Matrix stiffness promotes glioma cell stemness by activating BCL9L/Wnt/β-catenin signaling

Machine learning and artificial intelligence: Enabling the clinical translation of atomic force microscopy-based biomarkers for cancer diagnosis

The influence of biomechanics on cell function has become increasingly defined over recent years. Biomechanical changes are known to affect oncogenesis; however, these effects are not yet fully understood. Atomic force microscopy (AFM) is the gold standard method for measuring tissue mechanics on the micro- or nano-scale. Due to its complexity, however, AFM has yet to become integrated in routine clinical diagnosis. Artificial intelligence (AI) and machine learning (ML) have the potential to make AFM more accessible, principally through automation of analysis. In this review, AFM and its use for the assessment of cell and tissue mechanics in cancer is described. Research relating to the application of artificial intelligence and machine learning in the analysis of AFM topography and force spectroscopy of cancer tissue and cells are reviewed. The application of machine learning and artificial intelligence to AFM has the potential to enable the widespread use of nanoscale morphologic and biomechanical features as diagnostic and prognostic biomarkers in cancer treatment.

Polyethylene Glycol-Based Hydrogel as a 3D Extracellular Matrix Mimic for Cytotoxic T Lymphocytes

Three-dimensional (3D) in vitro models enable us to understand cell behavior that is a better reflection of what occurs in vivo than 2D in vitro models. As a result, developing 3D models for extracellular matrix (ECM) has been growing exponentially. Most of the efforts for these 3D models are geared toward understanding cancer cells. An intricate network of cells that engages with cancer cells and can kill them are the immune cells, particularly cytotoxic T lymphocytes (CTLs). However, limited reports are available for 3D ECM mimics to understand CTL dynamics. Currently, we lack ECM mimetic hydrogels for immune cells, with sufficient control over variables, such as stiffness, to fully understand CTL dynamics in vitro. Here, we developed PEG-based hydrogels as ECM mimics for CTLs. The ECM mimics are targeted to mimic the stiffness of soft tissues where CTLs reside, migrate, and deliver their function. To understand cell-material interaction, we determined the porosity, biocompatibility, and stiffness of the ECM mimics. The ECM mimics have median pore sizes of 10.7 and 13.3 μm, close to the average nucleus size of CTLs (~8.6 μm), and good biocompatibility to facilitate cell migration. The stiffness of the ECM mimics corresponds to biologically relevant microenvironments such as lungs and kidneys. Using time-lapse fluorescence microscopy, 3D cell migration was imaged and measured. CTLs migrated faster in softer ECM mimic with larger pores, consistent with previous studies in collagen (the gold standard ECM mimic for CTLs). The work herein demonstrates that the PEG-based ECM mimic can serve as an in vitro tool to elucidate the cell dynamics of CTLs. Thus, this study opens possibilities to study the mechanics of CTLs in well-defined ECM mimic conditions in vitro.

Matrix stiffening facilitates stemness of liver cancer stem cells by YAP activation and BMF inhibition

Matrix stiffening is one of the major risk factors for hepatocellular carcinoma (HCC) and drives tumor progression. The extracellular matrix (ECM) stiffness of HCC displays mechanical heterogeneity, with stiffness increasing from the core to the invasive frontier. The distribution of liver cancer stem cells (CSCs) is related to this mechanical property. However, it is not sufficiently understood how heterogeneous matrix stiffness regulates the stemness of CSCs. In this study, we developed an adjustable gelatin/alginate hydrogel to investigate the effect of various matrix stiffnesses on CSC stemness under three-dimensional culture conditions. Gelatin/alginate hydrogel with the stiffness of soft (5 kPa), medium (16 kPa), and stiff (81 kPa) were prepared by altering the concentration of calcium ions. It was found that a stiffer matrix promoted stemness-associated gene expression, reduced drug sensitivity, enhanced sphere-forming and clonogenic ability, and tumorigenic potential. Mechanistically, matrix stiffening facilitates CSC stemness by increasing Yes-associated protein (YAP) activity and inhibiting Bcl-2 modifying factor (BMF) expression. Knockdown of YAP or overexpression of BMF significantly attenuated matrix stiffening-induced stemness, suggesting the involvement of YAP and BMF in this process. Together, our results unravel the regulatory mechanism of heterogeneous matrix stiffness on CSC stemness and also provide a novel therapeutic strategy for eradicating CSCs and improving the efficiency of HCC treatment.

