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Alport syndrome is a genetic kidney disease that causes worsening of kidney function over time, often progressing to kidney failure. Some types of Alport syndrome cause other symptoms and signs, including hearing loss and eye abnormalities. Research now indicates that Alport syndrome (autosomal dominant inheritance) is the most common form. Alport syndrome can have X-linked or a rare form of autosomal recessive inheritance. Traditionally, a kidney biopsy was used to diagnose Alport syndrome, but genetic testing provides a more precise and less invasive means of diagnosis and reveals the underlying pattern of inheritance. At present, there are no specific curative treatments for Alport syndrome however there is a strong international effort in pursuit of future therapies. Currently, angiotensin-converting enzyme inhibitors (ACEi), or an angiotensin receptor blocker (ARB) if a patient cannot tolerate an ACEi, slow down the progression of kidney disease and can delay the onset of kidney failure by years. There are other potential treatments in research that potentially can help delay the onset of kidney issues. Early treatment of patients and identification of their at-risk relatives is a priority. People living with Alport syndrome and their doctors now benefit from an active international research community working on translating further treatments into clinical practice and providing up-to-date clinical guidelines.

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Recent studies in rabbits and case reports in humans have demonstrated the efficacy of topical losartan in the treatment of corneal scarring fibrosis after a wide range of injuries, including chemical burns, infections, surgical complications, and some diseases. It is hypothesized that the effect of losartan on the fibrotic corneal stroma occurs through a two-phase process in which losartan first triggers the elimination of myofibroblasts by directing their apoptosis via inhibition of extracellular signal-regulated kinase (ERK)-mediated signal transduction, and possibly through signaling effects on the viability and development of corneal fibroblast and fibrocyte myofibroblast precursor cells. This first step likely occurs within a week or two in most corneas with fibrosis treated with topical losartan, but the medication must be continued for much longer until the epithelial basement membrane (EBM) is fully regenerated or new myofibroblasts will develop from precursor cells. Once the myofibroblasts are eliminated from the fibrotic stroma, corneal fibroblasts can migrate into the fibrotic tissue and reabsorb/reorganize the disordered extracellular matrix (ECM) previously produced by the myofibroblasts. This second stage is longer and more variable in different eyes of rabbits and humans, and accounts for most of the variability in the time it takes for the stromal opacity to be markedly reduced by topical losartan treatment. Eventually, keratocytes reemerge in the previously fibrotic stromal tissue to fine-tune the collagens and other ECM components and maintain the normal structure of the corneal stroma. The efficacy of losartan in the prevention and treatment of corneal fibrosis suggests that it acts as a surrogate for the EBM, by suppressing TGF beta-directed scarring of the wounded corneal stroma, until control over TGF beta action is re-established by a healed EBM, while also supporting regeneration of the EBM by allowing corneal fibroblasts to occupy the subepithelial stroma in the place of myofibroblasts.

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The purpose of this study was to evaluate transforming growth factor beta (TGFß) isoform localization in rabbit corneas with spontaneous persistent epithelial defects (PEDs) after photorefractive keratectomy (PRK). Four cryofixed corneas from a previously reported series of PEDs in rabbits that had PRK were evaluated with triplex immunohistochemistry (IHC) for TGFß3, myofibroblast marker alpha-smooth muscle actin (α-SMA) and mesenchymal marker vimentin. One cornea had sufficient remaining tissue for triplex IHC for TGFß1, TGFß2, or TGFß3 (each with α-SMA and vimentin) using isoform-specific antibodies. All three TGFß isoforms were detected in the subepithelial stroma at and surrounding the PED. Some of each TGFß isoform co-localized with α-SMA of myofibroblasts, which could be TGFß isoform autocrine production by myofibroblasts or TGFß-1, -2, and -3 binding to these myofibroblasts.

