P2X7 receptor is essential for ST36-attenuated cardiac fibrosis upon beta-adrenergic insult.

P2X7 receptor (P2X7R) plays an important role in modulating inflammation and fibrosis, but information is limited whether Zusanli (ST36) can inhibit inflammation and fibrosis by regulating P2X7R. Isoprenaline at 5 mg/kg was subcutaneously injected to wild-type and P2X7R knockout mice for 7 days, while treatment groups received electroacupuncture (EA) stimulation at ST36 for 7 sessions. Following 7-session treatment, Masson's trichrome staining was performed to assess the fibrosis. Morphology, electrocardiogram, and echocardiography were carried out to evaluate the cardiac function and structure. Western blotting, hematoxylin and eosin staining, immunohistochemistry, and biochemical analysis of inflammatory cytokine and transmission electron microscopy were carried out to characterize the effect of ST36 on inflammation. P2X7R was overexpressed in ISO-treated mice. EA at ST36, but not at non-points, reduced ISO-induced cardiac fibrosis, increases in HW/BW, R+S wave relative to mice in ISO groups. In addition, EA at ST36 downregulated ISO-upregulated P2X7R and NLRP3 in ventricle. Moreover, EA reduced cytokines of IL-1ß, IL-6, and IL-18 in serum, and inhibited foam cell gathering, inflammatory cell infiltration, and autophagy. However, EA at ST36 failed to attenuate the cardiac fibrosis and hypertrophy in P2X7R knockout mice. In conclusion, EA at ST36 attenuated ISO-induced fibrosis possibly via P2X7R.

Prognostic and clinical value of circPRKCI expression in diverse human cancers.

BACKGROUND: Highly expressed in various human cancers, circular RNA Protein Kinase C Iota (circPRKCI) has been reported to play an important role in cancer development and progression. Herein, we sought to reveal the prognostic and clinical value of circPRKCI expression in diverse human cancers. METHODS: We searched the Pubmed, Web of Science, and the Cochrane Library databases from inception until May 16, 2021. The relationship between circPRKCI expression and cancer patients' survival, including overall survival (OS) and disease-free survival (DFS), was assessed by pooled hazard ratios (HR) with corresponding 95% confidence interval (CI). The correlation between circPRKCI expression and clinical outcomes was evaluated using odds ratios (OR) with corresponding 95% CI. The data were analyzed by STATA software (version 12.0) or Review Manager (RevMan 5.3). RESULTS: A total of 15 studies with 1109 patients were incorporated into our meta-analysis. The results demonstrated that high circPRKCI expression was significantly related to poor OS (HR = 1.96, 95% CI: 1.61, 2.39, P <0.001) when compared with low circPRKCI expression in diverse human cancers. However, elevated circPRKCI expression was not associated with DFS (HR = 1.34, 95% CI: 0.93, 1.95, P = 0.121). Furthermore, the patient with a higher circPRKCI expression was prone to have a larger tumor size, advanced clinical stage, and lymph node metastasis, but it was not significantly correlated with age, gender, and distant metastasis. CONCLUSION: Elevated circPRKCI expression was correlated with worse OS and unfavorable clinical features, suggesting a novel prognostic and predictive role of circPRKCI in diverse human cancers.

Identification of candidate genes and chemicals associated with osteoarthritis by transcriptome-wide association study and chemical-gene interaction analysis.

BACKGROUND: Osteoarthritis (OA) is a common degenerative joint disease and causes chronic pain and disability to the elderly. Several risk factors are involved, such as aging, obesity, genetic susceptibility, and environmental factors. We conducted a transcriptome-wide association study (TWAS) and chemical-related gene set enrichment analysis (CGSEA) to investigate the susceptibility genes and environmental factors. METHODS: TWAS analysis was conducted to identify the susceptibility genes by integrating the summary-level genome-wide association study data of knee OA (KOA) and hip OA (HOA) with the precomputed expression weights from the Genotype-Tissue Expression Project (Version 8). The FUSION software was used for both single-tissue and cross-tissue TWAS, which were combined using an aggregate Cauchy association test. The biological function and pathways of the TWAS genes were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases, and the human cartilage mRNA expression profiles were utilized to validate the TWAS genes. CGSEA analysis was performed to scan the OA-associated chemicals by integrating the TWAS results with the chemical-related gene sets. RESULTS: There were 44 and 93 unique TWAS genes identified in 7 and 11 chromosomes for KOA and HOA, respectively, fourteen and four of which showed significantly differential expression in the mRNA profiles, such as CRHR1, LTBP1, WWP2, LMX1B, and PTHLH. OA-related pathways were found in the KEGG and GO analysis, such as TGF-beta signaling pathway, MAPK signaling pathway, hyaluronan metabolic process, and chondrocyte differentiation. Forty-five OA-associated chemicals were identified, including quercetin, bisphenol A, and cadmium chloride. CONCLUSIONS: Several candidate OA-associated genes and chemicals were identified through TWAS and CGSEA analysis, which expanded our understanding of the relationship between genes, chemicals, and their impact on OA.