Glioma actively orchestrate a self-advantageous extracellular matrix to promote recurrence and progression

The intricate interplay between cancer cells and their surrounding microenvironment has emerged as a critical factor driving the aggressive progression of various malignancies, including gliomas. Among the various components of this dynamic microenvironment, the extracellular matrix (ECM) holds particular significance. Gliomas, intrinsic brain tumors that originate from neuroglial progenitor cells, have the remarkable ability to actively reform the ECM, reshaping the structural and biochemical landscape to their advantage. This phenomenon underscores the adaptability and aggressiveness of gliomas, and highlights the intricate crosstalk between tumor cells and their surrounding matrix.In this review, we delve into how glioma actively regulates glioma ECM to organize a favorable microenvironment for its survival, invasion, progression and therapy resistance. By unraveling the intricacies of glioma-induced ECM remodeling, we gain valuable insights into potential therapeutic strategies aimed at disrupting this symbiotic relationship and curbing the relentless advance of gliomas within the brain.

Cancer-associated fibroblasts and prostate cancer stem cells: crosstalk mechanisms and implications for disease progression

The functional heterogeneity and ecological niche of prostate cancer stem cells (PCSCs), which are major drivers of prostate cancer development and treatment resistance, have attracted considerable research attention. Cancer-associated fibroblasts (CAFs), which are crucial components of the tumor microenvironment (TME), substantially affect PCSC stemness. Additionally, CAFs promote PCSC growth and survival by releasing signaling molecules and modifying the surrounding environment. Conversely, PCSCs may affect the characteristics and behavior of CAFs by producing various molecules. This crosstalk mechanism is potentially crucial for prostate cancer progression and the development of treatment resistance. Using organoids to model the TME enables an in-depth study of CAF-PCSC interactions, providing a valuable preclinical tool to accurately evaluate potential target genes and design novel treatment strategies for prostate cancer. The objective of this review is to discuss the current research on the multilevel and multitarget regulatory mechanisms underlying CAF-PCSC interactions and crosstalk, aiming to inform therapeutic approaches that address challenges in prostate cancer treatment.

Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers

Glioma is currently one of the most prevalent types of primary brain cancer. Given its high level of heterogeneity along with the complex biological molecular markers, many efforts have been made to accurately classify the type of glioma in each patient, which, in turn, is critical to improve early diagnosis and increase survival. Nonetheless, as a result of the fast-growing technological advances in high-throughput sequencing and evolving molecular understanding of glioma biology, its classification has been recently subject to significant alterations. In this study, we integrate multiple glioma omics modalities (including mRNA, DNA methylation, and miRNA) from The Cancer Genome Atlas (TCGA), while using the revised glioma reclassified labels, with a supervised method based on sparse canonical correlation analysis (DIABLO) to discriminate between glioma types. We were able to find a set of highly correlated features distinguishing glioblastoma from lower-grade gliomas (LGGs) that were mainly associated with the disruption of receptor tyrosine kinases signaling pathways and extracellular matrix organization and remodeling. Concurrently, the discrimination of the LGG types was characterized primarily by features involved in ubiquitination and DNA transcription processes. Furthermore, we could identify several novel glioma biomarkers likely helpful in both diagnosis and prognosis of the patients, including the genes PPP1R8, GPBP1L1, KIAA1614, C14orf23, CCDC77, BVES, EXD3, CD300A, and HEPN1. Collectively, this comprehensive approach not only allowed a highly accurate discrimination of the different TCGA glioma patients but also presented a step forward in advancing our comprehension of the underlying molecular mechanisms driving glioma heterogeneity. Ultimately, our study also revealed novel candidate biomarkers that might constitute potential therapeutic targets, marking a significant stride toward personalized and more effective treatment strategies for patients with glioma.