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Rheumatoid arthritis (RA) is a chronic inflammatory joint disease that causes great distress to patients and society. Early diagnosis is the key to the successful treatment of RA. The basement membrane, one of the oldest tissue structures, is localized under the epithelium. Its complex composition and rich biological functions have made it a focus of research in recent years, while basement membrane-associated genetic variants are involved in most human disease processes. The aim of this study is to find new diagnostic biomarkers for RA and explore their role and possible mechanism in rheumatoid arthritis. The GSE12021, GSE55235 and GSE55457 datasets were downloaded from the GEO database. Their fraction associated with basement membrane genes was analyzed and differentially expressed genes between the disease and normal groups were explored. We identified two basement membrane-associated genes, lysine oxidase-like 1 (LOXL1) and discoid peptide receptor 2 (DDR2). Focusing on the more interesting LOXL1, we found that LOXL1 expression was significantly elevated in the synovium of patients with rheumatoid arthritis, and LOXL1 mRNA and protein levels were elevated in tumor necrosis factor α-stimulated human synovial sarcoma cells (SW982). And LOXL1 knockdown inhibited tumor necrosis factor α-induced inhibition in SW982 cells expression of inducible nitric oxide synthase (INOS), cyclooxygenase-2 (COX2), and interleukin-6 (IL-6). Interestingly, knockdown of LOXL1 inhibited the phosphorylation of PI3K and AKT. In summary, LOXL1 may become a novel diagnostic gene for RA, and knockdown of LoxL1 may inhibit synovial inflammation by affecting PI3K/AKT pathway.

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OBJECTIVE: The study aimed to identify biomarkers associated with basement membranes (BMs)-related genes (BMGs) in Alzheimer's disease (AD) and investigate their potential role in the progression of AD pathology. METHODS: Gene expression profiles were retrieved from Gene Expression Omnibus database. 222 human BMGs were collected from the relevant literature. Subsequently, the differentially expressed BMGs (DE-BMGs) were filtered, and the key DE-BMGs were identified using weighted gene correlation network analysis (WGCNA) and two machine learning algorithms. The expression levels, diagnostic values, clinical significances, enrichment analyses and regulatory networks of these candidate biomarkers were further examined. RESULTS: A total of 44 DE-BMGs were acquired by comparing AD temporal cortex with nondemented controls. Using WGCNA and machine learning, versiscan (VCAN), tissue inhibitor of metalloproteinase 1 (TIMP1), structural maintenance of chromosome 3 (SMC3), and laminin ß2 (LAMB2) were ultimately identified as candidate biomarkers, and they were verified in a murine model. These biomarkers had high diagnostic value (area under the curve (AUC)＞0.8). The diagnostic value of the four gene combination was then evaluated in multiple databases, yielding AUCs ranging from 0.688 to 1. Furthermore, a meaningful correlation between these biomarkers and AD pathology progression was observed. Finally, comprehensive analyses involving Hallmark pathway enrichment, immune cell infiltration analysis, transcriptional regulatory, and competitive endogenous RNA networks indicated that key DE-BMGs closely correlated with oxidative stress and immune dysfunction. CONCLUSION: Our study comprehensively identified four candidate BMGs and their combination model that play a crucial part in the diagnosis and pathogenesis of AD.

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BACKGROUND: Through bioinformatics analysis to identify the hub genes of Intervertebral disc degeneration (IVDD) associated with basement membranes (BMs) and find out the potential molecular targets and drugs for BMs-related annulus fibrosus (AF) degeneration based on bioinformatic analysis and molecular approach. METHODS: Intervertebral disc degeneration (IVDD) related targets were obtained from GeneCards, DisGenet and OMIM databases. BMs related genes were obtained from Basement membraneBASE database. The intersection targets were identified and subjected to protein-to-protein interaction (PPI) construction via STRING. Hub genes were identified and conducted Gene ontology (GO) and pathway enrichment analysis through MCODE and Clue GO in Cytospace respectively. DSigDB database was retrieved to predict therapeutic drugs and molecular docking was performed through PyMOL, AutoDock 1.5.6 to verify the binding energy between the drug and the different expressed hub genes. Finally, GSE70362 from GEO database was obtained to verify the different expression and correlation of each hub gene for AF degeneration. RESULTS: We identified 41 intersection genes between 3 disease targets databases and Basement membraneBASE database. PPI network revealed 25 hub genes and they were mainly enriched in GO terms relating to glycosaminoglycan catabolic process, the TGF-ß signaling pathway. 4 core targets were found to be significant via comparison of microarray samples and they showed strong correlation. The molecular docking results showed that the core targets have strong binding energy with predicting drugs including chitosamine and retinoic acid. CONCLUSIONS: In this study, we identified hub genes, pathways, potential targets, and drugs for treatment in BMs-related AF degeneration and IVDD.

