Identification of SLC3A2 as a Potential Therapeutic Target of Osteoarthritis Involved in Ferroptosis by Integrating Bioinformatics, Clinical Factors and Experiments

Battling pain from osteoarthritis: causing novel cell death

Osteoarthritis (OA) is a significant contributor to pain and disability worldwide. Pain is the main complaint of OA patients attending the clinic and has a large impact on their quality of life and economic standards. However, existing treatments for OA-related pain have not been shown to achieve good relief. The main focus is on preventing and slowing the progression of OA so that the problem of OA pain can be resolved. Pain caused by OA is complex, with the nature, location, duration, and intensity of pain changing as the disease progresses. Previous research has highlighted the role of various forms of cell death, such as apoptosis and necrosis, in the progression of pain in OA. Emerging studies have identified additional forms of novel cell death, such as pyroptosis, ferroptosis, and necroptosis that are linked to pain in OA. Different types of cell death contribute to tissue damage in OA by impacting inflammatory responses, reactive oxygen species (ROS) production, and calcium ion levels, ultimately leading to the development of pain. Evidence suggests that targeting novel types of cell death could help alleviate pain in OA patients. This review delves into the complex mechanisms of OA pain, explores the relationship between different modes of novel cell death and pain, and proposes novel cell death as a viable strategy for the treatment of these conditions, with the goal of providing scientific references for the development of future OA pain treatments and drugs.

The role of mitochondrial autophagy in osteoarthritis

Osteoarthritis (OA) is a progressive degenerative joint disease, and the underlying molecular mechanisms of OA remain poorly understood. This study aimed to elucidate the relationship between mitochondrial autophagy and OA by identifying key regulatory genes and their biological functions. Utilizing bioinformatics analyses of RNA expression profiles from the GSE55235 dataset, we identified 2,136 differentially expressed genes, leading to the discovery of hub genes associated with mitochondrial autophagy and OA. Gene set enrichment analysis (GSEA) revealed their involvement in critical pathways, highlighting their potential roles in OA pathogenesis. Furthermore, our study explored the immunological landscape of OA, identifying distinct immune cell infiltration patterns that contribute to the disease's inflammatory profile. We also evaluated the therapeutic potential of drugs targeting these hub genes, suggesting potential approaches for OA treatment. Collectively, this study advances our knowledge of mitochondrial autophagy in OA and proposes promising biomarkers and therapeutic targets.

Machine learning algorithm-based biomarker exploration and validation of mitochondria-related diagnostic genes in osteoarthritis

The role of mitochondria in the pathogenesis of osteoarthritis (OA) is significant. In this study, we aimed to identify diagnostic signature genes associated with OA from a set of mitochondria-related genes (MRGs). First, the gene expression profiles of OA cartilage GSE114007 and GSE57218 were obtained from the Gene Expression Omnibus. And the limma method was used to detect differentially expressed genes (DEGs). Second, the biological functions of the DEGs in OA were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Wayne plots were employed to visualize the differentially expressed mitochondrial genes (MDEGs) in OA. Subsequently, the LASSO and SVM-RFE algorithms were employed to elucidate potential OA signature genes within the set of MDEGs. As a result, GRPEL and MTFP1 were identified as signature genes. Notably, GRPEL1 exhibited low expression levels in OA samples from both experimental and test group datasets, demonstrating high diagnostic efficacy. Furthermore, RT-qPCR analysis confirmed the reduced expression of Grpel1 in an in vitro OA model. Lastly, ssGSEA analysis revealed alterations in the infiltration abundance of several immune cells in OA cartilage tissue, which exhibited correlation with GRPEL1 expression. Altogether, this study has revealed that GRPEL1 functions as a novel and significant diagnostic indicator for OA by employing two machine learning methodologies. Furthermore, these findings provide fresh perspectives on potential targeted therapeutic interventions in the future.

