MEG3 alleviates ankylosing spondylitis by suppressing osteogenic differentiation of mesenchymal stem cells through regulating microRNA-125a-5p-mediated TNFAIP3.

Osteoblasts are important regulators of bone formation, but their roles in ankylosing spondylitis (AS) remain unclear. This study aims to explore the role of long non-coding RNA (lncRNA) maternally expressed 3 (MEG3) MEG3 in AS. Serum from AS patients as well as AS mesenchymal stem cells (ASMSCs) and healthy donors mesenchymal stem cells (HDMSCs) was collected. Accordingly, poorly expressed MEG3 and TNF alpha induced protein 3 (TNFAIP3) as well as overexpressed microRNA-125a-5p (miR-125a-5p) were noted in the serum of AS patients and in ASMSCs during the osteogenic induction process. Meanwhile, the interaction among MEG3, miR-125a-5p, and TNFAIP3 was determined and their effect on osteoblast activity was examined in vitro and in vivo. Overexpression of MEG3 and TNFAIP3 or inhibition of miR-125a-5p was found to inactivate the Wnt/ß-catenin pathway, thus suppressing osteogenic differentiation of MSCs. MEG3 competitively bound to miR-125a-5p to increase TNFAIP3 expression, thereby inactivating the Wnt/ß-catenin pathway and repressing the osteogenic differentiation of MSCs. In proteoglycan (PG)-induced AS mouse models, MEG3 also reduced osteogenic activity of MSCs to inhibit AS progression through the miR-125a-5p/TNFAIP3/Wnt/ß-catenin axis. Therefore, up-regulation of MEG3 or depletion of miR-125a-5p holds potential of alleviating AS, which sheds light on a new therapeutic strategy for AS treatment.

STAT3 and SPI1, may lead to the immune system dysregulation and heterotopic ossification in ankylosing spondylitis.

OBJECTIVE: This study was aimed to identify the biomarkers for diagnosis and reveal the immune microenvironment changes in ankylosing spondylitis (AS). METHODS: GSE73754 was downloaded for the co-expression network construction and immune cell analyses. Flow cytometric analysis was performed to validate the results of bioinformatics analysis. Gene set enrichment analysis (GSEA) was performed to investigate the potential biological characteristic between different phenotypes. Pearson correlation analysis between the hub genes and the xCell score of immune cell types was performed. RESULTS: Signal transducer and activator of transcription 3 (STAT3) and Spi-1 proto-oncogene (SPI1) was identified as the hub genes in the datasets GSE73754. And the t-test showed that the expression level of STAT3 and SPI1 in the GSE73754 was significantly higher in AS and human leukocyte antigen (HLA)-B27(+) groups. Flow cytometric analysis showed that natural killer T cells (NKT) cells were upregulated, while Th1 cells were down-regulated in AS, which was consistent with the results obtained from bioinformatics analysis. STAT3 and SPI1 was correlated with the NKT cells and Th1 cells. CONCLUSION: STAT3 and SPI1 may be a key cytokine receptor in disease progression in AS.

A Retrospective Study of Factors Associated with Restoration of Thoracic Kyphosis in 43 Patients with Adolescent Idiopathic Scoliosis with Lenke Type 1 Curvature.

