Nanomechanical properties of solid tumors as treatment monitoring biomarkers

In vitro models: Can they unravel the complexities of cancer cell metastasis?

Metastasis still accounts for the majority of cancer-related deaths despite intense research efforts made worldwide to better understand the determinants involved and discover novel ways to halt it. However, studying the pathogenesis of metastasis in actual patients is indeed challenging which renders the need for the development of relevant experimental models urgent. Traditionally, several in vitro and in vivo models have been developed to study metastasis each of which having its own advantages and limitations. In the present review, we analyzed the current approaches used in cancer biology research to study cancer cell metastasis giving emphasis on the newly developed in vitro systems that take into account factors like the three-dimensional (3D) nature of the tumor, the interaction between cancer cells and the extracellular matrix or other cells present in the tumor microenvironment, and thus, better recapitulate the metastatic process. These approaches, namely 3D bioprinting, 3D tissue models, microfluidics systems, and spheroid generation are currently used separately or in combination depending on the research question and the cancer type in order to better represent the actual in vivo setting.

The mechanopathology of the tumor microenvironment: detection techniques, molecular mechanisms and therapeutic opportunities

The mechanical properties of the tumor microenvironment (TME) undergo significant changes during tumor growth, primarily driven by alterations in extracellular (ECM) stiffness and tumor viscoelasticity. These mechanical changes not only promote tumor progression but also hinder therapeutic efficacy by impairing drug delivery and activating mechanotransduction pathways that regulate crucial cellular processes such as migration, proliferation, and resistance to therapy. In this review, we examine the mechanisms through which tumor cells sense and transmit mechanical signals to maintain homeostasis in the biomechanically altered TME. We explore current computational modelling strategies for mechanotransduction pathways, highlighting the need for developing models that incorporate additional components of the mechanosignaling machinery. Furthermore, we review available methods for measuring the mechanical properties of tumors in clinical settings and strategies aiming at restoring the TME and blocking deregulated mechanotransduction pathways. Finally, we propose that proper characterization and a deeper understanding of the mechanical landscape of the TME, both at the tissue and cellular levels, are essential for developing therapeutic strategies that account for the influence of mechanical forces on treatment efficacy.

Impact of PSMD2 on Gastric Cancer Tissue Stiffness Investigated via Motor-Piezoceramic Coupled Atomic Force Microscopy

Gastric cancer is one of the deadliest malignant tumors of the digestive tract, and its development and metastasis are regulated by various factors. Some studies have shown that PSMD2 is involved in cancer development by regulating the tumor microenvironment stiffness. However, the exact mechanism is unclear, and effective means to quantify the effect of PSMD2 on gastric cancer tissue hardness are lacking. Herein, we revealed the mechanical heterogeneity of tumor tissues in gastric cancer patients using a large-scale AFM-based in situ method. Gastric cancer cryosections were probed by this method under aqueous condition. The in situ fluorescence images were measured to correlate tissue stiffness with PSMD2 expression. Experimental results clearly revealed the specific distribution of mechanics in gastric cancer tissues under differences in PSMD2 expression. The study unveils the effect of PSMD2 expression levels on cancer invasion and increased matrix stiffness, providing a novel insight into gastric cancer research.

Assessing sarcoma cell cytoskeleton remodeling in response to varying collagen concentration

Sarcomas, rare malignant tumors of mesenchymal origin, are often underdiagnosed and have face diagnostic ambiguities and limited treatment options. The main objective of this study was to define the nanomechanical and biophysical properties of sarcoma cells, particularly examining how the cytoskeleton's remodeling and related cellular processes such as cell migration and invasion in response to environmental stimuli due to collagen content. Utilizing one murine fibrosarcoma and one osteosarcoma cell line we employed atomic force microscopy, immunostaining, advanced image processing, in vitro cellular assays, and molecular techniques to investigate cells' cytoskeleton remodeling in response to varying collagen concentration. Our study focused on how alterations in collagen content affects the cytoskeletal dynamics and correlate with changes in gene expression profiles relevant to metastasis and an aggressive cancer phenotypes. Our findings indicate that despite their shared classification, fibrosarcoma and osteosarcoma cells display distinct biophysical properties and respond differently to mechanical forces. Notably, this difference in cellular behavior renders mechanical properties a potent novel biomarkers. Furthermore, the metastasis-related identified genes related to metastatic capability, could be potential therapeutic targets. This study highlights the significance of understanding the unique traits of sarcoma cells to improve diagnostic precision and expand therapeutic strategies, for this rare type of cancer.

