BRD4 Inhibition Suppresses Senescence and Apoptosis of Nucleus Pulposus Cells by Inducing Autophagy during Intervertebral Disc Degeneration: An In Vitro and In Vivo Study.

Intervertebral disc degeneration (IDD) is the most common chronic skeletal muscle degeneration disease. Although the underlying mechanisms remain unclear, nucleus pulposus (NP) autophagy, senescence, and apoptosis are known to play a critical role in this process. Previous studies suggest that bromodomain-containing protein 4 (BRD4) promotes senescent and apoptotic effects in several age-related degenerative diseases. It is not known, however, if BRD4 inhibition is protective in IDD. In this study, we explored whether BRD4 influenced IDD. In human clinical specimens, the BRD4 level was markedly increased with the increasing Pfirrmann grade. At the cellular level, BRD4 inhibition prevented IL-1ß-induced senescence and apoptosis of NP cells and activated autophagy via the AMPK/mTOR/ULK1 signaling pathway. Inhibition of autophagy by 3-methyladenine (3-MA) partially reversed the antisenescence and antiapoptotic effects of BRD4. In vivo, BRD4 inhibition attenuated IDD. Taken together, the results of this study showed that BRD4 inhibition reduced NP cell senescence and apoptosis by induced autophagy, which ultimately alleviated IDD. Therefore, BRD4 may serve as a novel potential therapeutic target for the treatment of IDD.

SKI knockdown suppresses apoptosis and extracellular matrix degradation of nucleus pulposus cells via inhibition of the Wnt/ß-catenin pathway and ameliorates disc degeneration.

This study aimed to determine the effects of SKI on interleukin (IL)-1ß-induced apoptosis of nucleus pulposus (NP) cells, intervertebral disc degeneration (IDD), and the Wnt signaling pathway. NP tissue specimens of different Pfirrmann grades (II-V) were collected from patients with different grades of IDD. Real-time polymerase chain reaction and western blotting were used to compare SKI mRNA and protein expression in NP tissues from patients. Using the IL-1ß-induced IDD model, NP cells were infected with lentivirus-coated si-SKI to downregulate the expression of SKI and treated with LiCl to evaluate the involvement of the Wnt/ß-catenin signaling pathway. Western blotting, immunofluorescence, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining were used to detect NP cell apoptosis, extracellular matrix (ECM) metabolism, and related protein expression changes in the Wnt/ß-catenin signaling pathway. To investigate the role of SKI in vivo, a rat IDD model was established by needle puncture of the intervertebral disc. Rats were injected with lentivirus-coated si-SKI and evaluated by magnetic resonance imaging (MRI), and hematoxylin and eosin (HE) and safranin O staining. SKI expression positively correlated with the severity of human IDD. In the IL-1ß-induced NP cell degeneration model, SKI expression increased significantly and reached a peak at 24 h. SKI knockdown protected against IL-1ß-induced NP cell apoptosis and ECM degradation. LiCl treatment reversed the protective effects of si-SKI on NP cells. Furthermore, lentivirus-coated si-SKI injection partially reversed the NP tissue damage in the IDD model in vivo. SKI knockdown reduced NP cell apoptosis and ECM degradation by inhibiting the Wnt/ß-catenin signaling pathway, ultimately protecting against IDD. Therefore, SKI may be an effective target for IDD treatment.

An Immune-Related Long Non-Coding RNA Signature to Predict the Prognosis of Ewing's Sarcoma Based on a Machine Learning Iterative Lasso Regression.