BACKGROUND This retrospective study aimed to identify the factors associated with successful surgical correction of thoracic kyphosis (TK) in 43 patients with adolescent idiopathic scoliosis (AIS) with Lenke type 1 curvature, in which the major curve with the largest Cobb angle was mainly in the thoracic region. MATERIAL AND METHODS We collected data from patients with Lenke 1 AIS. The following parameters were measured: Cobb angle, side-bending Cobb angle, cervical lordosis (CL), TK, lumbar lordosis (LL), pelvic incidence (PI), sacral slope (SS), pelvic tilt (PT), the sagittal vertical axis (SVA), the center of a C7 plumb line to the center sacral vertical line (C7-CSVL), correction rate, Ponte osteotomy, flexibility, and screw density. Univariate analysis and multivariate logistic regression analyses were performed. RESULTS Among the 43 cases analyzed, the mean postoperative Cobb angle at the last follow-up, C7-CSVL, SVA, CL, TK, LL, PI, SS, and PT were respectively 21.33±9.47°, 10.41±8.45 mm, 19.68±14.33 mm, 16.19±7.45°, 23.12±7.45°, 50.33±11.37°, 49.70±9.83°, 39.42±8.11°, and 10.16±6.63°. Univariate analysis suggested that preoperative TK, preoperative LL, and Ponte osteotomy were statistically significant (P<0.05), and multivariate analysis suggested that preoperative LL and Ponte osteotomy were statistically significant (P<0.05). CONCLUSIONS The results of this study demonstrated that preoperative TK, preoperative LL, and Ponte osteotomy were related factors for maintaining normal TK. Multivariate analysis suggested that preoperative LL and the use of Ponte osteotomy with full-thickness segmental resection of the spinal posterior column resulted in the successful surgical correction of TK in patients with AIS with Lenke type 1 curvature.

Is there a correlation between upper lumbar disc herniation and multifidus muscle degeneration? A retrospective study of MRI morphology.

BACKGROUND: The purpose of the study is to investigate the correlation between upper lumbar disc herniation (ULDH) and multifidus muscle degeneration via the comparison of width, the cross-sectional area and degree of fatty infiltration of the lumbar multifidus muscle. METHODS: Using the axial T2-weighted images of magnetic resonance imaging as an assessment tool, we retrospectively investigated 132 patients with ULDH and 132 healthy individuals. The total muscle cross-sectional area (TMCSA) and the pure muscle cross-sectional area (PMCSA) of the multifidus muscle at the L1/2, L2/3, and L3/4 intervertebral disc levels were measured respectively, and in the meantime, the average multifidus muscle width (AMMW) and degree of fatty infiltration of bilateral multifidus muscle were evaluated. The resulting data were analyzed to determine the presence/absence of statistical significance between the study and control groups. Multivariate logistical regression analyses were used to evaluate the correlation between ULDH and multifidus degeneration. RESULTS: The results of the analysis of the two groups showed that there were statistically significant differences (p < 0.05) between TMCSA, PMCSA, AMMW and degree of fatty infiltration. The multivariate logistic regression analysis indicated that the TMCSA, PMCSA, AMMW and the degree of fatty infiltration of multifidus muscle were correlated with ULDH, and the differences were statistically significant (P < 0.05). CONCLUSIONS: A correlation could exist between multifidus muscles degeneration and ULDH, that may be a process of mutual influence and interaction. Lumbar muscle strengthening training could prevent and improve muscle atrophy and degeneration.

A Mechanism Underlying Sex-Associated Differences in Ankylosing Spondylitis: Troponin C2, Fast Skeletal Type (TNNC2) and Calcium Signaling Pathway.

BACKGROUND Ankylosing spondylitis (AS) is a disease that causes pathological changes in the spine and sacroiliac joints. Numerous studies have shown that the characteristics of AS differ between males and females. The purpose of this study was to discover the key molecules that contribute to sex-associated differences in AS, which may provide a new molecular target for personalized treatment. MATERIAL AND METHODS The gene expression profile of GSE39340 was downloaded from the Gene Expression Comprehensive database, and 2 groups (AS vs. No-AS groups and male AS vs. female AS groups) of differentially expressed genes (EDGs) were obtained by GEO2R. The DAVID database was used for DEGs function and enrichment analysis. Based on data in the STRING online database, a protein-protein interaction (PPI) network was constructed in Cytoscape. Hub genes were selected from CytoHubba. With the intersection of the top 30 hub genes of 2 sets of EDGs, genes coexisting with the KEGG-related pathway were found. RESULTS We screened 560 genes between the AS and No-AS groups, and screened 710 genes that were differentially expressed between the male and female AS groups. GO analysis showed that DEGs were mainly co-enriched in molecular functions, including structural constituent of muscle. The KEGG pathway mainly included the structural constituent of muscle. Seven hub genes were obtained. Troponin C2 and fast skeletal type (TNNC2) were the key genes participating in the calcium signaling pathway. CONCLUSIONS This study contributes to understanding the molecular biological mechanism underlying sex-associated differences in AS. TNNC2 and calcium signaling pathway may be new targets for the individualized treatment of AS.