Ferroptosis: A Frontier in Osteoporosis

Reduced bone mass and degeneration of the microarchitecture of bone tissue are the hallmarks of osteoporosis, a bone metabolic disease that increases skeletal fragility and fracture susceptibility. Osteoporosis is primarily caused by unbalanced bone remodeling, in which bone synthesis is outpaced by bone resorption caused by osteoclasts. Along with the bone-building vitamins calcium and vitamin D, typical medications for treating osteoporosis include bisphosphonates and calcitonin. The present therapies effectively stop osteoclast activation that is too high, however they come with varying degrees of negative effects. Numerous factors can contribute to osteoporosis, which is characterized by a loss of bone mass and density due to the deterioration of the bone's microstructure, which makes the bone more fragile. As a result, it is a systemic bone condition that makes patients more likely to fracture. Interest in the function of ferroptosis in the pathophysiology of osteoporosis is developing. In this review, we go through the shape of the cell, the fundamental mechanisms of ferroptosis, the relationship between osteoclasts and osteoblasts, the association between ferroptosis and diabetic osteoporosis, steroid-induced osteoporosis, and the relationship between ferroptosis and postmenopausal osteoporosis. The functions of ferroptosis and osteoporosis in cellular function, signaling cascades, pharmacological inhibition, and gene silencing have been better understood thanks to recent advances in biomedical research.

Identification of biomarkers related to tryptophan metabolism in osteoarthritis

Background

OA (osteoarthritis) is a common joint disease characterized by damage to the articular cartilage and affects the entire joint tissue, with its main manifestations being joint pain, stiffness, and limited movement.Currently,we know that OA is a complex process composed of inflammatory and metabolic factors.It is reported that the occurrence and development of OA is related to the change of tryptophan metabolism.Therefore, the study of tryptophan metabolism and OA related genes is hopeful to find a new therapeutic target for OA.

Methods

Differentially expressed genes (DEGs) in GSE55235 were gained via differential expression analysis (OA samples vs normal samples). The tryptophan metabolic related DEGs (TMR-DEGs) were obtained by overlapping tryptophan metabolism related genes (TMRGs) and DEGs. Further, biomarkers were screening via Least absolute shrinkage and selection operator (LASSO), naive bayes (NB) and supportvector machine-recursive feature elimination (SVM-RFE) algorithm to establish a diagnostic model. Afterward, Gene Set Enrichment Analysis (GSEA) and drug prediction were performed based on diagnostic biomarkers by multiple software and databases. Eventually, expression level of biomarker public databases was verified using real-time quantitative polymerase chain reaction (RT-qPCR).

Results

Three tryptophan metabolism related biomarkers (TDO2, AOX1 and SLC3A2) were identified in OA. GSEA analysis demonstrated that biomarkers were associated with the function of 'FoxO signaling pathway', 'spliceosome' and 'ribosome'. There were seven drugs with therapeutic potential on TDO2 and AOX1. Ultimately, compared with normal group, expression of AOX1 and SLC3A2 in OA group remarkable lower.

Conclusion

Overall, three tryptophan metabolic related diagnostic biomarkers that associated with OA were obtained, which provided a original direction for the diagnosis and treatment of OA.

Recent Advances in Molecular Pathways and Therapeutic Implications for Peptic Ulcer Management: A Comprehensive Review

Peptic ulcers, recognized for their erosive impact on the gastrointestinal mucosa, present a considerable challenge in gastroenterology. Epidemiological insights underscore the global prevalence of peptic ulcers, affecting 5-10+% of individuals, with a yearly incidence of 0.3 to 1.9 cases per thousand. Recent decades have witnessed a decline in complications, attributed to improved diagnostics and therapeutic advancements. The review deepens into H. pylori-associated and NSAID-induced ulcers, emphasizing their distinct prevalence in developing and industrialized nations, respectively. Despite advancements, managing peptic ulcers remains challenging, notably in H. pylori-infected individuals facing recurrence and the rise of antibiotic resistance. The pathophysiology unravels the delicate balance between protective and destructive factors, including the intricate molecular mechanisms involving inflammatory mediators such as TNF-α, ILs, and prostaglandins. Genetic and ethnic factors, rare contributors, and recent molecular insights further enhance our understanding of peptic ulcer development. Diagnostic approaches are pivotal, with upper gastrointestinal endoscopy standing as the gold standard. Current treatment strategies focus on H. pylori eradication, NSAID discontinuation, and proton pump inhibitors. Surgical options become imperative for refractory cases, emphasizing a comprehensive approach. Advances include tailored H. pylori regimens, the emergence of vonoprazan, and ongoing vaccine development. Challenges persist, primarily in antibiotic resistance, side effects of acid suppressants, and translating natural compounds into standardized therapies. Promising avenues include the potential H. pylori vaccine and the exploration of natural compounds, with monoterpenes showing therapeutic promise. This review serves as a compass, guiding healthcare professionals, researchers, and policymakers through the intricate landscape of peptic ulcer management.

