Novel SPEF2 variants cause male infertility and likely primary ciliary dyskinesia.

PURPOSE: This study aimed to identify the genetic causes of male infertility and primary ciliary dyskinesia (PCD)/PCD-like phenotypes in three unrelated Han Chinese families. METHODS: We conducted whole-exome sequencing of three patients with male infertility and PCD/PCD-like phenotypes from three unrelated Chinese families. Ultrastructural and immunostaining analyses of patient spermatozoa and respiratory cilia and in vitro analyses were performed to analyze the effects of SPEF2 variants. Intracytoplasmic sperm injection (ICSI) was administered to three affected patients. RESULTS: We identified four novel SPEF2 variants, including one novel homozygous splicing site variant [NC_000005.10(NM_024867.4): c.4447 + 1G > A] of the SPEF2 gene in family 1, novel compound heterozygous nonsense variants [NC_000005.10(NM_024867.4): c.1339C > T (p.R447*) and NC_000005.10(NM_024867.4): c.1645G > T (p.E549*)] in family 2, and one novel homozygous missense variant [NC_000005.10(NM_024867.4): c.2524G > A (p.D842N)] in family 3. All the patients presented with male infertility and PCD/likely PCD. All variants were present at very low levels in public databases, predicted to be deleterious in silico prediction tools, and were further confirmed deleterious by in vitro analyses. Ultrastructural analyses of the spermatozoa of the patients revealed the absence of the central pair complex in the sperm flagella. Immunostaining of the spermatozoa and respiratory cilia of the patients validated the pathogenicity of the SPEF2 variants. All patients carrying SPEF2 variants underwent one ICSI cycle and delivered healthy infants. CONCLUSION: Our study reported four novel pathogenic variants of SPEF2 in three male patients with infertility and PCD/PCD-like phenotypes, which not only extend the spectrum of SPEF2 mutations but also provide information for genetic counseling and treatment of such conditions.

Prognostic analysis and validation of lncRNAs in bladder cancer on the basis of neutrophil extracellular traps.

BACKGROUND: Complex interactions in the tumor microenvironment (TME) between bladder cancer (BLCA) and immune cells are critical for cancer progression. However, studies of neutrophil extracellular trap-associated long non-coding RNAs (NET-lncRNAs) in the TME of BLCA have not been reported. This study aims to screen for NET-lncRNAs in BLCA and to preliminarily explore their effects on BLCA development. METHODS: The correlation of NET-related gene sets, which were identified from the cancer genome atlas (TCGA) BLCA datasets, with lncRNAs was analyzed and the prognosis-related genes were identified through random forest analysis. The least absolute shrinkage and selection operator (LASSO) model was utilized to obtain prognostic risk scores for NET-lncRNAs (NET-Score). We collected clinical BLCA samples, as well as SV-HUC-1 and BLCA cells, to validate the expression of NET-lncRNAs. Survival and independent prognostic analysis were performed. In J82 and UM-UC-3 cells, after NKILA expression was inhibited, cell proliferation and apoptosis levels were detected. RESULTS: NET-related gene sets mainly included CREB5, MMP9, PADI4, CRISPLD2, CD93, DYSF, MAPK3, TECPR2, MAPK1 and PIK3CA. Then, four NET-lncRNAs, MAP 3 K4-AS1, MIR100HG, NKILA and THY1-AS1, were identified. NET-Score had the highest hazard ratio for BLCA. An elevated NET-Score was linked to a significant increase in immune cell infiltration and copy number variation, as well as a notable decrease in survival rate and drug sensitivity. NET-lncRNA-related genes were mainly enriched in the pathways of angiogenesis, immune response, cell cycle and T cell activation. MAP 3 K4-AS1, MIR100HG, NKILA and THY1-AS1 expressions were significantly increased in BLCA tissues. Compared with SV-HUC-1 cells, NKILA expression was elevated in J82 and UM-UC-3 cells. Inhibition of NKILA expression inhibited the proliferation and promoted apoptosis of J82 and UM-UC-3 cells. CONCLUSIONS: Several NET-lncRNAs, including MAP 3 K4-AS1, MIR100HG, NKILA and THY1-AS1, were successfully screened in the BLCA. The NET-Score was an independent prognostic factor for BLCA. In addition, inhibition of NKILA expression suppressed BLCA cell development. The above NET-lncRNAs could serve as potential prognostic markers and targets in BLCA.