Risk Factors for Recurrent L5-S1 Disc Herniation After Percutaneous Endoscopic Transforaminal Discectomy: A Retrospective Study.

BACKGROUND This retrospective study aimed to investigate the risk factors associated with the recurrence of L5-S1 disc herniation after percutaneous endoscopic transforaminal discectomy (PETD). MATERIAL AND METHODS There were 484 patients L5-S1 disc herniation who underwent PETD who were divided into the recurrence group (n=46) and the non-recurrence group (n=438). Transforaminal endoscopic approaches included modifications of the Yeung endoscopy spine system (YESS) (the intraforaminal intradiscal approach) and the transforaminal endoscopic spine system (TESSYS) (intraforaminal extradiscal approach). Demographic and clinical characteristics and imaging data were analyzed. The two study groups were compared to determine the factors associated with the recurrence of L5-S1 disc herniation. The patients underwent postoperative follow-up for between one and four years. RESULTS At follow-up, 9.504% of patients (46/484) with the recurrence of L5-S1 disc herniation following PETD when compared with the non-recurrence group showed no significant difference for time to return to work, gender, history of diabetes mellitus, trauma, duration of symptoms, smoking and alcohol history, hypertension, location of disc herniation, transverse process length, intervertebral space height, and pelvic incidence angle (P>0.05). However, age, body mass index (BMI), the degree of disc degeneration, sagittal range of motion, lumbar lordosis angle, and sacral slope were significantly associated with the recurrence of L5-S1 disc herniation following PETD (P<0.05). Logistic regression analysis supported these main associations. CONCLUSIONS The recurrence of L5-S1 disc herniation following PETD was significantly associated with increased age and BMI, more severe disc degeneration, increased sagittal range of motion, increased lumbar lordosis, and sacral slope.

A recombinant trans-membrane protein hMnSOD-R9 inhibits the proliferation of cervical cancer cells in vitro.

Human manganese superoxide dismutase (hMnSOD) is a new type of cancer suppressor. Nonamer of arginine (R9) is an efficient protein transduction domain (PTD). The aim of the study was to improve the transduction efficiency of hMnSOD and investigate its activity in vitro. In this study, we designed, constructed, expressed, and purified a novel fusion protein containing the hMnSOD domain and R9 PTD (hMnSOD­R9). The DNA damaged by Fenton's reagent was found to be significantly reduced when treated with hMnSOD­R9. hMnSOD­R9 fusion protein was successfully delivered into HeLa cells. The MTT assay showed that proliferation of various cancer cell lines were inhibited by hMnSOD­R9 in a dose-dependent manner. In addition, the cell cycle of HeLa cells was arrested at the sub-G0 phase by hMnSOD­R9. hMnSOD­R9 induced apoptosis of HeLa cells in a dose-dependent manner. With hMnSOD­R9 treatment, Bax, JNK, TBK1 gene expression was increased and STAT3 gene expression was gradually down-regulated in HeLa cells. We also found that apoptosis was induced by hMnSOD­R9 in HeLa cells via up-regulation of cleaved caspase-3 and down-regulation phospho-STAT3 pathway. These results indicated that hMnSOD­R9 may provide benefits to cervical cancer treatment.

Predictors of osteoporotic fracture in postmenopausal women: a meta-analysis.

