Rapid Cancer Diagnosis and Early Prognosis of Metastatic Risk Based on Mechanical Invasiveness of Sampled Cells

A high-throughput microfabricated platform for rapid quantification of metastatic potential

Assays that measure morphology, proliferation, motility, deformability, and migration are used to study the invasiveness of cancer cells. However, native invasive potential of cells may be hidden from these contextual metrics because they depend on culture conditions. We created a micropatterned chip that mimics the native environmental conditions, quantifies the invasive potential of tumor cells, and improves our understanding of the malignancy signatures. Unlike conventional assays, which rely on indirect measurements of metastatic potential, our method uses three-dimensional microchannels to measure the basal native invasiveness without chemoattractants or microfluidics. No change in cell death or proliferation is observed on our chips. Using six cancer cell lines, we show that our system is more sensitive than other motility-based assays, measures of nuclear deformability, or cell morphometrics. In addition to quantifying metastatic potential, our platform can distinguish between motility and invasiveness, help study molecular mechanisms of invasion, and screen for targeted therapeutics.

Mechanobiological cell adaptations to changing microenvironments determine cancer invasiveness: Experimentally validated finite element modeling

Metastases are the leading cause of cancer-associated deaths. A key process in metastasis is cell invasiveness, which is driven and controlled by cancer cell interactions with their microenvironment. We have previously shown that invasive cancer cells forcefully push into and indent physiological stiffness gels to cell-scale depths, where the percentage of indenting cells and their attained depths provide clinically relevant predictions of tumor invasiveness and the potential metastatic risk. The cell-attained, invasive indentation depths are directly affected by gel-microenvironment mechanics, which can concurrently modulate the cells' mechanics and force application capacity, in a complex, coordinated mechanobiological response. As it is impossible to experimentally isolate the different contributions of cell and gel mechanics to cancer cell invasiveness, we perform finite element modeling with literature-based parameters. Under average-scale, cell cytoplasm and nucleus mechanics and cell-applied force levels, increasing gel stiffness 1-50 kPa significantly reduced the attained indentation depth by >200%, while the gel's Poisson ratio reduced depths only by up to 20% and only when the ratio was >0.4; this reveals microenvironment mechanics that can promote invasiveness. Experiments with varying-invasiveness cancer cells exhibited qualitative variations in their responses to gel stiffness increase, for example large/small reduction in indentation depth or increase and then reduction. We quantitatively and qualitatively reproduced the different experimental responses via coordinated changes in cell mechanics and applied force levels. Thus, the different cancer cell capacities to adapt their mechanobiology in response to mechanically changing microenvironments likely determine the varying cancer invasiveness and metastatic risk levels in patients.

Anti-Cancer Properties of Flaxseed Proteome

Flaxseed has been recognized as a valuable source of nutrients and bioactive compounds, including proteins that possess various health benefits. In recent years, studies have shown that flaxseed proteins, including albumins, globulins, glutelin, and prolamins, possess anti-cancer properties. These properties are attributed to their ability to inhibit cancer cell proliferation, induce apoptosis, and interfere with cancer cell signaling pathways, ultimately leading to the inhibition of metastasis. Moreover, flaxseed proteins have been reported to modulate cancer cell mechanobiology, leading to changes in cell behavior and reduced cancer cell migration and invasion. This review provides an overview of the anti-cancer properties of flaxseed proteins, with a focus on their potential use in cancer treatment. Additionally, it highlights the need for further research to fully establish the potential of flaxseed proteins in cancer therapy.

