Alport综合征是一种以基底膜结构异常为特征的遗传性肾脏疾病，临床上表现为进行性肾功能丧失、感音神经性听力损失和各种眼部异常，由负责编码基底膜Ⅳ型胶原蛋白α3、α4和α5链的基因变异引起。尚无根治性治疗方法，药物治疗只能延缓病情进展。近年来国内外学者在Alport综合征基因治疗研究方面取得了一定的进展与收获。本文旨在从动物模型、基因转移载体、实验性基因治疗方法3个角度综述Alport综合征基因治疗的研究现状及最新进展，并讨论基因治疗可能面临的问题与挑战。.

Corneal neovascularization (CoNV) is the second leading common cause of vision impairment worldwide and is a blinding pathological alteration brought on by ocular trauma, infection, and other factors. There are some limitations in the treatment of CoNV, hence it\'s critical to look into novel therapeutic targets. The corneal epithelial barrier, which is the initial barrier of the ocular surface, is an important structure that shields the eye from changes in the internal environment or invasion by the external environment. This study sought to collate evidence on the regulation of corneal epithelial barrier injury on the activation of vascular endothelial cells (VECs), basement membrane (BM) degradation, differentiation, migration, and proliferation of VECs, vascular maturation and stability, and other key processes in CoNV, so as to provide a novel concept for CoNV therapy targeting corneal epithelial barrier repair.

BACKGROUND: Basement membrane (BM) is an important component of the extracellular matrix, which plays an important role in the growth and metastasis of tumor cells. However, few biomarkers based on BM have been developed for prognostic assessment and prediction of immunotherapy in bladder cancer (BLCA).
METHODS: In this study, we used the BLCA public database to explore the relationship between BM-related genes (BMRGs) and prognosis. A novel molecular typing of BLCA was performed using consensus clustering. LASSO regression was used to construct a signature based on BMRGs, and its relationship with prognosis was explored using survival analysis. The pivotal BMRGs were further analyzed to assess its clinical characteristics and immune landscape. Finally, immunohistochemistry was used to detect the expression of the hub gene in BLCA patients who underwent surgery or received immune checkpoint inhibitor (ICI) immunotherapy in our hospital.
RESULTS: We comprehensively analyzed the relationship between BMRGs and BLCA, and established a prognostic-related signature which was an independent influence on the prognostic prediction of BLCA. We further screened and validated the pivotal gene-MMP14 in public database. In addition, we found that MMP14 expression in muscle invasive bladder cancer (MIBC) was significantly higher and high MMP14 expression had a poorer response to ICI treatment in our cohort.
CONCLUSIONS: Our findings highlighted the satisfactory value of BMRGs and suggested that MMP14 may be a potential biomarker in predicting prognosis and response to immunotherapy in BLCA.

BACKGROUND: This study sought to investigate the prognostic value of basement membrane (BM)-associated gene expressions in oral cancer.
METHODS: We harvested and integrated data on BM-associated genes (BMGs), the oral cancer transcriptome, and clinical information from public repositories. After identifying differentially expressed BMGs, we used Cox and Lasso regression analyses to create a BMG-based risk score for overall survival at various intervals. We then validated this score using the GSE42743 cohort as a validation set. The prognostic potential of the risk scores and their relations to clinical features were assessed. Further, we conducted functional pathway enrichment, immune cell infiltration, and immune checkpoint analyses to elucidate the immunological implications and therapeutic potential of the BMG-based risk score and constituent genes. To confirm the expression levels of the BMG LAMA3 in clinical samples of oral cancer tissue, we performed quantitative real-time PCR (qRT-PCR) and immunohistochemical staining.
RESULTS: The BMGs LAMA3, MMP14, and GPC2 demonstrated notable prognostic significance, facilitating the construction of a BMG-based risk score. A higher risk score derived from BMGs correlated with a poorer survival prognosis for oral cancer patients. Moreover, the risk-associated BMGs exhibited a significant relationship with immune function variability (P < 0.05), discrepancies in infiltrating immune cell fractions, and immune checkpoint expressions (P < 0.05). The upregulated expression levels of LAMA3 in oral cancer tissues were substantiated through qRT-PCR and immunohistochemical staining.
CONCLUSIONS: The BMG-based risk score emerged as a reliable prognostic tool for oral cancer, meriting further research for validation and potential clinical application.

