Basement membrane stiffness determines metastases formation

Temporally resolved proteomics identifies nidogen-2 as a cotarget in pancreatic cancer that modulates fibrosis and therapy response

Pancreatic ductal adenocarcinoma (PDAC) is characterized by increasing fibrosis, which can enhance tumor progression and spread. Here, we undertook an unbiased temporal assessment of the matrisome of the highly metastatic KPC (Pdx1-Cre, LSL-KrasG12D/+, LSL-Trp53R172H/+) and poorly metastatic KPflC (Pdx1-Cre, LSL-KrasG12D/+, Trp53fl/+) genetically engineered mouse models of pancreatic cancer using mass spectrometry proteomics. Our assessment at early-, mid-, and late-stage disease reveals an increased abundance of nidogen-2 (NID2) in the KPC model compared to KPflC, with further validation showing that NID2 is primarily expressed by cancer-associated fibroblasts (CAFs). Using biomechanical assessments, second harmonic generation imaging, and birefringence analysis, we show that NID2 reduction by CRISPR interference (CRISPRi) in CAFs reduces stiffness and matrix remodeling in three-dimensional models, leading to impaired cancer cell invasion. Intravital imaging revealed improved vascular patency in live NID2-depleted tumors, with enhanced response to gemcitabine/Abraxane. In orthotopic models, NID2 CRISPRi tumors had less liver metastasis and increased survival, highlighting NID2 as a potential PDAC cotarget.

Basement membrane-related MMP14 predicts poor prognosis and response to immunotherapy in bladder cancer

BACKGROUND

Basement membrane (BM) is an important component of the extracellular matrix, which plays an important role in the growth and metastasis of tumor cells. However, few biomarkers based on BM have been developed for prognostic assessment and prediction of immunotherapy in bladder cancer (BLCA).

METHODS

In this study, we used the BLCA public database to explore the relationship between BM-related genes (BMRGs) and prognosis. A novel molecular typing of BLCA was performed using consensus clustering. LASSO regression was used to construct a signature based on BMRGs, and its relationship with prognosis was explored using survival analysis. The pivotal BMRGs were further analyzed to assess its clinical characteristics and immune landscape. Finally, immunohistochemistry was used to detect the expression of the hub gene in BLCA patients who underwent surgery or received immune checkpoint inhibitor (ICI) immunotherapy in our hospital.

RESULTS

We comprehensively analyzed the relationship between BMRGs and BLCA, and established a prognostic-related signature which was an independent influence on the prognostic prediction of BLCA. We further screened and validated the pivotal gene-MMP14 in public database. In addition, we found that MMP14 expression in muscle invasive bladder cancer (MIBC) was significantly higher and high MMP14 expression had a poorer response to ICI treatment in our cohort.

CONCLUSIONS

Our findings highlighted the satisfactory value of BMRGs and suggested that MMP14 may be a potential biomarker in predicting prognosis and response to immunotherapy in BLCA.

Glyoxal-methyl-ethylene sulfonic acid fixative enhances the fixation of cytoskeletal structures for Förster resonance energy transfer measurements

Förster resonance energy transfer (FRET) serves as a tool for measuring protein-protein interactions using various sensor molecules. The tension sensor module relies on FRET technology. In our study, this module was inserted within the actinin molecule to measure the surface tension of the cells. Given that the decay curve of FRET efficiency correlates with surface tension increase, precise and accurate efficiency measurement becomes crucial. Among the methods of FRET measurements, FRET efficiency remains the most accurate if sample fixation is successful. However, when cells were fixed with 4% paraformaldehyde (PFA), the actinin-FRET sensor diffused across the cytoplasm; this prompted us to explore fixation method enhancements. Glyoxal fixative has been reported to improve cytoskeletal morphologies compared to PFA. However, it was not known whether glyoxal fits FRET measurements. Glyoxal necessitates an acetic acid solution for fixation; however, acidic conditions could compromise fluorescence stability. We observed that the pH working range of glyoxal fixative aligns closely with MES (methyl-ethylene sulfonic acid) Good's buffer. Initially, we switched the acidic solution for MES buffer and optimized the fixation procedure for in vitro and in vivo FRET imaging. By comparing FRET measurements on hydrogels with known stiffness to tumor nodules in mouse lung, we estimated in vivo stiffness. The estimated stiffness of cancerous tissue was harder than the reported stiffness of smooth muscle. This discovery shed lights on how cancer cells perceive environmental stiffness during metastasis.

Boosting antitumor efficacy of nanoparticles by modulating tumor mechanical microenvironment

Nanoparticles have shown great potential for tumor targeting delivery via enhanced permeability and retention effect. However, the tumor mechanical microenvironment, characterized by dense extracellular matrix (ECM), high tumor stiffness and solid stress, leads to only 0.7% of administered dose accumulating in solid tumors and even fewer (∼0.0014%) reaching tumor cells, limiting the therapeutic efficacy of nanoparticles. Furthermore, the tumor mechanical microenvironment can regulate tumor cell stemness, promote tumor invasion, metastasis and reduce treatment efficacy. In this review, methods detecting the mechanical are introduced. Strategies for modulating the mechanical microenvironment including elimination of dense ECM by physical, chemical and biological methods, disruption of ECM formation, depletion or inhibition of cancer-associated fibroblasts, are then summarized. Finally, prospects and challenges for further clinical applications of mechano-modulating strategies to enhance the therapeutic efficacy of nanomedicines are discussed. This review may provide guidance for the rational design and application of nanoparticles in clinical settings.

Revolutionizing Neurocare: Biomimetic Nanodelivery Via Cell Membranes

Brain disorders represent a significant challenge in medical science due to the formidable blood-brain barrier (BBB), which severely limits the penetration of conventional therapeutics, hindering effective treatment strategies. This review delves into the innovative realm of biomimetic nanodelivery systems, including stem cell-derived nanoghosts, tumor cell membrane-coated nanoparticles, and erythrocyte membrane-based carriers, highlighting their potential to circumvent the BBB's restrictions. By mimicking native cell properties, these nanocarriers emerge as a promising solution for enhancing drug delivery to the brain, offering a strategic advantage in overcoming the barrier's selective permeability. The unique benefits of leveraging cell membranes from various sources is evaluated and advanced technologies for fabricating cell membrane-encapsulated nanoparticles capable of masquerading as endogenous cells are examined. This enables the targeted delivery of a broad spectrum of therapeutic agents, ranging from small molecule drugs to proteins, thereby providing an innovative approach to neurocare. Further, the review contrasts the capabilities and limitations of these biomimetic nanocarriers with traditional delivery methods, underlining their potential to enable targeted, sustained, and minimally invasive treatment modalities. This review is concluded with a perspective on the clinical translation of these biomimetic systems, underscoring their transformative impact on the therapeutic landscape for intractable brain diseases.