Encapsulation and adhesion of nanoparticles as a potential biomarker for TNBC cells metastatic propensity

Metastasis is the main cause of cancer-related mortality; therefore, the ability to predict its propensity can remarkably affect survival rate. Metastasis development is predicted nowadays by lymph-node status, tumor size, histopathology, and genetic testing. However, all these methods may have inaccuracies, and some require weeks to complete. Identifying novel prognostic markers will open an essential source for risk prediction, possibly guiding to elevated patient treatment by personalized strategies. Cancer cell invasion is a critical step in metastasis. The cytoskeletal mechanisms used by metastatic cells for the invasion process are very similar to the utilization of actin cytoskeleton in the endocytosis process. In the current study, the adhesion and encapsulation efficiency of low-cost carboxylate-modified fluorescent nanoparticles by breast cancer cells with high (HM) and low metastatic potential (LM) have been evaluated; benign cells were used as control. Using high-content fluorescence imaging and analysis, we have revealed (within a short time of 1 h), that efficiency of nanoparticles adherence and encapsulation is sufficiently higher in HM cells compared to LM cells, while benign cells are not encapsulating or adhering the particles during experiment time at all. We have utilized custom-made automatic image analysis algorithms to find quantitative co-localization (Pearson's coefficients) of the nanoparticles with the imaged cells. The method proposed here is straightforward; it does not require especial equipment or expensive materials nor complicated cell manipulations, it may be potentially applicable for various cells, including patient-derived cells. Effortless and quantitative determination of the metastatic likelihood has the potential to be performed using patient-specific biopsy/surgery sample, which will directly influence the choice of protocols for cancer patient's treatment and, as a result, increase their life expectancy.

Physical confinement and cell proximity increase cell migration rates and invasiveness: A mathematical model of cancer cell invasion through flexible channels

Cancer cell migration between different body parts is the driving force behind cancer metastasis, which is the main cause of mortality of patients. Migration of cancer cells often proceeds by penetration through narrow cavities in locally stiff, yet flexible tissues. In our previous work, we developed a model for cell geometry evolution during invasion, which we extend here to investigate whether leader and follower (cancer) cells that only interact mechanically can benefit from sequential transmigration through narrow micro-channels and cavities. We consider two cases of cells sequentially migrating through a flexible channel: leader and follower cells being closely adjacent or distant. Using Wilcoxon's signed-rank test on the data collected from Monte Carlo simulations, we conclude that the modelled transmigration speed for the follower cell is significantly larger than for the leader cell when cells are distant, i.e. follower cells transmigrate after the leader has completed the crossing. Furthermore, it appears that there exists an optimum with respect to the width of the channel such that cell moves fastest. On the other hand, in the case of closely adjacent cells, effectively performing collective migration, the leader cell moves 12% faster since the follower cell pushes it. This work shows that mechanical interactions between cells can increase the net transmigration speed of cancer cells, resulting in increased invasiveness. In other words, interaction between cancer cells can accelerate metastatic invasion.

Proteomic Markers for Mechanobiological Properties of Metastatic Cancer Cells

The major cause (more than 90%) of all cancer-related deaths is metastasis, thus its prediction can critically affect the survival rate. Metastases are currently predicted by lymph-node status, tumor size, histopathology and genetic testing; however, all these are not infallible, and obtaining results may require weeks. The identification of new potential prognostic factors will be an important source of risk information for the practicing oncologist, potentially leading to enhanced patient care through the proactive optimization of treatment strategies. Recently, the new mechanobiology-related techniques, independent of genetics, based on the mechanical invasiveness of cancer cells (microfluidic, gel indentation assays, migration assays etc.), demonstrated a high success rate for the detection of tumor cell metastasis propensity. However, they are still far away from clinical implementation due to complexity. Hence, the exploration of novel markers related to the mechanobiological properties of tumor cells may have a direct impact on the prognosis of metastasis. Our concise review deepens our knowledge of the factors that regulate cancer cell mechanotype and invasion, and incites further studies to develop therapeutics that target multiple mechanisms of invasion for improved clinical benefit. It may open a new clinical dimension that will improve cancer prognosis and increase the effectiveness of tumor therapies.

