This study aimed to explore the pharmacological mechanism of Yourenji Capsules(YRJ) in improving osteoporosis by combining network pharmacology and proteomics technologies. The SD rats were randomly divided into a blank control group and a 700 mg·kg~(-1) YRJ group. The rats were subjected to gavage administration with the corresponding drugs, and the blank serum, drug-containing serum, and YRJ samples were compared using ultra performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS) to analyze the main components absorbed into blood. Network pharmacology analysis was conducted based on the YRJ components absorbed into blood to obtain related targets of the components and target genes involved in osteoporosis, and Venn diagrams were used to identify the intersection of drug action targets and disease targets. The STRING database was used for protein-protein interaction(PPI) network analysis of potential target proteins to construct a PPI network. Gene Ontology(GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment were performed using Enrichr to investigate the potential mechanism of action of YRJ. Ovariectomy(OVX) was performed to establish a rat model of osteoporosis, and the rats were divided into a sham group, a model group, and a 700 mg·kg~(-1) YRJ group. The rats were given the corresponding drugs by gavage. The femurs of the rats were subjected to label-free proteomics analysis to detect differentially expressed proteins, and GO functional enrichment and KEGG pathway enrichment analyses were performed on the differentially expressed proteins. With the help of network pharmacology and proteomics results, the mechanism by which YRJ improves osteoporosis was predicted. The analysis of the YRJ components absorbed into blood revealed 23 bioactive components of YRJ, and network pharmacology results indicated that key targets involved include tumor necrosis factor(TNF), tumor protein p53(TP53), protein kinase(AKT1), and matrix metalloproteinase 9(MMP9). These targets are mainly involved in osteoclast differentiation, estrogen signaling pathways, and nuclear factor-kappa B(NF-κB) signaling pathways. Additionally, the proteomics analysis highlighted important pathways such as peroxisome proliferator-activated receptor(PPAR) signaling pathways, mitogen-activated protein kinase(MAPK) signaling pathways, and β-alanine metabolism. The combined approaches of network pharmacology and proteomics have revealed that the mechanism by which YRJ improves osteoporosis may be closely related to the regulation of inflammation, osteoblast, and osteoclast metabolic pathways. The main pathways involved include the NF-κB signaling pathways, MAPK signaling pathways, and PPAR signaling pathways, among others.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Osteoporosis/metabolism* ; Proteomics ; Rats ; Rats, Sprague-Dawley ; Network Pharmacology ; Female ; Protein Interaction Maps/drug effects* ; Capsules ; Humans ; Signal Transduction/drug effects*

OBJECTIVE: To analyze the effectiveness of single three-dimensional (3D)-printed microporous titanium prostheses and flap combined prostheses implantation in the treatment of large segmental infectious bone defects in limbs. METHODS: A retrospective analysis was conducted on the clinical data of 76 patients with large segmental infectious bone defects in limbs who were treated between January 2019 and February 2024 and met the selection criteria. Among them, 51 were male and 25 were female, with an age of (47.7±9.4) years. Of the 76 patients, 51 had no soft tissue defects (single prostheses group), while 25 had associated soft tissue defects (flap combined group). The single prostheses group included 28 cases of tibial bone defects, 11 cases of femoral defects, 5 cases of humeral defects, 4 cases of radial bone defects, and 3 cases of metacarpal, or carpal bone defects, with bone defect length ranging from 3.5 to 28.0 cm. The flap combined group included 3 cases of extensive dorsum of foot soft tissue defects combined with large segmental metatarsal bone defects, 19 cases of lower leg soft tissue defects combined with large segmental tibial bone defects, and 3 cases of hand and forearm soft tissue defects combined with metacarpal, carpal, or radial bone defects, with bone defect length ranging from 3.8 to 32.0 cm and soft tissue defect areas ranging from 8 cm×5 cm to 33 cm×10 cm. In the first stage, vancomycin-loaded bone cement was used to control infection, and flap repair was performed in the flap combined group. In the second stage, 3D-printed microporous titanium prostheses were implanted. Postoperative assessments were performed to evaluate infection control and bone integration, and pain release was evaluated using the visual analogue scale (VAS) score. RESULTS: All patients were followed up postoperatively, with an average follow-up time of (35.2±13.4) months. In the 61 lower limb injury patients, the time of standing, walk with crutches, and fully bear weight were (2.2±0.6), (3.9±1.1), and (5.4±1.1) months, respectively. The VAS score at 1 year postoperatively was significantly lower than preoperative one ( t=-10.678, P<0.001). At 1 year postoperatively, 69 patients (90.8%) showed no complication such as infection, fracture, prosthesis displacement, or breakage, and X-ray films