Basement membrane remodeling guides cell migration and cell morphogenesis during development

Identification of a basement membrane-related gene signature for predicting prognosis, immune infiltration, and drug sensitivity in colorectal cancer

Background

Colorectal cancer (CRC) is the most common malignancy affecting the gastrointestinal tract. Extensive research indicates that basement membranes (BMs) may play a crucial role in the initiation and progression of the disease.

Methods

Data on the RNA expression patterns and clinicopathological information of patients with CRC were sourced from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. A BM-linked risk signature for the prediction of overall survival (OS) was formulated using univariate Cox regression and combined machine learning techniques. Survival outcomes, functional pathways, the tumor microenvironment (TME), and responses to both immunotherapy and chemotherapy within varying risk classifications were also investigated. The expression trends of the model genes were evaluated by reverse transcription polymerase chain reaction (RT-PCR) and the Human Protein Atlas (HPA) database.

Results

A nine-gene risk signature containing UNC5C, TINAG, TIMP1, SPOCK3, MMP1, AGRN, UNC5A, ADAMTS4, and ITGA7 was constructed for the prediction of outcomes in patients with CRC. The expression profiles of these candidate genes were verified using RT-PCR and the HPA database and were found to be consistent with the findings on differential gene expression in the TCGA dataset. The validity of the signature was confirmed using the GEO cohort. The patients were stratified into different risk groups according to differences in clinicopathological characteristics, TME features, enrichment functions, and drug sensitivities. Lastly, the prognostic nomogram model based on the risk score was found to be effective in identifying high-risk patients and predicting OS.

Conclusion

A basement membrane-related risk signature was constructed and found to be effective for predicting the prognosis of patients with CRC.

AdamTS proteases control basement membrane heterogeneity and organ shape in Drosophila

The basement membrane (BM) is an extracellular matrix that plays important roles in animal development. A spatial heterogeneity in composition and structural properties of the BM provide cells with vital cues for morphogenetic processes such as cell migration or cell polarization. Here, using the Drosophila egg chamber as a model system, we show that the BM becomes heterogeneous during development, with a reduction in Collagen IV density at the posterior pole and differences in the micropattern of aligned fiber-like structures. We identified two AdamTS matrix proteases required for the proper elongated shape of the egg chamber, yet the molecular mechanisms by which they act are different. Stall is required to establish BM heterogeneity by locally limiting Collagen IV protein density, whereas AdamTS-A alters the micropattern of fiber-like structures within the BM at the posterior pole. Our results suggest that AdamTS proteases control BM heterogeneity required for organ shape.

Profiling native pulmonary basement membrane stiffness using atomic force microscopy

Mammalian cells sense and react to the mechanics of their immediate microenvironment. Therefore, the characterization of the biomechanical properties of tissues with high spatial resolution provides valuable insights into a broad variety of developmental, homeostatic and pathological processes within living organisms. The biomechanical properties of the basement membrane (BM), an extracellular matrix (ECM) substructure measuring only ∼100-400 nm across, are, among other things, pivotal to tumor progression and metastasis formation. Although the precise assignment of the Young's modulus E of such a thin ECM substructure especially in between two cell layers is still challenging, biomechanical data of the BM can provide information of eminent diagnostic potential. Here we present a detailed protocol to quantify the elastic modulus of the BM in murine and human lung tissue, which is one of the major organs prone to metastasis. This protocol describes a streamlined workflow to determine the Young's modulus E of the BM between the endothelial and epithelial cell layers shaping the alveolar wall in lung tissues using atomic force microscopy (AFM). Our step-by-step protocol provides instructions for murine and human lung tissue extraction, inflation of these tissues with cryogenic cutting medium, freezing and cryosectioning of the tissue samples, and AFM force-map recording. In addition, it guides the reader through a semi-automatic data analysis procedure to identify the pulmonary BM and extract its Young's modulus E using an in-house tailored user-friendly AFM data analysis software, the Center for Applied Tissue Engineering and Regenerative Medicine processing toolbox, which enables automatic loading of the recorded force maps, conversion of the force versus piezo-extension curves to force versus indentation curves, calculation of Young's moduli and generation of Young's modulus maps, where the pulmonary BM can be identified using a semi-automatic spatial filtering tool. The entire protocol takes 1-2 d.