Integrated multiomic analysis and high-throughput screening reveal potential gene targets and synergetic drug combinations for osteosarcoma therapy.

Although great advances have been made over the past decades, therapeutics for osteosarcoma are quite limited. We performed long-read RNA sequencing and tandem mass tag (TMT)-based quantitative proteome on osteosarcoma and the adjacent normal tissues, next-generation sequencing (NGS) on paired osteosarcoma samples before and after neoadjuvant chemotherapy (NACT), and high-throughput drug combination screen on osteosarcoma cell lines. Single-cell RNA sequencing data were analyzed to reveal the heterogeneity of potential therapeutic target genes. Additionally, we clarified the synergistic mechanisms of doxorubicin (DOX) and HDACs inhibitors for osteosarcoma treatment. Consequently, we identified 2535 osteosarcoma-specific genes and several alternative splicing (AS) events with osteosarcoma specificity and/or patient heterogeneity. Hundreds of potential therapeutic targets were identified among them, which showed the core regulatory roles in osteosarcoma. We also identified 215 inhibitory drugs and 236 synergistic drug combinations for osteosarcoma treatment. More interestingly, the multiomic analysis pointed out the pivotal role of HDAC1 and TOP2A in osteosarcoma. HDAC inhibitors synergized with DOX to suppress osteosarcoma both in vitro and in vivo. Mechanistically, HDAC inhibitors synergized with DOX by downregulating SP1 to transcriptionally modulate TOP2A expression. This study provided a comprehensive view of molecular features, therapeutic targets, and synergistic drug combinations for osteosarcoma.

Comprehensive analysis of a novel cuproptosis-related lncRNA signature associated with prognosis and tumor matrix features to predict immunotherapy in soft tissue carcinoma.

Background: A crucial part of the malignant processes of soft tissue sarcoma (STS) is played by cuproptosis and lncRNAs. However, the connection between cuproptosis-related lncRNAs (CRLs) and STS is nevertheless unclear. As a result, our objective was to look into the immunological activity, clinical significance, and predictive accuracy of CRLs in STS. Methods: The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, respectively, provided information on the expression patterns of STS patients and the general population. Cuproptosis-related lncRNA signature (CRLncSig) construction involved the univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analysis. The predictive performance of the CRLncSig was evaluated using a serial analysis. Further research was done on the connections between the CRLncSig and the tumor immune milieu, somatic mutation, immunotherapy response, and chemotherapeutic drug susceptibility. Notably, an in vitro investigation served to finally validate the expression of the hallmark CRLs. Results: A novel efficient CRLncSig composed of seven CRLs was successfully constructed. Additionally, the low-CRLncSig group's prognosis was better than that of the high-CRLncSig group's based on the new CRLncSig. The innovative CRLncSig then demonstrated outstanding, consistent, and independent prognostic and predictive usefulness for patients with STS, according to the evaluation and validation data. The low-CRLncSig group's patients also displayed improved immunoreactivity phenotype, increased immune infiltration abundance and checkpoint expression, and superior immunotherapy response, whereas those in the high-CRLncSig group with worse immune status, increased tumor stemness, and higher collagen levels in the extracellular matrix. Additionally, there is a noticeable disparity in the sensitivity of widely used anti-cancer drugs amongst various populations. What's more, the nomogram constructed based on CRLncSig and clinical characteristics of patients also showed good predictive ability. Importantly, Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) demonstrated that the signature CRLs exhibited a significantly differential expression level in STS cell lines. Conclusion: In summary, this study revealed the novel CRLncSig could be used as a promising predictor for prognosis prediction, immune activity, tumor immune microenvironment, immune response, and chemotherapeutic drug susceptibility in patients with STS. This may provide an important direction for the clinical decision-making and personalized therapy of STS.