ATXN3 promotes prostate cancer progression by stabilizing YAP.

BACKGROUND: Prostate cancer (PC) is the most common neoplasm and is the second leading cause of cancer-related deaths in men worldwide. The Hippo tumor suppressor pathway is highly conserved in mammals and plays an important role in carcinogenesis. YAP is one of major key effectors of the Hippo pathway. However, the mechanism supporting abnormal YAP expression in PC remains to be characterized. METHODS: Western blot was used to measure the protein expression of ATXN3 and YAP, while the YAP target genes were measured by real-time PCR. CCK8 assay was used to detect cell viability; transwell invasion assay was used to measure the invasion ability of PC. The xeno-graft tumor model was used for in vivo study. Protein stability assay was used to detect YAP protein degradation. Immuno-precipitation assay was used to detect the interaction domain between YAP and ATXN3. The ubiquitin-based Immuno-precipitation assays were used to detect the specific ubiquitination manner happened on YAP. RESULTS: In the present study, we identified ATXN3, a DUB enzyme in the ubiquitin-specific proteases family, as a bona fide deubiquitylase of YAP in PC. ATXN3 was shown to interact with, deubiquitylate, and stabilize YAP in a deubiquitylation activity-dependent manner. Depletion of ATXN3 decreased the YAP protein level and the expression of YAP/TEAD target genes in PC, including CTGF, ANKRD1 and CYR61. Further mechanistic study revealed that the Josephin domain of ATXN3 interacted with the WW domain of YAP. ATXN3 stabilized YAP protein via inhibiting K48-specific poly-ubiquitination process on YAP protein. In addition, ATXN3 depletion significantly decreased PC cell proliferation, invasion and stem-like properties. The effects induced by ATXN3 depletion could be rescued by further YAP overexpression. CONCLUSIONS: In general, our findings establish a previously undocumented catalytic role for ATXN3 as a deubiquitinating enzyme of YAP and provides a possible target for the therapy of PC. Video Abstract.

MIR663AHG as a competitive endogenous RNA regulating TGF-ß-induced epithelial proliferation and epithelial-mesenchymal transition in benign prostate hyperplasia.

Benign prostate hyperplasia (BPH) is the most commonly seen disease among aging males. Transforming growth factor(TGF)-ß-mediated epithelial-mesenchymal transition (EMT) and epithelial overproliferation might be central events in BPH etiology and pathophysiology. In the present study, long noncoding RNA MIR663AHG, miR-765, and FOXK1 formed a competing endogenous RNAs network, modulating TGF-ß-mediated EMT and epithelial overproliferation in BPH-1 cells. miR-765 expression was downregulated in TGF-ß-stimulated BPH-1 cells; miR-765 overexpression ameliorated TGF-ß-mediated EMT and epithelial overproliferation in BPH-1 cells. MIR663AHG directly targeted miR-765 and negatively regulated miR-765; MIR663AHG knockdown also attenuated TGF-ß-induced EMT and epithelial overproliferation in BPH-1 cells, whereas miR-765 inhibition attenuated MIR663AHG knockdown effects on TGF-ß-stimulated BPH-1 cells. miR-765 directly targeted FOXK1 and negatively regulated FOXK1. FOXK1 knockdown attenuated TGF-ß-induced EMT and epithelial overproliferation and promoted autophagy in BPH-1 cells, and partially attenuated miR-765 inhibition effects on TGF-ß-stimulated BPH-1 cells. In conclusion, this study provides a MIR663AHG/miR-765/FOXK1 axis modulating TGF-ß-induced epithelial proliferation and EMT, which might exert an underlying effect on BPH development and act as therapeutic targets for BPH treatment regimens.