Osteoporosis affects more than 200 million women worldwide, with postmenopausal women being particularly susceptible to this condition and its severe sequelae disproportionately, such as osteoporotic fractures. To date, the current focus has been more on symptomatic treatment, rather than preventive measures. To address this, we performed a meta-analysis aiming to identify potential predictors of osteoporotic fractures in postmenopausal women, with the ultimate goal of identifying high-risk patients and exploring potential therapeutic approaches. We searched Embase, MEDLINE and Cochrane with search terms (postmenopausal AND fracture) AND ("risk factor" OR "predictive factor") in May 2022 for cohort and case-control studies on the predictors of osteoporotic fracture in postmenopausal women. Ten studies with 1,287,021 postmenopausal women were found eligible for analyses, in which the sample size ranged from 311 to 1,272,115. The surveyed date spanned from 1993 to 2021. Our results suggested that age, BMI, senior high school and above, parity ≥ 3, history of hypertension, history of diabetes mellitus, history of alcohol intake, age at menarche ≥ 15, age at menopause < 40, age at menopause > 50, estrogen use and vitamin D supplements were significantly associated with osteoporotic fracture in postmenopausal women. Our findings facilitate the early prediction of osteoporotic fracture in postmenopausal women and may contribute to potential therapeutic approaches. By focusing on preventive strategies and identifying high-risk individuals, we can work toward reducing the burden of osteoporosis-related fractures in this vulnerable population.

Using Machine Learning to Predict Surgical Site Infection After Lumbar Spine Surgery.

Objective: The objective of this study was to utilize machine learning techniques to analyze perioperative factors and identify blood glucose levels that can predict the occurrence of surgical site infection following posterior lumbar spinal surgery. Methods: A total of 4019 patients receiving lumbar internal fixation surgery from an institute were enrolled between June 2012 and February 2021. First, the filtered data were randomized into the test and verification groups. Second, in the test group, specific variables were screened using logistic regression analysis, Lasso regression analysis, support vector machine, and random forest. Specific variables obtained using the four methods were intersected, and a dynamic model was constructed. ROC and calibration curves were constructed to assess model performance. Finally, internal model performance was verified in the verification group using ROC and calibration curves. Results: The data from 4019 patients were collected. In total, 1327 eligible cases were selected. By combining logistic regression analysis with three machine learning algorithms, this study identified four predictors associated with SSI, namely Modic changes, sebum thickness, hemoglobin, and glucose. Using this information, a prediction model was developed and visually represented. Then, we constructed ROC and calibration curves using the test group; the area under the ROC curve was 0.988. Further, calibration curve analysis revealed favorable consistency of nomogram-predicted values compared with real measurements. The C-index of our model was 0.986 (95% CI 0.981-0.994). Finally, we used the validation group to validate the model internally; the AUC was 0.987. Calibration curve analysis revealed favorable consistency of nomogram-predicted values compared with real measurements. The C-index was 0.982 (95% CI 0.974-0.999). Conclusion: Logistic regression analysis and machine learning were employed to select four risk factors: Modic changes, sebum thickness, hemoglobin, and glucose. Then, a dynamic prediction model was constructed to help clinicians simplify the monitoring and prevention of SSI.

Comprehensive AI-assisted tool for ankylosing spondylitis based on multicenter research outperforms human experts.

Introduction: The diagnosis and treatment of ankylosing spondylitis (AS) is a difficult task, especially in less developed countries without access to experts. To address this issue, a comprehensive artificial intelligence (AI) tool was created to help diagnose and predict the course of AS. Methods: In this retrospective study, a dataset of 5389 pelvic radiographs (PXRs) from patients treated at a single medical center between March 2014 and April 2022 was used to create an ensemble deep learning (DL) model for diagnosing AS. The model was then tested on an additional 583 images from three other medical centers, and its performance was evaluated using the area under the receiver operating characteristic curve analysis, accuracy, precision, recall, and F1 scores. Furthermore, clinical prediction models for identifying high-risk patients and triaging patients were developed and validated using clinical data from 356 patients. Results: The ensemble DL model demonstrated impressive performance in a multicenter external test set, with precision, recall, and area under the receiver operating characteristic curve values of 0.90, 0.89, and 0.96, respectively. This performance surpassed that of human experts, and the model also significantly improved the experts' diagnostic accuracy. Furthermore, the model's diagnosis results based on smartphone-captured images were comparable to those of human experts. Additionally, a clinical prediction model was established that accurately categorizes patients with AS into high-and low-risk groups with distinct clinical trajectories. This provides a strong foundation for individualized care. Discussion: In this study, an exceptionally comprehensive AI tool was developed for the diagnosis and management of AS in complex clinical scenarios, especially in underdeveloped or rural areas that lack access to experts. This tool is highly beneficial in providing an efficient and effective system of diagnosis and management.