The aim of this study was to construct a new immune-associated long non-coding RNA (lncRNA) signature to predict the prognosis of Ewing sarcoma (ES) and explore its molecular mechanisms. We downloaded transcriptome and clinical prognosis data from the Gene Expression Omnibus (GSE17679, which included 88 ES samples and 18 matched normal skeletal muscle samples), and used it as a training set to identify immune-related lncRNAs with different expression levels in ES. Univariable Cox regression was used to screen immune-related lncRNAs related to ES prognosis, and an immune-related lncRNA signature was constructed based on machine learning iterative lasso regression. An external verification set was used to confirm the predictive ability of the signature. Clinical feature subgroup analysis was used to explore whether the signature was an independent prognostic factor. In addition, CIBERSORT was used to explore immune cell infiltration in the high- and low-risk groups, and to analyze the correlations between the lncRNA signature and immune cell levels. Gene set enrichment and variation analyses were used to explore the possible regulatory mechanisms of the immune-related lncRNAs in ES. We also analyzed the expression of 17 common immunotherapy targets in the high- and low-risk groups to identify any that may be regulated by immune-related lncRNAs. We screened 35 immune-related lncRNAs by univariate Cox regression. Based on this, an immune-related 11-lncRNA signature was generated by machine learning iterative lasso regression. Analysis of the external validation set confirmed its high predictive ability. DPP10 antisense RNA 3 was negatively correlated with resting dendritic cell, neutrophil, and γδ T cell infiltration, and long intergenic non-protein coding RNA 1398 was positively correlated with resting dendritic cells and M2 macrophages. These lncRNAs may affect ES prognosis by regulating GSE17721_CTRL_VS_PAM3CSK4_12H_BMDC_UP, GSE2770_IL4_ACT_VS_ACT_CD4_TCELL_48H_UP, GSE29615_CTRL_VS_DAY3_ LAIV_IFLU_VACCINE_PBMC_UP, complement signaling, interleukin 2-signal transducer and activator of transcription 5 signaling, and protein secretion. The immune-related 11-lncRNA signature may also have regulatory effects on the immunotherapy targets CD40 molecule, CD70 molecule, and CD276 molecule. In conclusion, we constructed a new immune-related 11-lncRNA signature that can stratify the prognoses of patients with ES.

Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients.

BACKGROUND: Osteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients. METHODS: We obtained expression and clinical data from osteosarcoma patients in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We acquired an autophagy gene list from the Human Autophagy Database (HADb) and identified autophagy-related lncRNAs by co-expression analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the autophagy-related lncRNAs were conducted. Univariate and multivariate Cox regression analyses were performed to assess the prognostic value of the autophagy-related lncRNA signature and validate the relationship between the signature and osteosarcoma patient survival in an independent cohort. We also investigated the relationship between the signature and immune cell infiltration. RESULTS: We initially identified 69 autophagy-related lncRNAs, 13 of which were significant predictors of overall survival in osteosarcoma patients. Kaplan-Meier analyses revealed that the 13 autophagy-related lncRNAs could stratify patients based on their outcomes. Receiver operating characteristic curve analyses confirmed the superior prognostic value of the lncRNA signature compared to clinically used prognostic biomarkers. Importantly, the autophagy-related lncRNA signature predicted patient prognosis independently of clinicopathological characteristics. Furthermore, we found that the expression levels of the autophagy-related lncRNA signature were significantly associated with the infiltration levels of different immune cell subsets, including T cells, NK cells, and dendritic cells. CONCLUSION: The autophagy-related lncRNA signature established here is an independent and robust predictor of osteosarcoma patient survival. Our findings also suggest that the expression of these 13 autophagy-related lncRNAs may promote osteosarcoma progression by regulating immune cell infiltration in the tumor microenvironment.

NF-κB signalling pathways in nucleus pulposus cell function and intervertebral disc degeneration.

Intervertebral disc degeneration (IDD) is a common clinical degenerative disease of the spine. A series of factors, such as inflammation, oxidative stress and mechanical stress, promote degradation of the extracellular matrix (ECM) of the intervertebral discs (IVD), leading to dysfunction and structural destruction of the IVD. Nuclear factor-κB (NF-κB) transcription factor has long been regarded as a pathogenic factor of IDD. Therefore, NF-κB may be an ideal therapeutic target for IDD. As NF-κB is a multifunctional functional transcription factor with roles in a variety of biological processes, a comprehensive understanding of the function and regulatory mechanism of NF-κB in IDD pathology will be useful for the development of targeted therapeutic strategies for IDD, which can prevent the progression of IDD and reduce potential risks. This review discusses the role of the NF-κB signalling pathway in the nucleus pulposus (NP) in the process of IDD to understand pathological NP degeneration further and provide potential therapeutic targets that may interfere with NF-κB signalling for IDD therapy.

Different Types of Double-Level Degenerative Lumber Spondylolisthesis: What Is Different in the Sagittal Plane?