Molecular characterization of immunogenic cell death indicates prognosis and tumor microenvironment infiltration in osteosarcoma.

Introduction: Osteosarcoma (OS) is a highly aggressive bone malignancy with a poor prognosis, mainly in children and adolescents. Immunogenic cell death (ICD) is classified as a type of programmed cell death associated with the tumor immune microenvironment, prognosis, and immunotherapy. However, the feature of the ICD molecular subtype and the related tumor microenvironment (TME) and immune cell infiltration has not been carefully investigated in OS. Methods: The ICD-related genes were extracted from previous studies, and the RNA expression profiles and corresponding data of OS were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database. The ICD-related molecular subtypes were classed by the "ConsensusclusterPlus" package and the construction of ICD-related signatures through univariate regression analysis. ROC curves, independent analysis, and internal validation were used to evaluate signature performance. Moreover, a series of bioinformatic analyses were used for Immunotherapy efficacy, tumor immune microenvironments, and chemotherapeutic drug sensitivity between the high- and low-risk groups. Results: Herein, we identified two ICD-related subtypes and found significant heterogeneity in clinical prognosis, TME, and immune response signaling among distinct ICD subtypes. Subsequently, a novel ICD-related prognostic signature was developed to determine its predictive performance in OS. Also, a highly accurate nomogram was then constructed to improve the clinical applicability of the novel ICD-related signature. Furthermore, we observed significant correlations between ICD risk score and TME, immunotherapy response, and chemotherapeutic drug sensitivity. Notably, the in vitro experiments further verified that high GALNT14 expression is closely associated with poor prognosis and malignant progress of OS. Discussion: Hence, we identified and validated that the novel ICD-related signature could serve as a promising biomarker for the OS's prognosis, chemotherapy, and immunotherapy response prediction, providing guidance for personalized and accurate immunotherapy strategies for OS.

Integrated Analysis of TME and Hypoxia Identifies a Classifier to Predict Prognosis and Therapeutic Biomarkers in Soft Tissue Sarcomas.

Soft tissue sarcoma (STS) is one of the rarest but most aggressive cancer. It is important to note that intratumoral hypoxia and tumor microenvironment (TME) infiltration play a significant role in the growth and therapeutic resistance of STS. The goal of this study was therefore to determine whether linking hypoxia-related parameters to TME cells could provide a more accurate prediction of prognosis and therapeutic response. An analysis of 109 hypoxia-related genes and 64 TME cells was conducted in STS. Hypoxia-TME classifier was constructed based on 6 hypoxia prognostic genes and 8 TME cells. As a result, we evaluated the prognosis, tumor, and immune characteristics, as well as the effectiveness of therapies in Hypoxia-TME-defined subgroups. The Lowplus group showed a better prognosis and therapeutic response than any other subgroup. It is possible to unravel these differences based on immune-related molecules and somatic mutations in tumors. Further validation of Hypoxia-TME was done in an additional cohort of 225 STS patients. Additionally, we identified five key genes through differential analysis and RT-qPCR, namely, ACSM5, WNT7B, CA9, MMP13, and RAC3, which could be targeted for therapy. As a whole, the Hypoxia-TME classifier demonstrated a pretreatment predictive value for prognosis and therapeutic outcome, providing new approaches to therapy strategizing for patients.

A bibliometric research based on hotspots and frontier trends of denosumab.