Biophysical perspectives to understanding cancer-associated fibroblasts

The understanding of cancer has evolved significantly, with the tumor microenvironment (TME) now recognized as a critical factor influencing the onset and progression of the disease. This broader perspective challenges the traditional view that cancer is primarily caused by mutations, instead emphasizing the dynamic interaction between different cell types and physicochemical factors within the TME. Among these factors, cancer-associated fibroblasts (CAFs) command attention for their profound influence on tumor behavior and patient prognoses. Despite their recognized importance, the biophysical and mechanical interactions of CAFs within the TME remain elusive. This review examines the distinctive physical characteristics of CAFs, their morphological attributes, and mechanical interactions within the TME. We discuss the impact of mechanotransduction on CAF function and highlight how these cells communicate mechanically with neighboring cancer cells, thereby shaping the path of tumor development and progression. By concentrating on the biomechanical regulation of CAFs, this review aims to deepen our understanding of their role in the TME and to illuminate new biomechanical-based therapeutic strategies.

Polymerizing laminins in development, health, and disease

Polymerizing laminins are multi-domain basement membrane (BM) glycoproteins that self-assemble into cell-anchored planar lattices to establish the initial BM scaffold. Nidogens, collagen-IV and proteoglycans then bind to the scaffold at different domain loci to create a mature BM. The LN domains of adjacent laminins bind to each other to form a polymer node, while the LG domains attach to cytoskeletal-anchoring integrins and dystroglycan, as well as to sulfatides and heparan sulfates. The polymer node, the repeating unit of the polymer scaffold, is organized into a near-symmetrical triskelion. The structure, recently solved by cryo-electron microscopy in combination with AlphaFold2 modeling and biochemical studies, reveals how the LN surface residues interact with each other and how mutations cause failures of self-assembly in an emerging group of diseases, the LN-lamininopathies, that include LAMA2-related dystrophy and Pierson syndrome.

Advantages of integrating Brillouin microscopy in multimodal mechanical mapping of cells and tissues

Recent research has highlighted the growing significance of the mechanical properties of cells and tissues in the proper execution of physiological functions within an organism; alterations to these properties can potentially result in various diseases. These mechanical properties can be assessed using various techniques that vary in spatial and temporal resolutions as well as applications. Due to the wide range of mechanical behaviors exhibited by cells and tissues, a singular mapping technique may be insufficient in capturing their complexity and nuance. Consequently, by utilizing a combination of methods-multimodal mechanical mapping-researchers can achieve a more comprehensive characterization of mechanical properties, encompassing factors such as stiffness, modulus, viscoelasticity, and forces. Furthermore, different mapping techniques can provide complementary information and enable the exploration of spatial and temporal variations to enhance our understanding of cellular dynamics and tissue mechanics. By capitalizing on the unique strengths of each method while mitigating their respective limitations, a more precise and holistic understanding of cellular and tissue mechanics can be obtained. Here, we spotlight Brillouin microscopy (BM) as a noncontact, noninvasive, and label-free mechanical mapping modality to be coutilized alongside established mechanical probing methods. This review summarizes some of the most widely adopted individual mechanical mapping techniques and highlights several recent multimodal approaches demonstrating their utility. We envision that future studies aim to adopt multimodal techniques to drive advancements in the broader realm of mechanobiology.

IGF2BP2 inhibits invasion and migration of clear cell renal cell carcinoma via targeting Netrin-4 in an m6A-dependent manner

Clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma, often leads to a poor prognosis due to metastasis. The investigation of N6-methyladenosine (m6A) methylation, a crucial RNA modification, and its role in ccRCC, particularly through the m6A reader insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), revealed significant insights. We found that IGF2BP2 was notably downregulated in ccRCC, which correlated with tumor aggressiveness and poor prognosis. Thus, IGFBP2 has emerged as an independent prognostic factor of ccRCC. Moreover, a strong positive correlation was observed between the expression of IGF2BP2 and Netrin-4. Netrin-4 was also downregulated in ccRCC, and its lower levels were associated with increased malignancy and poor prognosis. Overexpression of IGF2BP2 and Netrin-4 suppressed the invasion and migration of ccRCC cells, while Netrin-4 knockdown reversed these effects in ccRCC cell lines. RNA immunoprecipitation (RIP)-quantitative polymerase chain reaction validated the robust enrichment of Netrin-4 mRNA in anti-IGF2BP2 antibody immunoprecipitates. MeRlP showed significantly increased Netrin4 m6A levels after lGF2BP2 overexpression. Moreover, we found that IGF2BP2 recognized and bound to the m6A site within the coding sequence of Netrin-4, enhancing its mRNA stability. Collectively, these results showed that IGF2BP2 plays a suppressive role in the invasion and migration of ccRCC cells by targeting Netrin-4 in an m6A-dependent manner. These findings underscore the potential of IGF2BP2/Netrin-4 as a promising prognostic biomarker and therapeutic target in patients with ccRCC metastasis.

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.

Cell volume expansion and local contractility drive collective invasion of the basement membrane in breast cancer

Breast cancer becomes invasive when carcinoma cells invade through the basement membrane (BM)-a nanoporous layer of matrix that physically separates the primary tumour from the stroma. Single cells can invade through nanoporous three-dimensional matrices due to protease-mediated degradation or force-mediated widening of pores via invadopodial protrusions. However, how multiple cells collectively invade through the physiological BM, as they do during breast cancer progression, remains unclear. Here we developed a three-dimensional in vitro model of collective invasion of the BM during breast cancer. We show that cells utilize both proteases and forces-but not invadopodia-to breach the BM. Forces are generated from a combination of global cell volume expansion, which stretches the BM, and local contractile forces that act in the plane of the BM to breach it, allowing invasion. These results uncover a mechanism by which cells collectively interact to overcome a critical barrier to metastasis.