Bioinformatics Identification and Experimental Verification of Disulfidptosis-Related Genes in the Progression of Osteoarthritis

BACKGROUND

Osteoarthritis (OA) is a disabling and highly prevalent condition affecting millions worldwide. Recently discovered, disulfidptosis represents a novel form of cell death induced by the excessive accumulation of cystine. Despite its significance, a systematic exploration of disulfidptosis-related genes (DRGs) in OA is lacking.

METHODS

This study utilized three OA-related datasets and DRGs. Differentially expressed (DE)-DRGs were derived by intersecting the differentially expressed genes (DEGs) from GSE114007 with DRGs. Feature genes underwent screening through three machine learning algorithms. High diagnostic value genes were identified using the receiver operating characteristic curve. Hub genes were confirmed through expression validation. These hub genes were then employed to construct a nomogram and conduct enrichment, immune, and correlation analyses. An additional validation of hub genes was performed through in vitro cell experiments.

RESULTS

SLC3A2 and PDLIM1 were designated as hub genes, displaying excellent diagnostic performance. PDLIM1 exhibited low expression in early chondrocyte differentiation, rising significantly in the late stage, while SLC3A2 showed high overall expression, declining in the late differentiation stage. Cellular experiments corroborated the correlation of SLC3A2 and PDLIM1 with chondrocyte inflammation.

CONCLUSIONS

Two hub genes, SLC3A2 and PDLIM1, were identified in relation to disulfidptosis, providing potential directions for diagnosing and treating OA.

Iron metabolism and arthritis: Exploring connections and therapeutic avenues

ABSTRACT

Iron is indispensable for the viablility of nearly all living organisms, and it is imperative for cells, tissues, and organisms to acquire this essential metal sufficiently and maintain its metabolic stability for survival. Disruption of iron homeostasis can lead to the development of various diseases. There is a robust connection between iron metabolism and infection, immunity, inflammation, and aging, suggesting that disorders in iron metabolism may contribute to the pathogenesis of arthritis. Numerous studies have focused on the significant role of iron metabolism in the development of arthritis and its potential for targeted drug therapy. Targeting iron metabolism offers a promising approach for individualized treatment of arthritis. Therefore, this review aimed to investigate the mechanisms by which the body maintains iron metabolism and the impacts of iron and iron metabolism disorders on arthritis. Furthermore, this review aimed to identify potential therapeutic targets and active substances related to iron metabolism, which could provide promising research directions in this field.

An RNA Helicase DHX33 Inhibitor Shows Broad Anticancer Activity via Inducing Ferroptosis in Cancer Cells

RNA helicase DHX33 has been identified as a critical factor promoting cancer development. In the present study, a previously developed small molecule inhibitor for DHX33, KY386, was found to robustly kill cancer cells via a new path, the ferroptosis pathway. Mechanistically, DHX33 promotes the expression of critical players in lipid metabolism including FADS1, FADS2, and SCD1 genes, thereby sensitizing cancer cells to ferroptosis mediated cell death. Our study reveals a novel mechanism of DHX33 in promoting tumorigenesis and highlights that pharmacological targeting DHX33 can be a feasible option in human cancers. Normally differentiated cells are insensitive to DHX33 inhibition, and DHX33 inhibitors have little cellular toxicity in vitro and in vivo. Our studies demonstrated that DHX33 inhibitors can be promising anticancer agents with great potential for cancer treatment.

