Two-phase mechanism in the treatment of corneal stromal fibrosis with topical losartan

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.

Corneal stromal localization of TGF beta isoforms in spontaneous persistent epithelial defects after PRK in rabbits

The purpose of this study was to evaluate transforming growth factor beta (TGFβ) 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 TGFβ3, myofibroblast marker alpha-smooth muscle actin (α-SMA) and mesenchymal marker vimentin. One cornea had sufficient remaining tissue for triplex IHC for TGFβ1, TGFβ2, or TGFβ3 (each with α-SMA and vimentin) using isoform-specific antibodies. All three TGFβ isoforms were detected in the subepithelial stroma at and surrounding the PED. Some of each TGFβ isoform co-localized with α-SMA of myofibroblasts, which could be TGFβ isoform autocrine production by myofibroblasts or TGFβ-1, -2, and -3 binding to these myofibroblasts.

Systematic identification of key basement membrane related genes as potential new biomarkers in Alzheimer's disease

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 β2 (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.

Potential molecular targets and drugs for basement membranes-related intervertebral disk degeneration through bioinformatics analysis and molecular docking

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-β 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.

Comprehensive analysis of basement membrane and immune checkpoint related lncRNA and its prognostic value in hepatocellular carcinoma via machine learning

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.

Identification of basement membrane-related biomarkers associated with the diagnosis of osteoarthritis based on machine learning

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.

What the Adult Nephrologist Should Know About Alport Syndrome

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.

Corneal fibroblast collagen type IV negative feedback modulation of TGF beta: A fibrosis modulating system likely active in other organs

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.

TGF beta -1, -2 and -3 in the modulation of fibrosis in the cornea and other organs

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.

Convective influx/glymphatic system: tracers injected into the CSF enter and leave the brain along separate periarterial basement membrane pathways

Tracers injected into CSF pass into the brain alongside arteries and out again. This has been recently termed the “glymphatic system” that proposes tracers enter the brain along periarterial “spaces” and leave the brain along the walls of veins. The object of the present study is to test the hypothesis that: (1) tracers from the CSF enter the cerebral cortex along pial-glial basement membranes as there are no perivascular “spaces” around cortical arteries, (2) tracers leave the brain along smooth muscle cell basement membranes that form the Intramural Peri-Arterial Drainage (IPAD) pathways for the elimination of interstitial fluid and solutes from the brain. 2 μL of 100 μM soluble, fluorescent fixable amyloid β (Aβ) were injected into the CSF of the cisterna magna of 6–10 and 24–30 month-old male mice and their brains were examined 5 and 30 min later. At 5 min, immunocytochemistry and confocal microscopy revealed Aβ on the outer aspects of cortical arteries colocalized with α-2 laminin in the pial-glial basement membranes. At 30 min, Aβ was colocalised with collagen IV in smooth muscle cell basement membranes in the walls of cortical arteries corresponding to the IPAD pathways. No evidence for drainage along the walls of veins was found. Measurements of the depth of penetration of tracer were taken from 11 regions of the brain. Maximum depths of penetration of tracer into the brain were achieved in the pons and caudoputamen. Conclusions drawn from the present study are that tracers injected into the CSF enter and leave the brain along separate periarterial basement membrane pathways. The exit route is along IPAD pathways in which Aβ accumulates in cerebral amyloid angiopathy (CAA) in Alzheimer’s disease. Results from this study suggest that CSF may be a suitable route for delivery of therapies for neurological diseases, including CAA.