Adherens junctions as molecular regulators of emergent tissue mechanics

Tissue and organ development during embryogenesis relies on the collective and coordinated action of many cells. Recent studies have revealed that tissue material properties, including transitions between fluid and solid tissue states, are controlled in space and time to shape embryonic structures and regulate cell behaviours. Although the collective cellular flows that sculpt tissues are guided by tissue-level physical changes, these ultimately emerge from cellular-level and subcellular-level molecular mechanisms. Adherens junctions are key subcellular structures, built from clusters of classical cadherin receptors. They mediate physical interactions between cells and connect biochemical signalling to the physical characteristics of cell contacts, hence playing a fundamental role in tissue morphogenesis. In this Review, we take advantage of the results of recent, quantitative measurements of tissue mechanics to relate the molecular and cellular characteristics of adherens junctions, including adhesion strength, tension and dynamics, to the emergent physical state of embryonic tissues. We focus on systems in which cell-cell interactions are the primary contributor to morphogenesis, without significant contribution from cell-matrix interactions. We suggest that emergent tissue mechanics is an important direction for future research, bridging cell biology, developmental biology and mechanobiology to provide a holistic understanding of morphogenesis in health and disease.

Dual topologies of myotomal collagen XV and Tenascin C act in concert to guide and shape developing motor axons

During development, motor axons are guided toward muscle target by various extrinsic cues including extracellular matrix (ECM) proteins whose identities and cellular source remain poorly characterized. Here, using single-cell RNAseq of sorted GFP+ cells from smyhc1:gfp-injected zebrafish embryos, we unravel the slow muscle progenitors (SMP) pseudotemporal trajectory at the single-cell level and show that differentiating SMPs are a major source of ECM proteins. The SMP core-matrisome was characterized and computationally predicted to form a basement membrane-like structure tailored for motor axon guidance, including basement membrane-associated ECM proteins, as collagen XV-B, one of the earliest core-matrisome gene transcribed in differentiating SMPs and the glycoprotein Tenascin C. To investigate how contact-mediated guidance cues are organized along the motor path to exert their function in vivo, we used microscopy-based methods to analyze and quantify motor axon navigation in tnc and col15a1b knock-out fish. We show that motor axon shape and growth rely on the timely expression of the attractive cue Collagen XV-B that locally provides axons with a permissive soft microenvironment and separately organizes the repulsive cue Tenascin C into a unique functional dual topology. Importantly, bioprinted micropatterns that mimic this in vivo ECM topology were sufficient to drive directional motor axon growth. Our study offers evidence that not only the composition of ECM cues but their topology critically influences motor axon navigation in vertebrates with potential applications in regenerative medicine for peripheral nerve injury as regenerating nerves follow their original path.

Basement membrane diversification relies on two competitive secretory routes defined by Rab10 and Rab8 and modulated by dystrophin and the exocyst complex

The basement membrane (BM) is an essential structural element of tissues, and its diversification participates in organ morphogenesis. However, the traffic routes associated with BM formation and the mechanistic modulations explaining its diversification are still poorly understood. Drosophila melanogaster follicular epithelium relies on a BM composed of oriented BM fibrils and a more homogenous matrix. Here, we determined the specific molecular identity and cell exit sites of BM protein secretory routes. First, we found that Rab10 and Rab8 define two parallel routes for BM protein secretion. When both routes were abolished, BM production was fully blocked; however, genetic interactions revealed that these two routes competed. Rab10 promoted lateral and planar-polarized secretion, whereas Rab8 promoted basal secretion, leading to the formation of BM fibrils and homogenous BM, respectively. We also found that the dystrophin-associated protein complex (DAPC) and Rab10 were both present in a planar-polarized tubular compartment containing BM proteins. DAPC was essential for fibril formation and sufficient to reorient secretion towards the Rab10 route. Moreover, we identified a dual function for the exocyst complex in this context. First, the Exo70 subunit directly interacted with dystrophin to limit its planar polarization. Second, the exocyst complex was also required for the Rab8 route. Altogether, these results highlight important mechanistic aspects of BM protein secretion and illustrate how BM diversity can emerge from the spatial control of distinct traffic routes.