Construction of an explanatory model for predicting hepatotoxicity: a case study of the potentially hepatotoxic components of Gardenia jasminoides

It is well-known that the hepatotoxicity of drugs can significantly influence their clinical use. Despite their effective therapeutic efficacy, many drugs are severely limited in clinical applications due to significant hepatotoxicity. In response, researchers have created several machine learning-based hepatotoxicity prediction models for use in drug discovery and development. Researchers aim to predict the potential hepatotoxicity of drugs to enhance their utility. However, current hepatotoxicity prediction models often suffer from being unverified, and they fail to capture the detailed toxicological structures of predicted hepatotoxic compounds. Using the 56 chemical constituents of Gardenia jasminoides as examples, we validated the trained hepatotoxicity prediction model through literature reviews, principal component analysis (PCA), and structural comparison methods. Ultimately, we successfully developed a model with strong predictive performance and conducted visual validation. Interestingly, we discovered that the predicted hepatotoxic chemical constituents of Gardenia possess both toxic and therapeutic effects, which are likely dose-dependent. This discovery greatly contributes to our understanding of the dual nature of drug-induced hepatotoxicity.

Identification and verification of a novel signature that combines cuproptosis-related genes with ferroptosis-related genes in osteoarthritis using bioinformatics analysis and experimental validation

BACKGROUND

Exploring the pathogenesis of osteoarthritis (OA) is important for its prevention, diagnosis, and treatment. Therefore, we aimed to construct novel signature genes (c-FRGs) combining cuproptosis-related genes (CRGs) with ferroptosis-related genes (FRGs) to explore the pathogenesis of OA and aid in its treatment.

MATERIALS AND METHODS

Differentially expressed c-FRGs (c-FDEGs) were obtained using R software. Enrichment analysis was performed and a protein-protein interaction (PPI) network was constructed based on these c-FDEGs. Then, seven hub genes were screened. Three machine learning methods and verification experiments were used to identify four signature biomarkers from c-FDEGs, after which gene set enrichment analysis, gene set variation analysis, single-sample gene set enrichment analysis, immune function analysis, drug prediction, and ceRNA network analysis were performed based on these signature biomarkers. Subsequently, a disease model of OA was constructed using these biomarkers and validated on the GSE82107 dataset. Finally, we analyzed the distribution of the expression of these c-FDEGs in various cell populations.

RESULTS

A total of 63 FRGs were found to be closely associated with 11 CRGs, and 40 c-FDEGs were identified. Bioenrichment analysis showed that they were mainly associated with inflammation, external cellular stimulation, and autophagy. CDKN1A, FZD7, GABARAPL2, and SLC39A14 were identified as OA signature biomarkers, and their corresponding miRNAs and lncRNAs were predicted. Finally, scRNA-seq data analysis showed that the differentially expressed c-FRGs had significantly different expression distributions across the cell populations.

CONCLUSION

Four genes, namely CDKN1A, FZD7, GABARAPL2, and SLC39A14, are excellent biomarkers and prospective therapeutic targets for OA.

Identification and validation of RNA-binding protein SLC3A2 regulates melanocyte ferroptosis in vitiligo by integrated analysis of single-cell and bulk RNA-sequencing

BACKGROUND

The pathogenesis of vitiligo remains unclear. The genes encoding vitiligo-related RNA-binding proteins (RBPs) and their underlying pathogenic mechanism have not been determined.

RESULTS

Single-cell transcriptome sequencing (scRNA-seq) data from the CNCB database was obtained to identify distinct cell types and subpopulations and the relative proportion changes in vitiligo and healthy samples. We identified 14 different cell types and 28 cell subpopulations. The proportion of each cell subpopulation significantly differed between the patients with vitiligo and healthy groups. Using RBP genes for unsupervised clustering, we obtained the specific RBP genes of different cell types in vitiligo and healthy groups. The RBP gene expression was highly heterogeneous; there were significant differences in some cell types, such as keratinocytes, Langerhans, and melanocytes, while there were no significant differences in other cells, such as T cells and fibroblasts, in the two groups. The melanocyte-specific RBP genes were enriched in the apoptosis and immune-related pathways in the patients with vitiligo. Combined with the bulk RNA-seq data of melanocytes, key RBP genes related to melanocytes were identified, including eight upregulated RBP genes (CDKN2A, HLA-A, RPL12, RPL29, RPL31, RPS19, RPS21, and RPS28) and one downregulated RBP gene (SLC3A2). Cell experiments were conducted to explore the role of the key RBP gene SLC3A2 in vitiligo. Cell experiments confirmed that melanocyte proliferation decreased, whereas apoptosis increased, after SLC3A2 knockdown. SLC3A2 knockdown in melanocytes also decreased the SOD activity and melanin content; increased the Fe2+, ROS, and MDA content; significantly increased the expression levels of TYR and COX2; and decreased the expression levels of glutathione and GPX4.