indicated good integration at the prosthesis-bone interface. According to the Paley scoring system for the healing of infectious bone defects, the results were excellent in 37 cases, good in 29 cases, fair in 3 cases, and poor in 7 cases. In the single prostheses group, during the follow-up, there was 1 case each of femoral prostheses fracture, femoral infection, and tibial infection, with a treatment success rate of 94.1% (48/51). In lower limb injury patients, the time of fully bear weight was (5.0±1.0) months. In the flap combined group, during the follow-up, 1 case of tibial fixation prostheses screw fracture occurred, along with 2 cases of recurrent foot infection in diabetic patients and 1 case of tibial infection. The treatment success rate was 84.0% (21/25). The time of fully bear weight in lower limb injury patients was (5.8±1.2) months. The overall infection eradication rate for all patients was 93.4% (71/76). CONCLUSION The use of 3D-printed microporous titanium prostheses, either alone or in combination with flaps, for the treatment of large segmental infectious bone defects in the limbs results in good effectiveness with a low incidence of complications. It is a feasible strategy for the reconstruction of infectious bone defects.
Humans ; Male ; Female ; Middle Aged ; Printing, Three-Dimensional ; Titanium ; Retrospective Studies ; Surgical Flaps ; Adult ; Prosthesis Implantation/methods* ; Plastic Surgery Procedures/methods* ; Treatment Outcome ; Prostheses and Implants ; Bone Diseases, Infectious/surgery* ; Extremities/surgery* ; Prosthesis Design

Accurate timing of myelination is crucial for the proper functioning of the central nervous system. Here, we identified a de novo heterozygous mutation in TMEM63A (c.1894G>A; p. Ala632Thr) in a 7-year-old boy exhibiting hypomyelination. A Ca²⁺ influx assay suggested that this is a loss-of-function mutation. To explore how TMEM63A deficiency causes hypomyelination, we generated Tmem63a knockout mice. Genetic deletion of TMEM63A resulted in hypomyelination at postnatal day 14 (P14) arising from impaired differentiation of oligodendrocyte precursor cells (OPCs). Notably, the myelin dysplasia was transient, returning to normal levels by P28. Primary cultures of Tmem63a^-/- OPCs presented delayed differentiation. Lentivirus-based expression of TMEM63A but not TMEM63A_A632T rescued the differentiation of Tmem63a^-/- OPCs in vitro and myelination in Tmem63a^-/- mice. These data thus support the conclusion that the mutation in TMEM63A is the pathogenesis of the hypomyelination in the patient. Our study further demonstrated that TMEM63A-mediated Ca²⁺ influx plays critical roles in the early development of myelin and oligodendrocyte differentiation.
Animals ; Cell Differentiation/physiology* ; Oligodendroglia/metabolism* ; Mice, Knockout ; Mice ; Male ; Myelin Sheath/metabolism* ; Humans ; Child ; Cells, Cultured ; Oligodendrocyte Precursor Cells/metabolism*

Objective:To investigate the value of a cross-combination machine learning approach in constructing a PET radiomics score (RadScore) for predicting early treatment response and prognosis in patients with primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL).Methods:This retrospective cohort study was conducted on 108 patients (59 males and 49 females, age (55.6±12.1) years) diagnosed with PGI-DLBCL between November 2016 and December 2021 at Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University ( n=85) and West China Hospital, Sichuan University ( n=23). Patients were divided into a training set ( n=86) and a validation set ( n=22) with the ratio of 8∶2 using stratified random sampling method. Seven machine learning models were employed to generate 49 feature selection-classification candidates, and the optimal candidate was selected to construct the RadScore, with five-fold cross-validation applied to determine the best-performing model. Logistic regression analysis was performed to identify risk factors for early treatment response, and a radiomics nomogram was developed by integrating RadScore with clinical predictors. Survival results between different groups of RadScore was compared by log-rank test. Results:Nineteen predictive features were selected from 111 radiomic features to construct the RadScore. In the training set, lactate dehydrogenase (LDH) (odds ratio ( OR)=3.53, 95% CI: 1.21-10.31, P=0.021), intestinal involvement ( OR=3.04, 95% CI: 1.04-8.88, P=0.042), total lesion glycolysis (TLG; OR=6.73, 95% CI: 2.23-20.29, P<0.001) and RadScore ( OR=15.11, 95% CI: 3.95-57.80, P<0.001) were identified as independent risk factors for predicting early treatment response. The combined model integrating RadScore, LDH, intestinal involvement, and TLG demonstrated good discriminatory ability for early treatment response (AUC=0.860 in the training set; AUC=0.902 in the validation set). Significant differences were observed in progression-free survival (PFS) and overall survival (OS) between different RadScore groups ( χ2 values: 13.92 and 8.56, both P<0.01). Conclusions:The machine learning-based RadScore may effectively predict survival outcomes in patients with PGI-DLBCL. The combined model integrating RadScore, clinical factors, and metabolic indicators can predict early treatment response in PGI-DLBCL patients.