Denosumab is a monoclonal antibody that targets and inhibits the osteoclast activating factor receptor activator for nuclear factor-κB ligand (RANKL). It has been widely used in the treatment of osteoporosis, giant cell tumors of bone, and in the prevention of malignant skeletal-related events (SREs). We collected the research results and related MeSH terms of denosumab from 2011 to 2021 through the Web of Science and PubMed, respectively. The literature was visualized and analyzed by CiteSpace and bibliometric online analysis platforms. The MeSH terms were biclustered using the Bibliographic Co-Occurrence Analysis System (BICOMB) and graph clustering toolkit (gCLUTO). The results show that the number of denosumab-related annual publications had increased from 51 to 215, with the United States leading and Amgen Inc. being the most influential in the past 10 years. Articles published in the Journal of Bone and Mineral Research had the highest total citations. Three scholars from Shinshu University in Matsumoto, Yukio Nakamura, Takako Suzuki, and Hiroyuki Kato, joined the field relatively late but produced the most. The clinical comparison and combination of denosumab with other drugs in the treatment of osteoporosis was the most significant focus of research. Drug withdrawal rebound and management strategies have gained more attention and controversy recently. MeSH analysis revealed eight major categories of research hotspots. Among them, exploring the multiple roles of the RANK-RANKL-OPG system in tumor progression, metastasis, and other diseases is the potential direction of future mechanism research. It is a valuable surgical topic to optimize the perioperative drug administration strategy for internal spinal fixation and orthopedic prosthesis implantation. Taken together, the advantages of denosumab were broad and cost-effective. However, there were still problems such as osteonecrosis of the jaw, severe hypocalcemia, a high recurrence rate of giant cells in the treatment of bone and individual sarcoidosis, and atypical femoral fractures, which need to be adequately solved.

Identification of cuproptosis-related lncRNA prognostic signature for osteosarcoma.

Background: Copper is an indispensably mineral element involved in various metabolic processes and functions in the active sites of many metalloproteins. Copper dysregulation is associated with cancers such as osteosarcoma (OS), the most common primary bone malignancy with invasiveness and metastasis. However, the causality between cuproptosis and OS remains elusive. We aim to identify cuproptosis-related long non-coding RNAs (lncRNAs) for osteosarcomatous prognosis, immune microenvironment response, and immunotherapy. Methods: The Person correlation and differential expression analysis were used to identify differentially expressed cuproptosis-related lncRNAs (CRLs). The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were performed to construct the CRL signature. The Kaplan-Meier (K-M) survival analysis, receiver operating characteristic (ROC) curve, internal validation, independent prognostic analysis, and nomograph were used to evaluate the prognostic value. The functional enrichment, tumor microenvironment, immunotherapy and chemotherapy response between the two distinct groups were further explored using a series of algorithms. The expression of signature CRLs was verified by real-time quantitative polymerase chain reaction (RT-qPCR) in OS cell lines. Results: A novel CRL signature consisting of four CRLs were successfully identified. The K-M survival analysis indicated that the OS patients in the low-risk groups had a better prognosis than that in the high-risk group. Then, the ROC curve and subgroup survival analysis confirmed the prognostic evaluation performance of the signature. Equally, the independent prognostic analysis demonstrated that the CRL signature was an independently predicted factor for OS. Friends analysis determined the hub genes that played a critical role in differentially expressed genes between two distinct risk groups. In addition, the risk score was related to immunity status, immunotherapy response, and chemotherapeutic drug sensitivity. Finally, the expression of these signature CRLs detected by RT-qPCR was consistent with the bioinformatic analysis results. Conclusion: In summary, our study confirmed that the novel CRL signature could effectively evaluate prognosis, tumor immune microenvironment, and immunotherapy response in OS. It may benefit for clinical decision-making and provide new insights for personalized therapeutics.

A novel necroptosis-related lncRNAs signature effectively predicts the prognosis for osteosarcoma and is associated with immunity.

Background: Necroptosis is closely related to tumorigenesis and development. Accumulating evidence has revealed that long non-coding RNAs (lncRNAs) are also central players in osteosarcoma (OS). However, the role of necroptosis-related lncRNAs in OS remains unclear. In the present study, we aim to craft a prognostic signature based on necroptosis-related lncRNAs to improve the OS prognosis prediction. Methods: The signature based on necroptosis-related lncRNAs was discovered using univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. The prognosis efficiency of the signature was then estimated by employing various bioinformatics methods. Subsequently, immunological analysis and Gene Set Enrichment Analysis (GSEA) were used to explore the association between necroptosis-related lncRNAs with clinical outcomes and immune status. More importantly, several necroptosis-related lncRNAs were validated with RT-qPCR. Results: Consequently, a novel prognosis signature was successfully constructed based on eight necroptosis-related lncRNAs. Meanwhile, the novel necroptosis-related lncRNAs model could distribute OS patients into two risk groups with a stable and accurate predictive ability. Additionally, the GSEA and immune analysis revealed that the necroptosis-related lncRNAs signature affects the development and prognosis of OS by regulating the immune status. The necroptosis-related lncRNA signature was closely correlated with multiple anticancer agent susceptibility. Moreover, the RT-qPCR results indicated several necroptosis-related lncRNAs were significantly differently expressed in osteosarcoma and osteoblast cell lines. Conclusion: In this summary, a novel prognostic signature integrating necroptosis-related lncRNAs was firstly constructed and could accurately predict the prognosis of OS. This study may increase the predicted value and guide the personalized chemotherapy treatment for OS.