Computational modeling reveals a vital role for proximity-driven additive and synergistic cell-cell interactions in increasing cancer invasiveness

Solid-tumor cell invasion typically occurs by collective migration of attached cell-cohorts, yet we show here that indirect cell-interactions through the substrate can also drive invasiveness. We have previously shown that well-spaced, invasive cancer cells push-into and indent gels to depths of 10 µm, while closely adjacent, non-contacting cancer cells may reach up to 18 µm, potentially relying on cell-cell interactions through the gel-substrate. To test that, we developed finite element models of indenting cells, using experimental gel mechanics, cell mechanostructure, and force magnitudes. We show that under 50-350 nN of combined traction and normal forces, a stiff nucleus-region is essential in facilitating 5-10 µm single-cell indentations, while uniformly soft cells attain 1.6-fold smaller indentations. We observe that indentation depths of cells in close proximity (0.5-50 µm distance) increase relative to well-spaced cells, due to additive, continuum mechanics-driven contributions. Specifically, 2-3 cells applying 220 nN normal forces gained up to 3% in depth, which interestingly increased to 7.8% when two cells, 10 µm apart, applied unequal force-magnitudes (i.e., 220 and 350 nN). Such additive, energy-free contributions can reduce cell mechanical energy -output required for invasiveness, yet the experimentally observed 10-18 µm depths likely necessitate synergistic, mechanobiological changes, which may be mechanically triggered. We note that nucleus stiffening or cytoplasm softening by 25-50% increased indentation depths by only 1-7%, while depths increase nearly linearly with force-magnitude even to two-fold levels. Hence, cell-proximity triggered, synergistic and additive cell-interactions through the substrate can drive collective cancer-cell invasiveness, even without direct cell-cell interactions. STATEMENT OF SIGNIFICANCE: Metastatic cancer invasion typically occurs collectively in attached cell-cohorts. We have previously shown increased invasiveness in closely adjacent cancer cells that are able to push-into and indent soft-gels more deeply than single, well-spaced cells. Using finite element models, we reveal mechanisms of cell-proximity driven invasiveness, demonstrating an important role for the stiff nucleus. Cell-proximity can additively induce small increase in indentation depth via continuum mechanics contributions, especially when adjacent cells apply unequal forces, and without requiring increased cell-mechanical-energy-output. Concurrently, proximity-triggered synergistic interactions that produce changes in cell mechanics or capacity for increased force-levels can facilitate deep invasive-indentations. Thus, we reveal concurrent additive and synergistic mechanisms to drive collective cancer-cell invasiveness even without direct cell-cell interactions.

Breast cancer stem cells: mechanobiology reveals highly invasive cancer cell subpopulations

Cancer stem-like cells (CSCs) are a typically small subpopulation of highly tumorigenic cells that can self-renew, differentiate, drive tumor progression, and may mediate drug resistance and metastasis. Metastasis driving CSCs are expected to be highly invasive. To determine the relative invasiveness of CSCs, we isolate distinct subpopulations in the metastatic, MDA-MB-231 breast-cancer cell line, identified by the stem-cell markers aldehyde dehydrogenase (ALDH) and CD44. We determine CSC-subpopulation invasiveness levels using our rapid (2 h) mechanobiology-based assay. Specifically, invasive cells forcefully push and indent the surface of physiological-stiffness synthetic gels to cell-scale depths, where the percentage of indenting cells and their attained depths have previously provided clinically relevant predictions of the metastatic risk in different cancer types. We observe that the small (3.2%) CD44+ALDH+ cell-subpopulation indents more and attains significantly deeper depths (65% indenting to 6 ± 0.3 µm) relative to CD44+ALDH-, CD44-ALDH-, CD44-ALDH+ cells, and the whole-sample control (with 18-44% indenting cells reaching average depths of 4.4-5 µm). The CD44+ALDH+ similarly demonstrates twofold higher migratory capacity in Boyden chambers. The higher invasiveness of CD44+ALDH+ cells reveals their likely role in facilitating disease progression, providing prognostic markers for increased risk of recurrence and metastasis.