CONCLUSION

We identified the RBP genes of different cell subsets in patients with vitiligo and confirmed that downregulating SLC3A2 can promote ferroptosis in melanocytes. These findings provide new insights into the pathogenesis of vitiligo.

Identification of the feature genes involved in cytokine release syndrome in COVID-19

OBJECTIVE

Screening of feature genes involved in cytokine release syndrome (CRS) from the coronavirus disease 19 (COVID-19).

METHODS

The data sets related to COVID-19 were retrieved using Gene Expression Omnibus (GEO) database, the differentially expressed genes (DEGs) related to CRS were analyzed with R software and Venn diagram, and the biological processes and signaling pathways involved in DEGs were analyzed with GO and KEGG enrichment. Core genes were screened using Betweenness and MCC algorithms. GSE164805 and GSE171110 dataset were used to verify the expression level of core genes. Immunoinfiltration analysis was performed by ssGSEA algorithm in the GSVA package. The DrugBank database was used to analyze the feature genes for potential therapeutic drugs.

RESULTS

This study obtained 6950 DEGs, of which 971 corresponded with CRS disease genes (common genes). GO and KEGG enrichment showed that multiple biological processes and signaling pathways associated with common genes were closely related to the inflammatory response. Furthermore, the analysis revealed that transcription factors that regulate these common genes are also involved in inflammatory response. Betweenness and MCC algorithms were used for common gene screening, yielding seven key genes. GSE164805 and GSE171110 dataset validation revealed significant differences between the COVID-19 and normal controls in four core genes (feature genes), namely IL6R, TLR4, TLR2, and IFNG. The upregulated IL6R, TLR4, and TLR2 genes were mainly involved in the Toll-like receptor signaling pathway of the inflammatory pathway, while the downregulated IFNG genes primarily participated in the necroptosis and JAK-STAT signaling pathways. Moreover, immune infiltration analysis indicated that higher expression of these genes was associated with immune cell infiltration that mediates inflammatory response. In addition, potential therapeutic drugs for these four feature genes were identified via the DrugBank database.

CONCLUSION

IL6R, TLR4, TLR2, and IFNG may be potential pathogenic genes and therapeutic targets for the CRS associated with COVID-19.

Hsa_circ_0050900 affects ferroptosis in intrahepatic cholangiocarcinoma cells by targeting hsa‑miR-605‑3p to regulate SLC3A2

Intrahepatic cholangiocarcinoma (ICC) is a highly lethal hepatobiliary tumor with high aggressiveness. The role of circular RNA (circRNA) in ICC remains to be explored. The present study aimed to investigate whether hsa_circ_0050900 affected ferroptosis in ICC cells by regulating hsa-microRNA (miR)-605-3p/solute carrier family 3 member 2 (SLC3A2). Human ICC cells were cultured and hsa_circ_0050900 expression was evaluated by reverse transcription-quantitative PCR. hsa_circ_0050900 was knocked down and ferroptosis inhibitor ferrostatin-1 was added to HuCCT-1 cells. Following knockdown or overexpression of hsa-miR-605-3p, Fe2+, reactive oxygen species (ROS), glutathione peroxidase 4 and SLC3A2 levels were assessed using iron and ROS assay kit or RT-qPCR and western blotting, respectively. Cell function experiments were performed to examine proliferation and migration abilities. Dual-luciferase reporter gene and argonaute2-RNA immunoprecipitation assay verified the relationship among hsa_circ_0050900, hsa-miR-605-3p, and SLC3A2. hsa_circ_0050900 was derived from actinin alpha 4 gene and was elevated in ICC cells. Among HuCCT-1, QBC-939, HCCC-9810, and RBE cell lines, the highest expression was in HuCCT-1 cells. Inhibition of hsa_circ_0050900 inhibited proliferation and migration by facilitating ICC cell ferroptosis. hsa-miR-605-3p expression was elevated after knocking down hsa_circ_0050900 and hsa-miR-605-3p was negatively regulated by hsa_circ_0050900. In addition, hsa-miR-605-3p targeted SLC3A2. Overexpression of hsa-miR-605-3p regulated SLC3A2 to promote ICC cell ferroptosis and inhibit proliferation and migration. Taken together, knockdown of hsa_circ_0050900 inhibited SLC3A2 expression via sponging hsa-miR-605-3p to promote ICC cell ferroptosis, and finally suppressed proliferation and migration. The present study suggested that hsa_circ_0050900 was a potential therapeutic target for ICC.