Prognostic and clinicopathologic significance of circZFR in multiple human cancers.

BACKGROUND: Abnormally expressed in diverse cancers, circZFR has been correlated with clinical outcomes of cancer patients. Aim of this meta-analysis was to elucidate the prognostic role of circZFR in multiple human malignancies. METHODS: Literature retrieval was conducted by systematically searching on Pubmed, Web of Science, and the Cochrane Library up to December 2nd, 2021. Hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs) were pooled to evaluate the association between circZFR expression and overall survival (OS). The reliability of the pooled results was assessed through sensitivity analysis and the publication bias was measured by Begg's and Egger's test. RESULTS: A total of seventeen studies comprising 1098 Chinese patients were enrolled in this meta-analysis. Results demonstrated that high circZFR expression was correlated with an unfavorable OS (HR = 2.14, 95% CI 1.74, 2.64). High circZFR expression predicted larger tumor size (OR = 2.79, 95% CI 1.52, 5.12), advanced clinical stage (OR = 3.38, 95% CI 1.49, 7.65), tendentiousness of lymph node metastasis (LNM) (OR = 3.08, 95% CI 2.01, 4.71), and malignant grade (OR = 3.18, 95% CI 1.09, 9.30), but not related to age, gender, and distant metastasis (DM). CONCLUSIONS: High circZFR expression was associated with unfavorable OS and clinicopathologic parameters including tumor size, clinical stage, LNM, and histology grade, implicating a promising prognostic factor in cancers.

A Necroptosis-Related lncRNA Signature Predicts Prognosis and Indicates the Immune Microenvironment in Soft Tissue Sarcomas.

Background: The necroptosis and long noncoding RNA (lncRNA) are critical in the occurrence and development of malignancy, while the association between the necroptosis-related lncRNAs (NRlncRNAs) and soft tissue sarcoma (STS) remains controversial. Therefore, the present study aims to construct a novel signature based on NRlncRNAs to predict the prognosis of STS patients and investigate its possible role. Methods: The transcriptome data and clinical characteristics were extracted from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression database (GTEx). A novel NRlncRNA signature was established and verified by the COX regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, the K-M survival analysis, ROC, univariate, multivariate Cox regression analysis, and nomogram were used to evaluate the predictive value of the signature. Also, a variety of bioinformatic analysis algorithms explored the differences between the potential mechanism, tumor immune status, and drug sensitivity in the two-risk group. Finally, the RT-qPCR was performed to evaluate the expression of signature NRlncRNAs. Results: A novel signature consisting of seven NRlncRNAs was successfully established and verified with stable prediction performance and general applicability for STS. Next, the GSEA showed that the patients in the high-risk group were mainly enriched with tumor-related pathways, while the low-risk patients were significantly involved in immune-related pathways. In parallel, we found that the STS patients in the low-risk group had a better immune status than that in the high-risk group. Additionally, there were significant differences in the sensitivity to anti-tumor agents between the two groups. Finally, the RT-qPCR results indicated that these signature NRlncRNAs were abnormally expressed in STS. Conclusion: To the best of our knowledge, it is the first study to construct an NRlncRNA signature for STS. More importantly, the novel signature displays stable value and translational potential for predicting prognosis, tumor immunogenicity, and therapeutic response in STS.

Stem Cell-Laden Hydrogel-Based 3D Bioprinting for Bone and Cartilage Tissue Engineering.