The C. elegans anchor cell: A model to elucidate mechanisms underlying invasion through basement membrane

Cell invasion through basement membrane barriers is crucial during many developmental processes and in immune surveillance. Dysregulation of invasion also drives the pathology of numerous human diseases, such as metastasis and inflammatory disorders. Cell invasion involves dynamic interactions between the invading cell, basement membrane, and neighboring tissues. Owing to this complexity, cell invasion is challenging to study in vivo, which has hampered the understanding of mechanisms controlling invasion. Caenorhabditis elegans anchor cell invasion is a powerful in vivo model where subcellular imaging of cell-basement membrane interactions can be combined with genetic, genomic, and single-cell molecular perturbation studies. In this review, we outline insights gained by studying anchor cell invasion, which span transcriptional networks, translational regulation, secretory apparatus expansion, dynamic and adaptable protrusions that breach and clear basement membrane, and a complex, localized metabolic network that fuels invasion. Together, investigation of anchor cell invasion is building a comprehensive understanding of the mechanisms that underlie invasion, which we expect will ultimately facilitate better therapeutic strategies to control cell invasive activity in human disease.

An mTurq2-Col4a1 mouse model allows for live visualization of mammalian basement membrane development

Basement membranes (BMs) are specialized sheets of extracellular matrix that underlie epithelial and endothelial tissues. BMs regulate the traffic of cells and molecules between compartments, and participate in signaling, cell migration, and organogenesis. The dynamics of mammalian BMs, however, are poorly understood, largely due to a lack of models in which core BM components are endogenously labeled. Here, we describe the mTurquoise2-Col4a1 mouse in which we fluorescently tag collagen IV, the main component of BMs. Using an innovative planar-sagittal live imaging technique to visualize the BM of developing skin, we directly observe BM deformation during hair follicle budding and basal progenitor cell divisions. The BM's inherent pliability enables dividing cells to remain attached to and deform the BM, rather than lose adhesion as generally thought. Using FRAP, we show BM collagen IV is extremely stable, even during periods of rapid epidermal growth. These findings demonstrate the utility of the mTurq2-Col4a1 mouse to shed new light on mammalian BM developmental dynamics.

Identification of basement membrane-related signatures for estimating prognosis, immune infiltration landscape and drug candidates in pancreatic adenocarcinoma

Background: Pancreatic adenocarcinoma (PAAD) is a frequent digestive system cancer, which has high mortality and bad outcome. However, the role of basement membrane (BM)-related gene in assessing patient's outcome, microenvironment and treatment response remain unclear. Methods: Basement membrane (BM)-associated genes were detected by univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses using data from the TCGA databases. A risk score system was constructed to distinguish patients in the high- and low-risk groups. Prognostic gene distribution in various immune cell forms was explored through scRNA-seq. Immune cell infiltration was assessed using CIBERSORT and ESTIMATE. The IC50 of common chemotherapeutic drugs and useful molecule compounds were evaluated. The mRNA and protein expression of important signatures were validated utilizing GEPIA and HPA databases. Results: Compared to low risk PAAD patients, PAAD patients with high risk showed a significant much worse overall survival (OS). Risk score of BM-associated genes could estimate patient outcome well, and areas under the curve (AUC) of receiver operating characteristic (ROC) survival curve were 0.76, 0.85, and 0.85 at 1-, 3-, and 5-year. Clinical impact curve (CIC) curve demonstrated the clinical importance of risk score. scRNA-seq revealed that BM-related genes were mainly distributed in malignant cells. Significant variations existed in the immune microenvironment, immune checkpoint expression and chemotherapy response between the studied groups. Furthermore, the mRNA expression levels of FAM83A, LY6D, MET, MUC16, MYEOV, and WNT7A were elevated in PAAD tissues, while the protein expression patterns of LY6D, MET, MUC16, and WNT7A were higher in tumor sample. RO-90-7501, Scriptaid, TG-101348, XMD-892, and XMD-1150 may be valuable small molecule drugs to treat PAAD. Conclusions: In conclusion, we develop a novel BM-related gene signature provide new insights and targets for the diagnosis, outcome estimation, candidate drugs and therapy management of PAAD patients.