Mechanical interactions of invasive cancer cells through their substrate evolve from additive to synergistic

Non-contacting, adjacent cancer cells can mechanically interact through their substrate to increase their invasive and migratory capacities that underly metastases-formation. Such mechanical interactions may induce additive or synergistic enhancement of invasiveness, potentially indicating different underlying force-mechanisms. To identify cell-cell-gel interactions, we monitor the time-evolution of three-dimensional traction strains induced by MDA-MB-231 breast cancer cells adhering on physiological-stiffness (1.8 kPa) collagen gels and compare to simulations. Single metastatic cells apply strain energies of 0.2-2 pJ (average 0.51 ± 0.06 pJ) at all observation times (30-174 min) inducing a mechanical volume-of-effect in the collagen gel that is initially (<60 min from seeding) on the cell-volume scale (∼3000 µm³) and on average increases with time from cell seeding. When cells adhere closely adjacent, at short times (<60 min) we distinguish the additive contributions of neighboring cells to the strains, while at longer times strain fields are synergistically amplified and may facilitate increased cooperative/collective cancer-cell-invasiveness. The results of well-spaced and closely adjacent cells at short times match our simulations of additive deformations induced by radially applied strains with experimentally based inverse-distance decay. We thus reveal a time-dependent evolution from additive to synergistic interactions of adjacently adhering cells that may facilitate metastatic invasion.

Rapid, quantitative prediction of tumor invasiveness in non-melanoma skin cancers using mechanobiology-based assay

Non-melanoma skin cancers, including basal and squamous cell carcinomas (BCC and SCC), are the most common malignancies worldwide. BCC/SCC cancers are generally highly localized and can be surgically excised; however, invasive tumors may be fatal. Current diagnosis of skin cancer and prognosis of potential invasiveness are based mainly on clinical-pathological factors of the biopsied lesions. SCC invasiveness is also predicted by histomorphological factors, such as the degree of differentiation or the mitotic index, while BCCs are typically considered non-invasive. The above subjective measures do not provide direct, objective prognosis of cellular invasiveness in each specific sample. Hence, we have developed a mechanobiology-based approach to rapidly determine sample invasiveness. Here, cells from 15 fresh tissue samples of suspected non-melanoma skin cancer were seeded on physiological-stiffness (2.4 kPa) synthetic gels, and within 1-h invasive cell subsets were observed to push/indent the gel surface; clinicopathological results were separately obtained using standard protocols. The percentage of indenting cells from invasive (26.2 ± 2.4%) and non-invasive (4.8 ± 0.5%) SCC samples differed significantly (p < 0.0001), with well-separated invasiveness cutoffs of, respectively, > 12% and < 5%. The mechanical invasiveness directly agrees with the SCC cell-differentiation state, where over 3.3-fold more (p < 0.0001) cells from moderately differentiated samples indent the gels as compared to well-differentiated cell samples. In BCCs, < 20% of cells typically indented, and a highly migratory, desmoplastic sample was identified with 46%. By providing rapid, quantitative, early prognosis of invasiveness and potential metastatic risk, our rapid technology may facilitate informed (bed-side) decision making and choice of disease-management protocols on the time-scale of the initial diagnosis and surgical excision.

Modeling force application configurations and morphologies required for cancer cell invasion

We show that cell-applied, normal mechanical stresses are required for cells to penetrate into soft substrates, matching experimental observations in invasive cancer cells, while in-plane traction forces alone reproduce observations in non-cancer/noninvasive cells. Mechanobiological interactions of cells with their microenvironment drive migration and cancer invasion. We have previously shown that invasive cancer cells forcefully and rapidly push into impenetrable, physiological stiffness gels and indent them to cell-scale depths (up to 10 μm); normal, noninvasive cells indent at most to 0.7 μm. Significantly indenting cells signpost increased cancer invasiveness and higher metastatic risk in vitro and in vivo, as verified experimentally in different cancer types, yet the underlying cell-applied, force magnitudes and configurations required to produce the cell-scale gel indentations have yet to be evaluated. Hence, we have developed finite element models of forces applied onto soft, impenetrable gels using experimental cell/gel morphologies, gel mechanics, and force magnitudes. We show that in-plane traction forces can only induce small-scale indentations in soft gels (< 0.7 μm), matching experiments with various single, normal cells. Addition of a normal force (on the scale of experimental traction forces) produced cell-scale indentations that matched observations in invasive cancer cells. We note that normal stresses (force and area) determine the indentation depth, while contact area size and morphology have a minor effect, explaining the origin of experimentally observed cell morphologies. We have thus revealed controlling features facilitating invasive indentations by single cancer cells, which will allow application of our model to complex problems, such as multicellular systems.