In all mammals, the basement membrane serves as a pivotal extracellular matrix. Hepatocellular carcinoma (HCC) is a challenge among numerous cancer types shaped by basement membrane-related genes (BMGs). Our research established an innovative prognostic model that is highly accurate in its prediction of HCC prognoses and immunotherapy efficacy to summarize the crucial role of BMGs in HCC. We obtained HCC transcriptome analysis data and corresponding clinical data from The Cancer Genome Atlas (TCGA). To augment our dataset, we incorporated 222 differentially expressed BMGs identified from relevant literature. A weighted gene coexpression network analysis (WGCNA) of 10158 genes demonstrated four modules that were connected to HCC. Additionally, 66 genes that are found at the intersection of BMGs and HCC-related genes were designated as hub HCC-related BMGs. MMP1, ITGA2, P3H1, and CTSA comprise the novel model that was engineered using univariate and multivariate Cox regression analysis. Furthermore, the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) datasets encouraged the BMs model\'s validity. The overall survival (OS) of individuals with HCC may be precisely predicted in the TCGA and ICGC databases utilizing the BMs model. A nomogram based on the model was created in the TCGA database at similar time, and displayed a favorable discriminating ability for HCC. Particularly, when compared to the patients at an elevated risk, the patients with a low-risk profile presented different tumor microenvironment (TME) and hallmark pathways. Moreover, we discovered that a lower risk score of HCC patients would display a greater response to immunotherapy. Finally, quantitative real-time PCR (qRT-PCR) experiments were used to verify the expression patterns of BMs model. In summary, BMs model demonstrated efficacy in prognosticating the survival probability of HCC patients and their immunotherapeutic responsiveness.

Background: Uncover the pivotal link between lymphocyte-specific protein tyrosine kinase (Lck)-related genes and clinical risk stratification in pancreatic cancer. Methods: This study identifies shared genes between differentially expressed genes (DEGs) and Lck-related genes in pancreatic cancer using a methodological framework rooted in The Cancer Genome Atlas database. Feature gene selection is accomplished and a signature model is constructed. Statistical significant clinical endpoints such as overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were defined. Results: After performing random survival forest, Lasso regression, and multivariate Cox regression model, 7 trait genes out of 272 Lck-associated DEGs are selected to create a signature model that is independent of other clinical factors and can predict OS and DSS. It appears that high-risk patients have activated the TP53 signaling pathway and the cell cycle signaling pathway. LAMA3 turned out to be the hub gene of the signature with high expression in pancreatic cancer. Patients with increased expression of LAMA3 had a short OS, DSS, and PFI in comparison. The candidate competing endogenous RNA network of LAMA3 turned out to be OPI5-AS1/hsa-miR-186-5p/LAMA3 axis. Conclusions: A characteristic signature of seven Lck-related genes, especially LAMA3, has been shown to be a key factor in clinical risk stratification for pancreatic cancer.

Hepatocellular carcinoma (HCC) is the main type of primary liver cancer. This study aimed to develop a basement membrane (BM) related lncRNAs risk signature to evaluate the prognosis of HCC patients. We screened differentially expressed BM-related lncRNAs (DE-BMRlncRNAs) for risk evaluation, and identified six DE-BMRlncRNAs (AC072054.1, NUP50-DT, AC026412.3, AC109322.2, POLH-AS1 and LINC00595) for prognostic risk signature. HCC patients were divided to high or low risk according to median risk score. Our prognostic model predicted that patients with higher risk score had worse prognosis. We also created a nomogram to assist clinical decision-making according to risk score and clinicopathological features. Meanwhile, we confirmed the expression of six lncRNAs in HCC tissue and cells. POLH-AS1 knockdown inhibited the migration and invasion of HCC cells. In conclusion, we established a predictive model based on BMRlncRNAs to predict the prognosis of HCC. Our findings offer a rationale to further explore BM-related biomarkers for HCC.