Bioinformatics analysis of hub genes as osteoarthritis prognostic biomarkers

Osteoarthritis (OA) is a progressive cartilage degradation disease, concomitant with synovitis, osteophyte formation, and subchondral bone sclerosis. Over 37% of the elderly population is affected by OA, and the number of cases is increasing as the global population ages. Therefore, the objective of this study was to identify and analyze the hub genes of OA combining with comprehensive bioinformatics analysis tools to provide theoretical basis in further OA effective therapies. Two sample sets of GSE46750 contained 12 pairs OA synovial membrane and normal samples harvested from patients as well as GSE98918 including 12 OA and non-OA patients were downloaded from the Gene Expression Omnibus database (GEO) database. Differentially expressed genes (DEGs) were identified using Gene Expression Omnibus 2R (GEO2R), followed by functional enrichment analysis, protein-protein interaction networks construction. The hub genes were identified and evaluated. An OA rat model was constructed, hematoxylin and eosin staining, safranin O/fast green staining, cytokines concentrations of serum were used to verify the model. The hub genes expression level in the knee OA samples were verified using RT-qPCR. The top 20 significantly up-regulated and down-regulated DEGs were screened out from the two datasets, respectively. The top 18 GO terms and 10 KEGG pathways were enriched. Eight hub genes were identified, namely MS4A6A, C1QB, C1QC, CD74, CSF1R, HLA-DPA1, HLA-DRA and ITGB2. Among them, the hub genes were all up-regulated in in vivo OA rat model, compared with healthy controls. The eight hub genes identified (MS4A6A, C1QB, C1QC, CD74, CSF1R, HLA-DPA1, HLA-DRA and ITGB2) were shown to be associated with OA. These genes can serve as disease markers to discriminate OA patients from healthy controls.

New insight of the pathogenesis in osteoarthritis: the intricate interplay of ferroptosis and autophagy mediated by mitophagy/chaperone-mediated autophagy

Ferroptosis, characterized by iron accumulation and lipid peroxidation, is a form of iron-driven cell death. Mitophagy is a type of selective autophagy, where degradation of damaged mitochondria is the key mechanism for maintaining mitochondrial homeostasis. Additionally, Chaperone-mediated autophagy (CMA) is a biological process that transports individual cytoplasmic proteins to lysosomes for degradation through companion molecules such as heat shock proteins. Research has demonstrated the involvement of ferroptosis, mitophagy, and CMA in the pathological progression of Osteoarthritis (OA). Furthermore, research has indicated a significant correlation between alterations in the expression of reactive oxygen species (ROS), adenosine monophosphate (AMP)-activated protein kinase (AMPK), and hypoxia-inducible factors (HIFs) and the occurrence of OA, particularly in relation to ferroptosis and mitophagy. In light of these findings, our study aims to assess the regulatory functions of ferroptosis and mitophagy/CMA in the pathogenesis of OA. Additionally, we propose a mechanism of crosstalk between ferroptosis and mitophagy, while also examining potential pharmacological interventions for targeted therapy in OA. Ultimately, our research endeavors to offer novel insights and directions for the prevention and treatment of OA.