Machine-Learning Provides Patient-Specific Prediction of Metastatic Risk Based on Innovative, Mechanobiology Assay

Cancer mortality is mostly related to metastasis. Metastasis is currently prognosed via histopathology, disease-statistics, or genetics; those are potentially inaccurate, not rapidly available and require known markers. We had developed a rapid (~ 2 h) mechanobiology-based approach to provide early prognosis of the clinical likelihood for metastasis. Specifically, invasive cell-subsets seeded on impenetrable, physiological-stiffness polyacrylamide gels forcefully indent the gels, while non-invasive/benign cells do not. The number of indenting cells and their attained depths, the mechanical invasiveness, accurately define the metastatic risk of tumors and cell-lines. Utilizing our experimental database, we compare the capacity of several machine learning models to predict the metastatic risk. Models underwent supervised training on individual experiments using classification from literature and commercial-sources for established cell-lines and clinical histopathology reports for tumor samples. We evaluated 2-class models, separating invasive/non-invasive (e.g. benign) samples, and obtained sensitivity and specificity of 0.92 and 1, respectively; this surpasses other works. We also introduce a novel approach, using 5-class models (i.e. normal, benign, cancer-metastatic-non/low/high) that provided average sensitivity and specificity of 0.69 and 0.91. Combining our rapid, mechanical invasiveness assay with machine learning classification can provide accurate and early prognosis of metastatic risk, to support choice of treatments and disease management.

Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology

We provide an overview on the use of biological assays to calibrate and initialize mechanism-based models of cancer phenomena. Although artificial intelligence methods currently dominate the landscape in computational oncology, mathematical models that seek to explicitly incorporate biological mechanisms into their formalism are of increasing interest. These models can guide experimental design and provide insights into the underlying mechanisms of cancer progression. Historically, these models have included a myriad of parameters that have been difficult to quantify in biologically relevant systems, limiting their practical insights. Recently, however, there has been much interest calibrating biologically based models with the quantitative measurements available from (for example) RNA sequencing, time-resolved microscopy, and in vivo imaging. In this contribution, we summarize how a variety of experimental methods quantify tumor characteristics from the molecular to tissue scales and describe how such data can be directly integrated with mechanism-based models to improve predictions of tumor growth and treatment response.

Actin as a Target to Reduce Cell Invasiveness in Initial Stages of Metastasis

We demonstrate the relative roles of the cell cytoskeleton, and specific importance of actin in facilitating mechanical aspects of metastatic invasion. A crucial step in metastasis, the typically lethal spread of cancer to distant body-sites, is cell invasion through dense tissues composed of extracellular matrix and various non-cancerous cells. Cell invasion requires cell-cytoskeleton remodeling to facilitate dynamic morphological changes and force application. We have previously shown invasive cell subsets in heterogeneous samples can rapidly (2 h) and forcefully indent non-degradable, impenetrable, synthetic gels to cell-scale depths. The amounts of indenting cells and their attained depths provide the mechanical invasiveness of the sample, which as we have shown agrees with the in vitro metastatic potential and the in vivo metastatic risk in humans. To identify invasive force-application mechanisms, we evaluated changes in mechanical invasiveness following chemical perturbations targeting the structure and function of cytoskeleton elements and associated proteins. We evaluate effects on short-term (2-hr) indentations of single, well-spaced or closely situated cells as compared to long-time-scale Boyden chamber migration. We show that actomyosin inhibition may be used to reduce (mechanical) invasiveness of single or collectively invading cells, while actin-disruption may induce escape-response of treated single-cells, which may promote metastasis.