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.

Bioinformatics-based analysis of the roles of basement membrane-related gene AGRN in systemic lupus erythematosus and pan-cancer development

Introduction

Systemic lupus erythematosus (SLE) is an autoimmune disease involving many systems and organs, and individuals with SLE exhibit unique cancer risk characteristics. The significance of the basement membrane (BM) in the occurrence and progression of human autoimmune diseases and tumors has been established through research. However, the roles of BM-related genes and their protein expression mechanisms in the pathogenesis of SLE and pan-cancer development has not been elucidated.

Methods

In this study, we applied bioinformatics methods to perform differential expression analysis of BM-related genes in datasets from SLE patients. We utilized LASSO logistic regression, SVM-RFE, and RandomForest to screen for feature genes and construct a diagnosis model for SLE. In order to attain a comprehensive comprehension of the biological functionalities of the feature genes, we conducted GSEA analysis, ROC analysis, and computed levels of immune cell infiltration. Finally, we sourced pan-cancer expression profiles from the TCGA and GTEx databases and performed pan-cancer analysis.

Results

We screened six feature genes (AGRN, PHF13, SPOCK2, TGFBI, COL4A3, and COLQ) to construct an SLE diagnostic model. Immune infiltration analysis showed a significant correlation between AGRN and immune cell functions such as parainflammation and type I IFN response. After further gene expression validation, we finally selected AGRN for pan-cancer analysis. The results showed that AGRN's expression level varied according to distinct tumor types and was closely correlated with some tumor patients' prognosis, immune cell infiltration, and other indicators.

Discussion

In conclusion, BM-related genes play a pivotal role in the pathogenesis of SLE, and AGRN shows immense promise as a target in SLE and the progression of multiple tumors.

A Window into Mammalian Basement Membrane Development: Insights from the mTurq2-Col4a1 Mouse Model

Basement membranes (BMs) are specialized sheets of extracellular matrix that underlie epithelial and endothelial tissues. BMs regulate traffic of cells and molecules between compartments, and participate in signaling, cell migration and organogenesis. The dynamics of mammalian BMs, however, are poorly understood, largely due to a lack of models in which core BM components are endogenously labelled. Here, we describe the mTurquoise2-Col4a1 mouse, in which we fluorescently tag collagen IV, the main component of BMs. Using an innovative Planar-Sagittal live imaging technique to visualize the BM of developing skin, we directly observe BM deformation during hair follicle budding and basal progenitor cell divisions. The BM's inherent pliability enables dividing cells to remain attached to and deform the BM, rather than lose adhesion as generally thought. Using FRAP, we show BM collagen IV is extremely stable, even during periods of rapid epidermal growth. These findings demonstrate the utility of the mTurq2-Col4a1 mouse to shed new light on mammalian BM developmental dynamics.

Basement membrane dynamics and mechanics in tissue morphogenesis

The basement membrane (BM) is a thin, planar-organized extracellular matrix that underlies epithelia and surrounds most organs. During development, the BM is highly dynamic and simultaneously provides mechanical properties that stabilize tissue structure and shape organs. Moreover, it is important for cell polarity, cell migration, and cell signaling. Thereby BM diverges regarding molecular composition, structure, and modes of assembly. Different BM organization leads to various physical features. The mechanisms that regulate BM composition and structure and how this affects mechanical properties are not fully understood. Recent studies show that precise control of BM deposition or degradation can result in BMs with locally different protein densities, compositions, thicknesses, or polarization. Such heterogeneous matrices can induce temporospatial force anisotropy and enable tissue sculpting. In this Review, I address recent findings that provide new perspectives on the role of the BM in morphogenesis.