Objective:To explore the role of long noncoding RNA(lncRNA) CCDC18-AS1 in parathyroid carcinoma(PC) diagnosis.Methods:This cross-sectional study included 55 patients with primary hyperparathyroidism treated at Beijing Shijitan Hospital from 2013 to 2024. Of these, 12 patients were diagnosed with PC and 43 with parathyroid adenoma(PA). Tissue samples and clinical data were collected, and lncRNA CCDC18-AS1 expression were measured using real-time quantitative PCR(RT-qPCR).Results:LncRNA CCDC18-AS1 expression was significantly higher in the PC group than that in the PA group( P=0.003). It was identified as an independent risk factor for PC, independent of age, sex, or serum calcium levels. Among patients with hypophosphatemia, no significant differences in lncRNA CCDC18-AS1 expression was observed between the PC and PA groups. However, in patients with normal serum phosphate levels, lncRNA CCDC18-AS1 expression was significantly higher in the PC group( P<0.001) and showed a positive correlation with serum phosphorus concentration( P=0.001). The area under the receiver operating characteristic(ROC) curve(AUC) for lncRNA CCDC18-AS1 in PC diagnosis was 0.758(95% CI 0.620-0.866, P=0.005), comparable to that of lncRNA plasmacytoma variant translocation 1(PVT1). Among patients with normal serum phosphate, the AUC for lncRNA CCDC18-AS1 increased to 0.969(95% CI 0.835-0.999, P<0.001), with 100% sensitivity and 92.31% specificity, suggesting superior diagnostic performance compared to PVT1(0.840, 95% CI 0.653-0.950, P=0.001). Conclusions:LncRNA CCDC18-AS1 may serves as a potential biomarker for PC diagnosis, with greater diagnostic value in patients with normal serum phosphorus levels.

Objective:To investigate the short-term clinical efficacy of implantation with a 3D-printed microporous titanium prosthesis in the treatment of large segmental infectious tibial defects.Methods:A retrospective analysis was conducted of the electronic medical records of the 47 patients with large segmental tibial defects who had been treated with 3D-printed microporous titanium prostheses at Department of Orthopaedics, 920th Hospital of Joint Logistics Support Force from January 2019 to February 2024. The cohort included 36 males and 11 females, with an age of (46.2±11.8) years and a mean bone defect length of 12.3 (8.0, 16.8) cm. In the 19 patients complicated with soft tissue defects, the area of soft tissue defects ranged from 10.0 cm × 6.0 cm to 33.0 cm × 10.0 cm. For the 28 patients without soft tissue defects at the lower leg, the bone defects were filled with vancomycin-loaded calcium sulfate bone cement at the first stage; for the 19 patients complicated with soft tissue defects, the soft tissue defects at the lower limb were repaired using an anterolateral thigh flap with vascular anastomosis at the same time when bone defects were filled with vancomycin-loaded calcium sulfate bone cement at the first stage. After infection control at 2 to 8 months after surgery, individualized 3D-printed microporous titanium prostheses were implanted at the second stage to reconstruct the bone defects. Postoperative observations included the patients' first standing time, crutch walking time, full weight-bearing time, osseointegration of the tibial fracture and the prosthesis, and complications during follow-up.Results:The follow-up period for the 47 patients was (34.7±14.3) months. The first standing time was (2.2±0.6) months, crutch walking time (3.8±1.1) months, and full weight-bearing time (5.3±1.2) for this cohort. The evaluation by the Paley's bone healing score resulted in 25 excellent cases, 18 good cases, 1 medium case, and 3 poor cases, giving an excellent and good rate of 91.5% (43/47). One year after operation, the X-ray films showed that the tibial fractures and prostheses were well integrated in the 43 patients. Two patients developed recurrent tibial infection which was responded to replacement of the vancomycin-loaded calcium sulfate spacer. The fixation screws for tibial prosthesis were broken in one patient, but no recurrence of infection was observed after revision. The overall incidence of complications was 6.4% (3/47).Conclusion:In the treatment of large segmental infectious tibial defects, by facilitating rapid functional recovery and ensuring a low incidence of complications, implantation with a 3D-printed microporous titanium prosthesis demonstrates fine short-term clinical efficacy.