SOX5 promotes cell growth and migration through modulating the DNMT1/p21 pathway in bladder cancer.

Bladder cancer (BC) is one of the most prevalent and life-threatening cancers among the male population worldwide. Sex determining region Y-box protein 5 (SOX5) plays important roles in a variety of human cancers. However, little research has been conducted on the function and underlying mechanism of SOX5 in BC. In the present study, we first reveal the increased expression of SOX5 in BC tissues and in vitro cells lines. Second, we discover that inhibition of SOX5 inhibits cell growth and migration but promotes cell apoptosis. Meanwhile, ectopic SOX5 expression stimulates cell growth and migration in BC cells. Then, we show that suppressing SOX5 inhibits the expression of DNA methyltransferase 1 (DNMT1), and that overexpressing DNMT1 alleviates the cell progress of BC cells inhibited by SOX5. Furthermore, we demonstrate that DNMT1 inhibits p21 expression by affecting DNA methylation of the p21 promoter. Collectively, we demonstrate that SOX5 exerts its functions in BC cells by modulating the SOX5/DNMT1/p21 pathway. Finally, we demonstrate that SOX5 knockdown inhibits xenograft tumor growth in vivo. In conclusion, our study elucidates the oncogenic role of SOX5 and its underlying molecular mechanism in BC, and reveals a novel pathway which has the potential to serve as a diagnostic biomarker and therapeutic target for BC.

High expression of TRIP13 is associated with tumor progression in H. pylori infection induced gastric cancer.

BACKGROUND/OBJECTIVE: H. pylori is a recognized bacterial carcinogen in the world to cause gastric cancer (GC). However, the molecular mechanism of H. pylori infection-induced GC is not completely clear. Thus, there is an urgent need to reveal the precise mechanisms regulating cancer development due to H. pylori infection. METHODS: GEO microarray databases and TCGA databases were extracted for the analysis of different expression genes (DEGs). Then, Kaplan-Meier Plotter was used for prognostic analysis. Functional enrichment analysis of TRIP13 was performed by metascape database and TIMER database. Specific role of TRIP13 in GC with H. pylori infection was confirmed by CCK8, cell cycle analysis and WB. RESULTS: A total 10 DEGs were substantially elevated in GC and H. pylori+ tissues and might be associated with H. pylori infection in GC and only the highly expressed TRIP13 was statistically associated with poor prognosis in GC patients. Meanwhile, TRIP13 were upregulated in both CagA-transfected epithelial cells and GC cells. And TRIP13 deficiency inhibited cell proliferation and arrested the cell cycle at the G1 phase. CONCLUSION: Our study suggested that high expression of TRIP13 can promote the proliferation, cell cycle in GC cells, which could be used as a biomarker for H. pylori infection GC.

Epigenetic-related gene-based prognostic model construction and validation in prostate adenocarcinoma.

Prostate adenocarcinoma (PRAD), driven by both genetic and epigenetic factors, is a common malignancy that affects men worldwide. We aimed to identify and characterize differentially expressed epigenetic-related genes (ERGs) in PRAD and investigate their potential roles in disease progression and prognosis. We used PRAD samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to identify prognosis-associated ERGs. Thirteen ERGs with two distinct expression profiles were identified through consensus clustering. Gene set variation analysis highlighted differences in pathway activities, particularly in the Hedgehog and Notch pathways. Higher epigenetic scores correlated with favorable prognosis and improved immunotherapeutic response. Experimental validation underscored the importance of CBX3 and KAT2A, suggesting their pivotal roles in PRAD. This study provides crucial insights into the epigenetic scoring approach and presents a promising prognostic tool, with CBX3 and KAT2A as key players. These findings pave the way for targeted and personalized interventions for the treatment of PRAD.

Classification of Pericarpium Citri Reticulatae (Chenpi) age using surface-enhanced Raman spectroscopy.

