A novel thin plate spline methodology to model tissue surfaces and quantify tumor cell invasion in organ-on-chip models.

Organ-on-chip (OOC) models can be useful tools for cancer drug discovery. Advances in OOC technology have led to the development of more complex assays, yet analysis of these systems does not always account for these advancements, resulting in technical challenges. A challenging task in the analysis of these two-channel microfluidic models is to define the boundary between the channels so objects moving within and between channels can be quantified. We propose a novel imaging-based application of a thin plate spline method - a generalized cubic spline that can be used to model coordinate transformations - to model a tissue boundary and define compartments for quantification of invaded objects, representing the early steps in cancer metastasis. To evaluate its performance, we applied our analytical approach to an adapted OOC developed by Emulate, Inc., utilizing a two-channel system with endothelial cells in the bottom channel and colorectal cancer (CRC) patient-derived organoids (PDOs) in the top channel. Initial application and visualization of this method revealed boundary variations due to microscope stage tilt and ridge and valley-like contours in the endothelial tissue surface. The method was functionalized into a reproducible analytical process and web tool - the Chip Invasion and Contour Analysis (ChICA) - to model the endothelial surface and quantify invading tumor cells across multiple chips. To illustrate applicability of the analytical method, we applied the tool to CRC organoid-chips seeded with two different endothelial cell types and measured distinct variations in endothelial surfaces and tumor cell invasion dynamics. Since ChICA utilizes only positional data output from imaging software, the method is applicable to and agnostic of the imaging tool and image analysis system used. The novel thin plate spline method developed in ChICA can account for variation introduced in OOC manufacturing or during the experimental workflow, can quickly and accurately measure tumor cell invasion, and can be used to explore biological mechanisms in drug discovery.

A novel thin plate spline methodology to model tissue surfaces and quantify tumor cell invasion in organ-on-chip models.

Organ-on-chip (OOC) models can be useful tools for cancer drug discovery. Advances in OOC technology have led to the development of more complex assays, yet analysis of these systems does not always account for these advancements, resulting in technical challenges. A challenging task in the analysis of these two-channel microfluidic models is to define the boundary between the channels so objects moving within and between channels can be quantified. We propose a novel imaging-based application of a thin plate spline method - a generalized cubic spline that can be used to model coordinate transformations - to model a tissue boundary and define compartments for quantification of invaded objects, representing the early steps in cancer metastasis. To evaluate its performance, we applied our analytical approach to an adapted OOC developed by Emulate, Inc., utilizing a two-channel system with endothelial cells in the bottom channel and colorectal cancer (CRC) patient-derived organoids (PDOs) in the top channel. Initial application and visualization of this method revealed boundary variations due to microscope stage tilt and ridge and valley-like contours in the endothelial tissue surface. The method was functionalized into a reproducible analytical process and web tool - the Chip Invasion and Contour Analysis (ChICA) - to model the endothelial surface and quantify invading tumor cells across multiple chips. To illustrate applicability of the analytical method, we applied the tool to CRC organoid-chips seeded with two different endothelial cell types and measured distinct variations in endothelial surfaces and tumor cell invasion dynamics. Since ChICA utilizes only positional data output from imaging software, the method is applicable to and agnostic of the imaging tool and image analysis system used. The novel thin plate spline method developed in ChICA can account for variation introduced in OOC manufacturing or during the experimental workflow, can quickly and accurately measure tumor cell invasion, and can be used to explore biological mechanisms in drug discovery.

Integration of Patient-Derived Organoids and Organ-on-Chip Systems: Investigating Colorectal Cancer Invasion within the Mechanical and GABAergic Tumor Microenvironment.

Three-dimensional (3D) in vitro models are essential in cancer research, but they often neglect physical forces. In our study, we combined patient-derived tumor organoids with a microfluidic organ-on-chip system to investigate colorectal cancer (CRC) invasion in the tumor microenvironment (TME). This allowed us to create patient-specific tumor models and assess the impact of physical forces on cancer biology. Our findings showed that the organoid-on-chip models more closely resembled patient tumors at the transcriptional level, surpassing organoids alone. Using 'omics' methods and live-cell imaging, we observed heightened responsiveness of KRAS mutant tumors to TME mechanical forces. These tumors also utilized the γ-aminobutyric acid (GABA) neurotransmitter as an energy source, increasing their invasiveness. This bioengineered model holds promise for advancing our understanding of cancer progression and improving CRC treatments.

Breast cancer and neurotransmitters: emerging insights on mechanisms and therapeutic directions.

Exploring the relationship between various neurotransmitters and breast cancer cell growth has revealed their likely centrality to improving breast cancer treatment. Neurotransmitters play a key role in breast cancer biology through their effects on the cell cycle, epithelial mesenchymal transition, angiogenesis, inflammation, the tumor microenvironment and other pathways. Neurotransmitters and their receptors are vital to the initiation, progression and drug resistance of cancer and progress in our biological understanding may point the way to lower-cost and lower-risk antitumor therapeutic strategies. This review discusses multiple neurotransmitters in the context of breast cancer. It also discusses risk factors, repurposing of pharmaceuticals impacting neurotransmitter pathways, and the opportunity for better integrated models that encompass exercise, the intestinal microbiome, and other non-pharmacologic considerations. Neurotransmitters' role in breast cancer should no longer be ignored; it may appear to complicate the molecular picture but the ubiquity of neurotransmitters and their wide-ranging impacts provide an organizing framework upon which further understanding and progress against breast cancer can be based.

Neurotransmitter signaling: a new frontier in colorectal cancer biology and treatment.

