datasets. Additionally, the transcript levels of Hub genes in a mice model of osteoporosis were examined using quantitative PCR (qPCR). 464 DETh17RGs were identified in this study, with 421 genes showing positive associations and 43 genes showing negative associations. Among these, seven genes (CD44, TGFB1, ACTN4, ARHGDIA, ESR1, TLN1, FLNA) were considered as Hub DETh17RGs. The qPCR transcript levels of hub DETh17RGs in a mice model of osteoporosis exhibited consistent expression trends with the bioinformatics analysis. This research enhances our understanding of the molecular mechanisms involving Th17 cells in the development of osteoporosis and contributes to the discovery of potential biomarkers.

FNDC5/irisin ameliorates bone loss of type 1 diabetes by suppressing endoplasmic reticulum stress‑mediated ferroptosis

BACKGROUND

Ferroptosis is known to play a crucial role in diabetic osteopathy. However, key genes and molecular mechanisms remain largely unclear. This study aimed to identify a crucial ferroptosis-related differentially expressed gene (FR-DEG) in diabetic osteopathy and investigate its potential mechanism.

METHODS

We identified fibronectin type III domain-containing protein 5 (FNDC5)/irisin as an essential FR-DEG in diabetic osteopathy using the Ferroptosis Database (FerrDb) and GSE189112 dataset. Initially, a diabetic mouse model was induced by intraperitoneal injection of streptozotocin (STZ), followed by intraperitoneal injection of irisin. MC3T3-E1 cells treated with high glucose (HG) were used as an in vitro model. FNDC5 overexpression plasmid was used to explore underlying mechanisms in vitro experiments. Femurs were collected for micro-CT scan, histomorphometry, and immunohistochemical analysis. Peripheral serum was collected for ELISA analysis. Cell viability was assessed using a CCK-8 kit. The levels of glutathione (GSH), malondialdehyde (MDA), iron, reactive oxygen species (ROS), and lipid ROS were detected by the corresponding kits. Mitochondria ultrastructure was observed through transmission electron microscopy (TEM). Finally, mRNA and protein expressions were examined by quantitative real-time PCR (qRT-PCR) and western blot analysis.

RESULTS

The expression of FNDC5 was found to be significantly decreased in both in vivo and in vitro models. Treatment with irisin significantly suppressed ferroptosis and improved bone loss. This was demonstrated by reduced lipid peroxidation and iron overload, increased antioxidant capability, as well as the inhibition of the ferroptosis pathway in bone tissues. Furthermore, in vitro studies demonstrated that FNDC5 overexpression significantly improved HG-induced ferroptosis and promoted osteogenesis. Mechanistic investigations revealed that FNDC5 overexpression mitigated ferroptosis in osteoblasts by inhibiting the eukaryotic initiation factor 2 alpha (eIF2α)/activated transcription factor 4 (ATF4)/C/EBP-homologous protein (CHOP) pathway.

CONCLUSIONS

Collectively, our study uncovered the important role of FNDC5/irisin in regulating ferroptosis of diabetic osteopathy, which might be a potential therapeutic target.

Ferroptosis in Osteocytes as a Target for Protection Against Postmenopausal Osteoporosis

Ferroptosis is a necrotic form of iron-dependent regulatory cell death. Estrogen withdrawal can interfere with iron metabolism, which is responsible for the pathogenesis of postmenopausal osteoporosis (PMOP). Here, it is demonstrated that estrogen withdrawal induces iron accumulation in the skeleton and the ferroptosis of osteocytes, leading to reduced bone mineral density. Furthermore, the facilitatory effect of ferroptosis of osteocytes is verified in the occurrence and development of postmenopausal osteoporosis is associated with over activated osteoclastogenesis using a direct osteocyte/osteoclast coculture system and glutathione peroxidase 4 (GPX4) knockout ovariectomized mice. In addition, the nuclear factor erythroid derived 2-related factor-2 (Nrf2) signaling pathway is confirmed to be a crucial factor in the ferroptosis of osteocytic cells. Nrf2 regulates the expression of nuclear factor kappa-B ligand (RANKL) by regulating the DNA methylation level of the RANKL promoter mediated by DNA methyltransferase 3a (Dnmt3a), which is as an important mechanism in osteocytic ferroptosis-mediated osteoclastogenesis. Taken together, this data suggests that osteocytic ferroptosis is involved in PMOP and can be targeted to tune bone homeostasis.