Glycolysis‑related lncRNA may be associated with prognosis and immune activity in grade II‑III glioma

Glucose metabolism, as a novel theory to explain tumor cell behavior, has been intensively studied in various tumors. The present study explored the long non-coding RNAs (lncRNAs) related to glycolysis in grade II-III glioma, aiming to provide a promising target for further research. Pearson correlation analysis was used to identify glycolysis-related lncRNAs. Univariate/multivariate Cox regression analysis and the Least Absolute Shrinkage and Selection Operator algorithm were applied to identify glycolysis-related lncRNAs to construct a prognosis prediction model. Subsequently, multi-dimensional evaluations were used to verify whether the risk model could predict the prognosis and survival rate of patients with grade II-III glioma. Finally, it was verified by functional experiments. The present study finally identified seven glycolysis-related lncRNAs (CRNDE, AC022034.1, RHOQ-AS1, AL159169.2, AL133215.2, AC007098.1 and LINC02587) to construct a prognosis prediction model. The present study further investigated the underlying immune microenvironment, somatic landscape and functional enrichment pathways. Additionally, individualized immunotherapeutic strategies and candidate compounds were identified to guide clinical treatment. The experimental results demonstrated that CRNDE could increase the proliferation of SHG-44 cells. In conclusion, a large sample of human grade II-III glioma in The Cancer Genome Atlas database was used to construct a risk model using glycolysis-related lncRNAs to predict the prognosis of patients with grade II-III glioma.

DKK3 Expression in Glioblastoma: Correlations with Biomolecular Markers

Glioblastoma is the most common malignant primary tumor of the CNS. The prognosis is dismal, with a median survival of 15 months. Surgical treatment followed by adjuvant therapies such as radiotherapy and chemotherapy characterize the classical strategy. The WNT pathway plays a key role in cellular proliferation, differentiation, and invasion. The DKK3 protein, capable of acting as a tumor suppressor, also appears to be able to modulate the WNT pathway. We performed, in a series of 40 patients, immunohistochemical and Western blot evaluations of DKK3 to better understand how the expression of this protein can influence clinical behavior. We used a statistical analysis, with correlations between the expression of DKK3 and overall survival, age, sex, Ki-67, p53, and MGMT and IDH status. We also correlated our data with information included in the cBioPortal database. In our analyses, DKK3 expression, in both immunohistochemistry and Western blot analyses, was reduced or absent in many cases, showing downregulation. To date, no clinical study exists in the literature that reports a potential correlation between IDH and MGMT status and the WNT pathway through the expression of DKK3. Modulation of this pathway through the expression of DKK3 could represent a new tailored therapeutic strategy in the treatment of glioblastoma.

Dual-Sensitive Fluorescent Nanoprobes for Simultaneously Monitoring In Situ Changes in pH and Matrix Metalloproteinase Expression in Stiffness-Tunable Three-Dimensional In Vitro Scaffolds

A tumor microenvironment often presents altered physicochemical characteristics of the extracellular matrix (ECM) including changes in matrix composition, stiffness, protein expression, pH, temperature, or the presence of certain stromal and immune cells. Of these, overexpression of matrix metalloproteinases (MMPs) and extracellular acidosis are the two major hallmarks of cancer that can be exploited for tumor detection. The change in matrix stiffness and the release of certain cytokines (TNF-α) in the tumor microenvironment play major roles in inducing MMP-9 expression in cancerous cells. This study highlights the role of mechanical cues in upregulating MMP-9 expression in cancerous cells using stiffness-tunable matrix compositions and dual-sensitive fluorescent nanoprobes. Ionically cross-linked 3D alginate/gelatin (AG) scaffolds with three stiffnesses were chosen to reflect the ECM stiffnesses corresponding to healthy and pathological tissues. Moreover, a dual-sensitive nanoprobe, an MMP-sensitive peptide conjugated to carbon nanoparticles with intrinsic pH fluorescence properties, was utilized for in situ monitoring of the two cancer hallmarks in the 3D scaffolds. This platform was further utilized for designing a 3D core-shell platform for spatially mapping tumor margins and for visualizing TNF-α-induced MMP-9 expression in cancerous cells.

