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BACKGROUND: Although metastasis is the foremost cause of cancer-related death, a specialized mechanism that reprograms anchorage dependency of solid tumor cells into circulating tumor cells (CTCs) during metastatic dissemination remains a critical area of challenge. METHODS: We analyzed blood cell-specific transcripts and selected key Adherent-to-Suspension Transition (AST) factors that are competent to reprogram anchorage dependency of adherent cells into suspension cells in an inducible and reversible manner. The mechanisms of AST were evaluated by a series of in vitro and in vivo assays. Paired samples of primary tumors, CTCs, and metastatic tumors were collected from breast cancer and melanoma mouse xenograft models and patients with de novo metastasis. Analyses of single-cell RNA sequencing (scRNA-seq) and tissue staining were performed to validate the role of AST factors in CTCs. Loss-of-function experiments were performed by shRNA knockdown, gene editing, and pharmacological inhibition to block metastasis and prolong survival. RESULTS: We discovered a biological phenomenon referred to as AST that reprograms adherent cells into suspension cells via defined hematopoietic transcriptional regulators, which are hijacked by solid tumor cells to disseminate into CTCs. Induction of AST in adherent cells 1) suppress global integrin/ECM gene expression via Hippo-YAP/TEAD inhibition to evoke spontaneous cell-matrix dissociation and 2) upregulate globin genes that prevent oxidative stress to acquire anoikis resistance, in the absence of lineage differentiation. During dissemination, we uncover the critical roles of AST factors in CTCs derived from patients with de novo metastasis and mouse models. Pharmacological blockade of AST factors via thalidomide derivatives in breast cancer and melanoma cells abrogated CTC formation and suppressed lung metastases without affecting the primary tumor growth. CONCLUSION: We demonstrate that suspension cells can directly arise from adherent cells by the addition of defined hematopoietic factors that confer metastatic traits. Furthermore, our findings expand the prevailing cancer treatment paradigm toward direct intervention within the metastatic spread of cancer.
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Neoplasias da Mama , Neoplasias Pulmonares , Melanoma , Células Neoplásicas Circulantes , Camundongos , Animais , Humanos , Feminino , Linhagem Celular Tumoral , Células Neoplásicas Circulantes/patologia , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Melanoma/metabolismo , Neoplasias Pulmonares/patologia , Metástase NeoplásicaRESUMO
In quantitative micro-elastography (QME), a pre-characterized compliant layer with a known stress-strain curve is utilized to map stress at the sample surface. However, differences in the boundary conditions of the compliant layer when it is mechanically characterized and when it is used in QME experiments lead to inconsistent stress estimation and consequently, inaccurate elasticity measurements. Here, we propose a novel in situ stress estimation method using an optical coherence tomography (OCT)-based uniaxial compression testing system integrated with the QME experimental setup. By combining OCT-measured axial strain with axial stress determined using a load cell in the QME experiments, we can estimate in situ stress for the compliant layer, more accurately considering its boundary conditions. Our proposed method shows improved accuracy, with an error below 10%, compared to 85% using the existing QME technique with no lubrication. Furthermore, demonstrations on hydrogels and cells indicate the potential of this approach for improving the characterization of the micro-scale mechanical properties of cells and their interactions with the surrounding biomaterial, which has potential for application in cell mechanobiology.
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BACKGROUND AND OBJECTIVES: Techniques for imaging the mechanical properties of cells are needed to study how cell mechanics influence cell function and disease progression. Mechano-microscopy (a high-resolution variant of compression optical coherence elastography) generates elasticity images of a sample undergoing compression from the phase difference between optical coherence microscopy (OCM) B-scans. However, the existing mechano-microscopy signal processing chain (referred to as the algebraic method) assumes the sample stress is uniaxial and axially uniform, such that violation of these assumptions reduces the accuracy and precision of elasticity images. Furthermore, it does not account for prior information regarding the sample geometry or mechanical property distribution. In this study, we investigate the feasibility of training a conditional generative adversarial network (cGAN) to generate elasticity images from phase difference images of samples containing a cell spheroid embedded in a hydrogel. METHODS: To construct the cGAN training and simulated test sets, we generated 30,000 artificial elasticity images using a parametric model and computed the corresponding phase difference images using finite element analysis to simulate compression applied to the artificial samples. We also imaged real MCF7 breast tumor spheroids embedded in hydrogel using mechano-microscopy to construct the experimental test set and evaluated the cGAN using the algebraic elasticity images and co-registered OCM and confocal fluorescence microscopy (CFM) images. RESULTS: Comparison with the simulated test set ground truth elasticity images shows the cGAN produces a lower root mean square error (median: 3.47 kPa, 95 % confidence interval (CI) [3.41, 3.52]) than the algebraic method (median: 4.91 kPa, 95 % CI [4.85, 4.97]). For the experimental test set, the cGAN elasticity images contain features resembling stiff nuclei at locations corresponding to nuclei seen in the algebraic elasticity, OCM, and CFM images. Furthermore, the cGAN elasticity images are higher resolution and more robust to noise than the algebraic elasticity images. CONCLUSIONS: The cGAN elasticity images exhibit better accuracy, spatial resolution, sensitivity, and robustness to noise than the algebraic elasticity images for both simulated and real experimental data.