Tremendous advances in tissue engineering and regenerative medicine have revealed the potential of fabricating biomaterials to solve the dilemma of bone and articular defects by promoting osteochondral and cartilage regeneration. Three-dimensional (3D) bioprinting is an innovative fabrication technology to precisely distribute the cell-laden bioink for the construction of artificial tissues, demonstrating great prospect in bone and joint construction areas. With well controllable printability, biocompatibility, biodegradability, and mechanical properties, hydrogels have been emerging as an attractive 3D bioprinting material, which provides a favorable biomimetic microenvironment for cell adhesion, orientation, migration, proliferation, and differentiation. Stem cell-based therapy has been known as a promising approach in regenerative medicine; however, limitations arise from the uncontrollable proliferation, migration, and differentiation of the stem cells and fortunately could be improved after stem cells were encapsulated in the hydrogel. In this review, our focus was centered on the characterization and application of stem cell-laden hydrogel-based 3D bioprinting for bone and cartilage tissue engineering. We not only highlighted the effect of various kinds of hydrogels, stem cells, inorganic particles, and growth factors on chondrogenesis and osteogenesis but also outlined the relationship between biophysical properties like biocompatibility, biodegradability, osteoinductivity, and the regeneration of bone and cartilage. This study was invented to discuss the challenge we have been encountering, the recent progress we have achieved, and the future perspective we have proposed for in this field.

A Novel Glutamine Metabolism-Related Gene Signature in Prognostic Prediction of Osteosarcoma.

PURPOSE: Metabolic reprogramming, as one of the hallmarks of cancer, shows promising translational potential for cancer diagnosis, treatment and prognostic prediction. This study aims to construct and validate a prognostic prediction model for osteosarcoma based on glutamine metabolism-related genes. MATERIALS AND METHODS: A group of glutamine metabolism-related genes was identified from a public database and intersected with a list of osteosarcoma survival-related genes, and a risk score model based on sixteen glutamine metabolism-related genes was developed by using LASSO penalized Cox regression analysis. RESULTS: The prognosis of patients in the high-risk group was significantly worse than that of patients in the low-risk group in the training dataset (high- vs low-risk, 5-year overall survival: 11% vs 88%, p < 0.0001) and in two other external validation cohorts (high- vs low-risk, 5-year overall survival: 39% vs 81%, p = 0.015; 50% vs 94%, p = 0.011).In addition, a novel nomogram was constructed by integrating the risk score and clinical characteristics, including age, sex, metastasis status and chemotherapy response. This nomogram had superior predictive power compared with a nomogram composed of only conventional factors. Gene set enrichment analysis indicated that several well-known malignancy-associated gene sets, including MYC targets V1, DNA repair, and unfolded protein response, were enriched in the high-risk subgroup. CONCLUSION: A novel glutamine metabolism-related prognostic prediction model and nomogram for osteosarcoma was developed and validated in the present study, which could predict the survival of patients with osteosarcoma and may facilitate individualized clinical decision-making for patients.

Patients' risk factors for periprosthetic joint infection in primary total hip arthroplasty: a meta-analysis of 40 studies.

BACKGROUND: Periprosthetic joint infection (PJI) is a catastrophic complication after total hip arthroplasty (THA). Our meta-analysis aimed to identify the individual-related risk factors that predispose patients to PJI following primary THA. METHODS: Comprehensive literature retrieval from Pubmed, Web of Science, and the Cochrane Library was performed from inception to Feb 20th, 2021. Patient-related risk factors were compared as per the modifiable factors (BMI, smoke and alcohol abuse), non-modifiable factors (gender, age), and medical history characteristics, such as diabetes mellitus (DM), avascular necrosis (AVN) of femoral head, femoral neck fracture, rheumatoid arthritis (RA), cardiovascular disease (CVD), and osteoarthritis (OA) etc. The meta-analysis was applied by using risk ratios with 95% corresponding intervals. Sensitivity analysis and publication bias were performed to further assess the credibility of the results. RESULTS: Overall, 40 studies with 3,561,446 hips were enrolled in our study. By implementing cumulative meta-analysis, higher BMI was found associated with markedly increased PJI risk after primary THA [2.40 (2.01-2.85)]. Meanwhile, medical characteristics including DM [1.64 (1.25-2.21)], AVN [1.65 (1.07-2.56)], femoral neck fracture [1.75 (1.39-2.20)], RA [1.37 (1.23-1.54)], CVD [1.34 (1.03-1.74)], chronic pulmonary disease (CPD) [1.22 (1.08-1.37)], neurological disease [1.19 (1.05-1.35)], opioid use [1.53 (1.35-1.73)] and iron-deficiency anemia (IDA) [1.15 (1.13-1.17)] were also significantly correlated with higher rate of PJI. Conversely, dysplasia or dislocation [0.65 (0.45-0.93)], and OA [0.70 (0.62-0.79)] were protective factors. Of Note, female gender was protective for PJI only after longer follow-up. Besides, age, smoking, alcohol abuse, previous joint surgery, renal disease, hypertension, cancer, steroid use and liver disease were not closely related with PJI risk. CONCLUSION: Our finding suggested that the individual-related risk factors for PJI after primary THA included high BMI, DM, AVN, femoral neck fracture, RA, CVD, CPD, neurological disease, opioid use and IDA, while protective factors were female gender, dysplasia/ dislocation and OA.