Mechanics in the nervous system: From development to disease

Physical forces are ubiquitous in biological processes across scales and diverse contexts. This review highlights the significance of mechanical forces in nervous system development, homeostasis, and disease. We provide an overview of mechanical signals present in the nervous system and delve into mechanotransduction mechanisms translating these mechanical cues into biochemical signals. During development, mechanical cues regulate a plethora of processes, including cell proliferation, differentiation, migration, network formation, and cortex folding. Forces then continue exerting their influence on physiological processes, such as neuronal activity, glial cell function, and the interplay between these different cell types. Notably, changes in tissue mechanics manifest in neurodegenerative diseases and brain tumors, potentially offering new diagnostic and therapeutic target opportunities. Understanding the role of cellular forces and tissue mechanics in nervous system physiology and pathology adds a new facet to neurobiology, shedding new light on many processes that remain incompletely understood.

Functional Roles of CD133: More than Stemness Associated Factor Regulated by the Microenvironment

CD133 protein has been one of the most used surface markers to select and identify cancer cells with stem-like features. However, its expression is not restricted to tumoral cells; it is also expressed in differentiated cells and stem/progenitor cells in various normal tissues. CD133 participates in several cellular processes, in part orchestrating signal transduction of essential pathways that frequently are dysregulated in cancer, such as PI3K/Akt signaling and the Wnt/β-catenin pathway. CD133 expression correlates with enhanced cell self-renewal, migration, invasion, and survival under stress conditions in cancer. Aside from the intrinsic cell mechanisms that regulate CD133 expression in each cellular type, extrinsic factors from the surrounding niche can also impact CD33 levels. The enhanced CD133 expression in cells can confer adaptive advantages by amplifying the activation of a specific signaling pathway in a context-dependent manner. In this review, we do not only describe the CD133 physiological functions known so far, but importantly, we analyze how the microenvironment changes impact the regulation of CD133 functions emphasizing its value as a marker of cell adaptability beyond a cancer-stem cell marker.

Human Ductal Carcinoma In Situ: Advances and Future Perspectives

Due to widespread adoption of screening mammography, there has been a significant increase in new diagnoses of ductal carcinoma in situ (DCIS). However, DCIS outcomes remain unclear. A large fraction of human DCIS (>50%) may not need the multimodality treatment options currently offered to all DCIS patients. More importantly, while we may be overtreating many, we cannot identify those most at risk of invasion or metastasis following a DCIS diagnosis. This review summarizes the studies that have furthered our understanding of DCIS pathology and mechanisms of invasive progression by using advanced technologies including spatial genomics, transcriptomics, and multiplex proteomics. This review also highlights a need for rethinking DCIS with a more focused view on epithelial states and programs and their cross talk with the microenvironment.

Fibrotic Matrix Induces Mesenchymal Transformation of Epithelial Cells in Oral Submucous Fibrosis

Oral submucous fibrosis (OSF) is a potentially malignant disorder of the oral mucosa; however, whether and how the fibrotic matrix of OSF is involved in the malignant transformation of epithelial cells remains unknown. Herein, oral mucosa tissue from patients with OSF, OSF rat models, and their controls were used to observe the extracellular matrix changes and epithelial-mesenchymal transformation (EMT) in fibrotic lesions. Compared with controls, oral mucous tissues from patients with OSF showed an increased number of myofibroblasts, a decreased number of blood vessels, and increased type I and type III collagen levels. In addition, the oral mucous tissues from humans and OSF rats showed increased stiffness, accompanied by increased EMT activities of epithelial cells. The EMT activities of stiff construct-cultured epithelial cells were increased significantly by exogenous piezo-type mechanosensitive ion channel component 1 (Piezo1) activation, and decreased by yes-associated protein (YAP) inhibition. During ex vivo implantation, oral mucosal epithelial cells of the stiff group showed increased EMT activities and increased levels of Piezo1 and YAP compared with those in the sham and soft groups. These results indicate that increased stiffness of the fibrotic matrix in OSF led to increased proliferation and EMT of mucosal epithelial cells, in which the Piezo1-YAP signal transduction is important.