Combining WGCNA and machine learning to construct basement membrane-related gene index helps to predict the prognosis and tumor microenvironment of HCC patients and verifies the carcinogenesis of key gene CTSA

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.

The Caenorhabditis elegans anchor cell transcriptome: ribosome biogenesis drives cell invasion through basement membrane

Cell invasion through basement membrane (BM) barriers is important in development, immune function and cancer progression. As invasion through BM is often stochastic, capturing gene expression profiles of actively invading cells in vivo remains elusive. Using the stereotyped timing of Caenorhabditis elegans anchor cell (AC) invasion, we generated an AC transcriptome during BM breaching. Through a focused RNAi screen of transcriptionally enriched genes, we identified new invasion regulators, including translationally controlled tumor protein (TCTP). We also discovered gene enrichment of ribosomal proteins. AC-specific RNAi, endogenous ribosome labeling and ribosome biogenesis analysis revealed that a burst of ribosome production occurs shortly after AC specification, which drives the translation of proteins mediating BM removal. Ribosomes also enrich near the AC endoplasmic reticulum (ER) Sec61 translocon and the endomembrane system expands before invasion. We show that AC invasion is sensitive to ER stress, indicating a heightened requirement for translation of ER-trafficked proteins. These studies reveal key roles for ribosome biogenesis and endomembrane expansion in cell invasion through BM and establish the AC transcriptome as a resource to identify mechanisms underlying BM transmigration.

Development of a basement membrane gene signature and identification of the potential candidate therapeutic targets for pancreatic cancer

Background

Pancreatic cancer is a deadly cancer with a poor prognosis. In light of mounting evidence that basement membrane genes (BMGs) play a role in the development of cancer, we sought to examine the prognostic importance and role of BMGs in pancreatic ductal adenocarcinoma (PDAC) patients.

Methods

BMGs were obtained from previous top research studies. The clinical and messenger ribonucleic acid expression data were retrieved from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data sets, respectively. Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used for the PDAC risk modeling and gene identification. The Kaplan-Meier method was used to compare outcomes between the low- and high-risk groups. Finally, we analyzed small-molecule drugs that could be used to target BMGs for treatment using the Enrichr data set and validated the function of the tubulointerstitial nephritis antigen (TINAG) in pancreatic cancer.

Results

We successfully constructed and validated a 7 BMG-based model to predict PDAC patient outcomes. Additionally, we discovered that 7 BMG-based model was an independent predictive factor for PDAC. According to our functional analysis, the majority of the signaling pathways enriched in BMGs were those connected to malignancy. Immune cell infiltration and immunological checkpoints were also linked to the BMG-based model. Further, we identified 5 small-molecule drugs that may be useful in treating PDAC patients. We also found that TINAG promoted cell proliferation in pancreatic cancer.

Conclusions

Our study extended understandings of how BMGs work in PDAC. We identified a credible predictive biomarker for PDAC patients' survival.

Specialized cells that sense tissue mechanics to regulate Drosophila morphogenesis

Shaping of developing organs requires dynamic regulation of force and resistance to achieve precise outcomes, but how organs monitor tissue mechanical properties is poorly understood. We show that in developing Drosophila follicles (egg chambers), a single pair of cells performs such monitoring to drive organ shaping. These anterior polar cells secrete a matrix metalloproteinase (MMP) that specifies the appropriate degree of tissue elongation, rather than hyper- or hypo-elongated organs. MMP production is negatively regulated by basement membrane (BM) mechanical properties, which are sensed through focal adhesion signaling and autonomous contractile activity; MMP then reciprocally regulates BM remodeling, particularly at the anterior region. Changing BM properties at remote locations alone is sufficient to induce a remodeling response in polar cells. We propose that this small group of cells senses both local and distant stiffness cues to produce factors that pattern the organ's BM mechanics, ensuring proper tissue shape and reproductive success.