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Técnicas de Imagem por Elasticidade , Elasticidade , Esferoides Celulares , Humanos , Técnicas de Imagem por Elasticidade/métodos , Células MCF-7 , Algoritmos , Processamento de Imagem Assistida por Computador/métodos , Redes Neurais de Computação , Microscopia/métodos , Tomografia de Coerência Óptica/métodos , Análise de Elementos FinitosRESUMO
The tumor microenvironment presents spatiotemporal shifts in biomechanical properties with cancer progression. Hydrogel biomaterials like GelAGE offer the stiffness tuneability to recapitulate dynamic changes in tumor tissues by altering photo-energy exposures. Here, a tuneable hydrogel with spatiotemporal control of stiffness and mesh-network is developed. The volume of MCF7 spheroids encapsulated in a linear stiffness gradient demonstrates an inverse relationship with stiffness (p < 0.0001). As spheroids are exposed to increased crosslinking (stiffer) and greater mechanical confinement, spheroid stiffness increases. Protein expression (TRPV4, ß1 integrin, E-cadherin, and F-actin) decreases with increasing stiffness while showing strong correlations to spheroid volume (r2 > 0.9). To further investigate the role of volume, MCF7 spheroids are grown in a soft matrix for 5 days prior to a second polymerisation which presents a stiffness gradient to equally expanded spheroids. Despite being exposed to variable stiffness, these spheroids show even protein expression, confirming volume as a key regulator. Overall, this work showcases the versatility of GelAGE and demonstrates volume expansion as a key regulator of 3D mechanosensation in MCF7 breast cancer spheroids. This platform has the potential to further investigation into the role of stiffness and dimensionality in 3D spheroid culture for other types of cancers and diseases.
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Neoplasias da Mama , Humanos , Feminino , Neoplasias da Mama/patologia , Esferoides Celulares/metabolismo , Hidrogéis , Actinas , Microambiente TumoralRESUMO
Breast cancer remains a significant burden with 1 in 8 women affected and metastasis posing a significant challenge for patient survival. Disease progression involves remodeling of the extracellular matrix (ECM). In breast cancer, tissue stiffness increases owing to an increase in collagen production by recruited cancer-associated fibroblasts (CAFs). These stromal modifications are notable during primary tumor growth and have a dualistic action by creating a hard capsule to prevent penetration of anti-cancer therapies and forming a favorable environment for tumor progression. Remodeling of the tumor microenvironment immediately presented to cells can include changes in protein composition, concentration and structural arrangement and provides the first mechanical stimuli in the metastatic cascade. Not surprisingly, metastatic cancer cells possess the ability to mechanically adapt, and their adaptability ensures not only survival but successful invasion within altered environments. In the past decade, the importance of the microenvironment and its regulatory role in diseases have gained traction and this is evident in the shift from plastic culture to the development of novel biomaterials that mimic in vivo tissue. With these advances, elucidations can be made into how ECM remodeling and more specifically, altered cell-ECM adhesions, regulate tumor growth and cancer cell plasticity. Such enabling tools in mechanobiology will identify fundamental mechanisms in cancer progression that eventually help develop preventative and therapeutic treatment from a clinical perspective. This review will focus on current platforms engineered to mimic the micro and nano-properties of the tumor microenvironment and subsequent understanding of mechanically regulated pathways in cancer.