Development of fatty acid metabolism score based on gene signature for predicting prognosis and immunotherapy response in colon cancer

PURPOSE

Metabolic reprogramming is a novel hallmark and therapeutic target of cancer. Our study aimed to establish fatty acid metabolism-associated scores based on gene signature and investigated its effects on immunotherapy in colon cancer.

METHODS

Gene expression and clinical information were collected from Gene Expression Omnibus (GEO) database to identify a gene signature by non-negative matrix factorization (NMF) clustering and Cox regression analysis. Subsequently, we constructed the fatty acid metabolism score (FA-score) model by principal component analysis (PCA) and explored its relativity of prognosis and the response to immunotherapy in colon cancer. Finally, the Cancer Genome Atlas (TCGA) database was introduced and in vitro study was performed for verification.

RESULTS

The FA-score-high group had a higher level of fatty acid metabolism and was associated with worse patient overall survival. Significantly, FA-score correlated closely with the biomarkers of immunotherapy, and the FA-score-high group had a poorer therapeutic efficacy of immune checkpoint blockade. In vitro experiments demonstrated that ACSL5 may be a critical metabolic regulatory target.

CONCLUSIONS

Our study provided a comprehensive analysis of the heterogeneity of fatty acid metabolism in colon cancer. We highlighted the potential clinical utility of fatty acid metabolism-related genes to be biomarkers of colon cancer prognosis and targets to improve the effect of immunotherapy.

Identification of a potential signature to predict the risk of postmenopausal osteoporosis

BACKGROUND

Postmenopausal osteoporosis (PMOP) is related to the elevated risk of fracture in postmenopausal women. Thus, to effectively predict the occurrence of PMOP, we explored a novel gene signature for the prediction of PMOP risk.

METHODS

The WGCNA analysis was conducted to identify the PMOP-related gene modules based on the data from GEO database (GSE56116 and GSE100609). The "limma" R package was applied for screening differentially expressed genes (DEGs) based on the data from GSE100609 dataset. Next, LASSO Cox algorithm were applied to identify valuable PMOP-related risk genes and construct a risk score model. GSEA was then conducted to analyze potential signaling pathways between high-risk (HR) score and low-risk (LR) score groups.

RESULTS

A novel risk model with five PMOP-related risk genes (SCUBE3, TNNC1, SPON1, SEPT12 and ULBP1) was developed for predicting PMOP risk status. RT-qPCR and western blot assays validated that compared to postmenopausal non-osteoporosis (non-PMOP) patients, SCUBE3, ULBP1, SEPT12 levels were obviously elevated, and TNNC1 and SPON1 levels were reduced in blood samples from PMOP patients. Additionally, PMOP-related pathways such as MAPK signaling pathway, PI3K-Akt signaling pathway and HIF-1 signaling pathway were significantly activated in the HR-score group compared to the LR-score group. The circRNA-gene-miRNA and gene-transcription factor networks showed that 533 miRNAs, 13 circRNAs and 40 TFs might be involved in regulating the expression level of these five PMOP-related genes.

CONCLUSION

Collectively, we developed a PMOP-related gene signature based on SCUBE3, TNNC1, SPON1, SEPT12 and ULBP1 genes, and higher risk score indicated higher risk suffering from PMOP.

Investigating the impact of Wnt pathway-related genes on biomarker and diagnostic model development for osteoporosis in postmenopausal females

The Wnt signaling pathway is essential for bone development and maintaining skeletal homeostasis, making it particularly relevant in osteoporosis patients. Our study aimed to identify distinct molecular clusters associated with the Wnt pathway and develop a diagnostic model for osteoporosis in postmenopausal Caucasian women. We downloaded three datasets (GSE56814, GSE56815 and GSE2208) related to osteoporosis from the GEO database. Our analysis identified a total of 371 differentially expressed genes (DEGs) between low and high bone mineral density (BMD) groups, with 12 genes associated with the Wnt signaling pathway, referred to as osteoporosis-associated Wnt pathway-related genes. Employing four independent machine learning models, we established a diagnostic model using the 12 osteoporosis-associated Wnt pathway-related genes in the training set. The XGB model showed the most promising discriminative potential. We further validate the predictive capability of our diagnostic model by applying it to three external datasets specifically related to osteoporosis. Subsequently, we constructed a diagnostic nomogram based on the five crucial genes identified from the XGB model. In addition, through the utilization of DGIdb, we identified a total of 30 molecular compounds or medications that exhibit potential as promising therapeutic targets for osteoporosis. In summary, our comprehensive analysis provides valuable insights into the relationship between the osteoporosis and Wnt signaling pathway.