Hepatocellular carcinoma (HCC) is a significant cancer with limited treatments and a poor prognosis, with the basement membrane (BM) playing a crucial role in its initiation and growth. This study utilized data from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases to identify basement membrane-related genes differentially expressed in HCC. Through gene co-expression analysis, BM-associated long non-coding RNAs (lncRNAs) were discovered. LncRNAs related to HCC survival were selected via univariate analysis, and a prognostic model was constructed using LASSO regression and multivariate analysis. This model effectively classified HCC patients into high and low-risk groups, uncovering significant differences in prognosis, immune response, mutation, and drug sensitivity. Six BM-related lncRNAs (GSEC, MIR4435-2HG, AC092614.1, AC127521.1, LINC02580, and AC008050.1) were validated in normal and HCC cell lines, and the key role of AC092614.1 in regulating proliferation, migration, and invasion of HCC cells in vitro was explored. This research emphasizes the prognostic and therapeutic relevance of BM-related lncRNAs in HCC, highlighting AC092614.1\'s role in disease progression and as a potential target for targeted therapy.

Vascular endothelial cells (VECs) are key players in the formation of neovessels and tumor metastasis, the ultimate cause of the majority of cancer-related human death. However, the crosstalk between VECs and metastasis remain greatly elusive. Based on our finding that tumor-associated VECs present significant decrease of Nrdp1 protein which is closely correlated with higher metastatic probability, herein we show that the conditional medium from hypoxia-incubated cancer cells induces extensive Nrdp1 downregulation in human and mouse VECs by vascular endothelial growth factor (VEGF), which activates CHIP, followed by Nrdp1 degradation in ubiquitin-proteasome-dependent way. More importantly, lung metastases of cancer cells significantly increase in conditional VECs Nrdp1 knockout mice. Mechanically, Nrdp1 promotes degradation of Fam20C, a secretory kinase involved in phosphorylating numerous secreted proteins. Reciprocally, deficiency of Nrdp1 in VECs (ecNrdp1) results in increased secretion of Fam20C, which induces degradation of extracellular matrix and disrupts integrity of vascular basement membrane, thus driving tumor metastatic dissemination. In addition, specific overexpression of ecNrdp1 by Nrdp1-carrying adeno-associated virus or chemical Nrdp1 activator ABPN efficiently mitigates tumor metastasis in mice. Collectively, we explore a new mechanism for VEGF to enhance metastasis and role of Nrdp1 in maintaining the integrity of vascular endothelium, suggesting that ecNrdp1-mediated signaling pathways might become potential target for anti-metastatic therapies.

The blood-brain barrier (BBB) protects the central nervous system from infections or harmful substances1; its impairment can lead to or exacerbate various diseases of the central nervous system2-4. However, the mechanisms of BBB disruption during infection and inflammatory conditions5,6 remain poorly defined. Here we find that activation of the pore-forming protein GSDMD by the cytosolic lipopolysaccharide (LPS) sensor caspase-11 (refs. 7-9), but not by TLR4-induced cytokines, mediates BBB breakdown in response to circulating LPS or during LPS-induced sepsis. Mice deficient in the LBP-CD14 LPS transfer and internalization pathway10-12 resist BBB disruption. Single-cell RNA-sequencing analysis reveals that brain endothelial cells (bECs), which express high levels of GSDMD, have a prominent response to circulating LPS. LPS acting on bECs primes Casp11 and Cd14 expression and induces GSDMD-mediated plasma membrane permeabilization and pyroptosis in vitro and in mice. Electron microscopy shows that this features ultrastructural changes in the disrupted BBB, including pyroptotic endothelia, abnormal appearance of tight junctions and vasculature detachment from the basement membrane. Comprehensive mouse genetic analyses, combined with a bEC-targeting adeno-associated virus system, establish that GSDMD activation in bECs underlies BBB disruption by LPS. Delivery of active GSDMD into bECs bypasses LPS stimulation and opens the BBB. In CASP4-humanized mice, Gram-negative Klebsiella pneumoniae infection disrupts the BBB; this is blocked by expression of a GSDMD-neutralizing nanobody in bECs. Our findings outline a mechanism for inflammatory BBB breakdown, and suggest potential therapies for diseases of the central nervous system associated with BBB impairment.