The nanomechanical signature of liver cancer tissues and its molecular origin

Tunneling nanotubes mediate KRas transport: Inducing tumor heterogeneity and altering cellular membrane mechanical properties

Mutation in oncogene KRas plays a crucial role in the occurrence and progression of numerous malignant tumors. Malignancy involves changes in cell mechanics for extensive cellular deformation during metastatic dissemination. We hypothesize that oncogene KRas mutations are intrinsic to alterations in cellular mechanics that promote malignant tumor generation and progression. Here, we demonstrate the use of optical tweezers coupled with a confocal fluorescence imaging system and gene interference technique to reveal that the mutant KRas protein can be transported between homogeneous and heterogeneous tumor cells by tunneling nanotubes (TNTs), resulting in a significant reduction of membrane tension and acceleration of membrane phospholipid flow in the recipient cells. Simultaneously, the changes in membrane mechanical properties of the tumor cells also enhance the metastatic and invasive ability of the tumors, which further contribute to the deterioration of the tumors. This finding helps to clarify the association between oncogene mutations and changes in the mechanical properties of tumor cells, which provides a theoretical basis for the development of cancer treatment strategies. STATEMENT OF SIGNIFICANCE: Here, we present a laser confocal fluorescence system integrated with optical tweezers to observe the transfer of mutant KRasG12D protein from mutant cells to wild-type cells through TNTs. Malignancy involves changes in cell mechanics for extensive cellular deformation during metastatic dissemination. Our results demonstrate a significant decrease in membrane tension and an increase in membrane phospholipid flow in recipient cells. These alterations in mechanical properties augment the migration and invasive capabilities of tumor cells, contributing to tumor malignancy. Our findings propose that cellular mechanical properties could serve as new markers for tumor development, and targeting membrane tension may hold potential as a therapeutic strategy.

Beyond stiffness: Multiscale viscoelastic features as biomechanical markers for assessing cell types and states

Cell mechanics are pivotal in regulating cellular activities, diseases progression, and cancer development. However, the understanding of how cellular viscoelastic properties vary in physiological and pathological stimuli remains scarce. Here, we develop a hybrid self-similar hierarchical theory-microrheology approach to accurately and efficiently characterize cellular viscoelasticity. Focusing on two key cell types associated with livers fibrosis-the capillarized liver sinusoidal endothelial cells and activated hepatic stellate cells-we uncover a universal two-stage power-law rheology characterized by two distinct exponents, αshort and αlong. The mechanical profiles derived from both exponents exhibit significant potential for discriminating among diverse cells. This finding suggests a potential common dynamic creep characteristic across biological systems, extending our earlier observations in soft tissues. Using a tailored hierarchical model for cellular mechanical structures, we discern significant variations in the viscoelastic properties and their distribution profiles across different cell types and states from the cytoplasm (elastic stiffness E1 and viscosity η), to a single cytoskeleton fiber (elastic stiffness E2), and then to the cell level (transverse expansion stiffness E3). Importantly, we construct a logistic-regression-based machine-learning model using the dynamic parameters that outperforms conventional cell-stiffness-based classifiers in assessing cell states, achieving an area under the curve of 97% vs. 78%. Our findings not only advance a robust framework for monitoring intricate cell dynamics but also highlight the crucial role of cellular viscoelasticity in discerning cell states across a spectrum of liver diseases and prognosis, offering new avenues for developing diagnostic and therapeutic strategies based on cellular viscoelasticity.

Insights into the mechanobiology of cancer metastasis via microfluidic technologies

During cancer metastasis, cancer cells will encounter various microenvironments with diverse physical characteristics. Changes in these physical characteristics such as tension, stiffness, viscosity, compression, and fluid shear can generate biomechanical cues that affect cancer cells, dynamically influencing numerous pathophysiological mechanisms. For example, a dense extracellular matrix drives cancer cells to reorganize their cytoskeleton structures, facilitating confined migration, while this dense and restricted space also acts as a physical barrier that potentially results in nuclear rupture. Identifying these pathophysiological processes and understanding their underlying mechanobiological mechanisms can aid in the development of more effective therapeutics targeted to cancer metastasis. In this review, we outline the advances of engineering microfluidic devices in vitro and their role in replicating tumor microenvironment to mimic in vivo settings. We highlight the potential cellular mechanisms that mediate their ability to adapt to different microenvironments. Meanwhile, we also discuss some important mechanical cues that still remain challenging to replicate in current microfluidic devices in future direction. While much remains to be explored about cancer mechanobiology, we believe the developments of microfluidic devices will reveal how these physical cues impact the behaviors of cancer cells. It will be crucial in the understanding of cancer metastasis, and potentially contributing to better drug development and cancer therapy.

Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine learning (ML) framework, which integrates light gradient boosting machine and multivariate imputation by chained equations to enhance liver status assessment using biomechanical markers. Building upon our previously established multiscale mechanical characteristics in fibrotic and treated livers, this framework employs Gaussian Bayesian optimization for post-imputation, significantly improving classification performance. Our findings indicate a marked increase in the precision of liver fibrosis diagnosis and provide a novel, quantitative approach for assessing fibrosis treatment. This innovative combination of multiscale biomechanical markers with advanced ML algorithms represents a transformative step in liver disease diagnostics and treatment evaluation, with potential implications for other areas in medical diagnostics.

Mechanical properties of human hepatic tissues to develop liver-mimicking phantoms for medical applications

Using liver phantoms for mimicking human tissue in clinical training, disease diagnosis, and treatment planning is a common practice. The fabrication material of the liver phantom should exhibit mechanical properties similar to those of the real liver organ in the human body. This tissue-equivalent material is essential for qualitative and quantitative investigation of the liver mechanisms in producing nutrients, excretion of waste metabolites, and tissue deformity at mechanical stimulus. This paper reviews the mechanical properties of human hepatic tissues to develop liver-mimicking phantoms. These properties include viscosity, elasticity, acoustic impedance, sound speed, and attenuation. The advantages and disadvantages of the most common fabrication materials for developing liver tissue-mimicking phantoms are also highlighted. Such phantoms will give a better insight into the real tissue damage during the disease progression and preservation for transplantation. The liver tissue-mimicking phantom will raise the quality assurance of patient diagnostic and treatment precision and offer a definitive clinical trial data collection.

The Revolution in Breast Cancer Diagnostics: From Visual Inspection of Histopathology Slides to Using Desktop Tissue Analysers for Automated Nanomechanical Profiling of Tumours

We aim to develop new portable desktop tissue analysers (DTAs) to provide fast, low-cost, and precise test results for fast nanomechanical profiling of tumours. This paper will explain the reasoning for choosing indentation-type atomic force microscopy (IT-AFM) to reveal the functional details of cancer. Determining the subtype, cancer stage, and prognosis will be possible, which aids in choosing the best treatment. DTAs are based on fast IT-AFM at the size of a small box that can be made for a low budget compared to other clinical imaging tools. The DTAs can work in remote areas and all parts of the world. There are a number of direct benefits: First, it is no longer needed to wait a week for the pathology report as the test will only take 10 min. Second, it avoids the complicated steps of making histopathology slides and saves costs of labour. Third, computers and robots are more consistent, more reliable, and more economical than human workers which may result in fewer diagnostic errors. Fourth, the IT-AFM analysis is capable of distinguishing between various cancer subtypes. Fifth, the IT-AFM analysis could reveal new insights about why immunotherapy fails. Sixth, IT-AFM may provide new insights into the neoadjuvant treatment response. Seventh, the healthcare system saves money by reducing diagnostic backlogs. Eighth, the results are stored on a central server and can be accessed to develop strategies to prevent cancer. To bring the IT-AFM technology from the bench to the operation theatre, a fast IT-AFM sensor needs to be developed and integrated into the DTAs.

DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images

BACKGROUND

Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC).

METHODS

DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets. Then, we assessed its association with prognosis and treatment response. The multi-omics analysis and multiplex Immunohistochemistry were conducted to evaluate the potential pathogenesis and spatial immune contexture underlying DPS.

RESULTS

Multivariate analysis indicated that the DPS was an independent prognosticator with a better C-index (0.84 for overall survival and 0.71 for disease-free survival). Patients with low-DPS after neoadjuvant chemotherapy responded favorably to treatment. Spatial analysis indicated that exhausted immune clusters and increased infiltration of CD11b+CD11c+ immune cells were present at the invasive margin of high-DPS group. Multi-omics data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) hint at the relevance of DPS to myeloid derived suppressor cells infiltration and immune suppression.

CONCLUSION

DeepRisk network is a reliable tool that enhances prognostic value of TNM staging and aid in precise treatment, providing insights into the underlying pathogenic mechanisms.

Nanomechanical-based classification of prostate tumor using atomic force microscopy

BACKGROUND

The loss of mechanical homeostasis between tumor cells and microenvironment is an important factor in tumor metastasis. In the process, mechanical forces affect cell proliferation, differentiation, migration and tissue development.

AIMS

Using high spatial resolution of Atomic force microscopy (AFM) technology, our study provides the direct measurement of the nanomechanical properties of prostate cancer clinical tissue specimens.

MATERIALS AND METHODS

AFM was used to determine the biomechanical properties of prostate tissue with different grade scores. K-means clustering method and fuzzy C-means were used to distinguish the cellular component in prostate tissue from non-cellular component based on their viscoelasticity. Futhermore, AFM measurements in vitro cells, including metastatic prostate cells (PC-3) and normal human prostate cells (PZ-HPV-7) were carried out.

RESULTS

The Young's modulus was decreased in prostate cancer progression, and the elasticity of cellular component in prostate cancer tissue was smaller than that of normal prostate tissue. PC-3 cells were softer than PZ-HPV-7 cells. Further mechanism investigation showed that the difference in modulus between cancerous and normal prostate tissue may be associated with a greater actin cytoskeleton distribution inside the cancer cells.

CONCLUSION

The results suggests that the nanomechanical properties can classify the prostate tumor, which could be used as an index for the identification and classification of cancer at cellular level.

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.

Viscoelastic Multiscale Mechanical Indexes for Assessing Liver Fibrosis and Treatment Outcomes

Understanding liver tissue mechanics, particularly in the context of liver pathologies like fibrosis, cirrhosis, and carcinoma, holds pivotal significance for assessing disease severity and prognosis. Although the static mechanical properties of livers have been gradually studied, the intricacies of their dynamic mechanics remain enigmatic. Here, we characterize the dynamic creep responses of healthy, fibrotic, and mesenchymal stem cells (MSCs)-treated fibrotic lives. Strikingly, we unearth a ubiquitous two-stage power-law rheology of livers across different time scales with the exponents and their distribution profiles highly correlated to liver status. Moreover, our self-similar hierarchical theory effectively captures the delicate changes in the dynamical mechanics of livers. Notably, the viscoelastic multiscale mechanical indexes (i.e., power-law exponents and elastic stiffnesses of different hierarchies) and their distribution characteristics prominently vary with liver fibrosis and MSCs therapy. This study unveils the viscoelastic characteristics of livers and underscores the potential of proposed mechanical criteria for assessing disease evolution and prognosis.

The Mechanics of Tumor Cells Dictate Malignancy via Cytoskeleton-Mediated APC/Wnt/β-Catenin Signaling

Tumor cells progressively remodel cytoskeletal structures and reduce cellular stiffness during tumor progression, implicating the correlation between cell mechanics and malignancy. However, the roles of tumor cell cytoskeleton and the mechanics in tumor progression remain incompletely understood. We report that softening/stiffening tumor cells by targeting actomyosin promotes/suppresses self-renewal in vitro and tumorigenic potential in vivo. Weakening/strengthening actin cytoskeleton impairs/reinforces the interaction between adenomatous polyposis coli (APC) and β-catenin, which facilitates β-catenin nuclear/cytoplasmic localization. Nuclear β-catenin binds to the promoter of Oct4, which enhances its transcription that is crucial in sustaining self-renewal and malignancy. These results demonstrate that the mechanics of tumor cells dictate self-renewal through cytoskeleton-APC-Wnt/β-catenin-Oct4 signaling, which are correlated with tumor differentiation and patient survival. This study unveils an uncovered regulatory role of cell mechanics in self-renewal and malignancy, and identifies tumor cell mechanics as a hallmark not only for cancer diagnosis but also for mechanotargeting.

Atomic Force Microscopy Methods to Measure Tumor Mechanical Properties

Atomic force microscopy (AFM) is a popular tool for evaluating the mechanical properties of biological materials (cells and tissues) at high resolution. This technique has become particularly attractive to cancer researchers seeking to bridge the gap between mechanobiology and cancer initiation, progression, and treatment resistance. The majority of AFM studies thus far have been extensively focused on the nanomechanical characterization of cells. However, these approaches fail to capture the complex and heterogeneous nature of a tumor and its host organ. Over the past decade, efforts have been made to characterize the mechanical properties of tumors and tumor-bearing tissues using AFM. This has led to novel insights regarding cancer mechanopathology at the tissue scale. In this Review, we first explain the principles of AFM nanoindentation for the general study of tissue mechanics. We next discuss key considerations when using this technique and preparing tissue samples for analysis. We then examine AFM application in characterizing the mechanical properties of cancer tissues. Finally, we provide an outlook on AFM in the field of cancer mechanobiology and its application in the clinic.

Insights in Cell Biomechanics through Atomic Force Microscopy

We review the advances obtained by using Atomic Force Microscopy (AFM)-based approaches in the field of cell/tissue mechanics and adhesion, comparing the solutions proposed and critically discussing them. AFM offers a wide range of detectable forces with a high force sensitivity, thus allowing a broad class of biological issues to be addressed. Furthermore, it allows for the accurate control of the probe position during the experiments, providing spatially resolved mechanical maps of the biological samples with subcellular resolution. Nowadays, mechanobiology is recognized as a subject of great relevance in biotechnological and biomedical fields. Focusing on the past decade, we discuss the intriguing issues of cellular mechanosensing, i.e., how cells sense and adapt to their mechanical environment. Next, we examine the relationship between cell mechanical properties and pathological states, focusing on cancer and neurodegenerative diseases. We show how AFM has contributed to the characterization of pathological mechanisms and discuss its role in the development of a new class of diagnostic tools that consider cell mechanics as new tumor biomarkers. Finally, we describe the unique ability of AFM to study cell adhesion, working quantitatively and at the single-cell level. Again, we relate cell adhesion experiments to the study of mechanisms directly or secondarily involved in pathologies.