objective:To investigate the factors influencing failure of preoperative optimisation with exclusive enteral nutrition(EEN)in patients with Crohn's disease(CD)and to construct a predictive model.Methods:Clinical data of 161 patients with Crohn's disease who underwent surgical treatment after preoperative EEN optimization at the Inflammatory Bowel Disease Center of General Surgery of the Eastern Theater General Hospital from June 2021 to November 2023 were retrospectively analyzed.Patients were divided into two groups according to the preoperative EEN optimisation effect:optimisation success and optimisation failure.Logistic regression analysis was used to determine the factors influencing optimisation failure,and a column line graphical model was constructed using R4.4.0 software.Results:After at least 4 weeks of EEN treatment,a total of 44 patients(27.33%)failed preoperative optimization.Multifactorial analysis showed that FC>500 μg/g and use of corticosteroids were independent risk factors for failure of preoperative optimization,and an increase in prealbumin after 1 week of treatment was a protective factor for successful preoperative optimization.Based on the results of the multivariate analysis,a column graph was constructed,and the C-index was 0.873(95%CI=0.783～0.964).The calibration curve shows that the probability of failure predicted by the nomogram model prior to optimization is in good agreement with the actual probability.The clinical decision curve confirms that the risk threshold is between 0.03～0.96,and the nomogram model can be used to predict the failure of preoperative EEN optimization over other treatment options.Conclusion:FC>500μg/g and history of corticosteroid use were independent risk factors for failure of preoperative optimization,and an increase in prealbumin after 1 week of treatment was a protective factor for successful preoperative optimization.The nomogram constructed on the basis of these results has a good predictive value and is clinically applicable.

Objective:To evaluate the value of a combined model based on primary lesion 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT radiomics for predicting lymph node metastasis in non-small cell lung cancer (NSCLC) . Methods:A retrospective analysis was conducted on the clinical data of 203 NSCLC patients who underwent pre-treatment PET/CT imaging at Nanjing Drum Tower Hospital from June 2013 to July 2023. Patients were randomly assigned to the training set ( n=142) and the validation set ( n=61) at a ratio of 7∶3. A predictive model was developed in the training set, and its predictive performance and clinical application value were assessed in both the training and validation sets. Traditional PET/CT parameters and PET/CT radiomics features of the primary lesion were obtained by 3D-slicer software. Least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting were performed to extract features. Support vector machine was used to construct a radiomics score (Radscore). Univariate and multivariate logistic regression analysis was used to predict the influencing factors of lymph node metastasis in NSCLC patients and to establish models. Predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves and clinical application value was assessed by calibration curves and decision curve analysis (DCA) . Results:Among 203 NSCLC patients, 116 had lymph node metastasis, with 