Attenuating Epithelial-to-Mesenchymal Transition in Cancer through Angiopoietin-Like 4 Inhibition in a 3D Tumor Microenvironment Model

Epithelial-to-mesenchymal transition (EMT) plays a crucial role in metastatic cancer progression, and current research, which relies heavily on 2D monolayer cultures, falls short in recapitulating the complexity of a 3D tumor microenvironment. To address this limitation, a transcriptomic meta-analysis is conducted on diverse cancer types undergoing EMT in 2D and 3D cultures. It is found that mechanotransduction is elevated in 3D cultures and is further intensified during EMT, but not during 2D EMT. This analysis reveals a distinct 3D EMT gene signature, characterized by extracellular matrix remodeling coordinated by angiopoietin-like 4 (Angptl4) along with other canonical EMT regulators. Utilizing hydrogel-based 3D matrices with adjustable mechanical forces, 3D cancer cultures are established at varying physiological stiffness levels. A YAP:EGR-1 mediated up-regulation of Angptl4 expression is observed, accompanied by an upregulation of mesenchymal markers, at higher stiffness during cancer EMT. Suppression of Angptl4 using antisense oligonucleotides or anti-cAngptl4 antibodies leads to a dose-dependent abolishment of EMT-mediated chemoresistance and tumor self-organization in 3D, ultimately resulting in diminished metastatic potential and stunted growth of tumor xenografts. This unique programmable 3D cancer cultures simulate stiffness levels in the tumor microenvironment and unveil Angptl4 as a promising therapeutic target to inhibit EMT and impede cancer progression.

Modeling the extracellular matrix in cell migration and morphogenesis: a guide for the curious biologist

The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted. In processes of cell migration, the ECM also acts as a scaffold, providing structural support to cells as well as points of potential attachment. Although the ECM is a well-studied structure, its role in many biological processes remains difficult to investigate comprehensively due to its complexity and structural variation within an organism. In tandem with experiments, mathematical models are helpful in refining and testing hypotheses, generating predictions, and exploring conditions outside the scope of experiments. Such models can be combined and calibrated with in vivo and in vitro data to identify critical cell-ECM interactions that drive developmental and homeostatic processes, or the progression of diseases. In this review, we focus on mathematical and computational models of the ECM in processes such as cell migration including cancer metastasis, and in tissue structure and morphogenesis. By highlighting the predictive power of these models, we aim to help bridge the gap between experimental and computational approaches to studying the ECM and to provide guidance on selecting an appropriate model framework to complement corresponding experimental studies.

Integration of basement membrane-related genes in a risk signature for prognosis in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is characterized by high heterogeneity and recurrence rates, posing significant challenges for stratification and treatment. Basement membrane-related genes (BMGs) play a crucial role in tumor initiation and progression. Clinical and transcriptomic data of ccRCC patients were extracted from TCGA and GEO databases. We employed univariate regression and LASSO-Cox stepwise regression analysis to construct a BMscore model based on BMGs expression level. A nomogram combining clinical features and BMscore was constructed to predict individual survival probabilities. Further enrichment analysis and immune-related analysis were conducted to explore the enriched pathways and immune features associated with BMGs. High-risk individuals predicted by BMscore exhibited poorer overall survival, which was consistent with the validation dataset. BMscore was identified as an independent risk factor for ccRCC. Functional analysis revealed that BMGs were related to cell-matrix and tumor-associated signaling pathways. Immune profiling suggests that BMGs play a key role in immune interactions and the tumor microenvironment. BMGs serve as a novel prognostic predictor for ccRCC and play a role in the immune microenvironment and treatment response. Targeting the BM may represent an alternative therapeutic approach for ccRCC.

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.

The extracellular matrix as hallmark of cancer and metastasis: From biomechanics to therapeutic targets

The extracellular matrix (ECM) is essential for cell support during homeostasis and plays a critical role in cancer. Although research often concentrates on the tumor's cellular aspect, attention is growing for the importance of the cancer-associated ECM. Biochemical and physical ECM signals affect tumor formation, invasion, metastasis, and therapy resistance. Examining the tumor microenvironment uncovers intricate ECM dysregulation and interactions with cancer and stromal cells. Anticancer therapies targeting ECM sensors and remodelers, including integrins and matrix metalloproteinases, and ECM-remodeling cells, have seen limited success. This review explores the ECM's role in cancer and discusses potential therapeutic strategies for cell-ECM interactions.

Breaking through the basement membrane barrier to improve nanotherapeutic delivery to tumours

An effective nanotherapeutic transport from the vasculature to the tumour is crucial for cancer treatment with minimal side effects. Here we demonstrate that, in addition to the endothelial barrier, the tumour vascular basement membrane surrounding the endothelium acts as a formidable mechanical barrier that entraps nanoparticles (NPs) in the subendothelial void, forming perivascular NP pools. Breaking through this basement membrane barrier substantially increases NP extravasation. Using inflammation triggered by local hyperthermia, we develop a cooperative immunodriven strategy to overcome the basement membrane barrier that leads to robust tumour killing. Hyperthermia-triggered accumulation and inflammation of platelets attract neutrophils to the NP pools. The subsequent movement of neutrophils through the basement membrane can release the NPs entrapped in the subendothelial void, resulting in increased NP penetration into deeper tumours. We show the necessity of considering the tumour vascular basement membrane barrier when delivering nanotherapeutics. Understanding this barrier will contribute to developing more effective antitumour therapies.

Light-Induced Nanoscale Deformation in Azobenzene Thin Film Triggers Rapid Intracellular Ca2+ Increase via Mechanosensitive Cation Channels

Epithelial cells are in continuous dynamic biochemical and physical interaction with their extracellular environment. Ultimately, this interplay guides fundamental physiological processes. In these interactions, cells generate fast local and global transients of Ca2+ ions, which act as key intracellular messengers. However, the mechanical triggers initiating these responses have remained unclear. Light-responsive materials offer intriguing possibilities to dynamically modify the physical niche of the cells. Here, a light-sensitive azobenzene-based glassy material that can be micropatterned with visible light to undergo spatiotemporally controlled deformations is used. Real-time monitoring of consequential rapid intracellular Ca2+ signals reveals that the mechanosensitive cation channel Piezo1 has a major role in generating the Ca2+ transients after nanoscale mechanical deformation of the cell culture substrate. Furthermore, the studies indicate that Piezo1 preferably responds to shear deformation at the cell-material interphase rather than to absolute topographical change of the substrate. Finally, the experimentally verified computational model suggests that Na+ entering alongside Ca2+ through the mechanosensitive cation channels modulates the duration of Ca2+ transients, influencing differently the directly stimulated cells and their neighbors. This highlights the complexity of mechanical signaling in multicellular systems. These results give mechanistic understanding on how cells respond to rapid nanoscale material dynamics and deformations.