Transfer of microRNA-22-3p by M2 macrophage-derived extracellular vesicles facilitates the development of ankylosing spondylitis through the PER2-mediated Wnt/ß-catenin axis.

Pathological osteogenesis and inflammation possess critical significance in ankylosing spondylitis (AS). The current study aimed to elucidate the mechanisms regarding extracellular vesicle (EV)-packaged microRNA-22-3p (miR-22-3p) from M2 macrophages in the osteogenic differentiation of mesenchymal stem cells (MSCs) in AS. EVs were initially isolated from M2 macrophages, which had been treated with either restored or depleted miR-22-3p. AS-BMSCs were subsequently treated with M2 macrophage-derived EVs to detect osteogenic differentiation in BMSCs using gain- or loss-of-function experiments. The binding affinity among miR-22-3p, period circadian protein 2 (PER2), and Wnt7b was identified. Finally, AS mouse models were established for testing the effects of M2-EV-miR-22-3p on the bone metastatic microenvironment in vivo. miR-22-3p from M2 macrophages could be transferred into BMSCs via EVs, which promoted the osteogenic differentiation of AS-BMSCs. miR-22-3p inhibited PER2, while PER2 blocked the Wnt/ß-catenin signaling pathway via Wnt7b inhibition. M2-EV-shuttled miR-22-3p facilitated alkaline phosphatase activity and extracellular matrix mineralization via PER2-regulated Wnt/ß-catenin axis, stimulating the BMSC osteogenic differentiation. Taken together, these findings demonstrate that miR-22-3p in M2 macrophage-released EVs downregulates PER2 to facilitate the osteogenesis of MSCs via Wnt/ß-catenin axis.

Epithelial-mesenchymal transition interaction with CD8+ T cell, dendritic cell and immune checkpoints in the development of melanoma.

BACKGROUND: Melanoma is fatal cancer originating from melanocytes, whose high metastatic potential leads to an extremely poor prognosis. OBJECTIVE: This study aimed to reveal the relationship among EMT, TIICs, and immune checkpoints in melanoma. METHODS: Gene expression data and clinical data of melanoma were downloaded from TCGA, UCSC Xena and GEO databases. EMT-related DEGs were detected for risk score calculation. "ESTIMATE" and "xCell" were used for estimating TIICs and obtaining 64 immune cell subtypes, respectively. Moreover, we evaluated the relationship between the risk score and immune cell subtypes and immune checkpoints. RESULTS: Seven EMT-related genes were selected to establish a risk scoring system because of their integrated prognostic relevance. The results of GSEA revealed that most of the gene sets focused on immune-related pathways in the low-risk score group. The risk score was significantly correlated with the xCell score of some TIICs, which significantly affected the prognosis of melanoma. Patients with a low-risk score may be associated with a better response to ICI therapy. CONCLUSION: The individualized risk score could effectively conduct risk stratification, overall survival prediction, ICI therapy prediction, and TME judgment for patients with melanoma, which would be conducive to patients' precise treatment.

Ferroptosis-related gene SOCS1, a marker for tuberculosis diagnosis and treatment, involves in macrophage polarization and facilitates bone destruction in tuberculosis.