64 cases in the training set and 52 cases in the validation set. Three complementary classical machine learning methods were used for feature screening, and finally 10 radiomics features were obtained. The optimal threshold for Radscore-PET was 0.43 and the optimal threshold for Radscore-CT was 0.39. Univariate analysis showed that, sex ( OR=0.48, 95% CI: 0.24-0.95, P=0.036), tumor marker levels ( OR=3.81, 95% CI: 1.84-7.91, P<0.001), long diameter of tumor ( OR=2.56, 95% CI: 1.27-5.16, P=0.009), short diameter of tumor ( OR=3.73, 95% CI: 1.75-7.92, P=0.001), vacuolar sign ( OR=0.32, 95% CI: 0.12-0.86, P=0.024), ring-like metabolism ( OR=3.67, 95% CI: 1.33-10.13, P=0.012), maximum standardized uptake value (SUV max) ( OR=6.57, 95% CI: 3.03-14.25, P<0.001), metabolic tumor volume (MTV) ( OR=2.91, 95% CI: 1.43-5.92, P=0.003), total lesion glycolysis (TLG) ( OR=4.23, 95% CI: 2.08-8.59, P<0.001), Radscore-PET ( OR=21.93, 95% CI: 9.04-53.20, P<0.001) and Radscore-CT ( OR=13.72, 95% CI: 6.12-30.76, P<0.001) were all influencing factors for predicting lymph node metastasis in NSCLC patients. Multivariate analysis showed that, tumor marker levels ( OR=2.55, 95% CI: 1.11-5.90, P=0.028), vacuolar sign ( OR=0.26, 95% CI: 0.08-0.83, P=0.023), SUV max ( OR=5.94, 95% CI: 1.99-17.75, P=0.001), Radscore-PET ( OR=25.51, 95% CI: 5.92-110.22, P<0.001), and Radscore-CT ( OR=8.68, 95% CI: 2.73-27.61, P<0.001) were independent influencing factors for predicting lymph node metastasis in patients with NSCLC. Based on the above independent influencing factors, models were constructed: the traditional model (tumor marker levels, vacuolar sign, SUV max), the PET model (SUV max, Radscore-PET), the CT model (vacuolar sign, Radscore-CT), and the combined model (tumor marker levels, vacuolar sign, SUV max, Radscore-PET, Radscore-CT). ROC curve analysis showed that, the area under curve (AUC) of the traditional, PET, CT, and combined models in the training set were 0.75 (95% CI: 0.67-0.82), 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.78-0.90), and 0.94 (95% CI: 0.88-0.97), respectively. The predictive value of the combined model was higher than that of the traditional model ( Z=5.01, P<0.001), the PET model ( Z=1.99, P=0.047), and the CT model ( Z=3.25, P=0.001). In the validation set, the AUCs for the traditional model, PET model, CT model, and combined model were 0.65 (95% CI: 0.52-0.77), 0.86 (95% CI: 0.74-0.93), 0.85 (95% CI: 0.73-0.93), and 0.90 (95% CI: 0.80-0.96), respectively. The predictive value of the combined model was superior to that of the traditional model ( Z=3.23, P=0.001). The sensitivity and specificity of the combined model in the training set were 84.37% and 91.03%, while in the validation set, the sensitivity and specificity were 82.61% and 94.74%, respectively. Calibration curves showed a good agreement between the predicted and actual probabilities in both the training and validation sets. DCA showed that the combined models had good discriminative ability in both the training and validation sets. Conclusions:Tumor marker levels, vacuolar sign, SUV max, Radscore-PET, and Radscore-CT are all independent influencing factors for predicting lymph node metastasis in patients with NSCLC. The combined model based on these factors demonstrates excellent predictive performance and clinical application value for predicting lymph node metastasis in NSCLC.