A novel risk model based on the correlation between the expression of basement membrane genes and immune infiltration to predict the invasiveness of pituitary adenomas

Objective

Invasive pituitary adenomas (IPAs) are common tumors of the nervous system tumors for which invasive growth can lead to difficult total resection and a high recurrence rate. The basement membrane (BM) is a special type of extracellular matrix and plays an important role in the invasion of pituitary adenomas (PAs). The aim of this study was to develop a risk model for predicting the invasiveness of PAs by analyzing the correlation between the expression of BM genes and immune infiltration.

Methods

Four datasets, featuring samples IPAs and non-invasive pituitary adenomas (NIPAs), were obtained from the Gene Expression Omnibus database (GEO). R software was then used to identify differentially expressed genes (DEGs) and analyze their functional enrichment. Protein-protein interaction (PPI) network was used to screen BM genes, which were analyzed for immune infiltration; this led to the generation of a risk model based on the correlation between the expression of BM genes and immunity. A calibration curve and receiver operating characteristic (ROC) curve were used to evaluate and validate the model. Subsequently, the differential expression levels of BM genes between IPA and NIPA samples collected in surgery were verified by Quantitative Polymerase Chain Reaction (qPCR) and the prediction model was further evaluated. Finally, based on our analysis, we recommend potential drug targets for the treatment of IPAs.

Results

The merged dataset identified 248 DEGs that were mainly enriching in signal transduction, the extracellular matrix and channel activity. The PPI network identified 11 BM genes from the DEGs: SPARCL1, GPC3, LAMA1, SDC4, GPC4, ADAMTS8, LAMA2, LAMC3, SMOC1, LUM and THBS2. Based on the complex correlation between these 11 genes and immune infiltration, a risk model was established to predict PAs invasiveness. Calibration curve and ROC curve analysis (area under the curve [AUC]: 0.7886194) confirmed the good predictive ability of the model. The consistency between the qPCR results and the bioinformatics results confirmed the reliability of data mining.

Conclusion

Using a variety of bioinformatics methods, we developed a novel risk model to predict the probability of PAs invasion based on the correlation between 11 BM genes and immune infiltration. These findings may facilitate closer surveillance and early diagnosis to prevent or treat IPAs in patients and improve the clinical awareness of patients at high risk of IPAs.

Orientational cell adhesions (OCAs) for tissue morphogenesis

Distinct tissue architectures arise when cells are organized in specific orientations relative to neighboring cells. These orientational intercellular relationships are established and maintained by cell adhesions. We propose the concept of 'orientational cell adhesions' (OCAs) to couple cell orientations with cell adhesions, thus offering a new perspective to study tissue morphogenesis.

The basement membrane in epidermal polarity, stemness, and regeneration

The epidermis is a specialized epithelium that constitutes the outermost layer of the skin, and it provides a protective barrier against environmental assaults. Primarily consisting of multilayered keratinocytes, the epidermis is continuously renewed by proliferation of stem cells and the differentiation of their progeny, which undergo terminal differentiation as they leave the basal layer and move upward toward the surface, where they die and slough off. Basal keratinocytes rest on a basement membrane at the dermal-epidermal junction that is composed of specific extracellular matrix proteins organized into interactive and mechanically supportive networks. Firm attachment of basal keratinocytes, and their dynamic regulation via focal adhesions and hemidesmosomes, is essential for maintaining major skin processes, such as self-renewal, barrier function, and resistance to physical and chemical stresses. The adhesive integrin receptors expressed by epidermal cells serve structural, signaling, and mechanosensory roles that are critical for epidermal cell anchorage and tissue homeostasis. More specifically, the basement membrane components play key roles in preserving the stem cell pool, and establishing cell polarity cues enabling asymmetric cell divisions, which result in the transition from a proliferative basal cell layer to suprabasal cells committed to terminal differentiation. Finally, through a well-regulated sequence of synthesis and remodeling, the components of the dermal-epidermal junction play an essential role in regeneration of the epidermis during skin healing. Here too, they provide biological and mechanical signals that are essential to the restoration of barrier function.