Targeting Ferroptosis in Bone-Related Diseases: Facts and Perspectives

Ferroptosis is a new cell fate decision discovered in recent years. Unlike apoptosis, autophagy or pyroptosis, ferroptosis is characterized by iron-dependent lipid peroxidation and mitochondrial morphological changes. Ferroptosis is involved in a variety of physiological and pathological processes. Since its discovery, ferroptosis has been increasingly studied concerning bone-related diseases. In this review, we focus on the latest research progress and prospects, summarize the regulatory mechanisms of ferroptosis, and discuss the role of ferroptosis in the pathogenesis of bone-related diseases, such as osteoporosis (OP), osteoarthritis (OA), rheumatoid arthritis (RA), and osteosarcoma (OS), as well as its therapeutic potential.

Ferroptosis-related genes LPCAT3 and PGD are potential diagnostic biomarkers for osteoarthritis

BACKGROUND

Osteoarthritis (OA) is the most common chronic joint disease and how ferroptosis contributes to OA has garnered much attention recently. Bioinformatics promoted the discovery of ferroptosis-related biomarkers for OA. But since OA is a whole-joint disease, sensitive biomarkers for OA are still limited. We herein focused on subchondral bone, a joint component often-ignored by existing bioinformatic reports, to identify ferroptosis-related diagnostic biomarkers for OA.

METHOD

Microarray datasets GSE51588 and GSE55457 were downloaded from Gene Expression Omnibus database. Ferroptosis-related differential expression genes (Ferr-DEGs) between OA and normal samples were identified and their functional enrichment was analyzed. Common genes for OA diagnosis were selected from Ferr-DEGs using the combination of SVM-RFE, LASSO regression, and RandomForest machine learning algorithms. Common genes' diagnostic value was verified by receiver operating characteristic (ROC) curve and their association with immune infiltration was analyzed by CIBERSORT. Finally, candidate gene's expression was verified in chondrocytes from OA patients and in an in vitro IL-1β-induced OA model, by RT-PCR.

RESULTS

Two ferroptosis-related genes, LPCAT3 and PGD, were identified as OA diagnostic biomarkers and confirmed by ROC diagnostic test. The association of LPCAT3 and PGD with the infiltration of several types of immune cells was identified. The decreased expression of LPCAT3 and PGD was both confirmed in OA chondrocytes and IL-1β-induced OA condition.

CONCLUSIONS

We identified ferroptosis-related genes LPCAT3 and PGD as potential diagnostic biomarkers for OA, which may offer insight into the role of ferroptosis in OA and provides useful information for the diagnosis and treatment of OA.

Identification of EGFR as an essential regulator in chondrocytes ferroptosis of osteoarthritis using bioinformatics, in vivo, and in vitro study

Objective

The mechanisms of chondrocytes ferroptosis in osteoarthritis (OA) have not yet been fully elucidated. This study aimed to identify key ferroptosis related genes (FRGs) involved in chondrocytes ferroptosis.

Methods

LASSO, SVM-RFE, and receiver operating characteristic curve (ROC) were performed to screen key differentially expressed FRGs (DEFRGs). Functional analyses were conducted using GO, and KEGG analyses. Unsupervised clustering analysis was used to identify ferroptosis related patterns. The CeRNA network was constructed to predict the upstream miRNAs and lncRNAs. Finally, we validated the role of EGFR in chondrocytes ferroptosis using in vivo and in vitro experiments.

Results

A total of 42 DEFRGs were identified between OA and normal cartilages. GO and KEGG analyses indicated that these DEFRGs were significantly engaged in ferroptosis related biological processes and pathways, such as cellular response to oxidative stress, positive regulation of programmed cell death, MAPK and PI3K-Akt signaling pathways. Moreover, four key DEFRGs, including ACSF2, AURKA, EGFR, and KLHL24, were considered as potential biomarkers of OA. Moreover, two distinct ferroptosis related patterns were determined, and a total of 882 differentially expressed genes were identified which might participate in extracellular matrix degradation and inflammatory response. In addition, the CeRNA network showed that EGFR could be competitively regulated by 3 lncRNAs and 4 miRNAs. Significantly, the expression of EGFR was downregulated in human OA cartilages, OA mouse model, and erastin induced chondrocytes. EGFR inhibition could induce the occurrence of chondrocytes ferroptosis and ECM degradation which could be reversed by the addition of Ferrostatin-1.