Pancreatic Cancer Presents Distinct Nanomechanical Properties During Progression

Cancer progression is closely related to changes in the structure and mechanical properties of the tumor microenvironment (TME). In many solid tumors, including pancreatic cancer, the interplay among the different components of the TME leads to a desmoplastic reaction mainly due to collagen overproduction. Desmoplasia is responsible for the stiffening of the tumor, poses a major barrier to effective drug delivery and has been associated with poor prognosis. The understanding of the involved mechanisms in desmoplasia and the identification of nanomechanical and collagen-based properties that characterize the state of a particular tumor can lead to the development of novel diagnostic and prognostic biomarkers. In this study, in vitro experiments were conducted using two human pancreatic cell lines. Morphological and cytoskeleton characteristics, cells' stiffness and invasive properties were assessed using optical and atomic force microscopy techniques and cell spheroid invasion assay. Subsequently, the two cell lines were used to develop orthotopic pancreatic tumor models. Tissue biopsies were collected at different times of tumor growth for the study of the nanomechanical and collagen-based optical properties of the tissue using Atomic Force Microscopy (AFM) and picrosirius red polarization microscopy, respectively. The results from the in vitro experiments demonstrated that the more invasive cells are softer and present a more elongated shape with more oriented F-actin stress fibers. Furthermore, ex vivo studies of orthotopic tumor biopsies on MIAPaCa-2 and BxPC-3 murine tumor models highlighted that pancreatic cancer presents distinct nanomechanical and collagen-based optical properties relevant to cancer progression. The stiffness spectrums (in terms of Young's modulus values) showed that the higher elasticity distributions were increasing during cancer progression mainly due desmoplasia (collagen overproduction), while a lower elasticity peak was evident - due to cancer cells softening - on both tumor models. Optical microscopy studies highlighted that collagen content increases while collagen fibers tend to form align patterns. Consequently, during cancer progression nanomechanical and collagen-based optical properties alter in relation to changes in collagen content. Therefore, they have the potential to be used as novel biomarkers for assessing and monitoring tumor progression and treatment outcomes.

Constructing 3D In Vitro Models of Heterocellular Solid Tumors and Stromal Tissues Using Extrusion-Based Bioprinting

Malignant tumor tissues exhibit inter- and intratumoral heterogeneities, aberrant development, dynamic stromal composition, diverse tissue phenotypes, and cell populations growing within localized mechanical stresses in hypoxic conditions. Experimental tumor models employing engineered systems that isolate and study these complex variables using in vitro techniques are under development as complementary methods to preclinical in vivo models. Here, advances in extrusion bioprinting as an enabling technology to recreate the three-dimensional tumor milieu and its complex heterogeneous characteristics are reviewed. Extrusion bioprinting allows for the deposition of multiple materials, or selected cell types and concentrations, into models based upon physiological features of the tumor. This affords the creation of complex samples with representative extracellular or stromal compositions that replicate the biology of patient tissue. Biomaterial engineering of printable materials that replicate specific features of the tumor microenvironment offer experimental reproducibility, throughput, and physiological relevance compared to animal models. In this review, we describe the potential of extrusion-based bioprinting to recreate the tumor microenvironment within in vitro models.

Nanomechanical properties of solid tumors as treatment monitoring biomarkers

Many tumors, such as types of sarcoma and breast cancer, stiffen as they grow in a host healthy tissue, while individual cancer cells are becoming softer. Tumor stiffening poses major pathophysiological barriers to the effective delivery of drugs and compromises treatment efficacy. It has been established that normalization of the mechanical properties of a tumor by targeting components of the tumor microenvironment (TME) enhances the delivery of anti-cancer agents and consequently the therapeutic outcome. Consequently, there is an urgent need for the development of biomarkers, which characterize the mechanical state of a particular tumor for the development of personalized treatments or for monitoring therapeutic strategies that target the TME. In this work, Atomic Force Microscopy (AFM) was used to assess human and murine nanomechanical properties from tumor biopsies. In the case of murine tumor models, the nanomechanical properties during tumor progression were measured and a TME normalization drug (tranilast) along with chemotherapy doxorubicin were employed in order to investigate whether AFM has the ability to capture changes in the nanomechanical properties of a tumor during treatment. The nanomechanical data were further correlated with ex vivo characterization of structural components of the TME. The results highlighted that nanomechanical properties alter during cancer progression and AFM measurements are sensitive enough to capture even small alterations during different types of treatments, namely normalization and chemotherapy. The identification of unique AFM-based nanomechanical properties can lead to the development of biomarkers for treatment prediction and monitoring. STATEMENT OF SIGNIFICANCE: Cancer progression is associated with vast remodeling of the tumor microenvironment resulting in changes in the mechanical properties of the tissue. Indeed, many tumors stiffen as they grow and this stiffening compromises treatment efficacy. As a result, a number of treatments target tumor microenvironment in order to normalize its mechanical properties. Consequently, there is an urgent need for the development of innovative tools that can assess the mechanical properties of a particular tumor and monitor tumor progression and treatment outcomes. This work highlights the use of atomic force microscopy (AFM) for assessing the elasticity spectrum of solid tumors at different stages and during treatment. This knowledge is essential for the development of AFM-based nanomechanical biomarkers for treatment prediction and monitoring.

Improvement of the cell viability of hepatocytes cultured in three-dimensional collagen gels using pump-free perfusion driven by water level difference

Cell-containing collagen gels are one of the materials employed in tissue engineering and drug testing. A collagen gel is a useful three-dimensional (3D) scaffold that improves various cell functions compared to traditional two-dimensional plastic substrates. However, owing to poor nutrient availability, cells are not viable in thick collagen gels. Perfusion is an effective method for supplying nutrients to the gel. In this study, we maintained hepatocytes embedded in a 3D collagen gel using a simple pump-free perfusion cell culture system with ordinary cell culture products. Flow was generated by the difference in water level in the culture medium. Hepatocytes were found to be viable in a collagen gel of thickness 3.26 (± 0.16 S.E.)-mm for 3 days. In addition, hepatocytes had improved proliferation and gene expression related to liver function in a 3D collagen gel compared to a 2D culture dish. These findings indicate that our perfusion method is useful for investigating the cellular functions of 3D hydrogels.