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

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

Omics-Enhanced Nanomedicine for Cancer Therapy

Cancer nanomedicine has emerged as a promising approach to overcome the limitations of conventional cancer therapies, offering enhanced efficacy and safety in cancer management. However, the inherent heterogeneity of tumors presents increasing challenges for the application of cancer nanomedicine in both diagnosis and treatment. This heterogeneity necessitates the integration of advanced and high-throughput analytical techniques to tailor nanomedicine strategies to individual tumor profiles. Omics technologies, encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics, and more, provide unparalleled insights into the molecular and cellular mechanisms underlying cancer. By dissecting tumor heterogeneity across multiple levels, these technologies offer robust support for the development of personalized and precise cancer nanomedicine strategies. In this review, the principles, techniques, and applications of key omics technologies are summarized. Especially, the synergistic integration of omics and nanomedicine in cancer therapy is explored, focusing on enhanced diagnostic accuracy, optimized therapeutic strategies and the assessment of nanomedicine-mediated biological responses. Moreover, this review addresses current challenges and outlines future directions in the field of omics-enhanced nanomedicine. By offering valuable insights and guidance, this review aims to advance the integration of omics with nanomedicine, ultimately driving improved diagnostic and therapeutic strategies for cancer.

Estimates of natural frequencies for nuclear vibration, and an assessment of the feasibility of selective ultrasound ablation of cancer cells

Selective ablation of cancer cells by ultrasound would be transformative for cancer therapy, but has not yet been possible. A key challenge is that cancerous and non-cancerous cells typically have similar acoustic impedance and are thus indistinguishable as materials in their responses to ultrasound. However, in certain cancers, cytoskeletal and nuclear lamin structures differ between healthy and malignant cells, opening the possibility of exploiting structural differences that manifest as different vibrational responses. To assess the possibility that the nuclei of certain cancerous cells might vibrate at different frequencies, we measured sizes and effective indentation moduli of a range of cancerous and non-cancerous cells from several cell lines and regions of the brain, and estimated the natural frequencies for nuclear vibration. Results suggest a potential difference in natural frequency for nuclear vibration between certain cancerous and non-cancerous cells, on the order of tens of kHz. This gap is potentially sufficient for selective ablation and motivates future experimentation on these specific cell types.

Mechanical forces inducing oxaliplatin resistance in pancreatic cancer can be targeted by autophagy inhibition

Pancreatic cancer remains one of the most lethal malignancies, with limited treatment options and poor prognosis. A common characteristic among pancreatic cancer patients is the biomechanically altered tumor microenvironment (TME), which among others is responsible for the elevated mechanical stresses in the tumor interior. Although significant research has elucidated the effect of mechanical stress on cancer cell proliferation and migration, it has not yet been investigated how it could affect cancer cell drug sensitivity. Here, we demonstrated that mechanical stress triggers autophagy activation, correlated with increased resistance to oxaliplatin treatment in pancreatic cancer cells. Our results demonstrate that inhibition of autophagy using hydroxychloroquine (HCQ) enhanced the oxaliplatin-induced apoptotic cell death in pancreatic cancer cells exposed to mechanical stress. The combined treatment of HCQ with losartan, a known modulator of mechanical abnormalities in tumors, synergistically enhanced the therapeutic efficacy of oxaliplatin in murine pancreatic tumor models. Furthermore, our study revealed that the use of HCQ enhanced the efficacy of losartan to alleviate mechanical stress levels and restore blood vessel integrity beyond its role in autophagy modulation. These findings underscore the potential of co-targeting mechanical stresses and autophagy as a promising therapeutic strategy to overcome drug resistance and increase chemotherapy efficacy.

