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Ubiquitination is the most common post-translational modification and is essential for various cellular regulatory processes. RNF187, which is known as RING domain AP1 coactivator-1, is a member of the RING finger family. RNF187 can promote the proliferation and migration of various tumor cells. However, whether it has a similar role in regulating spermatogonia is not clear. This study explored the role and molecular mechanism of RNF187 in a mouse spermatogonia cell line (GC-1). We found that RNF187 knockdown reduced the proliferation and migration of GC-1 cells and promoted their apoptosis. RNF187 overexpression significantly increased the proliferation and migration of GC-1 cells. In addition, we identified Keratin36/Keratin84 (KRT36/KRT84) as interactors with RNF187 by co-immunoprecipitation and mass spectrometry analyses. RNF187 promoted GC-1 cell growth by degrading KRT36/KRT84 via lysine 48-linked polyubiquitination. Subsequently, we found that KRT36 or KRT84 overexpression significantly attenuated proliferation and migration of RNF187-overexpressing GC-1 cells. In summary, our study explored the involvement of RNF187 in regulating the growth of spermatogonia via lysine 48-linked polyubiquitination-mediated degradation of KRT36/KRT84. This may provide a promising new strategy for treating infertility caused by abnormal spermatogonia development.
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Lisina , Espermatogônias , Ubiquitina-Proteína Ligases , Animais , Masculino , Camundongos , Ubiquitina-Proteína Ligases/genética , UbiquitinaçãoRESUMO
BACKGROUND: The noninvasive assessment of hepatic inflammatory activity (HIA) is crucial for making clinical decisions and monitoring therapeutic efficacy in chronic liver disease (CLD). PURPOSE: To develop MRI-based radiomics models by extracting features from the whole liver and localized regions of the right liver lobe, compare the efficiency of two radiomics models, and further develop a radiomics nomogram for the assessment of HIA in CLD. STUDY TYPE: Retrospective. POPULATION: In all, 137 consecutive patients. FIELD STRENGTH/SEQUENCE: 1.5T/T2 -weighted imaging. ASSESSMENT: All patients (nonsignificant HIA, n = 98; significant HIA, n = 39) were randomly divided into a training (n = 95) and a test cohort (n = 42). Radiomics features were extracted from the regions covering the whole liver (ROI-w) and localized regions of the right liver lobe (ROI-r). Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analyses were used to select features and develop radiomics models. A combined model fusing the valuable radiomics features with clinical-radiological predictors was developed. Finally, a radiomics nomogram derived from the combined model was developed. STATISTICAL TESTS: Synthetic minority oversampling technique algorithm, LASSO, receiver operator characteristic curve, and calibration curve analysis were performed. RESULTS: The area under the curve (AUC), sensitivity, and specificity of the ROI-w radiomics model in assessing HIA were 0.858, 0.800, and 0.733, respectively. The ROI-r model were 0.844, 0.733, and 0.867, respectively. No differences were detected between the two radiomics models (P = 0.8329). The combined model fusing valuable ROI-w radiomics features, albumin, and periportal edema exhibited a promising performance (AUC, 0.911). The calibration curves showed good agreement between the actual observations and nomogram predictions. DATA CONCLUSION: The MRI-based radiomics models had a powerful ability to evaluate HIA and the ROI-w radiomics model was comparable to the ROI-r model. Moreover, the radiomics nomogram could be a favorable method to individually estimate HIA in CLD. J. MAGN. RESON. IMAGING 2020;52:1668-1678.