Conclusion

Our study has identified ACSF2, AURKA, EGFR, and KLHL24 as ferroptosis-related biomarkers in OA. Furthermore, we have conducted a preliminary investigation into the role of EGFR in regulating chondrocytes ferroptosis. These findings offer novel insights into the molecular mechanisms underlying OA.

Tomatidine targets ATF4-dependent signaling and induces ferroptosis to limit pancreatic cancer progression

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with high metastasis and therapeutic resistance. Activating transcription factor 4 (ATF4), a master regulator of cellular stress, is exploited by cancer cells to survive. Prior research and data reported provide evidence that high ATF4 expression correlates with worse overall survival in PDAC. Tomatidine, a natural steroidal alkaloid, is associated with inhibition of ATF4 signaling in multiple diseases. Here, we discovered that in vitro and in vivo tomatidine treatment of PDAC cells inhibits tumor growth. Tomatidine inhibited nuclear translocation of ATF4 and reduced the transcriptional binding of ATF4 with downstream promoters. Tomatidine enhanced gemcitabine chemosensitivity in 3D ECM-hydrogels and in vivo. Tomatidine treatment was associated with induction of ferroptosis signaling validated by increased lipid peroxidation, mitochondrial biogenesis, and decreased GPX4 expression in PDAC cells. This study highlights a possible therapeutic approach utilizing a plant-derived metabolite, tomatidine, to target ATF4 activity in PDAC.

Crosstalk between ferroptosis and chondrocytes in osteoarthritis: a systematic review of in vivo and in vitro studies

Purpose

Recent scientific reports have revealed a close association between ferroptosis and the occurrence and development of osteoarthritis (OA). Nevertheless, the precise mechanisms by which ferroptosis influences OA and how to hobble OA progression by inhibiting chondrocyte ferroptosis have not yet been fully elucidated. This study aims to conduct a comprehensive systematic review (SR) to address these gaps.

Methods

Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, we conducted a comprehensive search of the Embase, Ovid, ProQuest, PubMed, Scopus, the Cochrane Library, and Web of Science databases to identify relevant studies that investigate the association between ferroptosis and chondrocytes in OA. Our search included studies published from the inception of these databases until January 31st, 2023. Only studies that met the predetermined quality criteria were included in this SR.

Results

In this comprehensive SR, a total of 21 studies that met the specified criteria were considered suitable and included in the current updated synthesis. The mechanisms underlying chondrocyte ferroptosis and its association with OA progression involve various biological phenomena, including mitochondrial dysfunction, dysregulated iron metabolism, oxidative stress, and crucial signaling pathways.

Conclusion

Ferroptosis in chondrocytes has opened an entirely new chapter for the investigation of OA, and targeted regulation of it is springing up as an attractive and promising therapeutic tactic for OA.

Systematic review registration

https://inplasy.com/inplasy-2023-3-0044/, identifier INPLASY202330044.

Identification of Immune-Related Risk Genes in Osteoarthritis Based on Bioinformatics Analysis and Machine Learning

In this research, we aimed to perform a comprehensive bioinformatic analysis of immune cell infiltration in osteoarthritic cartilage and synovium and identify potential risk genes. Datasets were downloaded from the Gene Expression Omnibus database. We integrated the datasets, removed the batch effects and analyzed immune cell infiltration along with differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA) was used to identify the positively correlated gene modules. LASSO (least absolute shrinkage and selection operator)-cox regression analysis was performed to screen the characteristic genes. The intersection of the DEGs, characteristic genes and module genes was identified as the risk genes. The WGCNA analysis demonstrates that the blue module was highly correlated and statistically significant as well as enriched in immune-related signaling pathways and biological functions in the KEGG and GO enrichment. LASSO-cox regression analysis screened 11 characteristic genes from the hub genes of the blue module. After the DEG, characteristic gene and immune-related gene datasets were intersected, three genes, PTGS1, HLA-DMB and GPR137B, were identified as the risk genes in this research. In this research, we identified three risk genes related to the immune system in osteoarthritis and provide a feasible approach to drug development in the future.