Applying the Atomic Force Microscopy Technique in Medical Sciences-A Narrative Review

Penetrating deep into the cells of the human body in real time has become increasingly possible with the implementation of modern technologies in medicine. Atomic force microscopy (AFM) enables the effective live imaging of cellular and molecular structures of biological samples (such as cells surfaces, components of biological membranes, cell nuclei, actin networks, proteins, and DNA) and provides three-dimensional surface visualization (in X-, Y-, and Z-planes). Furthermore, the AFM technique enables the study of the mechanical, electrical, and magnetic properties of cells and cell organelles and the measurements of interaction forces between biomolecules. The technique has found wide application in cancer research. With the use of AFM, it is not only possible to differentiate between healthy and cancerous cells, but also to distinguish between the stages of cancerous conditions. For many years, AFM has been an important tool for the study of neurodegenerative diseases associated with the deposition of peptide amyloid plaques. In recent years, a significant amount of research has been conducted on the application of AFM in the evaluation of connective tissue cell mechanics. This review aims to provide the spectrum of the most important applications of the AFM technique in medicine to date.

Beyond stiffness: deciphering the role of viscoelasticity in cancer evolution and treatment response

There is increasing evidence that cancer progression is linked to tissue viscoelasticity, which challenges the commonly accepted notion that stiffness is the main mechanical hallmark of cancer. However, this new insight has not reached widespread clinical use, as most clinical trials focus on the application of tissue elasticity and stiffness in diagnostic, therapeutic, and surgical planning. Therefore, there is a need to advance the fundamental understanding of the effect of viscoelasticity on cancer progression, to develop novel mechanical biomarkers of clinical significance. Tissue viscoelasticity is largely determined by the extracellular matrix (ECM), which can be simulatedin vitrousing hydrogel-based platforms. Since the mechanical properties of hydrogels can be easily adjusted by changing parameters such as molecular weight and crosslinking type, they provide a platform to systematically study the relationship between ECM viscoelasticity and cancer progression. This review begins with an overview of cancer viscoelasticity, describing how tumor cells interact with biophysical signals in their environment, how they contribute to tumor viscoelasticity, and how this translates into cancer progression. Next, an overview of clinical trials focused on measuring biomechanical properties of tumors is presented, highlighting the biomechanical properties utilized for cancer diagnosis and monitoring. Finally, this review examines the use of biofabricated tumor models for studying the impact of ECM viscoelasticity on cancer behavior and progression and it explores potential avenues for future research on the production of more sophisticated and biomimetic tumor models, as well as their mechanical evaluation.

Modulating cancer mechanopathology to restore vascular function and enhance immunotherapy

Solid tumor pathology, characterized by abnormalities in the tumor microenvironment (TME), challenges therapeutic effectiveness. Mechanical factors, including increased tumor stiffness and accumulation of intratumoral forces, can determine the success of cancer treatments, defining the tumor's "mechanopathology" profile. These abnormalities cause extensive vascular compression, leading to hypoperfusion and hypoxia. Hypoperfusion hinders drug delivery, while hypoxia creates an unfavorable TME, promoting tumor progression through immunosuppression, heightened metastatic potential, drug resistance, and chaotic angiogenesis. Strategies targeting TME mechanopathology, such as vascular and stroma normalization, hold promise in enhancing cancer therapies with some already advancing to the clinic. Normalization can be achieved using anti-angiogenic agents, mechanotherapeutics, immune checkpoint inhibitors, engineered bacterial therapeutics, metronomic nanomedicine, and ultrasound sonopermeation. Here, we review the methods developed to rectify tumor mechanopathology, which have even led to cures in preclinical models, and discuss their bench-to-bedside translation, including the derivation of biomarkers from tumor mechanopathology for personalized therapy.

Stabilizing Tumor-Resident Mast Cells Restores T-Cell Infiltration and Sensitizes Sarcomas to PD-L1 Inhibition

PURPOSE

To explore the cellular cross-talk of tumor-resident mast cells (MC) in controlling the activity of cancer-associated fibroblasts (CAF) to overcome tumor microenvironment (TME) abnormalities, enhancing the efficacy of immune-checkpoint inhibitors in sarcoma.

EXPERIMENTAL DESIGN

We used a coculture system followed by further validation in mouse models of fibrosarcoma and osteosarcoma with or without administration of the MC stabilizer and antihistamine ketotifen. To evaluate the contribution of ketotifen in sensitizing tumors to therapy, we performed combination studies with doxorubicin chemotherapy and anti-PD-L1 (B7-H1, clone 10F.9G2) treatment. We investigated the ability of ketotifen to modulate the TME in human sarcomas in the context of a repurposed phase II clinical trial.