Molecular characterization of perivascular drainage pathways in the murine brain

Perivascular compartments surrounding central nervous system (CNS) vessels have been proposed to serve key roles in facilitating cerebrospinal fluid flow into the brain, CNS waste transfer, and immune cell trafficking. Traditionally, these compartments were identified by electron microscopy with limited molecular characterization. Using cellular markers and knowledge on cellular sources of basement membrane laminins, we here describe molecularly distinct compartments surrounding different vessel types and provide a comprehensive characterization of the arachnoid and pial compartments and their connection to CNS vessels and perivascular pathways. We show that differential expression of plectin, E-cadherin and laminins α1, α2, and α5 distinguishes pial and arachnoid layers at the brain surface, while endothelial and smooth muscle laminins α4 and α5 and smooth muscle actin differentiate between arterioles and venules. Tracer studies reveal that interconnected perivascular compartments exist from arterioles through to veins, potentially providing a route for fluid flow as well as the transport of large and small molecules.

Vascular basement membranes as pathways for the passage of fluid into and out of the brain

In the absence of conventional lymphatics, drainage of interstitial fluid and solutes from the brain parenchyma to cervical lymph nodes is along basement membranes in the walls of cerebral capillaries and tunica media of arteries. Perivascular pathways are also involved in the entry of CSF into the brain by the convective influx/glymphatic system. The objective of this study is to differentiate the cerebral vascular basement membrane pathways by which fluid passes out of the brain from the pathway by which CSF enters the brain. Experiment 1: 0.5 µl of soluble biotinylated or fluorescent Aβ, or 1 µl 15 nm gold nanoparticles was injected into the mouse hippocampus and their distributions determined at 5 min by transmission electron microscopy. Aβ was distributed within the extracellular spaces of the hippocampus and within basement membranes of capillaries and tunica media of arteries. Nanoparticles did not enter capillary basement membranes from the extracellular spaces. Experiment 2: 2 µl of 15 nm nanoparticles were injected into mouse CSF. Within 5min, groups of nanoparticles were present in the pial-glial basement membrane on the outer aspect of cortical arteries between the investing layer of pia mater and the glia limitans. The results of this study and previous research suggest that cerebral vascular basement membranes form the pathways by which fluid passes into and out of the brain but that different basement membrane layers are involved. The significance of these findings for neuroimmunology, Alzheimer’s disease, drug delivery to the brain and the concept of the Virchow–Robin space are discussed.

Deposition of amyloid β in the walls of human leptomeningeal arteries in relation to perivascular drainage pathways in cerebral amyloid angiopathy

Deposition of amyloid β (Aβ) in the walls of cerebral arteries as cerebral amyloid angiopathy (CAA) suggests an age-related failure of perivascular drainage of soluble Aβ from the brain. As CAA is associated with Alzheimer's disease and with intracerebral haemorrhage, the present study determines the unique sequence of changes that occur as Aβ accumulates in artery walls. Paraffin sections of post-mortem human occipital cortex were immunostained for collagen IV, fibronectin, nidogen 2, Aβ and smooth muscle actin and the immunostaining was analysed using Image J and confocal microscopy. Results showed that nidogen 2 (entactin) increases with age and decreases in CAA. Confocal microscopy revealed stages in the progression of CAA: Aβ initially deposits in basement membranes in the tunica media, replaces first the smooth muscle cells and then the connective tissue elements to leave artery walls completely or focally replaced by Aβ. The pattern of development of CAA in the human brain suggests expansion of Aβ from the basement membranes to progressively replace all tissue elements in the artery wall. Establishing this full picture of the development of CAA is pivotal in understanding the clinical presentation of CAA and for developing therapies to prevent accumulation of Aβ in artery walls. This article is part of a Special Issue entitled: Vascular Contributions to Cognitive Impairment and Dementia edited by M. Paul Murphy, Roderick A. Corriveau and Donna M. Wilcock.

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Lymphatic drainage of the brain is along basement membranes in the walls of arteries.

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Perivascular lymphatic drainage fails with age and arteriosclerosis.

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Aβ deposits in the perivascular drainage pathways of leptomeningeal arteries as CAA.

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As CAA progresses, Aβ replaces all elements of the ageing artery wall.

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Facilitation of perivascular drainage may prevent CAA and delay Alzheimer's disease.