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Background: Hepatocellular carcinoma (HCC), which is characterized by its high malignancy, generally exhibits poor response to immunotherapy. As part of the tumor microenvironment, basement membranes (BMs) are involved in tumor development and immune activities. Presently, there is no integrated analysis linking the basement membrane with immune checkpoints, especially from the perspective of lncRNA. Methods: Based on transcriptome data from The Cancer Genome Atlas, BMs-related and immune checkpoint-related lncRNAs were identified. By applying univariable Cox regression and Machine learning (LASSO and SVM-RFE algorithm), a 10-lncRNA prognosis signature was constructed. The prognostic significance of this signature was assessed by survival analysis. GSEA, ssGSEA, and drug sensitivity analysis were conducted to investigate potential functional pathways, immune status, and clinical implications of guiding individual treatments in HCC. Finally, the promoting migration effect of LINC01224 was validated via in vitro experiments. Results: The multiple Cox regression, receiver operating characteristic curves, and stratified survival analysis of clinical subgroups exhibited the robust prognostic ability of the lncRNA signature. Results of the GSEA and drug sensitivity analysis revealed significant differences in potential functional pathways and response to drugs between the two risk groups. In addition, the risk level of HCC patients was distinctly correlated with immune cell infiltration status. More importantly, LINC01224 was independently associated with the OS of HCC patients (P < 0.05), suppressing the expression of LINC01224 inhibited the migration of HCC cells. Conclusion: This study developed a reliable signature for the prognosis of HCC based on BM and immune checkpoint related lncRNA, revealing that LINC01224 might be a prognostic biomarker for HCC associated with the progression of HCC.

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BACKGROUND: Osteoarthritis is a very common clinical disease in middle-aged and elderly individuals, and with the advent of ageing, the incidence of this disease is gradually increasing. There are few studies on the role of basement membrane (BM)-related genes in OA. METHOD: We used bioinformatics and machine learning methods to identify important genes related to BMs in OA patients and performed immune infiltration analysis, lncRNA‒miRNA-mRNA network prediction, ROC analysis, and qRT‒PCR. RESULT: Based on the results of machine learning, we determined that LAMA2 and NID2 were the key diagnostic genes of OA, which were confirmed by ROC and qRT‒PCR analyses. Immune analysis showed that LAMA2 and NID2 were closely related to resting memory CD4 T cells, mast cells and plasma cells. Two lncRNAs, XIST and TTTY15, were simultaneously identified, and lncRNA‒miRNA‒mRNA network prediction was performed. CONCLUSION: LAMA2 and NID2 are important potential targets for the diagnosis and treatment of OA.

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Hepatocellular carcinoma (HCC) is a malignant tumor with high recurrence and metastasis rates and poor prognosis. Basement membrane is a ubiquitous extracellular matrix and is a key physical factor in cancer metastasis. Therefore, basement membrane-related genes may be new targets for the diagnosis and treatment of HCC. We systematically analyzed the expression pattern and prognostic value of basement membrane-related genes in HCC using the TCGA-HCC dataset, and constructed a new BMRGI based on WGCNA and machine learning. We used the HCC single-cell RNA-sequencing data in GSE146115 to describe the single-cell map of HCC, analyzed the interaction between different cell types, and explored the expression of model genes in different cell types. BMRGI can accurately predict the prognosis of HCC patients and was validated in the ICGC cohort. In addition, we also explored the underlying molecular mechanisms and tumor immune infiltration in different BMRGI subgroups, and confirmed the differences in response to immunotherapy in different BMRGI subgroups based on the TIDE algorithm. Then, we assessed the sensitivity of HCC patients to common drugs. In conclusion, our study provides a theoretical basis for the selection of immunotherapy and sensitive drugs in HCC patients. Finally, we also considered CTSA as the most critical basement membrane-related gene affecting HCC progression. In vitro experiments showed that the proliferation, migration and invasion abilities of HCC cells were significantly impaired when CTSA was knocked down.