Melanoma Detection by AFM Indentation of Histological Specimens

Melanoma is visible unlike other types of cancer, but it is still challenging to diagnose correctly because of the difficulty in distinguishing between benign nevus and melanoma. We conducted a robust investigation of melanoma, identifying considerable differences in local elastic properties between nevus and melanoma tissues by using atomic force microscopy (AFM) indentation of histological specimens. Specifically, the histograms of the elastic modulus of melanoma displayed multimodal Gaussian distributions, exhibiting heterogeneous mechanical properties, in contrast with the unimodal distributions of elastic modulus in the benign nevus. We identified this notable signature was consistent regardless of blotch incidence by sex, age, anatomical site (e.g., thigh, calf, arm, eyelid, and cheek), or cancer stage (I, IV, and V). In addition, we found that the non-linearity of the force-distance curves for melanoma is increased compared to benign nevus. We believe that AFM indentation of histological specimens may technically complement conventional histopathological analysis for earlier and more precise melanoma detection.

Multiscale biomechanics and mechanotransduction from liver fibrosis to cancer

A growing body of multiscale biomechanical studies has been proposed to highlight the mechanical cues in the development of hepatic fibrosis and cancer. At the cellular level, changes in mechanical microenvironment induce phenotypic and functional alterations of hepatic cells, initiating a positive feedback loop that promotes liver fibrogenesis and hepatocarcinogenesis. Tumor mechanical microenvironment of hepatocellular carcinoma facilitates tumor cell growth and metastasis, and hinders the drug delivery and immunotherapy. At the molecular level, mechanical forces are sensed and transmitted into hepatic cells via allosteric activation of mechanoreceptors on the cell membrane, leading to the activation of various mechanotransduction pathways including integrin and YAP signaling and then regulating cell function. Thus, the application of mechanomedicine concept in the treatment of liver diseases is promising for rational design and cell-specific delivery of therapeutic drugs. This review mainly discusses the correlation between biomechanical cues and liver diseases from the viewpoint of mechanobiology.

Insights into intercellular receptor-ligand binding kinetics in cell communication

Cell-cell communication is crucial for cells to sense, respond and adapt to environmental cues and stimuli. The intercellular communication process, which involves multiple length scales, is mediated by the specific binding of membrane-anchored receptors and ligands. Gaining insight into two-dimensional receptor-ligand binding kinetics is of great significance for understanding numerous physiological and pathological processes, and stimulating new strategies in drug design and discovery. To this end, extensive studies have been performed to illuminate the underlying mechanisms that control intercellular receptor-ligand binding kinetics via experiment, theoretical analysis and numerical simulation. It has been well established that the cellular microenvironment where the receptor-ligand interaction occurs plays a vital role. In this review, we focus on the advances regarding the regulatory effects of three factors including 1) protein-membrane interaction, 2) biomechanical force, and 3) bioelectric microenvironment to summarize the relevant experimental observations, underlying mechanisms, as well as their biomedical significances and applications. Meanwhile, we introduce modeling methods together with experiment technologies developed for dealing with issues at different scales. We also outline future directions to advance the field and highlight that building up systematic understandings for the coupling effects of these regulatory factors can greatly help pharmaceutical development.

Mechanobiology of Colorectal Cancer

Simple Summary

It is well documented that colorectal cancer (CRC) is the third most common cancer type, responsible for high mortality in developed countries, resulting in a high socio-economic impact. Several biochemical and gene expression pathways explaining the manifestation of this cancer in humans have already been identified. However, explanations for some of the related biophysical mechanisms and their influence on CRC remain elusive. In CRC, biophysics and medical research have already revealed the importance of studying the effects of the stiffness and viscoelasticity of the substrate on cells, as well as the effect of the shear stress of blood and lymphatic vessels on the behavior of cells and tissues. A deeper understanding of the relationship between the biophysical cues and biochemical signals could be advantageous to develop new diagnostic techniques and therapeutic strategies. Being a disease with a high mortality rate, it becomes crucial to dedicate efforts to finding effective, alternative therapeutic strategies.

Abstract

In this review, the mechanobiology of colorectal cancer (CRC) are discussed. Mechanotransduction of CRC is addressed considering the relationship of several biophysical cues and biochemical pathways. Mechanobiology is focused on considering how it may influence epithelial cells in terms of motility, morphometric changes, intravasation, circulation, extravasation, and metastization in CRC development. The roles of the tumor microenvironment, ECM, and stroma are also discussed, taking into account the influence of alterations and surface modifications on mechanical properties and their impact on epithelial cells and CRC progression. The role of cancer-associated fibroblasts and the impact of flow shear stress is addressed in terms of how it affects CRC metastization. Finally, some insights concerning how the knowledge of biophysical mechanisms may contribute to the development of new therapeutic strategies and targeting molecules and how mechanical changes of the microenvironment play a role in CRC disease are presented.

Atomic Force Microscopy for Tumor Research at Cell and Molecule Levels

Tumors have posed a serious threat to human life and health. Researchers can determine whether or not cells are cancerous, whether the cancer cells are invasive or metastatic, and what the effects of drugs are on cancer cells by the physical properties such as hardness, adhesion, and Young's modulus. The atomic force microscope (AFM) has emerged as a key important tool for biomechanics research on tumor cells due to its ability to image and collect force spectroscopy information of biological samples with nano-level spatial resolution and under near-physiological conditions. This article reviews the existing results of the study of cancer cells with AFM. The main foci are the operating principle of AFM and research advances in mechanical property measurement, ultra-microtopography, and molecular recognition of tumor cells, which allows us to outline what we do know it in a systematic way and to summarize and to discuss future directions.

Cancer cell mechanobiology: a new frontier for cancer research

The study of physical and mechanical features of cancer cells, or cancer cell mechanobiology, is a new frontier in cancer research. Such studies may enhance our understanding of the disease process, especially mechanisms associated with cancer cell invasion and metastasis, and may help the effort of developing diagnostic biomarkers and therapeutic drug targets. Cancer cell mechanobiological changes are associated with the complex interplay of activation/inactivation of multiple signaling pathways, which can occur at both the genetic and epigenetic levels, and the interactions with the cancer microenvironment. It has been shown that metastatic tumor cells are more compliant than morphologically similar benign cells in actual human samples. Subsequent studies from us and others further demonstrated that cell mechanical properties are strongly associated with cancer cell invasive and metastatic potential, and thus may serve as a diagnostic marker of detecting cancer cells in human body fluid samples. In this review, we provide a brief narrative of the molecular mechanisms underlying cancer cell mechanobiology, the technological platforms utilized to study cancer cell mechanobiology, the status of cancer cell mechanobiological studies in various cancer types, and the potential clinical applications of cancer cell mechanobiological study in cancer early detection, diagnosis, and treatment.

Cells on Hydrogels with Micron-Scaled Stiffness Patterns Demonstrate Local Stiffness Sensing

Cell rigidity sensing-a basic cellular process allowing cells to adapt to mechanical cues-involves cell capabilities exerting force on the extracellular environment. In vivo, cells are exposed to multi-scaled heterogeneities in the mechanical properties of the surroundings. Here, we investigate whether cells are able to sense micron-scaled stiffness textures by measuring the forces they transmit to the extracellular matrix. To this end, we propose an efficient photochemistry of polyacrylamide hydrogels to design micron-scale stiffness patterns with kPa/µm gradients. Additionally, we propose an original protocol for the surface coating of adhesion proteins, which allows tuning the surface density from fully coupled to fully independent of the stiffness pattern. This evidences that cells pull on their surroundings by adjusting the level of stress to the micron-scaled stiffness. This conclusion was achieved through improvements in the traction force microscopy technique, e.g., adapting to substrates with a non-uniform stiffness and achieving a submicron resolution thanks to the implementation of a pyramidal optical flow algorithm. These developments provide tools for enhancing the current understanding of the contribution of stiffness alterations in many pathologies, including cancer.