The laminin-keratin link shields the nucleus from mechanical deformation and signalling

The mechanical properties of the extracellular matrix dictate tissue behaviour. In epithelial tissues, laminin is a very abundant extracellular matrix component and a key supporting element. Here we show that laminin hinders the mechanoresponses of breast epithelial cells by shielding the nucleus from mechanical deformation. Coating substrates with laminin-111-unlike fibronectin or collagen I-impairs cell response to substrate rigidity and YAP nuclear localization. Blocking the laminin-specific integrin β4 increases nuclear YAP ratios in a rigidity-dependent manner without affecting the cell forces or focal adhesions. By combining mechanical perturbations and mathematical modelling, we show that β4 integrins establish a mechanical linkage between the substrate and keratin cytoskeleton, which stiffens the network and shields the nucleus from actomyosin-mediated mechanical deformation. In turn, this affects the nuclear YAP mechanoresponses, chromatin methylation and cell invasion in three dimensions. Our results demonstrate a mechanism by which tissues can regulate their sensitivity to mechanical signals.

Biophysics in tumor growth and progression: from single mechano-sensitive molecules to mechanomedicine

Evidence from physical sciences in oncology increasingly suggests that the interplay between the biophysical tumor microenvironment and genetic regulation has significant impact on tumor progression. Especially, tumor cells and the associated stromal cells not only alter their own cytoskeleton and physical properties but also remodel the microenvironment with anomalous physical properties. Together, these altered mechano-omics of tumor tissues and their constituents fundamentally shift the mechanotransduction paradigms in tumorous and stromal cells and activate oncogenic signaling within the neoplastic niche to facilitate tumor progression. However, current findings on tumor biophysics are limited, scattered, and often contradictory in multiple contexts. Systematic understanding of how biophysical cues influence tumor pathophysiology is still lacking. This review discusses recent different schools of findings in tumor biophysics that have arisen from multi-scale mechanobiology and the cutting-edge technologies. These findings range from the molecular and cellular to the whole tissue level and feature functional crosstalk between mechanotransduction and oncogenic signaling. We highlight the potential of these anomalous physical alterations as new therapeutic targets for cancer mechanomedicine. This framework reconciles opposing opinions in the field, proposes new directions for future cancer research, and conceptualizes novel mechanomedicine landscape to overcome the inherent shortcomings of conventional cancer diagnosis and therapies.

Bone-matrix mineralization dampens integrin-mediated mechanosignalling and metastatic progression in breast cancer

In patients with breast cancer, lower bone mineral density increases the risk of bone metastasis. Although the relationship between bone-matrix mineralization and tumour-cell phenotype in breast cancer is not well understood, mineralization-induced rigidity is thought to drive metastatic progression via increased cell-adhesion forces. Here, by using collagen-based matrices with adjustable intrafibrillar mineralization, we show that, unexpectedly, matrix mineralization dampens integrin-mediated mechanosignalling and induces a less proliferative stem-cell-like phenotype in breast cancer cells. In mice with xenografted decellularized physiological bone matrices seeded with human breast tumour cells, the presence of bone mineral reduced tumour growth and upregulated a gene-expression signature that is associated with longer metastasis-free survival in patients with breast cancer. Our findings suggest that bone-matrix changes in osteogenic niches regulate metastatic progression in breast cancer and that in vitro models of bone metastasis should integrate organic and inorganic matrix components to mimic physiological and pathologic mineralization.

Mechanobiology in oncology: basic concepts and clinical prospects

The interplay between genetic transformations, biochemical communications, and physical interactions is crucial in cancer progression. Metastasis, a leading cause of cancer-related deaths, involves a series of steps, including invasion, intravasation, circulation survival, and extravasation. Mechanical alterations, such as changes in stiffness and morphology, play a significant role in all stages of cancer initiation and dissemination. Accordingly, a better understanding of cancer mechanobiology can help in the development of novel therapeutic strategies. Targeting the physical properties of tumours and their microenvironment presents opportunities for intervention. Advancements in imaging techniques and lab-on-a-chip systems enable personalized investigations of tumor biomechanics and drug screening. Investigation of the interplay between genetic, biochemical, and mechanical factors, which is of crucial importance in cancer progression, offers insights for personalized medicine and innovative treatment strategies.

A preclinical platform for assessing long-term drug efficacy exploiting mechanically tunable scaffolds colonized by a three-dimensional tumor microenvironment

BACKGROUND

Long-term drug evaluation heavily relies upon rodent models. Drug discovery methods to reduce animal models in oncology may include three-dimensional (3D) cellular systems that take into account tumor microenvironment (TME) cell types and biomechanical properties.

METHODS

In this study we reconstructed a 3D tumor using an elastic polymer (acrylate-endcapped urethane-based poly(ethylene glycol) (AUPPEG)) with clinical relevant stiffness. Single cell suspensions from low-grade serous ovarian cancer (LGSOC) patient-derived early passage cultures of cancer cells and cancer-associated fibroblasts (CAF) embedded in a collagen gel were introduced to the AUPPEG scaffold. After self-organization in to a 3D tumor, this model was evaluated by a long-term (> 40 days) exposure to a drug combination of MEK and HSP90 inhibitors. The drug-response results from this long-term in vitro model are compared with drug responses in an orthotopic LGSOC xenograft mouse model.

RESULTS

The in vitro 3D scaffold LGSOC model mimics the growth ratio and spatial organization of the LGSOC. The AUPPEG scaffold approach allows to test new targeted treatments and monitor long-term drug responses. The results correlate with those of the orthotopic LGSOC xenograft mouse model.

CONCLUSIONS

The mechanically-tunable scaffolds colonized by a three-dimensional LGSOC allow long-term drug evaluation and can be considered as a valid alternative to reduce, replace and refine animal models in drug discovery.

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.