Functional interplay between long non-coding RNAs and the Wnt signaling cascade in osteosarcoma.

Osteosarcoma is a common and highly malignant bone tumor among children, adolescents and young adults. However, the underlying molecular mechanisms remain largely unexplored. LncRNAs are transcripts with no or limited protein-coding capacity in human genomes, and have been demonstrated to play crucial functions in initiation, progression, therapeutic resistance, recurrence and metastasis of tumor. Considerable studies revealed a dysregulated lncRNA expression pattern in osteosarcoma, which may act as oncogenes or suppressors to regulate osteosarcoma progression. Wnt signaling pathway is an important cascade in tumorigenesis by modulation of pleiotropic biological functions including cell proliferation, apoptosis, differentiation, stemness, genetic stability and chemoresistance. Hyperactivation or deficiency of key effectors in Wnt cascade is a common event in many osteosarcoma patients. Recently, increasing evidences have suggested that lncRNAs could interplay with component of Wnt pathway, and thereby contribute to osteosarcoma onset, progression and dissemination. In this review, we briefly summarize Wnt signaling-related lncRNAs in osteosarcoma progression, aiming to gain insights into their underlying crosstalk as well as clinical application in osteosarcoma therapeutic modalities.

Circular RNAs in osteoarthritis: indispensable regulators and novel strategies in clinical implications.

Over the past decades, circular RNAs (circRNAs) have emerged as a hot spot and sparked intensive interest. Initially considered as the transcriptional noises, further studies have indicated that circRNAs are crucial regulators in multiple cellular biological processes, and thus engage in the development and progression of many diseases including osteoarthritis (OA). OA is a prevalent disease that mainly affects those aging, obese and post-traumatic population, posing as a major source of socioeconomic burden. Recently, numerous circRNAs have been found aberrantly expressed in OA tissues compared with counterparts. More importantly, circRNAs have been demonstrated to interplay with components in OA microenvironments, such as chondrocytes, synoviocytes and macrophages, by regulation of their proliferation, apoptosis, autophagy, inflammation, or extracellular matrix reorganization. Herein, in this review, we extensively summarize the roles of circRNAs in OA microenvironment, progression, and putative treatment, as well as envision the future directions for circRNAs research in OA, with the aim to provide a novel insight into this field.

MTHFR Polymorphism Is Associated With Severe Methotrexate-Induced Toxicity in Osteosarcoma Treatment.

