Examination of the relationship between viscoelastic properties and the invasion of ovarian cancer cells by atomic force microscopy

Single-cell mechanical assay unveils viscoelastic similarities in normal and neoplastic brain cells

Understanding cancer cell mechanics allows for the identification of novel disease mechanisms, diagnostic biomarkers, and targeted therapies. In this study, we utilized our previously established fluid shear stress assay to investigate and compare the viscoelastic properties of normal immortalized human astrocytes and invasive human glioblastoma (GBM) cells when subjected to physiological levels of shear stress that are present in the brain microenvironment. We used a parallel-flow microfluidic shear system and a camera-coupled optical microscope to expose single cells to fluid shear stress and monitor the resulting deformation in real time, respectively. From the video-rate imaging, we fed cell deformation information from digital image correlation into a three-parameter generalized Maxwell model to quantify the nuclear and cytoplasmic viscoelastic properties of single cells. We further quantified actin cytoskeleton density and alignment in immortalized human astrocytes and GBM cells via fluorescence microscopy and image analysis techniques. Results from our study show that contrary to the behavior of many extracranial cells, normal and cancerous brain cells do not exhibit significant differences in their viscoelastic properties. Moreover, we also found that the viscoelastic properties of the nucleus and cytoplasm as well as the actin cytoskeletal densities of both brain cell types are similar. Our work suggests that malignant GBM cells exhibit unique mechanical behaviors not seen in other cancer cell types. These results warrant future studies to elucidate the distinct biophysical characteristics of the brain and reveal novel mechanical attributes of GBM and other primary brain tumors.

An AFM-Based Model-Fitting-Free Viscoelasticity Characterization Method for Accurate Grading of Primary Prostate Tumor

Viscoelasticity is a crucial property of cells, which plays an important role in label-free cell characterization. This paper reports a model-fitting-free viscoelasticity calculation method, correcting the effects of frequency, surface adhesion and liquid resistance on AFM force-distance (FD) curves. As demonstrated by quantifying the viscosity and elastic modulus of PC-3 cells, this method shows high self-consistency and little dependence on experimental parameters such as loading frequency, and loading mode (Force-volume vs. PeakForce Tapping). The rapid calculating speed of less than 1ms per curve without the need for a model fitting process is another advantage. Furthermore, this method was utilized to characterize the viscoelastic properties of primary clinical prostate cells from 38 patients. The results demonstrate that the reported characterization method a comparable performance with the Gleason Score system in grading prostate cancer cells, This method achieves a high average accuracy of 97.6% in distinguishing low-risk prostate tumors (BPH and GS6) from higher-risk (GS7-GS10) prostate tumors and a high average accuracy of 93.3% in distinguishing BPH from prostate cancer.

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.

Single-cell mechanical analysis reveals viscoelastic similarities between normal and neoplastic brain cells

Understanding cancer cell mechanics allows for the identification of novel disease mechanisms, diagnostic biomarkers, and targeted therapies. In this study, we utilized our previously established fluid shear stress assay to investigate and compare the viscoelastic properties of normal immortalized human astrocytes (IHAs) and invasive human glioblastoma (GBM) cells when subjected to physiological levels of shear stress that are present in the brain microenvironment. We used a parallel-flow microfluidic shear system and a camera-coupled optical microscope to expose single cells to fluid shear stress and monitor the resulting deformation in real-time, respectively. From the video-rate imaging, we fed cell deformation information from digital image correlation into a three-parameter generalized Maxwell model to quantify the nuclear and cytoplasmic viscoelastic properties of single cells. We further quantified actin cytoskeleton density and alignment in IHAs and GBM cells via immunofluorescence microscopy and image analysis techniques. Results from our study show that contrary to the behavior of many extracranial cells, normal and cancerous brain cells do not exhibit significant differences in their viscoelastic behavior. Moreover, we also found that the viscoelastic properties of the nucleus and cytoplasm as well as the actin cytoskeletal densities of both brain cell types are similar. Our work suggests that malignant GBM cells exhibit unique mechanical behaviors not seen in other cancer cell types. These results warrant future study to elucidate the distinct biophysical characteristics of the brain and reveal novel mechanical attributes of GBM and other primary brain tumors.