RESULTS

Inhibition of MC activation with ketotifen successfully suppressed CAF proliferation and stiffness of the extracellular matrix accompanied by an increase in vessel perfusion in fibrosarcoma and osteosarcoma as indicated by ultrasound shear wave elastography imaging. The improved tissue oxygenation increased the efficacy of chemoimmunotherapy, supported by enhanced T-cell infiltration and acquisition of tumor antigen-specific memory. Importantly, the effect of ketotifen in reducing tumor stiffness was further validated in sarcoma patients, highlighting its translational potential.

CONCLUSIONS

Our study suggests the targeting of MCs with clinically administered drugs, such as antihistamines, as a promising approach to overcome resistance to immunotherapy in sarcomas.

Machine learning analysis reveals tumor stiffness and hypoperfusion as biomarkers predictive of cancer treatment efficacy

In the pursuit of advancing cancer therapy, this study explores the predictive power of machine learning in analyzing tumor characteristics, specifically focusing on the effects of tumor stiffness and perfusion (i.e., blood flow) on treatment efficacy. Recent advancements in oncology have highlighted the significance of these physiological properties of the tumor microenvironment in determining treatment outcomes. We delve into the relationship between these tumor attributes and the effectiveness of cancer therapies in preclinical tumor models. Utilizing robust statistical methods and machine learning algorithms, our research analyzes data from 1365 cases of various cancer types, assessing how tumor stiffness and perfusion influence the efficacy of treatment protocols. We also investigate the synergistic potential of combining drugs that modulate tumor stiffness and perfusion with standard cytotoxic treatments. By incorporating these predictors into treatment planning, our study aims to enhance the precision of cancer therapy, tailoring treatment to individual tumor profiles. Our findings demonstrate a significant correlation between stiffness/perfusion and treatment efficacy, highlighting a new way for personalized cancer treatment strategies.

Self-Supplied Reactive Oxygen Species-Responsive Mitoxantrone Polyprodrug for Chemosensitization-Enhanced Chemotherapy under Moderate Hyperthermia

Currently, the secondary development and modification of clinical drugs has become one of the research priorities. Researchers have developed a variety of TME-responsive nanomedicine carriers to solve certain clinical problems. Unfortunately, endogenous stimuli such as reactive oxygen species (ROS), as an important prerequisite for effective therapeutic efficacy, are not enough to achieve the expected drug release process, therefore, it is difficult to achieve a continuous and efficient treatment process. Herein, a self-supply ROS-responsive cascade polyprodrug (PMTO) is designed. The encapsulation of the chemotherapy drug mitoxantrone (MTO) in a polymer backbone could effectively reduce systemic toxicity when transported in vivo. After PMTO is degraded by endogenous ROS of the TME, another part of the polyprodrug backbone becomes cinnamaldehyde (CA), which can further enhance intracellular ROS, thereby achieving a sustained drug release process. Meanwhile, due to the disruption of the intracellular redox environment, the efficacy of chemotherapy drugs is enhanced. Finally, the anticancer treatment efficacy is further enhanced due to the mild hyperthermia effect of PMTO. In conclusion, the designed PMTO demonstrates remarkable antitumor efficacy, effectively addressing the limitations associated with MTO.

Short-Term l-arginine Treatment Mitigates Early Damage of Dermal Collagen Induced by Diabetes

Changes in the structural properties of the skin due to collagen alterations are an important factor in diabetic skin complications. Using a combination of photonic methods as an optic diagnostic tool, we investigated the structural alteration in rat dermal collagen I in diabetes, and after short-term l-arginine treatment. The multiplex approach shows that in the early phase of diabetes, collagen fibers are partially damaged, resulting in the heterogeneity of fibers, e.g., "patchy patterns" of highly ordered/disordered fibers, while l-arginine treatment counteracts to some extent the conformational changes in collagen-induced by diabetes and mitigates the damage. Raman spectroscopy shows intense collagen conformational changes via amides I and II in diabetes, suggesting that diabetes-induced structural changes in collagen originate predominantly from individual collagen molecules rather than supramolecular structures. There is a clear increase in the amounts of newly synthesized proline and hydroxyproline after treatment with l-arginine, reflecting the changed collagen content. This suggests that it might be useful for treating and stopping collagen damage early on in diabetic skin. Our results demonstrate that l-arginine attenuates the early collagen I alteration caused by diabetes and that it could be used to treat and prevent collagen damage in diabetic skin at a very early stage.