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As post-COVID complications, chronic respiratory diseases are one of the foremost causes of mortality. The quest for a cure for this recent global challenge underlines that the lack of predictive in vitro lung models is one of the main bottlenecks in pulmonary preclinical drug development. Despite rigorous efforts to develop biomimetic in vitro lung models, the current cutting-edge models represent a compromise in numerous technological and biological aspects. Most advanced in vitro models are still in the "proof-of-concept" phase with a low clinical translation of the findings. On the other hand, advances in cellular and molecular studies are mainly based on relatively simple and unrealistic in vitro models. Herein, the current challenges and potential strategies toward not only bioinspired but truly biomimetic lung models are discussed.

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Background: The basement membranes (BMs) are involved in tumor progression, while few comprehensive analyses to date are performed on the role of BM-related gene signatures in lung adenocarcinoma (LUAD). Thus, we aimed to develop a novel prognostic model in LUAD based on BMs-related gene profiling. Methods: The LUAD BMs-related gene profiling and corresponding clinicopathological data were obtained from the basement membrane BASE, The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) databases. The Cox regression and least absolute shrinkage and selection operator (LASSO) methods were used to construct a BMs-based risk signature. The concordance index (C-index), receiver operating characteristic (ROC), and calibration curves were generated to evaluate the nomogram. The GSE72094 dataset was used to validate prediction of the signature. The differences in functional enrichment, immune infiltration, and drug sensitivity analyses were compared based on risk score. Results: In TCGA training cohort, 10 BMs-related genes were found, (e.g., ACAN, ADAMTS15, ADAMTS8, BCAN, etc). The signal signature based on these 10 genes was categorized into high- and low-risk groups regarding survival differences (p < 0.001). Multivariable analysis showed that the signature of combined 10 BMs-related genes was an independent prognostic predictor. Such a prognostic value of BMs-based signature in validation cohort of the GSE72094 were further verified. The GEO verification, C-index, and ROC curve showed that the nomogram had accurate prediction performance. The functional analysis suggested that BMs were mainly enriched in extracellular matrix-receptor (ECM-receptor) interaction. Moreover, the BMs-based model was correlated with immune checkpoint. Conclusion: This study identified BMs-based risk signature genes and demonstrated their ability to predict prognosis and guide personalized treatment of patients with LUAD.

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Inflammation following nerve injury and surgery often causes peripheral nerve adhesion (PNA) to the surrounding tissue. Numerous investigations independently examined the prevention or inhibition of PNA, however, an intervention targeting macrophages has not been fully elucidated. Basement membrane (BM) genes are known to modulate central nervous system (CNS) inflammation, however, their activities in the peripheral nervous system (PNS) remains undiscovered. In this report, we carried out weighted correlation network analysis (WCNA) to screen for principal sciatic nerve injury (SNI) module genes. Once an association between the module and BM genes was established, the protein-protein interaction (PPI) and immune infiltration analyses were employed to screen for relevant BM-related immune genes (Itgam, SDC1, Egflam, and CD44) in SNI. Subsequently, using the Drug SIGnatures (DSigDB) database and molecular docking, we demonstrated that Trichostatin A (TSA) interacted with key immune genes. TSA is known to enhance M2 macrophage expression and attenuate fibrosis. Nevertheless, the significance of the epigenetic modulation of macrophage phenotypes in dorsal root ganglion (DRG) is undetermined after SNI. In this article, we examined the TSA role in fibrogenesis and macrophage plasticity associated with DRG. We revealed that TSA enhanced M2 macrophage aggregation, inhibited fibroblast activation, and improved sciatic nerve regeneration (SNR) and sensory functional recovery (FR) after SNI. In addition, TSA suppressed M1 macrophages and enhanced M2 macrophage invasion within the DRG tissue. Furthermore, TSA dramatically reduced IL-1ß and TNFα levels, while upregulating IL-10 level. In summary, this research revealed for the first time that TSA alleviates fibrosis in DRG by promoting an M1 to M2 macrophage transition, which, in turn, accelerates SNR.