The biophysics of cancer: emerging insights from micro- and nanoscale tools

Cancer is a complex and dynamic disease that is aberrant both biologically and physically. There is growing appreciation that physical abnormalities with both cancer cells and their microenvironment that span multiple length scales are important drivers for cancer growth and metastasis. The scope of this review is to highlight the key advancements in micro- and nano-scale tools for delineating the cause and consequences of the aberrant physical properties of tumors. We focus our review on three important physical aspects of cancer: 1) solid mechanical properties, 2) fluid mechanical properties, and 3) mechanical alterations to cancer cells. Beyond posing physical barriers to the delivery of cancer therapeutics, these properties are also known to influence numerous biological processes, including cancer cell invasion and migration leading to metastasis, and response and resistance to therapy. We comment on how micro- and nanoscale tools have transformed our fundamental understanding of the physical dynamics of cancer progression and their potential for bridging towards future applications at the interface of oncology and physical sciences.

NKG2D discriminates diverse ligands through selectively mechano-regulated ligand conformational changes

Stimulatory immune receptor NKG2D binds diverse ligands to elicit differential anti‐tumor and anti‐virus immune responses. Two conflicting degeneracy recognition models based on static crystal structures and in‐solution binding affinities have been considered for almost two decades. Whether and how NKG2D recognizes and discriminates diverse ligands still remain unclear. Using live‐cell‐based single‐molecule biomechanical assay, we characterized the in situ binding kinetics of NKG2D interacting with different ligands in the absence or presence of mechanical force. We found that mechanical force application selectively prolonged NKG2D interaction lifetimes with the ligands MICA and MICB, but not with ULBPs, and that force‐strengthened binding is much more pronounced for MICA than for other ligands. We also integrated steered molecular dynamics simulations and mutagenesis to reveal force‐induced rotational conformational changes of MICA, involving formation of additional hydrogen bonds on its binding interface with NKG2D, impeding MICA dissociation under force. We further provided a kinetic triggering model to reveal that force‐dependent affinity determines NKG2D ligand discrimination and its downstream NK cell activation. Together, our results demonstrate that NKG2D has a discrimination power to recognize different ligands, which depends on selective mechanical force‐induced ligand conformational changes.

Targeting Tumor-Stromal Interactions in Pancreatic Cancer: Impact of Collagens and Mechanical Traits

Pancreatic ductal adenocarcinoma (PDAC) has one of the worst outcomes among cancers with a 5-years survival rate of below 10%. This is a result of late diagnosis and the lack of effective treatments. The tumor is characterized by a highly fibrotic stroma containing distinct cellular components, embedded within an extracellular matrix (ECM). This ECM-abundant tumor microenvironment (TME) in PDAC plays a pivotal role in tumor progression and resistance to treatment. Cancer-associated fibroblasts (CAFs), being a dominant cell type of the stroma, are in fact functionally heterogeneous populations of cells within the TME. Certain subtypes of CAFs are the main producer of the ECM components of the stroma, with the most abundant one being the collagen family of proteins. Collagens are large macromolecules that upon deposition into the ECM form supramolecular fibrillar structures which provide a mechanical framework to the TME. They not only bring structure to the tissue by being the main structural proteins but also contain binding domains that interact with surface receptors on the cancer cells. These interactions can induce various responses in the cancer cells and activate signaling pathways leading to epithelial-to-mesenchymal transition (EMT) and ultimately metastasis. In addition, collagens are one of the main contributors to building up mechanical forces in the tumor. These forces influence the signaling pathways that are involved in cell motility and tumor progression and affect tumor microstructure and tissue stiffness by exerting solid stress and interstitial fluid pressure on the cells. Taken together, the TME is subjected to various types of mechanical forces and interactions that affect tumor progression, metastasis, and drug response. In this review article, we aim to summarize and contextualize the recent knowledge of components of the PDAC stroma, especially the role of different collagens and mechanical traits on tumor progression. We furthermore discuss different experimental models available for studying tumor-stromal interactions and finally discuss potential therapeutic targets within the stroma.

Stain-free identification of tissue pathology using a generative adversarial network to infer nanomechanical signatures

Intraoperative frozen section analysis can be used to improve the accuracy of tumour margin estimation during cancer resection surgery through rapid processing and pathological assessment of excised tissue. Its applicability is limited in some cases due to the additional risks associated with prolonged surgery, largely from the time-consuming staining procedure. Our work uses a measurable property of bulk tissue to bypass the staining process: as tumour cells proliferate, they influence the surrounding extra-cellular matrix, and the resulting change in elastic modulus provides a signature of the underlying pathology. In this work we accurately localise atomic force microscopy measurements of human liver tissue samples and train a generative adversarial network to infer elastic modulus from low-resolution images of unstained tissue sections. Pathology is predicted through unsupervised clustering of parameters characterizing the distributions of inferred values, achieving 89% accuracy for all samples based on the nominal assessment (n = 28), and 95% for samples that have been validated by two independent pathologists through post hoc staining (n = 20). Our results demonstrate that this technique could increase the feasibility of intraoperative frozen section analysis for use during resection surgery and improve patient outcomes.

DIAPH1 Promotes Laryngeal Squamous Cell Carcinoma Progression Through Cell Cycle Regulation

The diaphanous related formin 1 (DIAPH1) protein is involved in the regulation of dynamic cytoskeleton reorganization, which is closely related to mitosis and the cell cycle. Cell cycle disorders are generally regarded as important underlying causes of many cancers. In the current study, we have revealed that DIAPH1 expression is an independent prognostic factor for overall survival in patients with laryngeal squamous cell carcinoma (LSCC) and that DIAPH1 promotes colony formation, cell proliferation, and G1/S progression in LSCC cells. Additionally, DIAPH1 promotes growth of AMC-HN-8 LSCC-derived tumors in vivo. In this study, RNA-sequencing analysis revealed that DIAPH1 knockdown led to changes in the expression of genes associated with signaling during the cell cycle. Using western blot analyses, we further demonstrated that DIAPH1 knockdown resulted in upregulation of p21^Waf1/Cip1, p19^Ink4d, p27^Kip1, and p16^Ink4a and downregulation of cyclinA2, cyclinD1, CDK2, CDK4, and CDK6. These results suggest that DIAPH1 influences the expression of genes in several signaling pathways and promotes LSCC progression by regulating the cell cycle.