This study was aimed to reveal the role of ferroptosis in tuberculosis infection. To elucidate the ferroptosis-related DEGs, GEO datasets associated with tuberculosis infection were downloaded. The two external validation GEO datasets were exploited for subsequent verification of the ferroptosis-related DEGs. We further evaluated the correlation among the ferroptosis-related DEGs, therapeutic effects, and drug resistance. Finally, we tried to reveal the engagement of the ferroptosis-related DEGs in bone destruction during TB infection. The present study identified SOCS1 as the only ferroptosis-related DEGs. Compared to the non-TB patients, up-regulation of SOCS1 was evident in the TB patients. After receiving standard anti-TB treatment, significant down-regulation of SOCS1 confirmed its acceptance as the marker for therapeutic efficacy. The involvement of SOCS1 has also been suggested in the regulation of the micro immune environment in TB. Furthermore, SOCS1 might play an important role in causing bone destruction during TB infection. FRGs-SOCS1 may be the key gene involved in the pathogenesis and progression of TB infection.

Immune cell infiltration-related clinical diagnostic model for Ankylosing Spondylitis.

Background: The pathogenesis and diagnosis of Ankylosing Spondylitis (AS) has remained uncertain due to several reasons, including the lack of studies on the local and systemic immune response in AS. To construct a clinical diagnostic model, this study identified the micro RNA-messenger RNA (miRNA-mRNA) interaction network and immune cell infiltration-related hub genes associated with AS. Materials and Methods: Total RNA was extracted and purified from the interspinous ligament tissue samples of three patients with AS and three patients without AS; miRNA and mRNA microarrays were constructed using the extracted RNA. Bioinformatic tools were used to construct an miRNA-mRNA network, identify hub genes, and analyze immune infiltration associated with AS. Next, we collected the blood samples and clinical characteristics of 359 patients (197 with AS and 162 without AS). On the basis of the clinical characteristics and results of the routine blood tests, we selected immune-related cells whose numbers were significantly different in patients with AS and patients without AS. Univariate and multivariate logistic regression analysis was performed to construct a nomogram. Immunohistochemistry staining analysis was utilized to verify the differentially expression of LYN in AS and controls. Results: A total of 225 differentially expressed miRNAs (DE miRNAs) and 406 differentially expressed mRNAs (DE mRNAs) were identified from the microarray. We selected 15 DE miRNAs and 38 DE mRNAs to construct a miRNA-mRNA network. The expression of LYN, an immune-related gene, correlated with the counts of monocytes, neutrophils, and dendritic cells. Based on the independent predictive factors of sex, age, and counts of monocytes, neutrophils, and white blood cells, a nomogram was established. Receiver operating characteristic (ROC) analysis was performed to evaluate the nomogram, with a C-index of 0.835 and AUC of 0.855. Conclusion: LYN, an immune-related hub gene, correlated with immune cell infiltration in patients with AS. In addition, the counts of monocytes and neutrophils were the independent diagnostic factors for AS. If verified in future studies, a diagnostic model based on these findings may be used to predict AS effectively.

STAT1 and CXCL10 involve in M1 macrophage polarization that may affect osteolysis and bone remodeling in extrapulmonary tuberculosis.

OBJECTIVE: This study was aimed to reveal the molecular mechanism of bone destruction due to macrophage polarization leading to during extrapulmonary tuberculosis (EPTB) infection. METHODS: The dataset GSE83456 was downloaded from the GEO database, and the xCell tool was used to obtain the 64 types of immune cells. The flow cytometry was performed to identified the differences between M1 and M2 macrophages between EPTB and the healthy controls (HCs). The enrichment analyses were performed on the differentially expressed genes (DEGs) and their functionally related modules. The hub genes were screened out, and their relationships with EPTB and the immune cell subtypes were further analyzed. RESULTS: The flow cytometric analysis validated this hypothesis of M1-macrophage polarization correlated with the pathogenesis of EPTB. Of the obtained 103 DEGs, 97 genes were upregulated, and 6 genes were downregulated. The GO and KEGG pathway analyses showed that the DEGs were particularly involved in the immune-related processes. The hub genes (STAT1 and CXCL10) might be involved in M1-macrophage polarization and correlated with the pathogenesis of EPTB. STAT1 and CXCL10 could also behave as biomarkers for EPTB. CONCLUSION: STAT1 and CXCL10 were involved in the M1-macrophage polarization and correlated with the pathogenesis of EPTB. Besides, both of them could also behave as biomarkers for EPTB diagnosis and provide the required clues for targeted therapy in the future.