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BACKGROUND AND PURPOSE: In the central nervous system, a multitude of changes have been described associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, such as microglial activation, perivascular lymphocyte cuffing, hypoxic-ischaemic changes, microthrombosis, infarcts or haemorrhages. It was sought here to assess the vascular basement membranes (vBMs) and surrounding perivascular astrocytes for any morphological changes in acute respiratory syndrome (coronavirus disease 2019, COVID-19) patients. METHODS: The light microscopy morphology of the vBMs and perivascular astrocytes from brains of 14 patients with confirmed SARS-CoV-2 infection was analysed and compared to four control patients utilizing fluorescent immunohistochemistry for collagen IV and astrocytes (GFAP), endothelia (CD31), tight junction 1 (TJ1) adhesion protein, as well as the aquaporin 4 (AQP4) water channel. On 2D and 3D deconvoluted images from the cortex and white matter, vessel densities, diameters, degree of gliosis, collagen IV/GFAP and GFAP/AQP4 colocalizations were calculated, as well as the fractal dimension of astrocytes and vBMs viewed in tangential planes. RESULTS: Fractal dimension analysis of the GFAP-stained astrocytes revealed lower branching complexities and decreased GFAP/collagen IV colocalization for COVID-19 patients. Interestingly, vBMs showed significantly increased irregularities (fractal dimension values) compared to controls. Vessel diameters were increased in COVID-19 cases, especially for the white matter, TJ1 protein decreased its colocalization with the endothelia, and AQP4 reduced its co-expression in astrocytes. CONCLUSIONS: Our data on the irregularity of the basement membranes, loss of endothelial tight junction, reduction of the astrocyte end-feet and decrease of AQP4 suggest subtle morphological changes of the blood-brain barrier in COVID-19 brains that could be linked with indirect inflammatory signalling or hypoxia/hypercapnia.

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Recent trends in the diagnosis, treatment, and classification of collagen IV-associated kidney disease are likely to result in increasing numbers of people in adult nephrology practices who have a confirmed diagnosis of Alport syndrome. These trends include the increasing use of genetic testing in the diagnostic evaluation of people with hematuria, focal segmental glomerulosclerosis, and chronic kidney disease of unknown etiology; early treatment with inhibitors of the renin-angiotensin-aldosterone system to delay kidney failure; and application of an expanded definition of Alport syndrome based on genotype rather than phenotype. This commentary discusses these trends and their implications for the adult nephrologist.

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Alport syndrome is an inherited disorder of the kidneys that results from variants in three collagen IV genes-COL4A3, COL4A4, and COL4A5. Early diagnosis and pharmacologic intervention can delay the progression of chronic kidney disease and the onset of kidney failure in patients with Alport syndrome. This article describes the evolution of approaches to the diagnosis and early treatment of Alport syndrome.

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Collagen type IV (COL IV) is a major component of basement membranes (BM) in all organs. It serves functions related to BM organization and modulates the passage of growth factors from one tissue compartment to another. COL IV binds transforming growth factor (TGF) beta-1 and TGF beta-2 and, therefore, is a major modulator of TGF beta pro-fibrotic functions. After fibrotic corneal injury, TGF beta enters into the stroma from the tears, epithelium, endothelium and/or aqueous humor and markedly upregulates COL IV production in corneal fibroblasts in the adjacent stroma far removed from BMs. It is hypothesized this non-BM stromal COL IV binds TGF beta-1 (and likely TGF beta-2) in competition with the binding of the growth factors to TGF beta cognate receptors and serves as a negative feedback regulatory pathway to mitigate the effects of TGF beta on stromal cells, including reducing the developmental transition of corneal fibroblasts and fibrocytes into myofibroblasts. Losartan, a known TGF beta signaling inhibitor, when applied topically to the cornea after fibrotic injury, alters this COL IV-TGF beta pathway by down-regulating COL IV production by corneal fibroblasts. Non-BM COL IV produced in response to injuries in other organs, including the lung, skin, liver, kidney, and gut, may participate in similar COL IV-TGF beta pathways and have an important role in controlling TGF beta pro-fibrotic effects in these organs.