Objective:To explore the effects and potential mechanisms of chemokine-like factor-like MARVEL transmembrane domain-containing Protein 3 (CMTM3) on the proliferation and migration of glioblastoma (GBM) cells.Methods:Using CMTM3 expression data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, we analyzed the differential expression of CMTM3 in GBM tissues and its impact on the prognosis of GBM patients. Immunohistochemical staining and protein content determination of CMTM3 was performed on GBM and adjacent non-cancerous tissue samples from 11 GBM patients who underwent surgical treatment at the Affiliated Hospital of Guizhou Medical University between November 3, 2022 and March 15, 2023. Additionally, the expression of CMTM3 was validated in GBM cell lines U87, U251, LN229, and the human astrocyte (NHA) cell line using real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot analyses. Stable cell lines with silenced and overexpressed CMTM3 (sh-CMTM3 group and OE-CMTM3 group) were constructed using U251 cells. The effect of CMTM3 expression on cell proliferation was assessed using the Cell Counting Kit-8 (CCK-8) assay. Flow cytometry was employed to examine the impact of CMTM3 expression on the cell cycle. Transwell assays were conducted to evaluate the influence of CMTM3 expression on cell migration. Bioinformatics analysis, Western blotting, NF-κB activation-nuclear translocation assays, and the NF-κB pathway inhibitor pyrrolidine dithiocarbamate ammonium (PDTC) were used to validate the effect of CMTM3 on the NF-κB pathway. Finally, a subcutaneous tumorigenesis assay in nude mice was performed to observe the impact of CMTM3 expression on the in vivo growth of U251 cells. Results:Bioinformatics analysis revealed that CMTM3 is highly expressed in GBM tissues. Patients with a high CMTM3 expression had lower overall survival (OS) and disease-free survival (DFS) rates compared with those with a low CMTM3 expression (with P values of 0.010 and 0.032, respectively). Among the 11 GBM pathological specimens, 10 samples exhibited higher CMTM3 protein expression levels in the cancerous tissue compared with the adjacent non-cancerous tissue. The average CMTM3 protein expression in these samples was 0.44±0.09, significantly higher than that in the adjacent non-cancerous tissues (0.12±0.02, P＜0.001). In one sample, the difference in CMTM3 protein expression between the cancerous and adjacent non-cancerous tissues was not statistically significant ( P=0.750).The RT-qPCR results showed that the mRNA expression level of CMTM3 in NHA cells was 1.0±0.1, whereas in GBM cells U87, LN229, and U251, the levels were 2.1±0.3, 3.4±0.5, and 3.7±0.8, respectively, all significantly higher than that in NHA cells (all P＜0.01). Western blot results demonstrated that the protein expression levels of CMTM3 in GBM cells U87, LN229, and U251 were 1.5±0.2, 1.8±0.2, and 1.9±0.1, respectively, also higher than that in NHA cells (0.7±0.2, all P＜0.01), with the highest level observed in U251 cells. The CCK-8 assay, Flow cytometry, and Transwell migration experiments indicated that cell viability was inhibited in the sh-CMTM3 group, with an increase in the proportion of cells in the G 0/G 1 phase ( P＜0.01) and a decrease in the S phase ( P＜0.01), and the number of migrated cells was 233.6±35.5, lower than that in the sh-NC group ( P＜0.001). Conversely, the OE-CMTM3 group showed enhanced cell viability, a reduction in the proportion of cells in the G 0/G 1 phase ( P＜0.01), and an increase in the S phase ( P＜0.01), and the number of migrated cells was 1212.0±20.8, higher than that in the OE-NC group ( P＜0.001). However, in the OE-CMTM3+PDTC group, cell viability, cell cycle distribution (G 1, S, and G 2 phases), and cell migration numbers showed no significant changes (all P＞0.05). Western blot analysis and NF-κB activation-nuclear translocation assay results indicated that in the sh-CMTM3 group, the p-p65/p65 ratio was 0.51±0.04 and the p-IκBα/IκBα ratio was 0.39±0.03, both lower than those in the sh-NC group (both P＜0.01). The cytoplasmic staining rate was (49.29±1.98)%, higher than that in the sh-NC group ( P＜0.01). In the OE-CMTM3 group, the p-p65/p65 ratio was 2.27±0.10 and the p-IκBα/IκBα ratio was 2.14±0.15, both higher than those in the OE-NC group (both P＜0.01). The cytoplasmic staining rate was (18.96±1.44)%, lower than that in the OE-NC group ( P＜0.01). In the OE-CMTM3+PDTC group, there were no significant differences in the p-p65/p65 ratio, p-IκBα/IκBα ratio, and cytoplasmic staining rate compared with the OE-NC group (all P＞0.05). The subcutaneous tumorigenesis assay in nude mice showed that the tumor volume in the sh-CMTM3 group was (408.9±96.2) mm3, smaller than that in the sh-NC group ( P=0.003). The tumor volume in the OE-CMTM3 group was (1 514.5±251.5) mm3, larger than that in the OE-NC group ( P=0.005). Conclusions:In GBM, CMTM3 is highly expressed and negatively correlated with both OS and DFS of patients. CMTM3 regulates the proliferation and migration abilities of U251 cells through the NF-κB signaling pathway.