Mechanism of Hip Arthropathy in Ankylosing Spondylitis: Abnormal Myeloperoxidase and Phagosome.

Background: The pathogenesis of Ankylosing spondylitis (AS) has not been elucidated, especially involving hip joint disease. The purpose of this study was to analyze the proteome of diseased hip in AS and to identify key protein biomarkers. Material and Methods: We used label-free quantification combined with liquid chromatography mass spectrometry (LC-MS/MS) to screen for differentially expressed proteins in hip ligament samples between AS and No-AS groups. Key protein was screened by Bioinformatics methods. and verified by in vitro experiments. Results: There were 3,755 identified proteins, of which 92.916% were quantified. A total of 193 DEPs (49 upregulated proteins and 144 downregulated proteins) were identified according to P < 0.01 and Log|FC| > 1. DEPs were mainly involved in cell compartment, including the vacuolar lumen, azurophil granule, primary lysosome, etc. The main KEGG pathway included Phagosome, Glycerophospholipid metabolism, Lysine degradation, Pentose phosphate pathway. Myeloperoxidase (MPO) was identified as a key protein involved in Phagosome pathway. The experiment of siRNA interfering with cells further confirmed that the upregulated MPO may promote the inflammatory response of fibroblasts. Conclusions: The overexpression of MPO may contribute to the autoimmune inflammatory response of AS-affected hip joint through the phagosome pathway.

CCT6A, a novel prognostic biomarker for Ewing sarcoma.

BACKGROUND: Ewing sarcoma (ES), the second most prevalent bone malignant tumor has no widely known prognostic biomarker. Earlier studies have suggested that chaperonin containing TCP1 complex 6A (CCT6A), which encodes a molecular protein chaperone, is involved in the pathogenesis of many cancers. However, there are no known reports providing clear evidence of its role in ES pathogenesis. METHODS: We performed a bioinformatic analysis of 32 ES specimens from the GSE17618 dataset concentrating on the differences in gene expression, OS, event-free survival (EFS) in the different subgroups. Immunohistochemical studies were also performed to identify the expression levels of selected genes in ES and immediate paracancerous tissues. RESULTS: After 3 screenings, CCT6A was identified to be highly correlated with ES prognosis. Our survival analysis revealed a low overall survival (OS) for high CCT6A expression (P-value = .024). Our Cox regression analysis identified CCT6A expression, lEFS, and age were strongly associated with prognosis of ES. Our multivariate Cox regression analysis shows that CCT6A (P-value = .015), age (P-value = .026), and EFS (P-value = .002) were independent poor prognostic biomarkers. Our immunohistochemical analysis showed that the expression levels of CCT6A were significantly higher in ES tissues compared to the paracancerous tissues. CONCLUSION: From the results of our study, we identified the expression levels of CCT6A to be strongly associated with prognosis of ES. Thus, the expression levels of the CCT6A gene could serve as a biomarker for the prediction of ES prognosis.

Glycolysis- and immune-related novel prognostic biomarkers of Ewing's sarcoma: glucuronic acid epimerase and triosephosphate isomerase 1.