Decoding tumor heterogeneity in uveal melanoma: basement membrane genes as novel biomarkers and therapeutic targets revealed by multi-omics approaches for cancer immunotherapy

Background: Uveal melanoma (UVM) is a primary intraocular malignancy that poses a significant threat to patients' visual function and life. The basement membrane (BM) is critical for establishing and maintaining cell polarity, adult function, embryonic and organ morphogenesis, and many other biological processes. Some basement membrane protein genes have been proven to be prognostic biomarkers for various cancers. This research aimed to develop a novel risk assessment system based on BMRGs that would serve as a theoretical foundation for tailored and accurate treatment. Methods: We used gene expression profiles and clinical data from the TCGA-UVM cohort of 80 UVM patients as a training set. 56 UVM patients from the combined cohort of GSE84976 and GSE22138 were employed as an external validation dataset. Prognostic characteristics of basement membrane protein-related genes (BMRGs) were characterized by Lasso, stepwise multifactorial Cox. Multivariate analysis revealed BMRGs to be independent predictors of UVM. The TISCH database probes the crosstalk of BMEGs in the tumor microenvironment at the single-cell level. Finally, we investigated the function of ITGA5 in UVM using multiple experimental techniques, including CCK8, transwell, wound healing assay, and colony formation assay. Results: There are three genes in the prognostic risk model (ADAMTS10, ADAMTS14, and ITGA5). After validation, we determined that the model is quite reliable and accurately forecasts the prognosis of UVM patients. Immunotherapy is more likely to be beneficial for UVM patients in the high-risk group, whereas the survival advantage may be greater for UVM patients in the low-risk group. Knockdown of ITGA5 expression was shown to inhibit the proliferation, migration, and invasive ability of UVM cells in vitro experiments. Conclusion: The 3-BMRGs feature model we constructed has excellent predictive performance which plays a key role in the prognosis, informing the individualized treatment of UVM patients. It also provides a new perspective for assessing pre-immune efficacy.

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.

Cell-extracellular matrix mechanotransduction in 3D

Mechanical properties of extracellular matrices (ECMs) regulate essential cell behaviours, including differentiation, migration and proliferation, through mechanotransduction. Studies of cell-ECM mechanotransduction have largely focused on cells cultured in 2D, on top of elastic substrates with a range of stiffnesses. However, cells often interact with ECMs in vivo in a 3D context, and cell-ECM interactions and mechanisms of mechanotransduction in 3D can differ from those in 2D. The ECM exhibits various structural features as well as complex mechanical properties. In 3D, mechanical confinement by the surrounding ECM restricts changes in cell volume and cell shape but allows cells to generate force on the matrix by extending protrusions and regulating cell volume as well as through actomyosin-based contractility. Furthermore, cell-matrix interactions are dynamic owing to matrix remodelling. Accordingly, ECM stiffness, viscoelasticity and degradability often play a critical role in regulating cell behaviours in 3D. Mechanisms of 3D mechanotransduction include traditional integrin-mediated pathways that sense mechanical properties and more recently described mechanosensitive ion channel-mediated pathways that sense 3D confinement, with both converging on the nucleus for downstream control of transcription and phenotype. Mechanotransduction is involved in tissues from development to cancer and is being increasingly harnessed towards mechanotherapy. Here we discuss recent progress in our understanding of cell-ECM mechanotransduction in 3D.

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.

Netrin Family Genes as Prognostic Markers and Therapeutic Targets for Clear Cell Renal Cell Carcinoma: Netrin-4 Acts through the Wnt/β-Catenin Signaling Pathway

Clear cell renal cell carcinoma (ccRCC, or KIRC) is the most common type of kidney cancer, originating within the renal cortex. The current outcomes for early diagnosis and late treatment of ccRCC are unsatisfactory. Therefore, it is important to explore tumor biomarkers and therapeutic opportunities for ccRCC. In this study, we used bioinformatics methods to systematically evaluate the expression and prognostic value of Netrin family genes in ccRCC. Through our analysis, three potential biomarkers for ccRCC were identified, namely NTNG1, NTNG2, and NTN4. Moreover, we performed in vitro and in vivo experiments to explore the possible biological roles of NTN4 and found that NTN4 could regulate ccRCC development through Wnt/β-catenin signaling. We elucidate the molecular mechanism by which NTN4 modulates β-catenin expression and nuclear translocation to inhibit ccRCC progression, providing a new theoretical basis for developing therapeutic targets for ccRCC. Thus, we suggest that Netrin-related studies may offer new directions for the diagnosis, treatment, and prognosis of ccRCC patients.

Function and prognostic value of basement membrane -related genes in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) has become a common cause of cancer-related death. Many studies have shown that the basement membrane (BM) is associated with the development of cancer. However, BM-related gene expression and its relationship to LUAD prognosis remains unclear. Methods: BM-related genes from previous studies were used. Clinical and mRNA expression information were obtained from TCGA database. Cox, minimum absolute contraction, and selection operator regression were applied to analyze the selected genes affecting LUAD prognosis. A prognostic-risk model was then established. Furthermore, this study applied Kaplan-Meier analysis to assess the outcomes of high- and low-risk groups, then explored their differences in drug sensitivity. The DSigDB database was used to screen for therapeutic small-molecule drugs. Results: Fourteen prognostic models based on BM-related genes were successfully constructed and validated in patients with LUAD. We also found that independence was a prognostic factor in all 14 BM-based models. Functional analysis showed that the enrichment of BM-related genes mainly originated from signaling pathways related to cancer. The BM-based model also suggested that immune cell infiltration is associated with checkpoints. The low-risk patients may benefit from cyclopamine and docetaxel treatments. Conclusion: This study identified a reliable biomarker to predict survival in patients with LUAD and offered new insights into the function of BM-related genes in LUAD.

Identification of basement membrane-related prognostic signature for predicting prognosis, immune response and potential drug prediction in papillary renal cell carcinoma

Papillary renal cell carcinoma (PRCC) is a malignant neoplasm of the kidney and is highly interesting due to its increasing incidence. Many studies have shown that the basement membrane (BM) plays an important role in the development of cancer, and structural and functional changes in the BM can be observed in most renal lesions. However, the role of BM in the malignant progression of PRCC and its impact on prognosis has not been fully studied. Therefore, this study aimed to explore the functional and prognostic value of basement membrane-associated genes (BMs) in PRCC patients. We identified differentially expressed BMs between PRCC tumor samples and normal tissue and systematically explored the relevance of BMs to immune infiltration. Moreover, we constructed a risk signature based on these differentially expressed genes (DEGs) using Lasso regression analysis and demonstrated their independence using Cox regression analysis. Finally, we predicted 9 small molecule drugs with the potential to treat PRCC and compared the differences in sensitivity to commonly used chemotherapeutic agents between high and low-risk groups to better target patients for more precise treatment planning. Taken together, our study suggested that BMs might play a crucial role in the development of PRCC, and these results might provide new insights into the treatment of PRCC.