Assessing the roles of collagen fiber morphology and matrix stiffness on ovarian cancer cell migration dynamics using multiphoton fabricated orthogonal image-based models

Ovarian cancer remains the deadliest of the gynecological cancers, where this arises from poor screening and imaging tools that can detect early disease, and also limited understanding of the structural and functional aspects of the tumor microenvironment. To gain insight into the underlying cellular dynamics, we have used multiphoton excited fabrication to create Second Harmonic Generation (SHG) image-based orthogonal models from collagen/GelMA that represent both the collagen matrix morphology and stiffness (∼2-8 kPa) of normal ovarian stroma and high grade serous ovarian cancers (HGSOC). These scaffolds are used to study migration/cytoskeletal dynamics of normal (IOSE) and ovarian cancer (OVCA433) cell lines. We found that the highly aligned fiber morphology of HGSOC promotes aspects of motility (motility coefficient, motility, and focal adhesion expression) through a contact guidance mechanism and that stiffer matrix further promotes these same processes through a mechanosensitive mechanism, where these trends were similar for both normal and cancer cells. However, cell specific differences were found on these orthogonal models relative to those providing only morphology, showing the importance of presenting both morphology and stiffness cues. Moreover, we found increased cadherin expression and decreased cell alignment only for cancer cells on scaffolds of intermediate modulus suggesting different stiffness-dependent mechanotransduction mechanisms are engaged. This overall approach affords decoupling the roles of matrix morphology, stiffness and cell genotype and affords hypothesis testing of the factors giving rise to disease progression and metastasis. Further, more established fabrication techniques cannot simultaneously reproduce both the 3D collagen fiber morphology and stiffness. STATEMENT OF SIGNIFICANCE: Ovarian cancer metastasizes when lesions are small, where cells exfoliate from the surface of the ovary and reattach at distal sites in the peritoneum. The adhesion/migration dynamics are not well understood and there is a need for new 3D in vitro models of the extracellular matrix to study the biology. Here we use multiphoton excited crosslinking to fabricate ECM orthogonal models that represent the collagen morphology and stiffness in human ovarian tissues. These are then used to study ovarian cancer cell migration dynamics and we found that contact guidance and a mechanosensitive response and cell genotype all combine to affect the behavior. These models provide insight into disease etiology and progression not readily possible by other fabrication methods.

Effects of substrate stiffness on the viscoelasticity and migration of prostate cancer cells examined by atomic force microscopy

The stiffness of the extracellular matrix of tumour cells plays a key role in tumour cell metastasis. However, it is unclear how mechanical properties regulate the cellular response to the environmental matrix. In this study, atomic force microscopy (AFM) and laser confocal imaging were used to qualitatively evaluate the relationship between substrate stiffness and migration of prostate cancer (PCa) cells. Cells cultured on stiff substrates (35 kPa) undergone several interesting phenomena compared to those on soft substrates (3 kPa). Here, the stimulation generated by the stiff substrates triggered the F-actin skeleton to bundle its filaments, increasing the polarity index of the external contour of PCa cells. Analysis of AFM force-distance curves indicated that the elasticity of the cells cultured on 35 kPa substrates increased while the viscosity decreased. Wound-healing experiments showed that PCa cells cultured on 35 kPa substrates have higher migration potential. These phenomena suggested that the mechanical properties may be correlated with the migration of PCa cells. After actin depolymerisation, the elasticity of the PCa cells decreased while the viscosity increased, and the migration ability was correspondingly decreased. In conclusion, this study clearly demonstrated the relationship between substrate stiffness and the mechanical properties of cells in prostate tumour metastasis, providing a basis for understanding the changes in the biomechanical properties at a single-cell level.

Unusual dimeric flavonoids (brachydins) induce ultrastructural membrane alterations associated with antitumor activity in cancer cell lines

Notwithstanding the advances in molecular target-based drugs, chemotherapy remains the most common cancer treatment, despite its high toxicity. Consequently, effective anticancer therapies with fewer adverse effects are needed. Therefore, this study aimed to determine the anticancer activity of the dichloromethane fraction (DCMF) isolated from Arrabidae brachypoda roots, whose components are three unusual dimeric flavonoids. The toxicity of DCMF was investigated in breast (MCF-7), prostate (DU145), and cervical (HeLa) tumor cells, as well as non-tumor cells (PNT2), using sulforhodamine B (cell viability), Comet (genotoxicity), clonogenicity (reproductive capacity) and wound healing (cell migration) assays, and atomic force microscopy (AFM) for ultrastructural cell membrane alterations. Molecular docking revealed affinity between albumin and each rare flavonoid, supporting the impact of fetal bovine serum in DCMF antitumor activity. The IC₅₀ values for MCF7, HeLa, and DU145 were 2.77, 2.46, and 2.51 µg/mL, respectively, and 4.08 µg/mL for PNT2. DCFM was not genotoxic to tumor or normal cells when exposed to twice the IC₅₀ for up to 24 h, but it inhibited tumor cell migration and reproduction compared to normal cells. Additionally, AFM revealed alterations in the ultrastructure of tumor nuclear membrane surfaces, with a positive correlation between DCMF concentration and tumor cell roughness. Finally, we found a negative correlation between roughness and the ability of DCMF-treated tumor cells to migrate and form colonies with more than 50 cells. These findings suggest that DCFM acts by causing ultrastructural changes in tumor cell membranes while having fewer toxicological effects on normal cells.