BACKGROUND: Degenerative lumber spondylolisthesis (DLS) is a common orthopedic condition, described as a condition that compared with the lower vertebra, the superior vertebra slides forward or backward in the sagittal plane without accompanying isthmic spondylolisthesis. Information pertaining to different types of double-level DLS is scarce. This study aims to analyze parameters of patients with different types of double-level DLS to provide a reference for guiding surgical treatment and restoring sagittal balance of patients with DLS. METHODS: From January 2014 to January 2020, records of patients with double-level DLS were retrospectively reviewed. Patients with double-level DLS were divided into 3 types: anterior, posterior, and combined; the anterior and combined types were studied. The sagittal spinopelvic parameters included C7 tilt, maximal thoracic kyphosis, maximal lumbar lordosis (LLmax), pelvic incidence (PI), pelvic tilt (PT), and sacral slope (SS). After descriptive analysis, demographic and radiographic data were compared. RESULTS: Forty and 18 patients were included in the anterior and combined type groups, respectively. Both groups had different levels of chronic low back pain, but the incidence of radiating leg pain and neurogenic claudication was significantly higher in the anterior type. Oswestry Disability Index and visual analog scale low back scores were also higher in the anterior type. In the anterior type, C7 tilt (7.14 ± 2.15 vs. 5.41 ± 2.28, P = 0.007), LLmax (50.02 ± 14.76 vs. 36.96 ± 14.56, P = 0.003), PI (68.28 ± 9.16 vs. 55.53 ± 14.19, P < 0.001), PT (28.68 ± 7.31 vs. 19.38 ± 4.70, P < 0.001), and PT/PI (42.45 ± 11.22 vs. 36.04 ± 9.87, P = 0.041) were significantly higher. In the anterior type, PI correlated positively with LLmax (r = 0.59) and SS (r = 0.71). LLmax and SS (r = 0.65) had a positive correlation. PT/PI and SS (r = -0.77) had a negative correlation. In the combined type, PI correlated positively with LLmax (r = 0.61) and SS (r = 0.88), and PT/PI correlated negatively with SS (r = -0.81). CONCLUSIONS: In patients with double-level DLS, the sagittal spinopelvic parameters differed between the anterior and combined types. Overall, spinal surgeons should focus on correcting sagittal deformities, relieving postoperative clinical symptoms, and improving quality of life during fusion surgery.

Role of the Wnt pathway in the formation, development, and degeneration of intervertebral discs.

Intervertebral disc degeneration (IVDD) is an age-related degenerative disease that is the main cause of low back pain. It seriously affects the quality of life of patients and places a heavy economic burden on families and society. The Wnt pathway plays an important role in the growth, development, and degeneration of intervertebral discs (IVDs). In the embryonic stage, the Wnt pathway participates in the growth and development of IVD by promoting the transformation of progenitor cells into notochord cells and the extension of the notochord. However, the activation of the Wnt pathway after birth promotes IVD cell senescence, apoptosis, and degradation of the extracellular matrix and induces the production of inflammatory factors, thereby accelerating the IVDD process. This article reviews the relationship between the Wnt pathway and IVD, emphasizing its influence on IVD growth, development, and degeneration. Targeting this pathway may become an effective strategy for the treatment of IVDD.

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

PURPOSE: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient prognosis based on immune-related genes (IRGs). METHODS: We analyzed the ES gene expression profile dataset, GSE17679, from the GEO database and extracted differential expressed IRGs (DEIRGs). Then, we conducted functional correlation and protein-protein interaction (PPI) analyses of the DEIRGs and used the machine learning algorithm-iterative Lasso Cox regression analysis to build an optimal DEIRG signature. In addition, we applied ES samples from the ICGC database to test the optimal gene signature. We performed univariate and multivariate Cox regressions on clinicopathological characteristics and optimal gene signature to evaluate whether signature is an important prognostic factor. Finally, we calculated the infiltration of 24 immune cells in ES using the ssGSEA algorithm, and analyzed the correlation between the DEIRGs in the optimal gene signature and immune cells. RESULTS: A total of 249 DEIRGs were screened and an 11-gene signature with the strongest correlation with patient prognoses was analyzed using a machine learning algorithm. The 11-gene signature also had a high prognostic value in the ES external verification set. Univariate and multivariate Cox regression analyses showed that 11-gene signature is an independent prognostic factor. We found that macrophages and cytotoxic, CD8 T, NK, mast, B, NK CD56bright, TEM, TCM, and Th2 cells were significantly related to patient prognoses; the infiltration of cytotoxic and CD8 T cells in ES was significantly different. By correlating prognostic biomarkers with immune cell infiltration, we found that FABP4 and macrophages, and NDRG1 and Th2 cells had the strongest correlation. CONCLUSION: Overall, the IRG-related 11-gene signature can be used as a reliable ES prognostic biomarker and can provide guidance for personalized ES therapy.