Mangiferin attenuates osteoporosis by inhibiting osteoblastic ferroptosis through Keap1/Nrf2/SLC7A11/GPX4 pathway

BACKGROUND

Ferroptosis is a crucial contributor to impaired osteoblast function in osteoporosis. Mangiferin, a xanthonoid glucoside isolated from mangoes, exhibits anti-osteoporosis effects. However, its potential mechanism is not fully understood.

PURPOSE

This study explores the potencies of mangiferin on osteoblastic ferroptosis and deciphers its direct target in the context of solute carrier family 7-member 11 (SLC7A11)/glutathione peroxidases 4 (GPX4) pathway.

METHODS

In vivo models include bilateral ovariectomy induced osteoporosis mice, iron-dextran induced iron-overloaded mice, and nuclear factor-erythroid 2-related factor 2 (Nrf2)-knockout mice. Mice are orally administrated mangiferin (10, 50 or 100 mg.kg-1.d-1) for 12 weeks. In vitro osteoblast models include iron-dextran induced iron-overloaded cells, erastin induced ferroptosis cells, and gene knockout cells. RNA sequencing is applied for investigating the underlying mechanisms. The direct target of mangiferin is studied using a cellular thermal shift assay, silico docking, and surface plasmon resonance.

RESULTS

Mangiferin promotes bone formation and inhibits ferroptosis in vivo models (osteoporosis mice, iron-overloaded mice) and in vitro models (ferroptosis osteoblast, iron-overloaded osteoblasts). Mechanismly, mangiferin directly binds to the kelch-like ECH-associated protein 1 (Keap1) and activates the downstream Nrf2/SLC7A11/GPX4 pathway in both the in vivo and in vitro models. Mangiferin failed to restore the osteoporosis and ferroptosis in Nrf2-knockout mice. Silencing Nrf2, SLC7A11 or GPX4 abolished the anti-ferroptosis effect of mangiferin in erastin-induced cells. Addition of the ferroptosis agonist RSL-3 also blocked the protective effects of mangiferin on iron-overloaded cells. Furthermore, mangiferin had better effects on osteogenesis than the ferroptosis inhibitor (ferrostatin-1) and the Nrf2 agonists (sulforaphane, dimethyl fumarate, and bardoxolone).

CONCLUSIONS

We identify for the first time mangiferin as a ferroptosis inhibitor and a direct Keap1 conjugator that promotes bone formation and alleviates osteoporosis. This work also provides a potentially practical pharmacological approach for treating ferroptosis-driven diseases.

Network pharmacology-based pharmacological mechanism prediction of Lycii Fructus against postmenopausal osteoporosis

Postmenopausal osteoporosis (PMOP) has become one of most frequent bone diseases worldwide with aging population. Lycii Fructus, a common plant fruit with the property of drug homologous food, has long since been used to treat PMOP. The aim of this study is to explore pharmacological mechanisms of Lycii Fructus against PMOP through using network pharmacology approach. The active ingredients of Lycii Fructus were obtained from Traditional Chinese Medicine System Pharmacology database. Target fishing was performed on these ingredients in UniProt database for identification of the relative targets. Then, we screened the targets related to PMOP using GeneCards database and DisGeNET database. The overlapping genes between PMOP and Lycii Fructus were obtained to perform protein-protein interaction, gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis. A total of 35 active ingredients were identified in Lycii Fructus, and fished 158 related targets. Simultaneously, 292 targets associated with PMOP were obtained from GeneCards database and DisGeNET database. By drawing Venn diagram, 41 overlapping genes were obtained, and were considered as therapeutically relevant. Gene ontology enrichment analysis predicted that anti-inflammation and promotion of angiogenesis might be 2 potential mechanism of Lycii Fructus for PMOP treatment. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed several pathways, such as IL-17 pathway, TNF pathway, MAPK pathway, PI3K-Akt signaling pathway and HIF signaling pathway were involved in regulating these 2 biological processes. Through the method of network pharmacology, we systematically investigated the mechanisms of Lycii Fructus against PMOP. The identified multi-targets and multi-pathways provide new insights to further determinate its exact pharmacological mechanisms.