Ovarian Biomechanics: From Health to Disease

Biomechanics is a physical phenomenon which mainly related with deformation and movement of life forms. As a mechanical signal, it participates in the growth and development of many tissues and organs, including ovary. Mechanical signals not only participate in multiple processes in the ovary but also play a critical role in ovarian growth and normal physiological functions. Additionally, the involvement of mechanical signals has been found in ovarian cancer and other ovarian diseases, prompting us to focus on the roles of mechanical signals in the process of ovarian health to disease. This review mainly discusses the effects and signal transduction of biomechanics (including elastic force, shear force, compressive stress and tensile stress) in ovarian development as a regulatory signal, as well as in the pathological process of normal ovarian diseases and cancer. This review also aims to provide new research ideas for the further research and treatment of ovarian-related diseases.

Personalized models of heterogeneous 3D epithelial tumor microenvironments: Ovarian cancer as a model

Intractable human diseases such as cancers, are context dependent, unique to both the individual patient and to the specific tumor microenvironment. However, conventional cancer treatments are often nonspecific, targeting global similarities rather than unique drivers. This limits treatment efficacy across heterogeneous patient populations and even at different tumor locations within the same patient. Ultimately, this poor efficacy can lead to adverse clinical outcomes and the development of treatment-resistant relapse. To prevent this and improve outcomes, it is necessary to be selective when choosing a patient's optimal adjuvant treatment. In this review, we posit the use of personalized, tumor-specific models (TSM) as tools to achieve this remarkable feat. First, using ovarian cancer as a model disease, we outline the heterogeneity and complexity of both the cellular and extracellular components in the tumor microenvironment. Then we examine the advantages and disadvantages of contemporary cancer models and the rationale for personalized TSM. We discuss how to generate precision 3D models through careful and detailed analysis of patient biopsies. Finally, we provide clinically relevant applications of these versatile personalized cancer models to highlight their potential impact. These models are ideal for a myriad of fundamental cancer biology and translational studies. Importantly, these approaches can be extended to other carcinomas, facilitating the discovery of new therapeutics that more effectively target the unique aspects of each individual patient's TME. STATEMENT OF SIGNIFICANCE: In this article, we have presented the case for the application of biomaterials in developing personalized models of complex diseases such as cancers. TSM could bring about breakthroughs in the promise of precision medicine. The critical components of the diverse tumor microenvironments, that lead to treatment failures, include cellular- and extracellular matrix- heterogeneity, and biophysical signals to the cells. Therefore, we have described these dynamic components of the tumor microenvironments, and have highlighted how contemporary biomaterials can be utilized to create personalized in vitro models of cancers. We have also described the application of the TSM to predict the dynamic patterns of disease progression, and predict effective therapies that can produce durable responses, limit relapses, and treat any minimal residual disease.

Elongation Index as a Sensitive Measure of Cell Deformation in High-Throughput Microfluidic Systems

One of the promising approaches for high-throughput screening of cell mechanotype is microfluidic deformability cytometry (mDC), in which the apparent deformation index (DI) of the cells stretched by extensional flow at the stagnation point of a cross-slot microchannel is measured. The DI is subject to substantial measurement errors due to cell offset from the flow centerline and velocity fluctuations in inlet channels, leading to artificial widening of DI versus cell size plots. Here, we simulated an mDC experiment using a custom computational algorithm for viscoelastic cell migration. Cell motion and deformation in a cross-slot channel was modeled for fixed or randomized values of cellular mechanical properties (diameter, shear elasticity, cortical tension) and initial cell placement, with or without sinusoidal fluctuations between the inlet velocities. Our numerical simulation indicates that mDC loses sensitivity to changes in shear elasticity when the offset distance exceeds 5 μm, and just 1% velocity fluctuation causes an 11.7% drop in the DI. The obtained relationships between the cell diameter, shear elasticity, and offset distance were used to establish a new measure of cell deformation, referred to as the "elongation index" (EI). In the randomized study, the EI scatter plots were visibly separated for the low- and high-elasticity populations of cells, with a mean of 300 and 3500 Pa, whereas the standard DI output was unable to distinguish between these two groups of cells. The successful suppression of the offset artifacts with a narrower data distribution was shown for the EI output of MCF-7 cells.