Ski: Double roles in cancers.

The Ski (Sloan-Kettering Institute) is an evolutionarily conserved protein that plays a dual role as an oncoprotein and tumor suppressor gene in the development of human cancer. The Ski oncogene was first identified as a transforming protein of the avian Sloan-Kettering retrovirus in 1986. Since its discovery, Ski has been identified as a carcinogenic regulator in a variety of malignant tumors. Later, it was reported that Ski regulates the occurrence and development of some cancers by acting as an oncogene. Ski mediates the proliferation, differentiation, metastasis, and invasion of numerous cancer cells through various mechanisms. Several studies have shown that Ski expression is correlated with the clinical characteristics of cancer patients and is a promising biomarker and therapeutic target for cancer. In this review, we summarize the mechanisms and potential clinical implications of Ski in dimorphism, cancer occurrence, and progression in various types of cancer.

Development of a novel immune-related genes prognostic signature for osteosarcoma.

Immune-related genes (IRGs) are responsible for osteosarcoma (OS) initiation and development. We aimed to develop an optimal IRGs-based signature to assess of OS prognosis. Sample gene expression profiles and clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) databases. IRGs were obtained from the ImmPort database. R software was used to screen differentially expressed IRGs (DEIRGs) and functional correlation analysis. DEIRGs were analyzed by univariate Cox regression and iterative LASSO Cox regression analysis to develop an optimal prognostic signature, and the signature was further verified by independent cohort (GSE39055) and clinical correlation analysis. The analyses yielded 604 DEIRGs and 10 hub IRGs. A prognostic signature consisting of 13 IRGs was constructed, which strikingly correlated with OS overall survival and distant metastasis (p < 0.05, p < 0.01), and clinical subgroup showed that the signature's prognostic ability was independent of clinicopathological factors. Univariate and multivariate Cox regression analyses also supported its prognostic value. In conclusion, we developed an IRGs signature that is a prognostic indicator in OS patients, and the signature might serve as potential prognostic indicator to identify outcome of OS and facilitate personalized management of the high-risk patients.

The role of long non-coding RNA MIAT in cancers.

Long non-coding RNAs (lncRNAs), a kind of non-coding single-strand RNAs, play an important role as carcinogenic genes or tumor suppressors in the development of human cancer. Myocardial infarction-associated transcript (MIAT) was first identified as a lncRNA in 2006 and originally isolated as a candidate gene for myocardial infarction. Later, it was reported that MIAT exhibits regulatory effects on the human cell cycle. Since its discovery, MIAT has also been identified as a carcinogenic regulator in many malignant tumors. High expression of MIAT is related to the clinicopathological characteristics of cancer patients. It can also regulate cell proliferation, invasion, metastasis, and anti-apoptosis through a variety of mechanisms. Therefore, MIAT is considered a potential biomarker and therapeutic target in cancer. In this review, we summarize the biological function, mechanism, and potential clinical significance of MIAT during tumorigenesis.

GRB10 and E2F3 as Diagnostic Markers of Osteoarthritis and Their Correlation with Immune Infiltration.

This study aimed to find potential diagnostic markers for osteoarthritis (OA) and analyze the role of immune cells infiltration in this pathology. We used OA datasets from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and perform functional correlation analysis. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination algorithms were used to screen and verify the diagnostic markers of OA. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in OA tissues, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. A total of 458 DEGs were screened in this study. GRB10 and E2F3 (AUC = 0.962) were identified as diagnostic markers of OA. Immune cell infiltration analysis found that resting mast cells, T regulatory cells, CD4 memory resting T cells, activated NK cells, and eosinophils may be involved in the OA process. In addition, GRB10 was correlated with NK resting cells, naive CD4 + T cells, and M1 macrophages, while E2F3 was correlated with resting mast cells. In conclusion, GRB10 and E2F3 can be used as diagnostic markers of osteoarthritis, and immune cell infiltration plays an important role in the occurrence and progression of OA.