Multiscale elasticity mapping of biological samples in 3D at optical resolution

The mechanical properties of biological tissues have emerged as an integral determinant of tissue function in health and disease. Nonetheless, characterizing the elasticity of biological samples in 3D and at high resolution remains challenging. Here, we present a µElastography platform: a scalable elastography system that maps the elastic properties of tissues from cellular to organ scales. The platform leverages the use of a biocompatible, thermo-responsive hydrogel to deliver compressive stress to a biological sample and track its resulting deformation. By surrounding the specimen with a reference hydrogel of known Young's modulus, we are able to map the absolute values of elastic properties in biological samples. We validate the experimental and computational components of the platform using a hydrogel phantom and verify the system's ability to detect internal mechanical heterogeneities. We then apply the platform to map the elasticity of multicellular spheroids and the murine lymph node. With these applications, we demonstrate the platform's ability to map tissue elasticity at internal planes of interest, as well as capture mechanical heterogeneities neglected by most macroscale characterization techniques. The µElastography platform, designed to be implementable in any biology lab with access to 3D microscopy (e.g., confocal, multiphoton, or optical coherence microscopy), will provide the capability to characterize the mechanical properties of biological samples to labs across the large community of biological sciences by eliminating the need of specialized instruments such as atomic force microscopy. STATEMENT OF SIGNIFICANCE: Understanding the elasticity of biological tissues is of great importance, but characterizing these properties typically requires highly specialized equipment. Utilizing stimulus-responsive hydrogels, we present a scalable, hydrogel-based elastography method that uses readily available reagents and imaging modalities to generate resolved maps of internal elasticity within biomaterials and biological samples at optical resolution. This new approach is capable of detecting internal stiffness heterogeneities within the 3D bulk of samples and is highly scalable across both imaging modalities and biological length scales. Thus, it will have significant impact on the measurement capabilities of labs studying engineered biomaterials, mechanobiology, disease progression, and tissue engineering and development.

Pirfenidone-Loaded Polymeric Micelles as an Effective Mechanotherapeutic to Potentiate Immunotherapy in Mouse Tumor Models

Ongoing research is actively exploring the use of immune checkpoint inhibitors to treat solid tumors by inhibiting the PD-1/PD-L1 axis and reactivating the function of cytotoxic T effector cells. Many types of solid tumors, however, are characterized by a dense and stiff stroma and are difficult to treat. Mechanotherapeutics have formed a recent class of drugs that aim to restore biomechanical abnormalities of the tumor microenvironment, related to increased stiffness and hypo-perfusion. Here, we have developed a polymeric formulation containing pirfenidone, which has been successful in restoring the tumor microenvironment in breast tumors and sarcomas. We found that the micellar formulation can induce similar mechanotherapeutic effects to mouse models of 4T1 and E0771 triple negative breast tumors and MCA205 fibrosarcoma tumors but with a dose 100-fold lower than that of the free pirfenidone. Importantly, a combination of pirfenidone-loaded micelles with immune checkpoint inhibition significantly delayed primary tumor growth, leading to a significant improvement in overall survival and in a complete cure for the E0771 tumor model. Furthermore, the combination treatment increased CD4+ and CD8+ T cell infiltration and suppressed myeloid-derived suppressor cells, creating favorable immunostimulatory conditions, which led to immunological memory. Ultrasound shear wave elastography (SWE) was able to monitor changes in tumor stiffness during treatment, suggesting optimal treatment conditions. Micellar encapsulation is a promising strategy for mechanotherapeutics, and imaging methods, such as SWE, can assist their clinical translation.