Smoking index and COPD duration as potential risk factors for development of osteoporosis in patients with non-small cell lung cancer - A retrospective case control study evaluated by CT Hounsfield unit

Objective

To investigate the effect of smoking index (calculated as number of cigarettes per day × smoking years) and chronic obstructive pulmonary disease (COPD) duration on osteoporosis (OP)evaluated by opportunistic chest CT in patients with non-small cell lung cancer (NSCLC).

Methods

A total of 101 patients diagnosed with NSCLC were included in our cohort study. Among them, 50 patients with a history of smoking and COPD were assigned to the experimental group, while 51 patients without a history of smoking and COPD were assigned to the control group. Hounsfield unit (HU) value was measured by conventional chest CT to investigate the bone mineral density; and the mean values of axial HU value in the upper, middle and lower parts of T4, T7, T10 and L1 vertebral bodies were measured as the study variables.

Results

There were no significant differences in gender, age, body mass index, type of lung cancer, clinical stage of lung cancer and comorbidities between the two groups (P = 0.938，P = 0.158，P = 0.722,P = 0.596,P = 0.813,P = 0.655). The overall mean HU values of T4, T7, T10, L1 in the experimental group were 116.60 ± 30.67, 110.56 ± 30.03, 109.18 (96.85-122.95), 94.63 (85.20-104.12) and 106.86 ± 22.26, respectively, which were significantly lower than those in the control group (189.55 ± 34.57, 174.54 ± 35.30, 172.73 (156.33-199.50), 158.20 (141.60-179.40) and 177.50 ± 33.49) (P ＜0.05). And in the experimental group, smoking index and COPD duration were significantly and negatively correlated with HU values (r = -0.627, -0.542, P ＜0.05, respectively).

Conclusion

Patients with NSCLC who have a history of smoking and COPD exhibit a notably lower HU value compared to the control groups. Additionally, it has been observed that the smoking index and duration of COPD may be influential factors affecting bone mineral density in NSCLC patients.

Identification of ROCK1 as a novel biomarker for postmenopausal osteoporosis and pan-cancer analysis

BACKGROUND

Postmenopausal osteoporosis (PMOP) is a prevalent bone disorder with significant global impact. The elevated risk of osteoporotic fracture in elderly women poses a substantial burden on individuals and society. Unfortunately, the current lack of dependable diagnostic markers and precise therapeutic targets for PMOP remains a major challenge.

METHODS

PMOP-related datasets GSE7429, GSE56814, GSE56815, and GSE147287, were downloaded from the GEO database. The DEGs were identified by "limma" packages. WGCNA and Machine Learning were used to choose key module genes highly related to PMOP. GSEA, DO, GO, and KEGG enrichment analysis was performed on all DEGs and the selected key hub genes. The PPI network was constructed through the GeneMANIA database. ROC curves and AUC values validated the diagnostic values of the hub genes in both training and validation datasets. xCell immune infiltration and single-cell analysis identified the hub genes' function on immune reaction in PMOP. Pan-cancer analysis revealed the role of the hub genes in cancers.

RESULTS

A total of 1278 DEGs were identified between PMOP patients and the healthy controls. The purple module and cyan module were selected as the key modules and 112 common genes were selected after combining the DEGs and module genes. Five Machine Learning algorithms screened three hub genes (KCNJ2, HIPK1, and ROCK1), and a PPI network was constructed for the hub genes. ROC curves validate the diagnostic values of ROCK1 in both the training (AUC = 0.73) and validation datasets of PMOP (AUC = 0.81). GSEA was performed for the low-ROCK1 patients, and the top enriched field included protein binding and immune reaction. DCs and NKT cells were highly expressed in PMOP. Pan-cancer analysis showed a correlation between low ROCK1 expression and SKCM as well as renal tumors (KIRP, KICH, and KIRC).

CONCLUSIONS

ROCK1 was significantly associated with the pathogenesis and immune infiltration of PMOP, and influenced cancer development, progression, and prognosis, which provided a potential therapy target for PMOP and tumors. However, further laboratory and clinical evidence is required before the clinical application of ROCK1 as a therapeutic target.