Cancer stem cells in brain tumors: From origin to clinical implications

Malignant brain tumors are highly heterogeneous tumors with a poor prognosis and a high morbidity and mortality rate in both children and adults. The cancer stem cell (CSC, also named tumor-initiating cell) model states that tumor growth is driven by a subset of CSCs. This model explains some of the clinical observations of brain tumors, including the almost unavoidable tumor recurrence after initial successful chemotherapy and/or radiotherapy and treatment resistance. Over the past two decades, strategies for the identification and characterization of brain CSCs have improved significantly, supporting the design of new diagnostic and therapeutic strategies for brain tumors. Relevant studies have unveiled novel characteristics of CSCs in the brain, including their heterogeneity and distinctive immunobiology, which have provided opportunities for new research directions and potential therapeutic approaches. In this review, we summarize the current knowledge of CSCs markers and stemness regulators in brain tumors. We also comprehensively describe the influence of the CSCs niche and tumor microenvironment on brain tumor stemness, including interactions between CSCs and the immune system, and discuss the potential application of CSCs in brain-based therapies for the treatment of brain tumors.

Characterizing viscoelastic properties of human melanoma tissue using Prony series

Melanoma is the most invasive and deadly skin cancer, which causes most of the deaths from skin cancer. It has been demonstrated that the mechanical properties of tumor tissue are significantly altered. However, data about characterizing the mechanical properties of in vivo melanoma tissue are extremely scarce. In addition, the viscoelastic or viscous properties of melanoma tissue are rarely reported. In this study, we measured and quantitated the viscoelastic properties of human melanoma tissues based on the stress relaxation test, using the indentation-based mechanical analyzer that we developed previously. The melanoma tissues from eight patients of different ages (57–95), genders (male and female patients), races (White and Asian), and sites (nose, arm, shoulder, and chest) were excised and tested. The results showed that the elastic property (i.e., shear modulus) of melanoma tissue was elevated compared to normal tissue, while the viscous property (i.e., relaxation time) was reduced. Moreover, the tissue thickness had a significant impact on the viscoelastic properties, probably due to the amount of the adipose layer. Our findings provide new insights into the role of the viscous and elastic properties of melanoma cell mechanics, which may be implicated in the disease state and progression.

Screening of potential immune-related genes expressed during sepsis using gene sequencing technology

To screen potential pivotal targets in sepsis through peripheral blood. Septic patients (n = 23) and healthy volunteers (n = 10) were enrolled according to SEPSIS 3.0. Peripheral blood was collected within 24 h of enrollment, RNA-seq was performed on the peripheral blood. The sequencing data was screened for DEGs (p < 0.01; logFC ≥ 2). PPI, WGCNA and survival curve analysis were used to identify potential targets. Then, 5 PBMC samples were conducted by single-cell sequencing for cell lineage location. Finally, mouse sepsis model and clinic samples were performed to verify the targets gene using RNA-seq and RT-PCR, respectively. Compared to the control group, 1007 DEGs were found in septic group. BCL9L, BCL11B, CD247, CD96, MAFG and SAMD3 were in the core of network. These six genes correlated to the survival rate of septic patients and they were mainly expressed in T cells, except that MAFG was located in monocyte cell. The expression levels of six key genes were confirmed by animal and clinical samples. BCL9L, BCL11B, CD247, CD96 and SAMD3 were decreased in sepsis and mainly expressed in the T cell; while MAFG increased in sepsis and localizes to monocytes. These genes may be therapeutic targets for sepsis.

Gastrointestinal pan-cancer landscape of tumor matrix heterogeneity identifies biologically distinct matrix stiffness subtypes predicting prognosis and chemotherapy efficacy

Gastrointestinal (GI) cancers are a heterogeneous group of primary solid tumors, arising in GI tract from the esophagus to rectum. Matrix stiffness (MS) is a critical physical factor for cancer progression; however, its importance in tumor progression remains to be comprehensively recognized. Herein, we conducted a comprehensive pan-cancer analysis of MS subtypes across seven GI-cancer types. Using unsupervised clustering based on literature-derived MS-specific pathway signatures, the GI-tumor samples were divided into three MS subtypes, termed as the Soft, Mixed and Stiff. Then, distinct prognoses, biological features, tumor microenvironments and mutation landscapes among three MS subtypes were revealed. The Stiff tumor subtype was associated with the poorest prognosis, the most malignant biological behaviors, and the immunosuppressive tumor stromal microenvironment. Furthermore, multiple machine learning algorithms were used to develop an 11-gene MS-signature to identify the MS subtypes of GI-caner and predict chemotherapy sensitivity, which were further validated in two external GI-cancer cohorts. This novel MS-based classification on GI-cancers could enhance our understanding of the important role of MS in tumor progression, and may have implications for the optimization of individualized cancer management.