A prognostic and therapeutic hallmark developed by the integrated profile of basement membrane and immune infiltrative landscape in lung adenocarcinoma

Basement membranes (BMs) are specialised extracellular matrices that maintain cellular integrity and resist the breaching of carcinoma cells for metastases while regulating tumour immunity. The tumour immune microenvironment (TME) is essential for tumour growth and the response to and benefits from immunotherapy. In this study, the BM score and TME score were constructed based on the expression signatures of BM-related genes and the presence of immune cells in lung adenocarcinoma (LUAD), respectively. Subsequently, the BM-TME classifier was developed with the combination of BM score and TME score for accurate prognostic prediction. Further, Kaplan-Meier survival estimation, univariate Cox regression analysis and receiver operating characteristic curves were used to cross-validate and elucidate the prognostic prediction value of the BM-TME classifier in several cohorts. Findings from functional annotation analysis suggested that the potential molecular regulatory mechanisms of the BM-TME classifier were closely related to the cell cycle, mitosis and DNA replication pathways. Additionally, the guiding value of the treatment strategy of the BM-TME classifier for LUAD was determined. Future clinical disease management may benefit from the findings of our research.

Expression of basement membrane genes and their prognostic significance in clear cell renal cell carcinoma patients

Background

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with limited treatment options. A recent study confirmed the involvement of basement membrane (BM) genes in the progression of many cancers. Therefore, we studied the role and prognostic significance of BM genes in ccRCC.

Methods

Co-expression analysis of ccRCC-related information deposited in The Cancer Genome Atlas database and a BM geneset from a recent study was conducted. The differentially expressed BM genes were validated using quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Least absolute shrinkage and selection operator regression and univariate Cox regression analyses were performed to identify a BM gene signature with prognostic significance for ccRCC. Multivariate Cox regression, time-dependent receiver operating characteristic, Kaplan–Meier, and nomogram analyses were implemented to appraise the prognostic ability of the signature and the findings were further verified using a Gene Expression Omnibus dataset. Additionally, immune cell infiltration and and pathway enrichment analyses were performed using ImmuCellAI and Gene Set Enrichment Analysis (GSEA), respectively. Finally, the DSIGDB dataset was used to screen small-molecule therapeutic drugs that may be useful in treating ccRCC patients.

Results

We identified 108 BM genes exhibiting different expression levels compared to that in normal kidney tissues, among which 32 genes had prognostic values. The qRT-PCR analyses confirmed that the expression patterns of four of the ten selected genes were the same as the predicted ones. Additionally, we successfully established and validated a ccRCC patient prediction model based on 16 BM genes and observed that the model function is an independent predictor. GSEA revealed that differentially expressed BM genes mainly displayed significant enrichment of tumor and metabolic signaling cascades. The BM gene signature was also associated with immune cell infiltration and checkpoints. Eight small-molecule drugs may have therapeutic effects on ccRCC patients.

Conclusion

This study explored the function of BM genes in ccRCC for the first time. Reliable prognostic biomarkers that affect the survival of ccRCC patients were determined, and a BM gene-based prognostic model was established.