Multilevel Assessment of Stent-Induced Inflammation in the Adjacent Vascular Tissue

A recent U.S. Food and Drug Administration report presented the currently available scientific information related to biological response to metal implants. In this work, a multilevel approach was employed to assess the implant-induced and biocorrosion-related inflammation in the adjacent vascular tissue using a mouse stent implantation model. The implications of biocorrosion on peri-implant tissue were assessed at the macroscopic level via in vivo imaging and histomorphology. Elevated matrix metalloproteinase activity, colocalized with the site of implantation, and histological staining indicated that stent surface condition and implantation time affect the inflammatory response and subsequent formation and extent of neointima. Hematological measurements also demonstrated that accumulated metal particle contamination in blood samples from corroded-stetted mice causes a stronger immune response. At the cellular level, the stent-induced alterations in the nanostructure, cytoskeleton, and mechanical properties of circulating lymphocytes were investigated. It was found that cells from corroded-stented samples exhibited higher stiffness, in terms of Young's modulus values, compared to noncorroded and sham-stented samples. Nanomechanical modifications were also accompanied by cellular remodeling, through alterations in cell morphology and stress (F-actin) fiber characteristics. Our analysis indicates that surface wear and elevated metal particle contamination, prompted by corroded stents, may contribute to the inflammatory response and the multifactorial process of in-stent restenosis. The results also suggest that circulating lymphocytes could be a novel nanomechanical biomarker for peri-implant tissue inflammation and possibly the early stage of in-stent restenosis. Large-scale studies are warranted to further investigate these findings.

Modulating tumor mechanics with nanomedicine for cancer therapy

Over the past several decades, the importance of the tumor mechanical microenvironment (TMME) in cancer progression or cancer therapy has been recognized by researchers worldwide. The abnormal mechanical properties of tumor tissues include high mechanical stiffness, high solid stress, and high interstitial fluid pressure (IFP), which form physical barriers resulting in suboptimal treatment efficacy and resistance to different types of therapy by preventing drugs infiltrating the tumor parenchyma. Therefore, preventing or reversing the establishment of the abnormal TMME is critical for cancer therapy. Nanomedicines can enhance drug delivery by exploiting the enhanced permeability and retention (EPR) effect, so nanomedicines that target and modulate the TMME can further boost antitumor efficacy. Herein, we mainly discuss the nanomedicines that can regulate mechanical stiffness, solid stress, and IFP, with a focus on how nanomedicines change abnormal mechanical properties and facilitate drug delivery. We first introduce the formation, characterizing methods and biological effects of tumor mechanical properties. Conventional TMME modulation strategies will be briefly summarized. Then, we highlight representative nanomedicines capable of modulating the TMME for augmented cancer therapy. Finally, current challenges and future opportunities for regulating the TMME with nanomedicines will be provided.

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.

Ultrasound stiffness and perfusion markers correlate with tumor volume responses to immunotherapy

Immunotherapy has revolutionized the treatment of dozens of cancers and became a standard of care for some tumor types. However, the majority of patients do not benefit from current immunotherapeutics and many develop severe toxicities. Therefore, the identification of biomarkers to classify patients as likely responders or non-responders to immunotherapy is a timely task. Here, we test ultrasound imaging markers of tumor stiffness and perfusion. Ultrasound imaging is non-invasive and clinically available and can be used both for stiffness and perfusion evaluation. In this study, we employed syngeneic orthotopic models of two breast cancers, a fibrosarcoma and melanoma, to demonstrate that ultrasound-derived measures of tumor stiffness and perfusion (i.e., blood volume) correlate with the efficacy of immune checkpoint inhibition (ICI) in terms of changes in primary tumor volume. To modulate tumor stiffness and perfusion and thus, get a range of therapeutic outcomes, we employed the mechanotherapeutic tranilast. Mechanotherapeutics combined with ICI are advancing through clinical trials, but biomarkers of response have not been tested until now. We found the existence of linear correlations between tumor stiffness and perfusion imaging biomarkers as well as strong linear correlations between the stiffness and perfusion markers with ICI efficacy on primary tumor growth rates. Our findings set the basis for ultrasound imaging biomarkers predictive of ICI therapy in combination with mechanotherapeutics. STATEMENT OF SIGNIFICANCE: Hypothesis: Monitoring Tumor Microenvironment (TME) mechanical abnormalities can predict the efficacy of immune checkpoint inhibition (ICI) and provide biomarkers predictive of response. Tumor stiffening and solid stress elevation are hallmarks of tumor patho-physiology in desmoplastic tumors. They induce hypo-perfusion and hypoxia by compressing tumor vessels, posing major barriers to immunotherapy. Mechanotherapeutics is a new class of drugs that target the TME to reduce stiffness and improve perfusion and oxygenation. In this study, we show that measures of stiffness and perfusion derived from ultrasound shear wave elastography and contrast enhanced ultrasound can provide biomarkers of tumor response.

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.