Novel TCF21high pericyte subpopulation promotes colorectal cancer metastasis by remodelling perivascular matrix

OBJECTIVE

Haematogenous dissemination is a prevalent route of colorectal cancer (CRC) metastasis. However, as the gatekeeper of vessels, the role of tumour pericytes (TPCs) in haematogenous metastasis remains largely unknown. Here, we aimed to investigate the heterogeneity of TPCs and their effects on CRC metastasis.

DESIGN

TPCs were isolated from patients with CRC with or without liver metastases and analysed by single-cell RNA sequencing (scRNA-seq). Clinical CRC specimens were collected to analyse the association between the molecular profiling of TPCs and CRC metastasis. RNA-sequencing, chromatin immunoprecipitation-sequencing and bisulfite-sequencing were performed to investigate the TCF21-regulated genes and mechanisms underlying integrin α5 on TCF21 DNA hypermethylation. Pericyte-conditional Tcf21-knockout mice were constructed to investigate the effects of TCF21 in TPCs on CRC metastasis. Masson staining, atomic force microscopy, second-harmonic generation and two-photon fluorescence microscopy were employed to observe perivascular extracellular matrix (ECM) remodelling.

RESULTS

Thirteen TPC subpopulations were identified by scRNA-seq. A novel subset of TCF21^high TPCs, termed 'matrix-pericytes', was associated with liver metastasis in patients with CRC. TCF21 in TPCs increased perivascular ECM stiffness, collagen rearrangement and basement membrane degradation, establishing a perivascular metastatic microenvironment to instigate colorectal cancer liver metastasis (CRCLM). Tcf21 depletion in TPCs mitigated perivascular ECM remodelling and CRCLM, whereas the coinjection of TCF21^high TPCs and CRC cells markedly promoted CRCLM. Mechanistically, loss of integrin α5 inhibited the FAK/PI3K/AKT/DNMT1 axis to impair TCF21 DNA hypermethylation in TCF21^high TPCs.

CONCLUSION

This study uncovers a previously unidentified role of TPCs in haematogenous metastasis and provides a potential diagnostic marker and therapeutic target for CRC metastasis.

A novel basement membrane-related gene signature for prognosis of lung adenocarcinomas

BACKGROUND

Lung adenocarcinoma (LUAD) remains a global health concern with its poor prognosis and high mortality. Whether tumor cells invade through the basement membrane (BM) is the key factor to determine the prognosis of LUAD. This study aimed to identify the BM-related gene signatures to improve the overall prognosis of LUAD.

MATERIALS & METHODS

A series of bioinformatics analyses were conducted based on TCGA and GEO datasets. Unsupervised consistent cluster analysis was performed, and 500 LUAD patients were assigned to two different groups according to expressions of 222 BM-related genes. The differentially expressed genes (DEGs) between the two clusters were identified, and Lasso regression, ROC curve, univariate and multivariate Cox regression analyses and enrichment analysis were conducted. Besides, ssGSEA, CIBERSORT and ESTIMATE algorithmwere were employed to understand the relationship between the tumor microenvironment (TME) and risk scores. Moreover, single cell clustering and trajectory analyses were performed to further understand the significance of BM-related genes. Finally, qRT-PCR was used to verify the prognosis model.

RESULTS

A total of 31 prognostic BM-related genes were determined for LUAD, and a novel 17-mRNA prognostic model named BMsocre was successfully established to predict the overall survival of LUAD patients. The high BMscore group indicated worse prognosis. Seventeen DEGs were enriched mainly in metabolism, ECM-receptor interaction and immune response. In addition, the high-risk group showed higher TMB and lower immune score. The low-risk group had a better immunotherapeutic response where immune escape was less likely. The BMscore model was verified in our patient cohort. Furthermore, NELL2 was mainly expressed in clusters of T cells, and was identified to play a critical role in T-cell differentiation.

CONCLUSIONS

A novel BMscore model was successfully established and might be effective for providing guidance to LUAD therapy.

Cryo-EM reveals the molecular basis oflaminin polymerization and LN-lamininopathies

Laminin polymerization is the major step in basement membranes assembly. Its failures cause laminin N-terminal domain lamininopathies including Pierson syndrome. We have employed cryo-electron microscopy to determine a 3.7 Å structure of the trimeric laminin polymer node containing α1, β1 and γ1 subunits. The structure reveals the molecular basis of calcium-dependent formation of laminin lattice, and provides insights into polymerization defects manifesting in human disease.

Extracting, quantifying, and comparing dynamical and biomechanical properties of living matter through single particle tracking

A panoply of new tools for tracking single particles and molecules has led to an explosion of experimental data, leading to novel insights into physical properties of living matter governing cellular development and function, health and disease. In this Perspective, we present tools to investigate the dynamics and mechanics of living systems from the molecular to cellular scale via single-particle techniques. In particular, we focus on methods to measure, interpret, and analyse complex data sets that are associated with forces, materials properties, transport, and emergent organisation phenomena within biological and soft-matter systems. Current approaches, challenges, and existing solutions in the associated fields are outlined in order to support the growing community of researchers at the interface of physics and the life sciences. Each section focuses not only on the general physical principles and the potential for understanding living matter, but also on details of practical data extraction and analysis, discussing limitations, interpretation, and comparison across different experimental realisations and theoretical frameworks. Particularly relevant results are introduced as examples. While this Perspective describes living matter from a physical perspective, highlighting experimental and theoretical physics techniques relevant for such systems, it is also meant to serve as a solid starting point for researchers in the life sciences interested in the implementation of biophysical methods.

Mechanosensitive brain tumor cells construct blood-tumor barrier to mask chemosensitivity

Major obstacles in brain cancer treatment include the blood-tumor barrier (BTB), which limits the access of most therapeutic agents, and quiescent tumor cells, which resist conventional chemotherapy. Here, we show that Sox2⁺ tumor cells project cellular processes to ensheathe capillaries in mouse medulloblastoma (MB), a process that depends on the mechanosensitive ion channel Piezo2. MB develops a tissue stiffness gradient as a function of distance to capillaries. Sox2⁺ tumor cells perceive substrate stiffness to sustain local intracellular calcium, actomyosin tension, and adhesion to promote cellular process growth and cell surface sequestration of β-catenin. Piezo2 knockout reverses WNT/β-catenin signaling states between Sox2⁺ tumor cells and endothelial cells, compromises the BTB, reduces the quiescence of Sox2⁺ tumor cells, and markedly enhances the MB response to chemotherapy. Our study reveals that mechanosensitive tumor cells construct the BTB to mask tumor chemosensitivity. Targeting Piezo2 addresses the BTB and tumor quiescence properties that underlie treatment failures in brain cancer.