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Hepatopatias , Imageamento por Ressonância Magnética , Humanos , Hepatopatias/diagnóstico por imagem , Nomogramas , Estudos RetrospectivosRESUMO
BACKGROUND: Preoperative estimation of hepatocellular carcinoma (HCC) recurrence after conventional transcatheter arterial chemoembolization (c-TACE) is crucial for subsequent follow-up and therapy decisions. PURPOSE: To evaluate the associations of radiomics models based on pretreatment contrast-enhanced MRI, a clinical-radiological model and a combined model with the recurrence-free survival (RFS) of patients with HCC after c-TACE, and to develop a radiomics nomogram for individual RFS estimations and risk stratification. STUDY TYPE: Retrospective. POPULATION: In all, 184 consecutive HCC patients. FIELD STRENGTH/SEQUENCE: 1.5T or 3.0T, including T2 WI, T1 WI, and contrast-enhanced T1 WI. ASSESSMENT: All HCC patients were randomly divided into the training (n = 110) and validation datasets (n = 74). Radiomics signatures capturing intratumoral and peritumoral expansion (1, 3, and 5 mm) were constructed, and the radiomics models were set up using least absolute shrinkage and selection operator (LASSO) Cox regression. Clinical-radiological features were identified by univariate and multivariate Cox regression. The clinical-radiological model and the combined model fusing the radiomics signature with the clinical-radiological risk factors were developed by a multivariate Cox proportional hazard model. A radiomics nomogram derived from the combined model was established. STATISTICAL TESTS: LASSO Cox regression, univariate and multivariate Cox regression, Kaplan-Meier analysis were performed. The discrimination performance of each model was quantified by the C-index. RESULTS: Among the different peritumoral expansion models, only the 3-mm peritumoral expansion model (C-index, 0.714) showed a comparable performance (P = 0.4087) to that of the portal venous phase intratumoral model (C-index, 0.727). The combined model showed the best performance and the C-index was 0.802. Kaplan-Meier analysis showed that the cutoff values of the combined model relative to a median value (1.7426) perfectly stratified these patients into high-risk and low-risk subgroups. DATA CONCLUSION: The combined model is more valuable than the clinical-radiological model or radiomics model alone for evaluating the RFS of HCC patients after c-TACE, and the radiomics nomogram can be used to preoperatively and individually estimate RFS. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2020;52:461-473.
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Carcinoma Hepatocelular , Quimioembolização Terapêutica , Neoplasias Hepáticas , Carcinoma Hepatocelular/diagnóstico por imagem , Carcinoma Hepatocelular/terapia , Humanos , Neoplasias Hepáticas/diagnóstico por imagem , Neoplasias Hepáticas/terapia , Imageamento por Ressonância Magnética , Recidiva Local de Neoplasia/diagnóstico por imagem , Estudos RetrospectivosRESUMO
BACKGROUND: F-box-only protein 22 (FBXO22), an important substrate receptor of the SKP1-Cullin-F-box (SCF) ubiquitin ligases, has been reported to be involved in many biological processes, including tumorigenesis, neurological disorders, cellular senescence, and DNA damage. However, the specific role of FBXO22 during spermatogenesis is poorly understood. METHODS: We produced Fbxo22 conditional knockout (cKO) and global knockout (KO) mice and assessed their sperm masurements using a computer-assisted sperm analysis (CASA) system. Additionally, we conducted histologic staining and immunostaining to examine the impact of Fbxo22 loss on spermatogenesis. RESULTS: Our results revealed that there were no notable differences in semen quality, fertility test results, or histologic findings in Fbxo22-KO and Fbxo22-cKO mice compared to the control group. CONCLUSIONS: Our study demonstrated that Fbxo22 is not significant for spermatogenesis or male fertility in mice. These findings will help researchers avoid redundant efforts and serve as a foundational resource for genetic studies on human fertility.
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Background: Risk factors for colorectal cancer (CRC) affect the way patients are subsequently treated and their prognosis. Dual-energy computerized tomography (DECT) is an advanced imaging technique that enables the quantitative evaluation of lesions. This study aimed to evaluate the quality of DECT images based on the Mono+ algorithm in CRC, and based on this, to assess the value of DECT in the diagnosis of CRC risk factors. Methods: This prospective study was performed from 2021 to 2023. A dual-phase DECT protocol was established for consecutive patients with primary CRC. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), overall image quality, lesion delineation, and image noise of the dual-phase DECT images were assessed. Next, the optimal energy-level image was selected to analyze the iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number, electron density, dual-energy index (DEI), and slope of the energy spectrum curve within the tumor for the high- and low-risk CRC groups. A multifactor binary logistic regression analysis was used to construct a differential diagnostic regression model for high- and low-risk CRC, receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to assess the diagnostic value of the model. Results: A total of 74 patients were enrolled in this study, of whom 41 had high-risk factors and 33 had low-risk factors. The SNR and CNR were best at 40 keV virtual monoenergetic imaging (VMI) based on the Mono+ algorithm (VMI+) (SNR 8.79±1.27, P<0.001; CNR 14.89±1.77, P=0.027). The overall image quality and lesion contours were best at 60 keV VMI+ and 40 keV VMI+, respectively (P=0.001). Among all the DECT parameters, the arterial phase (AP)-IC, NIC, DEI, energy spectrum curve, and venous phase-NIC differed significantly between the two groups. The AP-IC was the optimal DECT parameter for predicting high- and low-risk CRC with AUC, sensitivity, specificity, and cut-off values of 0.96, 97.06%, 87.80%, and 2.94, respectively, and the 95% confidence interval (CI) of the AUC was 0.88-0.99. Integrating the clinical factors and DECT parameters, the AUC, sensitivity, specificity, and predictive accuracy of the model were 0.99, 100.00%, 92.68%, and 94.67%, respectively, and the 95% CI of the AUC was 0.93-1.00. Conclusions: The DECT parameters based on 40 keV noise-optimized VMI+ reconstruction images depicted the CRC tumors best, and the clinical DECT model may have significant implications for the preoperative prediction of high-risk factors in CRC patients.