"May the Force Be with You!" Force-Volume Mapping with Atomic Force Microscopy

Information of the chemical, mechanical, and electrical properties of materials can be obtained using force volume mapping (FVM), a measurement mode of scanning probe microscopy (SPM). Protocols have been developed with FVM for a broad range of materials, including polymers, organic films, inorganic materials, and biological samples. Multiple force measurements are acquired with the FVM mode within a defined 3D volume of the sample to map interactions (i.e., chemical, electrical, or physical) between the probe and the sample. Forces of adhesion, elasticity, stiffness, deformation, chemical binding interactions, viscoelasticity, and electrical properties have all been mapped at the nanoscale with FVM. Subsequently, force maps can be correlated with features of topographic images for identifying certain chemical groups presented at a sample interface. The SPM tip can be coated to investigate-specific reactions; for example, biological interactions can be probed when the tip is coated with biomolecules such as for recognition of ligand-receptor pairs or antigen-antibody interactions. This review highlights the versatility and diverse measurement protocols that have emerged for studies applying FVM for the analysis of material properties at the nanoscale.

Effects of Lipid Deposition on Viscoelastic Response in Human Hepatic Cell Line HepG2

Hepatic steatosis is associated with various liver diseases. The main pathological feature of steatosis is the excessive lipid accumulation. Ultrasound has been extensively used for the diagnosis of hepatic steatosis. However, most ultrasound-based non-invasive methods are still not accurate enough for cases with light lipid infiltration. One important reason is that the extent to which lipid infiltration may affect mechanical properties of hepatocytes remains unknown. In this work, we used atomic force microscope and in vitro dose-dependent lipid deposition model to detect the quantitative changes of mechanical properties under different degrees of steatosis in a single-cell level. The results show that hepatic cells with lipid deposition can be treated as linear viscoelastic materials with the power law creep compliance and relaxation modulus. Further analysis showed that even slight accumulation of lipid can lead to measurable decrease of stiffness and increased fluidity in liver cells. The accurate detection of viscoelastic properties of hepatocytes and the analysis methods may provide novel insights into hepatic steatosis grading, especially in the very early stage with reversible liver lesion. The application of viscoelasticity index for grading fat deposition might be a new detection indicator in future clinical diagnosis.

Atomic Force Microscope Nanoindentation Analysis of Diffuse Astrocytic Tumor Elasticity: Relation with Tumor Histopathology

This study aims to investigate the influence of isocitrate dehydrogenase gene family (IDH) mutations, World Health Organization (WHO) grade, and mechanical preconditioning on glioma and adjacent brain elasticity through standard monotonic and repetitive atomic force microscope (AFM) nanoindentation. The elastic modulus was measured ex vivo on fresh tissue specimens acquired during craniotomy from the tumor and the peritumoral white matter of 16 diffuse glioma patients. Linear mixed-effects models examined the impact of tumor traits and preconditioning on tissue elasticity. Tissues from IDH-mutant cases were stiffer than those from IDH-wildtype ones among anaplastic astrocytoma patients (p = 0.0496) but of similar elasticity to IDH-wildtype cases for diffuse astrocytoma patients (p = 0.480). The tumor was found to be non-significantly softer than white matter in anaplastic astrocytomas (p = 0.070), but of similar elasticity to adjacent brain in diffuse astrocytomas (p = 0.492) and glioblastomas (p = 0.593). During repetitive indentation, both tumor (p = 0.002) and white matter (p = 0.003) showed initial stiffening followed by softening. Stiffening was fully reversed in white matter (p = 0.942) and partially reversed in tumor (p = 0.015). Tissue elasticity comprises a phenotypic characteristic closely related to glioma histopathology. Heterogeneity between patients should be further explored.

Cell-stiffness and morphological architectural patterns in clinical samples of high grade serous ovarian cancers

High grade serous ovarian carcinoma (HGSOC) is recognized as the most frequent type of ovarian cancer and the main cause of ovarian cancer related deaths worldwide. Although homologous recombination deficiency testing has been adopted in the clinical workflow, morphological analysis remains the main diagnostic tool. In this study Atomic Force Microscopy (AFM) was tested in standard hematoxylin and eosin (H&E) stained sections to investigate the biomechanical properties of different architectural growing patterns of HGSOC. Our results showed that AFM was able to discriminate HGSOC morphological growing patterns as well as patients' stage. Micropapillary pattern, which has been associated to poor outcome, had lower Young's moduli. In addition stage IV HGSOC was significantly softer than stage III cancers. Based on our results, AFM analysis could represent an additional tool in HGSOC morphological diagnosis as the biomechanical proprieties of HGSOC were quantitatively associated to tumor staging and architectural pattern.

Recent Advances in the Label-Free Characterization of Exosomes for Cancer Liquid Biopsy: From Scattering and Spectroscopy to Nanoindentation and Nanodevices

Exosomes (EXOs) are nano-sized vesicles secreted by most cell types. They are abundant in bio-fluids and harbor specific molecular constituents from their parental cells. Due to these characteristics, EXOs have a great potential in cancer diagnostics for liquid biopsy and personalized medicine. Despite this unique potential, EXOs are not yet widely applied in clinical settings, with two main factors hindering their translational process in diagnostics. Firstly, conventional extraction methods are time-consuming, require large sample volumes and expensive equipment, and often do not provide high-purity samples. Secondly, characterization methods have some limitations, because they are often qualitative, need extensive labeling or complex sampling procedures that can induce artifacts. In this context, novel label-free approaches are rapidly emerging, and are holding potential to revolutionize EXO diagnostics. These methods include the use of nanodevices for EXO purification, and vibrational spectroscopies, scattering, and nanoindentation for characterization. In this progress report, we summarize recent key advances in label-free techniques for EXO purification and characterization. We point out that these methods contribute to reducing costs and processing times, provide complementary information compared to the conventional characterization techniques, and enhance flexibility, thus favoring the discovery of novel and unexplored EXO-based biomarkers. In this process, the impact of nanotechnology is systematically highlighted, showing how the effectiveness of these techniques can be enhanced using nanomaterials, such as plasmonic nanoparticles and nanostructured surfaces, which enable the exploitation of advanced physical phenomena occurring at the nanoscale level.

Biomechanical Properties of Cancer Cells

Since the crucial role of the microenvironment has been highlighted, many studies have been focused on the role of biomechanics in cancer cell growth and the invasion of the surrounding environment. Despite the search in recent years for molecular biomarkers to try to classify and stratify cancers, much effort needs to be made to take account of morphological and nanomechanical parameters that could provide supplementary information concerning tissue complexity adaptation during cancer development. The biomechanical properties of cancer cells and their surrounding extracellular matrix have actually been proposed as promising biomarkers for cancer diagnosis and prognosis. The present review first describes the main methods used to study the mechanical properties of cancer cells. Then, we address the nanomechanical description of cultured cancer cells and the crucial role of the cytoskeleton for biomechanics linked with cell morphology. Finally, we depict how studying interaction of tumor cells with their surrounding microenvironment is crucial to integrating biomechanical properties in our understanding of tumor growth and local invasion.