Substrate stiffness effect on molecular crosstalk of epithelial-mesenchymal transition mediators of human glioblastoma cells

The complexity of the microenvironment effects on cell response, show accumulating evidence that glioblastoma (GBM) migration and invasiveness are influenced by the mechanical rigidity of their surroundings. The epithelial–mesenchymal transition (EMT) is a well-recognized driving force of the invasive behavior of cancer. However, the primary mechanisms of EMT initiation and progression remain unclear. We have previously showed that certain substrate stiffness can selectively stimulate human GBM U251-MG and GL15 glioblastoma cell lines motility. The present study unifies several known EMT mediators to uncover the reason of the regulation and response to these stiffnesses. Our results revealed that changing the rigidity of the mechanical environment tuned the response of both cell lines through change in morphological features, epithelial-mesenchymal markers (E-, N-Cadherin), EGFR and ROS expressions in an interrelated manner. Specifically, a stiffer microenvironment induced a mesenchymal cell shape, a more fragmented morphology, higher intracellular cytosolic ROS expression and lower mitochondrial ROS. Finally, we observed that cells more motile showed a more depolarized mitochondrial membrane potential. Unravelling the process that regulates GBM cells’ infiltrative behavior could provide new opportunities for identification of new targets and less invasive approaches for treatment.

Correlation of Matrisome-Associatted Gene Expressions with LOX Family Members in Astrocytomas Stratified by IDH Mutation Status

Tumor cell infiltrative ability into surrounding brain tissue is a characteristic of diffusely infiltrative astrocytoma and is strongly associated with extracellular matrix (ECM) stiffness. Collagens are the most abundant ECM scaffolding proteins and contribute to matrix organization and stiffness. LOX family members, copper-dependent amine oxidases, participate in the collagen and elastin crosslinking that determine ECM tensile strength. Common IDH mutations in lower-grade gliomas (LGG) impact prognosis and have been associated with ECM stiffness. We analyzed the expression levels of LOX family members and matrisome-associated genes in astrocytoma stratified by malignancy grade and IDH mutation status. A progressive increase in expression of all five LOX family members according to malignancy grade was found. LOX, LOXL1, and LOXL3 expression correlated with matrisome gene expressions. LOXL1 correlations were detected in LGG with IDH mutation (IDH^mut), LOXL3 correlations in LGG with IDH wild type (IDH^wt) and strong LOX correlations in glioblastoma (GBM) were found. These increasing correlations may explain the increment of ECM stiffness and tumor aggressiveness from LGG-IDH^mut and LGG-IDH^wt through to GBM. The expression of the mechanosensitive transcription factor, β-catenin, also increased with malignancy grade and was correlated with LOXL1 and LOXL3 expression, suggesting involvement of this factor in the outside–in signaling pathway.

Identification of Prognostic Genes in Gliomas Based on Increased Microenvironment Stiffness

With a median survival time of 15 months, glioblastoma multiforme is one of the most aggressive primary brain cancers. The crucial roles played by the extracellular matrix (ECM) stiffness in glioma progression and treatment resistance have been reported in numerous studies. However, the association between ECM-stiffness-regulated genes and the prognosis of glioma patients remains to be explored. Thus, using bioinformatics analysis, we first identified 180 stiffness-dependent genes from an RNA-Seq dataset, and then evaluated their prognosis in The Cancer Genome Atlas (TCGA) glioma dataset. Our results showed that 11 stiffness-dependent genes common between low- and high-grade gliomas were prognostic. After validation using the Chinese Glioma Genome Atlas (CGGA) database, we further identified four stiffness-dependent prognostic genes: FN1, ITGA5, OSMR, and NGFR. In addition to high-grade glioma, overexpression of the four-gene signature also showed poor prognosis in low-grade glioma patients. Moreover, our analysis confirmed that the expression levels of stiffness-dependent prognostic genes in high-grade glioma were significantly higher than in low-grade glioma, suggesting that these genes were associated with glioma progression. Based on a pathophysiology-inspired approach, our findings illuminate the link between ECM stiffness and the prognosis of glioma patients and suggest a signature of four stiffness-dependent genes as potential therapeutic targets.