The role of ferroptosis in metabolic diseases

The annual incidence of metabolic diseases such as diabetes, non-alcoholic fatty liver disease (NAFLD), osteoporosis, and atherosclerosis (AS) is increasing, resulting in a heavy burden on human health and the social economy. Ferroptosis is a novel form of programmed cell death driven by iron-dependent lipid peroxidation, which was discovered in recent years. Emerging evidence has suggested that ferroptosis contributes to the development of metabolic diseases. Here, we summarize the mechanisms and molecular signaling pathways involved in ferroptosis. Then we discuss the role of ferroptosis in metabolic diseases. Finally, we analyze the potential of targeting ferroptosis as a promising therapeutic approach for metabolic diseases.

Identification of copper death-associated molecular clusters and immunological profiles in rheumatoid arthritis

Objective

An analysis of the relationship between rheumatoid arthritis (RA) and copper death-related genes (CRG) was explored based on the GEO dataset.

Methods

Based on the differential gene expression profiles in the GSE93272 dataset, their relationship to CRG and immune signature were analysed. Using 232 RA samples, molecular clusters with CRG were delineated and analysed for expression and immune infiltration. Genes specific to the CRGcluster were identified by the WGCNA algorithm. Four machine learning models were then built and validated after selecting the optimal model to obtain the significant predicted genes, and validated by constructing RA rat models.

Results

The location of the 13 CRGs on the chromosome was determined and, except for GCSH. LIPT1, FDX1, DLD, DBT, LIAS and ATP7A were expressed at significantly higher levels in RA samples than in non-RA, and DLST was significantly lower. RA samples were significantly expressed in immune cells such as B cells memory and differentially expressed genes such as LIPT1 were also strongly associated with the presence of immune infiltration. Two copper death-related molecular clusters were identified in RA samples. A higher level of immune infiltration and expression of CRGcluster C2 was found in the RA population. There were 314 crossover genes between the 2 molecular clusters, which were further divided into two molecular clusters. A significant difference in immune infiltration and expression levels was found between the two. Based on the five genes obtained from the RF model (AUC = 0.843), the Nomogram model, calibration curve and DCA also demonstrated their accuracy in predicting RA subtypes. The expression levels of the five genes were significantly higher in RA samples than in non-RA, and the ROC curves demonstrated their better predictive effect. Identification of predictive genes by RA animal model experiments was also confirmed.

Conclusion

This study provides some insight into the correlation between rheumatoid arthritis and copper mortality, as well as a predictive model that is expected to support the development of targeted treatment options in the future.

Identification and validation of ferroptosis-related gene signature in intervertebral disc degeneration

Lower back pain (LBP) is a leading cause of disability in the elderly and intervertebral disc degeneration (IDD) is the major contributor to LBP. Ferroptosis is a newly discovered programmed cell death, characterized by iron-dependent lethal lipid peroxidation. Growing evidence has shown that ferroptosis plays important roles in various human diseases. However, the underlying mechanism of ferroptosis in IDD remains elusive. This study is aimed to uncover the key roles of ferroptosis in the pathogenesis and progression of IDD comprehensively. To investigate the ferroptosis related differentially expressed genes (FRDEGs) in IDD, we analyzed the microarray data from the Gene Expression Omnibus (GEO) database. Then we performed functional enrichment analysis and protein-protein interaction (PPI) network analysis, and screened out the hub FRDEGs. To further evaluate the predictive value of these hub FRDEGs, we performed ROC analysis based on the GSE124272 dataset. A total of 80 FRDEGs were identified, including 20 downregulated and 60 upregulated FRDEGs. The FRDEGs were primarily involved in the biological processes of response to chemical, and response to stress. KEGG pathway enrichment analysis showed that the FRDEGs were mainly involved in ferroptosis, TNF signaling pathway, HIF-1 signaling pathway, NOD-like receptor signaling pathway, and IL-17 signaling pathway. Ten hub OSRDEGs were obtained according to the PPI analysis, including HMOX1, KEAP1, MAPK1, HSPA5, TXNRD1, IL6, PPARA, JUN, HIF1A, DUSP1. The ROC analysis and RT-qPCR validation results suggested that most of the hub FRDEGs might be potential signature genes for IDD. This study reveals that ferroptosis might provide promising strategy for the diagnosis and treatment of IDD.