BACKGROUND: Previous studies have revealed the critical role of methylene tetrahydrofolate reductase (MTHFR) polymorphisms in response to high-dose methotrexate (MTX)-induced toxicity in osteosarcoma patients. However, the conclusions remain controversial. In this setting, we performed a meta-analysis to determine their association more precisely. METHOD: Eligible studies were searched and screened in PubMed, Web of Science, Cochrane Library, Clinical-Trials.gov, Embase, and China National Knowledge Infrastructure (CNKI) following specific inclusion and exclusion criteria. The required information was retrieved and collected for subsequent meta-analysis. Association between MTHFR polymorphism and MTX toxicity was evaluated by odds ratios (ORs). RESULTS: Seven studies containing 585 patients were enrolled and analyzed in this meta-analysis. Overall, the MTX related grade 3-4 liver toxicity was significantly associated with MTHFR rs1801133 allele (T vs. C: OR=1.61, 95%CI=1.07-2.42, P=0.024), homozygote (TT vs. CC: OR=2.11, 95%CI=1.06-4.21, P=0.011), and dominant genetic model (TT/TC vs. CC: OR=3.15, 95%CI=1.30-7.60, P=0.035) in Asian population. Meanwhile, close associations between MTX mediated grade 3-4 mucositis and MTHFR rs1801133 polymorphism were identified in allele contrast (T vs. C: OR=2.28, 95%CI=1.49-3.50, P<0.001), homozygote comparison (TT vs. CC: OR=4.07, 95%CI=1.76-9.38, P=0.001), heterozygote comparison (TC vs. CC: OR=2.55, 95%CI=1.20-5.42, P=0.015), recessive genetic model (TT vs. TC/CC: OR=2.09, 95%CI=1.19-3.67, P=0.010), and dominant genetic model (TT/TC vs. CC: OR=2.97, 95%CI=1.48-5.96, P=0.002). Additionally, kidney toxicity was corelated with the heterozygote comparison (TC vs. CC: OR=2.63, 95%CI=1.31-5.29, P=0.007) of rs1801133 polymorphism. CONCLUSION: The MTHFR rs1801133 polymorphism was significantly associated with severer liver toxicity induced by high-dose MTX treatment in the Asian population. In the meantime, patients with MTHFR rs1801133 polymorphism were predisposed to MTX- related mucositis.

Multifaceted Functions and Novel Insight Into the Regulatory Role of RNA N6-Methyladenosine Modification in Musculoskeletal Disorders.

RNA modifications have emerged as key regulators of transcript expression in diverse physiological and pathological processes. As one of the most prevalent types of RNA modifications, N6-methyladenosine (m6A) has become the highlight in modulation of various diseases through interfering RNA splicing, translation, nuclear export, and decay. In many cases, the detailed functions of m6A in cellular processes and diseases remain unclear. Notably, recent studies have determined the relationship between m6A modification and musculoskeletal disorders containing osteosarcoma, osteoarthritis, rheumatoid arthritis, osteoporosis, etc. Herein, this review comprehensively summarizes the recent advances of m6A modification in pathogenesis and progression of musculoskeletal diseases. Specifically, the underlying molecular mechanisms, detection technologies, regulatory functions, clinical implications, and future perspectives of m6A in musculoskeletal disorders are discussed, with the aim to provide a novel insight into their association.

Upregulated expression of LncRNA nicotinamide nucleotide transhydrogenase antisense RNA 1 is correlated with unfavorable clinical outcomes in cancers.

BACKGROUND: The nicotinamide nucleotide transhydrogenase antisense RNA 1 (NNT-AS1) is a long non-coding RNA aberrantly expressed in human malignancies. We aimed to analyze available data to evaluate the correlation between NNT-AS1 expression and cancer prognosis. METHODS: Literature retrieval was performed by systematic searching related databases from inception to April 2, 2020. Studies regarding correlation between NNT-AS1 expression, survival outcomes and clinical characteristics of cancer patients were collected and pooled to calculate the the hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (95% CIs). RESULTS: Ten studies comprising 699 patients were included, all of which were conducted in China according to literature selection criteria. Overexpression of NNT-AS1 had a significant association with unfavorable overall survival (OS) (HR = 2.08, 95% CI: 1.84-2.36, P < 0.001). Stratified analysis showed that tumor type, sample size, follow-up months, and survival analysis approach did not change the predictive value of NNT-AS1 on OS. Furthermore, elevated NNT-AS1 level had significant association with distant metastasis (DM) (OR = 2.45, 95% CI: 1.39-4.30), lymph node metastasis (LNM) (OR = 3.92, 95% CI: 1.35-11.41), TNM stage (OR = 4.25, 95% CI: 1.71-10.56), and vascular invasion (OR = 3.98, 95% CI: 2.06-7.71), but was not associated with age and gender. The TCGA dataset further consistently showed that the NNT-AS1 expression was associated with poor OS and disease-free survival. CONCLUSIONS: High expression of NNT-AS1 is associated with unfavorable survival outcomes and poor clinicopathologic characteristics. However, large-cohort data and geographical studies are still needed to further validate the prognostic value of NNT-AS1 in cancers.