Nanomechanical and Morphological AFM Mapping of Normal Tissues and Tumors on Live Brain Slices Using Specially Designed Embedding Matrix and Laser-Shaped Cantilevers

Cell and tissue nanomechanics has been intriguingly introduced into biomedical research, not only complementing traditional immunophenotyping and molecular analysis, but also bringing unexpected new insights for clinical diagnostics and bioengineering. However, despite the progress in the study of individual cells in culture by atomic force microscopy (AFM), its application for mapping live tissues has a number of technical limitations. Here, we elaborate a new technique to study live slices of normal brain tissue and tumors by combining morphological and nanomechanical AFM mapping in high throughput scanning mode, in contrast to the typically utilized force spectroscopy mode based on single-point probe application. This became possible due to the combined use of an appropriate embedding matrix for vibratomy and originally modified AFM probes. The embedding matrix composition was carefully developed by regulating the amounts of agar and collagen I to reach optimal viscoelastic properties for obtaining high-quality live slices that meet AFM requirements. AFM tips were rounded by irradiating them with focused nanosecond laser pulses, while the resulting tip morphology was verified by scanning electron microscopy. Live slices preparation and AFM investigation take only 55 min and could be combined with a vital cell tracer analysis or immunostaining, thus making it promising for biomedical research and clinical diagnostics.

Matrix Stiffness Contributes to Cancer Progression by Regulating Transcription Factors

Simple Summary

Matrix stiffness is recognized as a critical factor in cancer progression. Recent studies have shown that matrix stiffening is caused by the accumulation, contraction, and crosslinking of the extracellular matrix by cancer and stromal cells. Cancer and stromal cells respond to matrix stiffness, which determines the phenotypes of these cells. In addition, matrix stiffness activates and/or inactivates specific transcription factors in cancer and stromal cells to regulate cancer progression. In this review, we discuss the mechanisms of cancer stiffening and progression that are regulated by transcription factors responding to matrix stiffness.

Abstract

Matrix stiffness is critical for the progression of various types of cancers. In solid cancers such as mammary and pancreatic cancers, tumors often contain abnormally stiff tissues, mainly caused by stiff extracellular matrices due to accumulation, contraction, and crosslinking. Stiff extracellular matrices trigger mechanotransduction, the conversion of mechanical cues such as stiffness of the matrix to biochemical signaling in the cells, and as a result determine the cellular phenotypes of cancer and stromal cells in tumors. Transcription factors are key molecules for these processes, as they respond to matrix stiffness and are crucial for cellular behaviors. The Yes-associated protein (YAP)/transcriptional coactivator with PDZ-binding motif (TAZ) is one of the most studied transcription factors that is regulated by matrix stiffness. The YAP/TAZ are activated by a stiff matrix and promotes malignant phenotypes in cancer and stromal cells, including cancer-associated fibroblasts. In addition, other transcription factors such as β-catenin and nuclear factor kappa B (NF-κB) also play key roles in mechanotransduction in cancer tissues. In this review, the mechanisms of stiffening cancer tissues are introduced, and the transcription factors regulated by matrix stiffness in cancer and stromal cells and their roles in cancer progression are shown.

Mechanical Properties in the Glioma Microenvironment: Emerging Insights and Theranostic Opportunities