A New Approach for the AFM-Based Mechanical Characterization of Biological Samples

The AFM nanoindentation technique is a powerful tool for the mechanical characterization of biological samples at the nanoscale. The data analysis of the experimentally obtained results is usually performed using the Hertzian contact mechanics. However, the aforementioned theory can be applied only in cases that the sample is homogeneous and isotropic and presents a linear elastic response. However, biological samples often present depth-dependent mechanical properties, and the Hertzian analysis cannot be used. Thus, in this paper, a different approach is presented, based on a new physical quantity used for the determination of the mechanical properties at the nanoscale. The aforementioned physical quantity is the work done by the indenter per unit volume. The advantages of the presented analysis are significant since the abovementioned magnitude can be used to examine if a sample can be approximated to an elastic half-space. If this approximation is valid, then the new proposed method enables the accurate calculation of Young's modulus. Additionally, it can be used to explore the mechanical properties of samples that are characterized by a depth-dependent mechanical behavior. In conclusion, the proposed analysis presents an accurate yet simple technique for the determination of the mechanical properties of biological samples at the nanoscale that can be also used beyond the Hertzian limit.

Spatial mapping of the collagen distribution in human and mouse tissues by force volume atomic force microscopy

Changes in the elastic properties of living tissues during normal development and in pathological processes are often due to modifications of the collagen component of the extracellular matrix at various length scales. Force volume AFM can precisely capture the mechanical properties of biological samples with force sensitivity and spatial resolution. The integration of AFM data with data of the molecular composition contributes to understanding the interplay between tissue biochemistry, organization and function. The detection of micrometer-size, heterogeneous domains at different elastic moduli in tissue sections by AFM has remained elusive so far, due to the lack of correlations with histological, optical and biochemical assessments. In this work, force volume AFM is used to identify collagen-enriched domains, naturally present in human and mouse tissues, by their elastic modulus. Collagen identification is obtained in a robust way and affordable timescales, through an optimal design of the sample preparation method and AFM parameters for faster scan with micrometer resolution. The choice of a separate reference sample stained for collagen allows correlating elastic modulus with collagen amount and position with high statistical significance. The proposed preparation method ensures safe handling of the tissue sections guarantees the preservation of their micromechanical characteristics over time and makes it much easier to perform correlation experiments with different biomarkers independently.

Application of atomic force microscope in diagnosis of single cancer cells

Changes in mechanical properties of cells are closely related to a variety of diseases. As an advanced technology on the micro/nano scale, atomic force microscopy is the most suitable tool for information acquisition of living cells in human body fluids. AFMs are able to measure and characterize the mechanical properties of cells which can be used as effective markers to distinguish between different cell types and cells in different states (benign or cancerous). Therefore, they can be employed to obtain additional information to that obtained via the traditional biochemistry methods for better identifying and diagnosing cancer cells for humans, proposing better treatment methods and prognosis, and unravelling the pathogenesis of the disease. In this report, we review the use of AFMs in cancerous tissues, organs, and cancer cells cultured in vitro to obtain cellular mechanical properties, demonstrate and summarize the results of AFMs in cancer biology, and look forward to possible future applications and the direction of development.

Baicalein inhibits non-small-cell lung cancer invasion and metastasis by reducing ezrin tension in inflammation microenvironment

Baicalein, a flavonoid phytochemical, has been shown to be effective as an anti‐metastatic agent for various cancers, especially for non‐small‐cell lung cancer (NSCLC). However, the underlying mechanism of how baicalein targets cellular processes during NSCLC cell invasion and metastasis remains elusive. In this study, we found that non‐cytotoxic concentrations of baicalein still retained anti‐dissemination activity both in vitro and in vivo. Using a genetic encoding tension probe based on Förster resonance energy transfer (FRET) theory, baicalein was shown to significantly decrease ezrin tension by downregulating cellular ezrin S‐nitrosylation (SNO) levels in NSCLC cells in the inflammatory microenvironment. Decreased ezrin tension inhibited the formation of an aggressive phenotype of NSCLC cell and leader cell in collective migration, and subsequently suppressed NSCLC dissemination. Baicalein restrained SNO‐mediated ezrin tension by decreasing iNOS expression levels. Overall this study demonstrates the novel mechanism used by baicalein to suppress NSCLC invasion and metastasis from a mechanopharmacology perspective and illustrates a new direction for drug development.

Mechanical properties of human glioma

Brain gliomas represent some of the most aggressive tumors encountered by modern medicine and, despite major efforts to optimize early diagnosis and treatment, the prognosis remains poor. Due to the complex structure of the brain and the unique mechanical properties of the extracellular matrix, gliomas invade and expand into the brain parenchyma, along white matter tracts and within perivascular spaces, usually sparing normal vessels. Different methods have been developed to study the mechanical properties of gliomas in a wide range of scales, from cells and the microscale to tissues and the macroscale. In this review, the current view on glioma mechanics is presented and the methods used to determine glioma mechanical properties are outlined. Their principles and current state of affairs are discussed.

Diphenylalanine-Derivative Peptide Assemblies with Increased Aromaticity Exhibit Metal-like Rigidity and High Piezoelectricity

Diphenylalanine (FF) represents the simplest peptide building block that self-assembles into ordered nanostructures with interesting physical properties. Among self-assembled peptide structures, FF nanotubes display notable stiffness and piezoelectric parameters (Young's modulus = 19-27 GPa, strain coefficient d33 = 18 pC/N). Yet, inorganic alternatives remain the major materials of choice for many applications due to higher stiffness and piezoelectricity. Here, aiming to broaden the applications of the FF motif in materials chemistry, we designed three phenyl-rich dipeptides based on the β,β-diphenyl-Ala-OH (Dip) unit: Dip-Dip, cyclo-Dip-Dip, and tert-butyloxycarbonyl (Boc)-Dip-Dip. The doubled number of aromatic groups per unit, compared to FF, produced a dense aromatic zipper network with a dramatically improved Young's modulus of ∼70 GPa, which is comparable to aluminum. The piezoelectric strain coefficient d33 of ∼73 pC/N of such assembly exceeds that of poled polyvinylidene-fluoride (PVDF) polymers and compares well to that of lead zirconium titanate (PZT) thin films and ribbons. The rationally designed π-π assemblies show a voltage coefficient of 2-3 Vm/N, an order of magnitude higher than PVDF, improved thermal stability up to 360 °C (∼60 °C higher than FF), and useful photoluminescence with wide-range excitation-dependent emission in the visible region. Our data demonstrate that aromatic groups improve the rigidity and piezoelectricity of organic self-assembled materials for numerous applications.