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RING finger 187 (RNF187), a ubiquitin-ligating (E3) enzyme, plays a crucial role in the proliferation of cancer cells. However, it remains unclear whether RNF187 exhibits comparable functionality in the development of germline cells. To investigate the potential involvement of RNF187 in germ cell development, we conducted interference and overexpression assays using GC-2 cells, a mouse spermatocyte-derived cell line. Our findings reveal that the interaction between RNF187 and histone H3 increases the viability, proliferation, and migratory capacity of GC-2 cells. Moreover, we provide evidence demonstrating that RNF187 interacts with H3 and mediates the ubiquitination of H3 at lysine 57 (K57) or lysine 80 (K80), directly or indirectly resulting in increased cellular transcription. This is a study to report the role of RNF187 in maintaining the development of GC-2 cells by mediating histone H3 ubiquitination, thus highlighting the involvement of the K57 and K80 residues of H3 in the epistatic regulation of gene transcription. These discoveries provide a new theoretical foundation for further comprehensive investigations into the function of RNF187 in the reproductive system.
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Proliferação de Células , Histonas , Ubiquitina-Proteína Ligases , Ubiquitinação , Animais , Histonas/metabolismo , Camundongos , Ubiquitina-Proteína Ligases/metabolismo , Ubiquitina-Proteína Ligases/genética , Masculino , Proliferação de Células/fisiologia , Proliferação de Células/genética , Linhagem Celular , Espermatócitos/metabolismo , Movimento Celular/genética , Movimento Celular/fisiologia , Lisina/metabolismo , Sobrevivência Celular/fisiologia , Sobrevivência Celular/genéticaRESUMO
Breast cancer has become the most common malignant tumor worldwide. Triple-negative breast cancer (TNBC) is a type of breast cancer that is negative for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Compared with other molecular subtypes of breast cancer, TNBC is the most aggressive and highly heterogeneous. TNBC is insensitive to endocrine and anti-HER2 therapy, and chemotherapy is currently the main systemic treatment. With the continuous development of detection techniques and deepening research on TNBC molecular subtypes, drugs targeting immune checkpoints and different targets have emerged, such as atezolizumab, pembrolizumab, poly (ADP-ribose) polymerase (PARP) inhibitors, trophoblast cell-surface antigen 2 (TROP-2), and antibody-drug conjugates. These therapies provide new hope for TNBC treatment. Based on the analysis and classification of TNBC, this article summarizes the immunotherapy, targeted therapy, and new treatment combinations, providing references for the precise treatment of TNBC in the future.
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Background: To compare the diagnostic performance of radiomics models with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion parameters for the preoperative prediction of extramural venous invasion (EMVI) in rectal cancer patients and to develop a preoperative nomogram for predicting the EMVI status. Methods: In total, 106 rectal cancer patients were enrolled in our study. All patients under went preoperative rectal high-resolution MRI and DCE-MRI. We built five models based on the perfusion parameters of DCE-MRI (quantitative model), the radiomics of T2-weighted (T2W) CUBE imaging (R1 model), DCE-MRI (R2 model), clinical features (clinical model), and clinical-radiomics features. The predictive efficacy of the radiomics signature was assessed and internally verified. The area under the receiver operating curve (AUC) was used to compare the diagnostic performance of different radiomics models and DCE-MRI quantitative parameters. The radiomics score and clinical-pathologic risk factors were incorporated into an easy-to-use nomogram. Results: The quantitative parameters K trans and Ve were significantly higher in the EMVI-positive group than in the EMVI-negative group (both P =0.02). K trans combined with Ve showed a fair degree of accuracy (AUC 0.680 in the training cohort and AUC 0.715 in the validation cohort) compared with K trans or Ve alone. The AUCs of the R1 and R2 models were 0.826, 0.715 and 0.872, 0.812 in the training and validation cohorts, respectively. In addition, the R2-C model yielded an AUC of 0.904 in the training cohort and 0.812 in the validation cohort. The nomogram was presented based on the clinical-radiomics model. The calibration curves showed good agreement. Conclusion: The radiomics nomogram that incorporates the radiomics score, histopathological grade and T stage demonstrated better diagnostic accuracy than the DCE-MRI quantitative parameters and may have significant clinical implications for the preoperative individualized prediction of EMVI in rectal cancer patients.