Pericarpium Citri Reticulatae (PCR) is used in food and medical herbal formula, and its quality is determined by its age. Raman spectroscopy is a laser technology for molecular fingerprinting. The feasibility of using surface-enhanced Raman spectroscopy (SERS) to determine the PCR age was investigated. The Raman peaks were acquired using a Raman spectrometer with a 785 nm diode laser and were analyzed using principal component analysis (PCA) followed by linear discriminant analysis (PCA-LDA). There were six major peaks at 600, 730, 990, 1370, 1607, and 1742 cm-1 in the SERS spectra, and their intensity, especially the peak at 1607 cm-1, was inversely correlated with the PCR age. The different ages of PCR could be correctly classified with over 90 % accuracy by using PCA-LDA based on the SERS spectra. In conclusion, a Raman spectrometer may be used as a novel method to identify the age of PCR products.

An IFN-γ-related signature predicts prognosis and immunotherapy response in bladder cancer: Results from real-world cohorts.

Bladder cancer (BLCA) is featured with high incidence and mortality. Whether the IFN-γ signaling could be used as an immunotherapy determinant for BLCA has not been fully confirmed. In this study, the transcriptome data and clinical information of BLCA samples were collected from The Cancer Genome Atlas (TCGA). Besides, four immunotherapy cohorts including IMvigor210 cohort, Gide cohort, Van Allen cohort, and Lauss cohort were collected. The Xiangya real-world cohort was used for independent validation. An IFN-γ-related signature was developed and validated in BLCA for predicting prognosis, mutation, tumor microenvironment status, and immunotherapy response. This is the first study focusing on the comprehensive evaluation of predictive values on the IFN-γ-related signature in BLCA. The potential clinical application of the IFN-γ-related signature was expected to be further validated with more prospective clinical cohorts.

Computer-aided diagnosis of prostate cancer based on deep neural networks from multi-parametric magnetic resonance imaging.

Objectives: To evaluate a new deep neural network (DNN)-based computer-aided diagnosis (CAD) method, namely, a prostate cancer localization network and an integrated multi-modal classification network, to automatically localize prostate cancer on multi-parametric magnetic resonance imaging (mp-MRI) and classify prostate cancer and non-cancerous tissues. Materials and methods: The PROSTAREx database consists of a "training set" (330 suspected lesions from 204 cases) and a "test set" (208 suspected lesions from 104 cases). Sequences include T2-weighted, diffusion-weighted, Ktrans, and apparent diffusion coefficient (ADC) images. For the task of abnormal localization, inspired by V-net, we designed a prostate cancer localization network with mp-MRI data as input to achieve automatic localization of prostate cancer. Combining the concepts of multi-modal learning and ensemble learning, the integrated multi-modal classification network is based on the combination of mp-MRI data as input to distinguish prostate cancer from non-cancerous tissues through a series of operations such as convolution and pooling. The performance of each network in predicting prostate cancer was examined using the receiver operating curve (ROC), and the area under the ROC curve (AUC), sensitivity (TPR), specificity (TNR), accuracy, and Dice similarity coefficient (DSC) were calculated. Results: The prostate cancer localization network exhibited excellent performance in localizing prostate cancer, with an average error of only 1.64 mm compared to the labeled results, an error of about 6%. On the test dataset, the network had a sensitivity of 0.92, specificity of 0.90, PPV of 0.91, NPV of 0.93, and DSC of 0.84. Compared with multi-modal classification networks, the performance of single-modal classification networks is slightly inadequate. The integrated multi-modal classification network performed best in classifying prostate cancer and non-cancerous tissues with a TPR of 0.95, TNR of 0.82, F1-Score of 0.8920, AUC of 0.912, and accuracy of 0.885, which fully confirmed the feasibility of the ensemble learning approach. Conclusion: The proposed DNN-based prostate cancer localization network and integrated multi-modal classification network yielded high performance in experiments, demonstrating that the prostate cancer localization network and integrated multi-modal classification network can be used for computer-aided diagnosis (CAD) of prostate cancer localization and classification.