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.

Identification of a basement membrane-based risk scoring system for prognosis prediction and individualized therapy in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) belongs to one of the 10 most frequently diagnosed cancers worldwide and has a poor prognosis at the advanced stage. Although multiple therapeutic agents have been proven to be curative in ccRCC, their clinical application was limited due to the lack of reliable biomarkers. Considering the important role of basement membrane (BM) in tumor metastasis and TME regulation, we investigated the expression of BM-related genes in ccRCC and identified prognostic BM genes through differentially expression analysis and univariate cox regression analysis. Then, BM-related ccRCC subtypes were recognized through consensus non-negative matrix factorization based on the prognostic BM genes and evaluated with regard to clinical and TME features. Next, utilizing the differentially expressed genes between the BM-related subtypes, a risk scoring system BMRS was established after serial analysis of univariate cox regression analysis, lasso regression analysis, and multivariate cox regression analysis. Time-dependent ROC curve revealed the satisfactory prognosis predictive capacity of BMRS with internal, and external validation. Multivariate analysis proved the independent predictive ability of BMRS and a BMRS-based nomogram was constructed for clinical application. Some featured mutants were discovered through genomic analysis of the BMRS risk groups. Meanwhile, the BMRS groups were found to have distinct immune scores, immune cell infiltration levels, and immune-related functions. Moreover, with the help of data from The Cancer Immunome Atlas (TCIA) and Genomics of Drug Sensitivity in Cancer (GDSC), the potential of BMRS in predicting therapeutic response was evaluated and some possible therapeutic compounds were proposed through ConnectivityMap (CMap). For the practicability of BMRS, we validated the expression of BMRS-related genes in clinical samples. After all, we identified BM-related ccRCC subtypes with distinct clinical and TME features and constructed a risk scoring system for the prediction of prognosis, therapeutic responses, and potential therapeutic agents of ccRCC. As ccRCC systemic therapy continues to evolve, the risk scoring system BMRS we reported may assist in individualized medication administration.

Laminin N-terminus (LaNt) proteins, laminins and basement membrane regulation

Basement membranes (BMs) are structured regions of the extracellular matrix that provide multiple functions including physical support and acting as a barrier, as a repository for nutrients and growth factors, and as biophysical signalling hubs. At the core of all BMs is the laminin (LM) family of proteins. These large heterotrimeric glycoproteins are essential for tissue integrity, and differences between LM family members represent a key nexus in dictating context and tissue-specific functions. These variations reflect genetic diversity within the family, which allows for multiple structurally and functionally distinct heterotrimers to be produced, each with different architectures and affinities for other matrix proteins and cell surface receptors. The ratios of these LM isoforms also influence the biophysical properties of a BM owing to differences in their relative ability to form polymers or networks. Intriguingly, the LM superfamily is further diversified through the related netrin family of proteins and through alternative splicing leading to the generation of non-LM short proteins known as the laminin N-terminus (LaNt) domain proteins. Both the netrins and LaNt proteins contain structural domains involved in LM-to-LM interaction and network assembly. Emerging findings indicate that one netrin and at least one LaNt protein can potently influence the structure and function of BMs, disrupting the networks, changing physical properties, and thereby influencing tissue function. These findings are altering the way that we think about LM polymerisation and, in the case of the LaNt proteins, suggest a hitherto unappreciated form of LM self-regulation.

A novel murine model of combined hepatocellular carcinoma and intrahepatic cholangiocarcinoma

Primary liver cancer (PLC) is a common gastrointestinal malignancy worldwide. While hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are two major pathologic types of PLC, combined HCC and ICC (cHCC-ICC) is a relatively rare subtype that shares both hepatocyte and cholangiocyte differentiation. However, the molecular feature of this unique tumor remains elusive because of its low incidence and lack of a suitable animal model. Herein, we generated a novel spontaneous cHCC-ICC model using a Sleeping Beauty-dependent transposon plasmid co-expressing oncogenic Myc and AKT1 and a CRISPR-Cas9 plasmid expressing single-guide RNA targeting p53 into mouse hepatocytes via in situ electroporation. The histological and transcriptional analysis confirmed that this model exhibits cHCC-ICC features and activates pathways committing cHCC-ICC formation, such as TGF-β, WNT, and NF-κB. Using this model, we further screened and identified LAMB1, a protein involved in cell adhesion and migration, as a potential therapeutic target for cHCC-ICC. In conclusion, our work presents a novel genetic cHCC-ICC model and provides new insights into cHCC-ICC.

Reversing the PAI-1-induced fibrotic immune exclusion of solid tumor by multivalent CXCR4 antagonistic nano-permeator

Fibrosis is one of the key factors that lead to the immune exclusion of solid tumors. Although degradation of fiber is a promising strategy, its application was still bottlenecked by the side effects of causing metastasis, resulting in the failure of immunotherapy. Here, we developed an antimetastatic polymer (HPA) for the delivery of chemo-drug and antifibrotic siPAI-1 to form the nano-permeator. Nano-permeator shrank after protonation and deeply penetrated into the tumor core to down-regulate the expression of PAI-1 for antifibrosis, and further promoted the sustained infiltration and activation of T cells for killing tumor cells. Moreover, metastasis after fiber elimination was prevented by multivalent CXCR4 antagonistic HPA to reduce the attraction of CXCL12 secreted by distant organs. The administration of stroma-alleviated immunotherapy increased the infiltration of CD8⁺ T cells to 52.5% in tumor tissues, inhibiting nearly 90% metastasis by HPA in distant organs. The nano-permeator reveals the mechanism and correlation between antifibrosis and antimetastasis and was believed to be the optimizing immunotherapy for solid fibrotic tumors.

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.

Characterization of the basement membrane in kidney renal clear cell carcinoma to guide clinical therapy

Background

Renal cell carcinoma (RCC) is the most common kidney cancer in adults. According to the histological features, it could be divided into several subtypes, of which the most common one is kidney renal clear cell carcinoma (KIRC), which contributed to more than 90% of cases for RCC and usually ends with a dismal outcome. Previous studies suggested that basement membrane genes (BMGs) play a pivotal role in tumor development. However, the significance and prognostic value of BMGs in KIRC still wrap in the mist.