Gliomas represent the most common malignant primary brain tumors, and a high-grade subset of these tumors including glioblastoma are particularly refractory to current standard-of-care therapies including maximal surgical resection and chemoradiation. The prognosis of patients with these tumors continues to be poor with existing treatments and understanding treatment failure is required. The dynamic interplay between the tumor and its microenvironment has been increasingly recognized as a key mechanism by which cellular adaptation, tumor heterogeneity, and treatment resistance develops. Beyond ongoing lines of investigation into the peritumoral cellular milieu and microenvironmental architecture, recent studies have identified the growing role of mechanical properties of the microenvironment. Elucidating the impact of these biophysical factors on disease heterogeneity is crucial for designing durable therapies and may offer novel approaches for intervention and disease monitoring. Specifically, pharmacologic targeting of mechanical signal transduction substrates such as specific ion channels that have been implicated in glioma progression or the development of agents that alter the mechanical properties of the microenvironment to halt disease progression have the potential to be promising treatment strategies based on early studies. Similarly, the development of technology to measure mechanical properties of the microenvironment in vitro and in vivo and simulate these properties in bioengineered models may facilitate the use of mechanical properties as diagnostic or prognostic biomarkers that can guide treatment. Here, we review current perspectives on the influence of mechanical properties in glioma with a focus on biophysical features of tumor-adjacent tissue, the role of fluid mechanics, and mechanisms of mechanical signal transduction. We highlight the implications of recent discoveries for novel diagnostics, therapeutic targets, and accurate preclinical modeling of glioma.

The effect of mechanical force in genitourinary malignancies

INTRODUCTION

Mechanical force is attributed to the formation of tumor blood vessels, influences cancer cell invasion and metastasis, and promotes reprogramming of the energy metabolism. Currently, therapy strategies for the tumor microenvironment are being developed progressively. The purpose of this article is to discuss the molecular mechanism, diagnosis, and treatment of mechanical force in urinary tract cancers and outline the medications used in the mechanical microenvironment.

AREAS COVERED

This review covers the complex mechanical elements in the microenvironment of urinary system malignancies, focusing on mechanical molecular mechanisms for diagnosis and treatment.

EXPERT OPINION

The classification of various mechanical forces, such as matrix stiffness, shear force, and other forces, is relatively straightforward. However, little is known about the molecular process of mechanical forces in urinary tract malignancies. Because mechanical therapy is still controversial, it is critical to understand the molecular basis of mechanical force before adding mechanical therapy solutions.

The Role of Cancer-Associated Fibroblast as a Dynamic Player in Mediating Cancer Stemness in the Tumor Microenvironment

The enrichment of cancer-associated fibroblast (CAFs) in a tumor microenvironment (TME) cultivates a pro-tumorigenic niche via aberrant paracrine signaling and matrix remodeling. A favorable niche is critical to the maintenance of cancer stem cells (CSCs), a population of cells that are characterized by their enhanced ability to self-renew, metastasis, and develop therapy resistance. Mounting evidence illustrates the interplay between CAF and cancer cells expedites malignant progression. Therefore, targeting the key cellular components and factors in the niche may promote a more efficacious treatment. In this study, we discuss how CAF orchestrates a niche that enhances CSC features and the potential therapeutic implication.

Opposed Interplay between IDH1 Mutations and the WNT/β-Catenin Pathway: Added Information for Glioma Classification

Gliomas are the main common primary intraparenchymal brain tumor in the central nervous system (CNS), with approximately 7% of the death caused by cancers. In the WHO 2016 classification, molecular dysregulations are part of the definition of particular brain tumor entities for the first time. Nevertheless, the underlying molecular mechanisms remain unclear. Several studies have shown that 75% to 80% of secondary glioblastoma (GBM) showed IDH1 mutations, whereas only 5% of primary GBM have IDH1 mutations. IDH1 mutations lead to better overall survival in gliomas patients. IDH1 mutations are associated with lower stimulation of the HIF-1α a, aerobic glycolysis and angiogenesis. The stimulation of HIF-1α and the process of angiogenesis appears to be activated only when hypoxia occurs in IDH1-mutated gliomas. In contrast, the observed upregulation of the canonical WNT/β-catenin pathway in gliomas is associated with proliferation, invasion, aggressive-ness and angiogenesis.. Molecular pathways of the malignancy process are involved in early stages of WNT/β-catenin pathway-activated-gliomas, and this even under normoxic conditions. IDH1 mutations lead to decreased activity of the WNT/β-catenin pathway and its enzymatic targets. The opposed interplay between IDH1 mutations and the canonical WNT/β-catenin pathway in gliomas could participate in better understanding of the observed evolution of different tumors and could reinforce the glioma classification.