INTRODUCTION: Owing to the poor prognosis of Ewing's sarcoma, reliable prognostic biomarkers are highly warranted for clinical diagnosis of the disease. MATERIALS AND METHODS: A combination of the weighted correlation network analysis and differentially expression analysis was used for initial screening; glycolysis-related genes were extracted and subjected to univariate Cox, LASSO regression, and multivariate Cox analyses to construct prognostic models. The immune cell composition of each sample was analysed using CIBERSORT software. Immunohistochemical analysis was performed for assessing the differential expression of modelled genes in Ewing's sarcoma and paraneoplastic tissues. RESULTS: A logistic regression model constructed for the prognosis of Ewing's sarcoma exhibited that the patient survival rate in the high-risk group is much lower than in the low-risk group. CIBERSORT analysis exhibited a strong correlation of Ewing's sarcoma with naïve B cells, CD8+ T cells, activated NK cells, and M0 macrophages (P < 0.05). Immunohistochemical analysis confirmed the study findings. CONCLUSIONS: GLCE and TPI1 can be used as prognostic biomarkers to predict the prognosis of Ewing's sarcoma, and a close association of Ewing's sarcoma with naïve B cells, CD8+ T cells, activated NK cells, and M0 macrophages provides a novel approach to the disease immunotherapy.

TYROBP, TLR4 and ITGAM regulated macrophages polarization and immune checkpoints expression in osteosarcoma.

We established a relationship among the immune-related genes, tumor-infiltrating immune cells (TIICs), and immune checkpoints in patients with osteosarcoma. The gene expression data for osteosarcoma were downloaded from UCSC Xena and GEO database. Immune-related differentially expressed genes (DEGs) were detected to calculate the risk score. "Estimate" was used for immune infiltrating estimation and "xCell" was used to obtain 64 immune cell subtypes. Furthermore, the relationship among the risk scores, immune cell subtypes, and immune checkpoints was evaluated. The three immune-related genes (TYROBP, TLR4, and ITGAM) were selected to establish a risk scoring system based on their integrated prognostic relevance. The GSEA results for the Hallmark and KEGG pathways revealed that the low-risk score group exhibited the most gene sets that were related to immune-related pathways. The risk score significantly correlated with the xCell score of macrophages, M1 macrophages, and M2 macrophages, which significantly affected the prognosis of osteosarcoma. Thus, patients with low-risk scores showed better results with the immune checkpoints inhibitor therapy. A three immune-related, gene-based risk model can regulate macrophage activation and predict the treatment outcomes the survival rate in osteosarcoma.

Construction of autophagy prognostic signature and analysis of prospective molecular mechanisms in skin cutaneous melanoma patients.

BACKGROUND: Autophagy is closely related to skin cutaneous melanoma (SKCM), but the mechanism involved is unclear. Therefore, exploration of the role of autophagy-related genes (ARGs) in SKCM is necessary. MATERIALS AND METHODS: Differential expression autophagy-related genes (DEARGs) were first analysed. Univariate and multivariate Cox regression analyses were used to evaluate the expression of DEARGs and prognosis of SKCM. Further, the expression levels of prognosis-related DEARGs were verified by immunohistochemical (IHC) staining. Finally, gene set enrichment analysis (GSEA) was used to explore the underlying molecular mechanisms of SKCM. RESULTS: Five ARGs (APOL1, BIRC5, EGFR, TP63, and SPNS1) were positively correlated with the prognosis of SKCM. IHC verified the results of the differential expression of these 5 ARGs in the bioinformatics analysis. According to the receiver operating characteristic curve, the signature had a good performance at predicting overall survival in SKCM. The signature could classify SKCM patients into high-risk or low-risk groups according to distinct overall survival. The nomogram confirmed that the risk score has a particularly large impact on the prognosis of SKCM. Calibration plot displayed excellent agreement between nomogram predictions and actual observations. Principal component analysis indicated that patients in the high-risk group could be distinguished from those in low-risk group. Results of GSEA indicated that the low-risk group is enriched with aggressiveness-related pathways such as phosphatidylinositol-3-kinase/protein kinase B and mitogen-activated protein kinase signalling pathways. CONCLUSION: Our study identified a 5-gene signature. It revealed the mechanisms of autophagy that lead to the progression of SKCM and established a prognostic nomogram that can predict overall survival of patients with SKCM. The findings of this study provide novel insights into the relationship between ARGs and prognosis of SKCM.