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Every organ develops fibrosis that compromises functions in response to infections, injuries, or diseases. The cornea is a relatively simple, avascular organ that offers an exceptional model to better understand the pathophysiology of the fibrosis response. Injury and defective regeneration of the epithelial basement membrane (EBM) or the endothelial Descemet's basement membrane (DBM) triggers the development of myofibroblasts from resident corneal fibroblasts and bone marrow-derived blood borne fibrocytes due to the increased entry of TGF beta-1/-2 into the stroma from the epithelium and tears or residual corneal endothelium and aqueous humor. The myofibroblasts, and disordered extracellular matrix these cells produce, persist until the source of injury is removed, the EBM and/or DBM are regenerated, or replaced surgically, resulting in decreased stromal TGF beta requisite for myofibroblast survival. A similar BM injury-related pathophysiology can underly the development of fibrosis in other organs such as skin and lung. The normal liver does not contain traditional BMs but develops sinusoidal endothelial BMs in many fibrotic diseases and models. However, normal hepatic stellate cells produce collagen type IV and perlecan that can modulate TGF beta localization and cognate receptor binding in the space of Dissé. BM-related fibrosis is deserving of more investigation in all organs.

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In vitro modeling of alveolar epithelium needs to recapitulate features of both cellular and noncellular components of the lung tissues. Herein, a method is presented to generate alveolar epithelium by using human induced pluripotent stem cells (hiPSCs) and reconstituted or artificial basement membrane (ABM). The ABM is obtained by self-assembling type IV collagen and laminin with a monolayer of crosslinked gelatin nanofibers as backbone and a patterned honeycomb microframe for handling. Alveolar organoids are obtained from hiPSCs and then dissociated into single cells. After replating the alveolar cells on the ABM and a short-period incubation under submerged and air-liquid interface culture conditions, an alveolar epithelium is achieved, showing high-level expressions of both alveolar cell-specific proteins and characteristic tight junctions. Besides, endothelial cells derived from the same hiPSCs are cocultured on the backside of the epithelium, forming an air-blood barrier. The method is generic and can potentially be applied to other types of artificial epithelium and endothelium.

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The glomerular filtration barrier (GFB) filters the blood to remove toxins while retaining high molecular weight proteins in the circulation. The glomerular basement membrane (GBM) and podocytes, highly specialized epithelial cells, are critical components of the filtration barrier. The GBM serves as a physical barrier to passage of molecules into the filtrate. Podocytes adhere to the filtrate side of the GBM and further restrict passage of high molecular weight molecules into the filtrate. Here, a 3D cell culture model of the glomerular filtration barrier to evaluate the role of the GBM and podocytes in mediating molecular diffusion is developed. GBM is isolated from mammalian kidneys to recapitulate the composition and mechanics of the in vivo basement membrane. The GFB model exhibits molecular selectivity that is comparable to the in vivo filtration barrier. The GBM alone provides a stringent barrier to passage of albumin and Ficoll. Podocytes further restrict molecular diffusion. Damage to the GBM that is typical of diabetic kidney disease is simulated using hypochlorous acid and results in increased molecular diffusion. This system can serve as a platform to evaluate the effects of GBM damage, podocyte injury, and reciprocal effects of altered podocyte-GBM interactions on kidney microvascular permeability.

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The TGF beta-1, -2 and -3 isoforms are transcribed from different genes but bind to the same receptors and signal through the same canonical and non-canonical signal transduction pathways. There are numerous regulatory mechanisms controlling the action of each isoform that include the organ-specific cells producing latent TGF beta growth factors, multiple effectors that activate the isoforms, ECM-associated SLRPs and basement membrane components that modulate the activity and localization of the isoforms, other interactive cytokine-growth factor receptor systems, such as PDGF and CTGF, TGF beta receptor expression on target cells, including myofibroblast precursors, receptor binding competition, positive and negative signal transduction effectors, and transcription and translational regulatory mechanisms. While there has long been the view that TGF beta-1and TGF beta-2 are pro-fibrotic, while TGF beta-3 is anti-fibrotic, this review suggests that view is too simplistic, at least in adult tissues, since TGF beta-3 shares far more similarities in its modulation of fibrotic gene expression with TGF beta-1 and TGF beta-2, than it does differences, and often the differences are subtle. Rather, TGF beta-3 should be seen as a fibro-modulatory partner to the other two isoforms that modulates a nuanced and better controlled response to injury. The complex interplay between the three isoforms and numerous interactive proteins, in the context of the cellular milieu, controls regenerative non-fibrotic vs. fibrotic healing in a response to injury in a particular organ, as well as the resolution of fibrosis, when that occurs.

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