Fluidity and elasticity form a concise set of viscoelastic biomarkers for breast cancer diagnosis based on Kelvin-Voigt fractional derivative modeling

Cancer progression involves biomechanical changes within transformed cells and the surrounding extracellular matrix (ECM). The viscoelastic features of fluidity and elasticity that are based on a novel Kelvin-Voigt fractional derivative (KVFD) model were found capable of discriminating normal, benign and malignant breast biopsy tissues on the cellular scale. The improved specificity of KVFD model parameters derives from greater accuracy of fitting the entire approaching force-indentation measurement curve ([Formula: see text] > 0.99) compared with traditional elastic models ([Formula: see text] < 0.86). Moreover, model parameters can be interpreted in terms of histopathological features. First, statistical comparisons reveal there are significant differences (p < 0.001) in elasticity E₀, fluidity [Formula: see text], and viscosity [Formula: see text] among healthy, benign, and malignant groups. Malignant breast tissues show low-value, broad-distributions in E₀ and with high fluidity [Formula: see text] as compared with healthy and benign tissues. Second, histograms of E₀ and [Formula: see text] provide distinctive features by fitting to Gaussian mixture (GM) models. The histograms of E₀ and [Formula: see text] are best fit by two kernels GM for malignant tissues, indicating that the cells are soft but with high fluidity and the ECM is stiff but with low fluidity. However, the data suggest one-kernel GM model for benign tissue and a patched uniform distribution for healthy tissue. Third, using fluidity [Formula: see text] as the test statistic, the area under the receiver operator characteristic curve (AUC) is 0.701 ± 0.012 (p < 0.0001) for control versus malignant and 0.706 ± 0.013 (p < 0.0001) for benign versus malignant group. Variations in tissue fluidity and elasticity offer a concise set of viscoelastic biomarkers that correlate well with histopathological features.

Micro/Nano fabricated cantilever based biosensor platform: A review and recent progress

Recent trends in biosensing research have motivated scientists and research professionals to investigate the development of miniaturized bioanalytical devices to make them portable, label-free and smaller in size. The performance of the cantilever-based devices which is one of the very important domains of sensitive field level detection has improved significantly with the development of new micro/nanofabrication technologies and surface functionalization techniques. The cantilevers have scaled down to Nano from micro-level and have become exceptionally sensitive and also have some anomalous associated properties due to the scale. In this review we have discussed about fundamental principles of cantilever operation, detection methods, and previous, present and future approaches of study through cantilever-based sensing platform. Other than that, we have also discussed the past major bio-sensing efforts through micro/nano cantilevers and about recent progress in the field.

Synthetic asters as elastic and radial skeletons

The radial geometry with rays radiated from a common core occurs ubiquitously in nature for its symmetry and functions. Herein, we report a class of synthetic asters with well-defined core-ray geometry that can function as elastic and radial skeletons to harbor nano- and microparticles. We fabricate the asters in a single, facile, and high-yield step that can be readily scaled up; specifically, amphiphilic gemini molecules self-assemble in water into asters with an amorphous core and divergently growing, twisted crystalline ribbons. The asters can spontaneously position microparticles in the cores, along the radial ribbons, or by the outer rims depending on particle sizes and surface chemistry. Their mechanical properties are determined on single- and multiple-aster levels. We further maneuver the synthetic asters as building blocks to form higher-order structures in virtue of aster-aster adhesion induced by ribbon intertwining. We envision the astral structures to act as rudimentary spatial organizers in nanoscience for coordinated multicomponent systems, possibly leading to emergent, synergistic functions.

Nanosystems capable of organisation and the formation of structures are of interest in nanotechnology. Here, the authors report on synthetic asters made of gemini surfactant which are able to position microparticles based on size and chemical composition which can also be organised into higher order structures.

Elucidation of Differential Nano-Textural Attributes for Normal Oral Mucosa and Pre-Cancer

Computational analysis on altered micro-nano-textural attributes of the oral mucosa may provide precise diagnostic information about oral potentially malignant disorders (OPMDs) instead of an existing handful of qualitative reports. This study evaluated micro-nano-textural features of oral epithelium from scanning electron microscopic (SEM) images and the sub-epithelial connective tissue from light microscopic (LM) and atomic force microscopic (AFM) images for normal and OPMD (namely oral sub-mucous fibrosis, i.e., OSF). Objective textural descriptors, namely discrete wavelet transform, gray-level co-occurrence matrix (GLCM), and local binary pattern (LBP), were extracted and fed to standard classifiers. Best classification accuracy of 87.28 and 93.21%; sensitivity of 93 and 96%; specificity of 80 and 91% were achieved, respectively, for SEM and AFM. In the study groups, SEM analysis showed a significant (p < 0.01) variation for all the considered textural descriptors, while for AFM, a remarkable alteration (p < 0.01) was only found in GLCM and LBP. Interestingly, sub-epithelial collagen nanoscale and microscale textural information from AFM and LM images, respectively, were complementary, namely microlevel contrast was more in normal (0.251) than OSF (0.193), while nanolevel contrast was more in OSF (0.283) than normal (0.204). This work, thus, illustrated differential micro-nano-textural attributes for oral epithelium and sub-epithelium to distinguish OPMD precisely and may be contributory in early cancer diagnostics.

Mechanical Heterogeneity in Tissues Promotes Rigidity and Controls Cellular Invasion

We study the influence of cell-level mechanical heterogeneity in epithelial tissues using a vertex-based model. Heterogeneity is introduced into the cell shape index (p_{0}) that tunes the stiffness at a single-cell level. The addition of heterogeneity can always enhance the mechanical rigidity of the epithelial layer by increasing its shear modulus, hence making it more rigid. There is an excellent scaling collapse of our data as a function of a single scaling variable f_{r}, which accounts for the overall fraction of rigid cells. We identify a universal threshold f_{r}^{*} that demarcates fluid versus solid tissues. Furthermore, this rigidity onset is far below the contact percolation threshold of rigid cells. These results give rise to a separation of rigidity and contact percolation processes that leads to distinct types of solid states. We also investigate the influence of heterogeneity on tumor invasion dynamics. There is an overall impedance of invasion as the tissue becomes more rigid. Invasion can also occur in an intermediate heterogeneous solid state that is characterized by significant spatial-temporal intermittency.

Efficient Spatial Sampling for AFM-Based Cancer Diagnostics: A Comparison between Neural Networks and Conventional Data Analysis

Atomic force microscopy (AFM) in spectroscopy mode receives a lot of attention because of its potential in distinguishing between healthy and cancer tissues. However, the AFM translational process in clinical practice is hindered by the fact that it is a time-consuming technique in terms of measurement and analysis time. In this paper, we attempt to address both issues. We propose the use of neural networks for pattern recognition to automatically classify AFM force–distance (FD) curves, with the aim of avoiding curve-fitting with the Sneddon model or more complicated ones. We investigated the applicability of this method to the classification of brain cancer tissues. The performance of the classifier was evaluated with receiving operating characteristic (ROC) curves for the approach and retract curves separately and in combination with each other. Although more complex and comprehensive models are required to demonstrate the general applicability of the proposed approach, preliminary evidence is given for the accuracy of the results, and arguments are presented to support the possible applicability of neural networks to the classification of brain cancer tissues. Moreover, we propose a possible strategy to shorten measurement times based on the estimation of the minimum number of FD curves needed to classify a tissue with a confidence level of 0.005. Taken together, these results have the potential to stimulate the design of more effective protocols to reduce AFM measurement times and to get rid of curve-fitting, which is a complex and time-consuming issue that requires experienced staff with a strong data-analysis background.