Methods

KIRC data were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. A prognostic risk score (PRS) model based on BMGs was established using univariate and least absolute shrinkage and selection operator (LASSO) and the Cox regression analysis was performed for prognostic prediction. The Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, receiver operating characteristic (ROC) curves, nomogram, and calibration curves were utilized to evaluate and validate the PRS model. All KIRC cases were divided into the high-risk score (HRS) group and the low-risk score (LRS) group according to the median risk scores. In addition, single-sample gene set enrichment analysis (ssGSEA), immune analysis, tumor microenvironment (TME) analysis, principal component analysis (PCA), and half-maximal inhibitory concentration (IC50) were also applied. Expression levels of BMGs were confirmed by qRT-PCR in both human renal cancer cell lines and tissues.

Results

We established the BMGs-based prognostic model according to the following steps. Within the TCGA cohort, patients’ prognosis of the HRS group was significantly worse than that of the LRS group, which was consistent with the analysis results of the GEO cohort. PCA patterns were significantly distinct for LRS and HRS groups and pathological features of the HRS group were more malignant compared with the LRS group. Correlation analysis of the PRS model and TME features, such as immune cell scores, stromal cell scores, and ESTIMATE values, revealed a higher immune infiltration in the HRS group compared with the LRS group. The chemotherapeutic response was also evaluated in KIRC treatment. It showed that the HRS group exhibited stronger chemoresistance to chemotherapeutics like FR-180204, GSK1904529A, KIN001-102, and YM201636. The therapeutic reactivity of the other 27 chemotherapeutic agents was summarized as well. Furthermore, the FREM2 level was measured in both human kidney tissues and associated cell lines, which suggested that lower FREM2 expression prompts a severer pathology and clinical ending.

Conclusions

Our study showed that KIRC is associated with a unique BMG expression pattern. The risk scores related to the expression levels of 10 BMGs were assessed by survival status, TME, pathological features, and chemotherapeutic resistance. All results suggested that FREM2 could be a potential candidate for KIRC prognosis prediction. In this study, we established a valid model and presented new therapeutic targets for the KIRC prognosis prediction as well as the clinical treatment recommendation, and finally, facilitated precision tumor therapy for every single individual.

Precise fibrin decomposition and tumor mechanics modulation with hydroxyethyl starch-based smart nanomedicine for enhanced antitumor efficacy

Chemotherapy is a conventional cancer treatment in clinical settings. Although numerous nano drug delivery systems have been developed, the chemotherapeutic effect is greatly limited by abnormal tumor mechanics in solid tumors. Tumor stiffening and accumulated solid stress compress blood vessels and inhibit drug delivery to tumor cells, becoming critical challenges for chemotherapy. By loading doxorubicin (DOX), tissue plasminogen activator (tPA), and fibrin targeting peptide CREKA (Cys-Arg-Glu-Lys-Ala) within pH responsive amphiphilic block polymers, pyridyldithio-hydroxyethyl starch-Schiff base-polylactic acid (PA-HES-pH-PLA), we report a smart nanomedicine, DOX@CREKA/tPA-HES-pH-PLA (DOX@CREKA/tPA-HP), which exhibits a potent antitumor efficacy. In triple-negative breast cancer (TNBC) 4T1 tumors, DOX@CREKA/tPA-HP precisely targeted and effectively decomposed fibrin matrix. By measuring Young's Modulus of tumor slices and quantifying tumor openings, we demonstrated that DOX@CREKA/tPA-HP remarkably reduced tumor stiffness and solid stress. Consequently, the alleviated tumor mechanics decompressed tumor blood vessels, promoted drug delivery, and led to amplified antitumor effect. Our work reveals that decomposing fibrin is a significant means for modulating tumor mechanics, and DOX@CREKA/tPA-HP is a promising smart nanomedicine for treating TNBC.

Comprehensive analysis of FRAS1/FREM family as potential biomarkers and therapeutic targets in renal clear cell carcinoma

Background: FRAS1 (Fraser syndrome protein 1), together with FREM1 (the Fras1-related extracellular matrix proteins 1) and FREM2, belonging to the FRAS1/FREM extracellular matrix protein family, are considered to play essential roles in renal organogenesis and cancer progression. However, their roles in kidney renal clear cell carcinoma (KIRC) remain to be elucidated.

Methods: FRAS1/FREM RNA expression analysis was performed using TCGA/GTEx databases, and valided using GEO databases and real-time PCR. Protein expression was peformed using CPTAC databases. Herein, we employed an array of bioinformatics methods and online databases to explore the potential oncogenic roles of FRAS1/FREM in KIRC.

Results: We found that FRAS1, FREM1 and FREM2 genes and proteins expression levels were significantly decreased in KIRC tissues than in normal tissues. Decreased FRAS1/FREM expression levels were significantly associated with advanced clinicopathological parameters (pathological stage, grade and tumor metastasis status). Notably, the patients with decreased FRAS1/FREM2 expression showed a high propensity for metastasis and poor prognosis. FRAS1/FREM were correlated with various immune infiltrating cells, especially CD4+ T cells and its corresponding subsets (Th1, Th2, Tfh and Tregs). FRAS1 and FREM2 had association with DNA methylation and their single CpG methylation levels were associated with prognosis. Moreover, FRAS1/FREM might exert antitumor effects by functioning in key oncogenic signalling pathways and metabolic pathways. Drug sensitivity analysis indicated that high FRAS1 and FREM2 expression can be a reliable predictor of targeted therapeutic drug response, highlighting the potential as anticancer drug targets.

Conclusion: Together, our results indicated that FRAS1/FREM family members could be potential therapeutic targets and valuable prognostic biomarkers of KIRC.

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.

Can't handle the stress? Mechanobiology and disease

Mechanobiology is a rapidly growing research area focused on how mechanical forces and properties influence biological systems at the cell, molecular, and tissue level, and how those biological systems, in turn, control mechanical parameters. Recently, it has become apparent that disrupted mechanobiology has a significant role in many diseases, from cardiovascular disease to muscular dystrophy and cancer. An improved understanding of this intricate process could be harnessed toward developing alternative and more targeted treatment strategies, and to advance the fields of regenerative and personalized medicine. Modulating the mechanical properties of the cellular microenvironment has already been used successfully to boost antitumor immune responses and to induce cardiac and spinal regeneration, providing inspiration for further research in this area.