Basement-Membrane-Related Gene Signature Predicts Prognosis in WHO Grade II/III Gliomas

Gliomas that are classified as grade II or grade III lesions by the World Health Organization (WHO) are highly aggressive, and some may develop into glioblastomas within a short period, thus portending the conferral of a poor prognosis for patients. Previous studies have implicated basement membrane (BM)-related genes in glioma development. In this study, we constructed a prognostic model for WHO grade II/III gliomas in accordance with the risk scores of BM-related genes. Differentially expressed genes (DEGs) in the glioma samples relative to normal samples were screened from the GEO database, and five prognostically relevant BM-related genes, including NELL2, UNC5A, TNC, CSPG4, and SMOC1, were selected using Cox regression analyses for the risk score model. The median risk score was calculated, based on which high- and low-risk groups of patients were generated. The clinical information, pathological information, and risk group were combined to establish a prognostic nomogram. Both the nomogram and risk score model performed well in the independent CGGA cohort. Gene set enrichment analysis (GSEA) and immune profile, drug sensitivity, and tumor mutation burden (TMB) analyses were performed in the two risk groups. A significant enrichment of 'Autophagy-other', 'Collecting duct acid secretion', 'Glycosphingolipid biosynthesis-lacto and neolacto series', 'Valine, leucine, and isoleucine degradation', 'Vibrio cholerae infection', and other pathways were observed for patients with high risk. In addition, higher proportions of monocytes and resting CD4 memory T cells were observed in the low- and high-risk groups, respectively. In conclusion, the BM-related gene risk score model can guide the clinical management of WHO grade II and III gliomas.

A newly defined basement membrane-related gene signature for the prognosis of clear-cell renal cell carcinoma

Background: Basement membranes (BMs) are associated with cell polarity, differentiation, migration, and survival. Previous studies have shown that BMs play a key role in the progression of cancer, and thus could serve as potential targets for inhibiting the development of cancer. However, the association between basement membrane-related genes (BMRGs) and clear cell renal cell carcinoma (ccRCC) remains unclear. To address that gap, we constructed a novel risk signature utilizing BMRGs to explore the relationship between ccRCC and BMs.

Methods: We gathered transcriptome and clinical data from The Cancer Genome Atlas (TCGA) and randomly separated the data into training and test sets to look for new potential biomarkers and create a predictive signature of BMRGs for ccRCC. We applied univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses to establish the model. The risk signature was further verified and evaluated through principal component analysis (PCA), the Kaplan-Meier technique, and time-dependent receiver operating characteristics (ROC). A nomogram was constructed to predict the overall survival (OS). The possible biological pathways were investigated through functional enrichment analysis. In this study, we also determined tumor mutation burden (TMB) and performed immunological analysis and immunotherapeutic drug analysis between the high- and low-risk groups.

Results: We identified 33 differentially expressed genes and constructed a risk model of eight BMRGs, including COL4A4, FREM1, CSPG4, COL4A5, ITGB6, ADAMTS14, MMP17, and THBS4. The PCA analysis showed that the signature could distinguish the high- and low-risk groups well. The K-M and ROC analysis demonstrated that the model could predict the prognosis well from the areas under the curves (AUCs), which was 0.731. Moreover, the nomogram showed good predictability. Univariate and multivariate Cox regression analysis validated that the model results supported the hypothesis that BMRGs were independent risk factors for ccRCC. Furthermore, immune cell infiltration, immunological checkpoints, TMB, and the half-inhibitory concentration varied considerably between high- and low-risk groups.

Conclusion: Employing eight BMRGs to construct a risk model as a prognostic indicator of ccRCC could provide us with a potential progression trajectory as well as predictions of therapeutic response.

A basement membrane discovery pipeline uncovers network complexity, regulators, and human disease associations

Basement membranes (BMs) are ubiquitous extracellular matrices whose composition remains elusive, limiting our understanding of BM regulation and function. By developing a bioinformatic and in vivo discovery pipeline, we define a network of 222 human proteins and their animal orthologs localized to BMs. Network analysis and screening in C. elegans and zebrafish uncovered BM regulators, including ADAMTS, ROBO, and TGFβ. More than 100 BM network genes associate with human phenotypes, and by screening 63,039 genomes from families with rare disorders, we found loss-of-function variants in LAMA5, MPZL2, and MATN2 and show that they regulate BM composition and function. This cross-disciplinary study establishes the immense complexity of BMs and their impact on in human health.