The brain-gut axis, a bidirectional network between the central and enteric nervous system, plays a critical role in modulating the gastrointestinal tract function and homeostasis. Recently, increasing evidence suggests that neuronal signaling molecules can promote gastrointestinal cancers, however, the mechanisms remain unclear. Aberrant expression of neurotransmitter signaling genes in colorectal cancer supports the role of neurotransmitters to stimulate tumor growth and metastatic spread by promoting cell proliferation, migration, invasion, and angiogenesis. In addition, neurotransmitters can interact with immune and endothelial cells in the tumor microenvironment to promote inflammation and tumor progression. As such, pharmacological targeting of neurotransmitter signaling represent a promising novel anticancer approach. Here, we present an overview of the current evidence supporting the role of neurotransmitters in colorectal cancer biology and treatment.

Roadmap on plasticity and epigenetics in cancer.

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

Multiplexed imaging and effluent analysis to monitor cancer cell intravasation using a colorectal cancer-on-chip.

Despite colorectal cancer's (CRC) prevalence, its progression is not well understood. The microfluidic organ-on-chip (OOC) model described herein recreates the epithelial-endothelial tissue-tissue interface, fluid flow, and mechanical forces that exist in vivo , making it an attractive model to understand and ultimately disrupt CRC intravasation. This protocol provides step-by-step details for tumor cell seeding to create a CRC-on-chip model, chip effluent collection and analysis, and on-chip imaging to monitor tumor cell invasion within a more physiologically relevant microenvironment. For complete details on the use and execution of this protocol, please refer to Strelez et al. (2021).

Human colorectal cancer-on-chip model to study the microenvironmental influence on early metastatic spread.

Colorectal cancer (CRC) progression is a complex process that is not well understood. We describe an in vitro organ-on-chip model that emulates in vivo tissue structure and the tumor microenvironment (TME) to better understand intravasation, an early step in metastasis. The CRC-on-chip incorporates fluid flow and peristalsis-like cyclic stretching and consists of endothelial and epithelial compartments, separated by a porous membrane. On-chip imaging and effluent analyses are used to interrogate CRC progression and the resulting cellular heterogeneity. Mass spectrometry-based metabolite profiles are indicative of a CRC disease state. Tumor cells intravasate from the epithelial channel to the endothelial channel, revealing differences in invasion between aggressive and non-aggressive tumor cells. Tuning the TME by peristalsis-like mechanical forces, the epithelial:endothelial interface, and the addition of fibroblasts influences the invasive capabilities of tumor cells. The CRC-on-chip is a tunable human-relevant model system and a valuable tool to study early invasive events in cancer.

Imaging-Based Machine Learning Analysis of Patient-Derived Tumor Organoid Drug Response.

Three-quarters of compounds that enter clinical trials fail to make it to market due to safety or efficacy concerns. This statistic strongly suggests a need for better screening methods that result in improved translatability of compounds during the preclinical testing period. Patient-derived organoids have been touted as a promising 3D preclinical model system to impact the drug discovery pipeline, particularly in oncology. However, assessing drug efficacy in such models poses its own set of challenges, and traditional cell viability readouts fail to leverage some of the advantages that the organoid systems provide. Consequently, phenotypically evaluating complex 3D cell culture models remains difficult due to intra- and inter-patient organoid size differences, cellular heterogeneities, and temporal response dynamics. Here, we present an image-based high-content assay that provides object level information on 3D patient-derived tumor organoids without the need for vital dyes. Leveraging computer vision, we segment and define organoids as independent regions of interest and obtain morphometric and textural information per organoid. By acquiring brightfield images at different timepoints in a robust, non-destructive manner, we can track the dynamic response of individual organoids to various drugs. Furthermore, to simplify the analysis of the resulting large, complex data files, we developed a web-based data visualization tool, the Organoizer, that is available for public use. Our work demonstrates the feasibility and utility of using imaging, computer vision and machine learning to determine the vital status of individual patient-derived organoids without relying upon vital dyes, thus taking advantage of the characteristics offered by this preclinical model system.

A Perspective on Expanding Our Understanding of Cancer Treatments by Integrating Approaches from the Biological and Physical Sciences.

Multicellular systems such as cancer suffer from immense complexity. It is imperative to capture the heterogeneity of these systems across scales to achieve a deeper understanding of the underlying biology and develop effective treatment strategies. In this perspective article, we will discuss how recent technologies and approaches from the biological and physical sciences have transformed traditional ways of measuring, interpreting, and treating cancer. During the SLAS 2019 Annual Meeting, SBI2 hosted a Special Interest Group (SIG) on this topic. Academic and industry leaders engaged in discussions surrounding what biological model systems are appropriate to study cancer complexity, what assays are necessary to interrogate this complexity, and how physical sciences approaches may be useful to detangle this complexity. In particular, we examined the utility of mathematical models in predicting cancer progression and treatment response when tightly integrated with reproducible, quantitative, and dynamic biological measurements achieved using high-content imaging and analysis. The dialogue centered around the impetus for convergent biosciences, bringing new perspectives to cancer research to further understand this complex adaptive system and successfully intervene therapeutically.

A non-foaming proteosurfactant engineered from Ranaspumin-2.

Advances in biological surfactant proteins have already yielded a diverse range of benefits from dramatically improved survival rates for premature births to artificial photosynthesis. Presented here is the design, development, and analysis of a novel biosurfactant protein we call Surfactant Resisting Foam formatioN (SRFN). Starting with the Tungara frog's foam forming protein Ranaspumin-2, we have engineered a new surfactant protein with a destabilized hinge region to alter the kinetics and equilibrium of the protein structural transition from aqueous globular form to an extended surfactant structure at the air/water interface. SRFN is capable of approximately the same total surface tension reduction, but with the unique property of forming quickly collapsible foams. The difference in foam formation is attributed to the destabilizing glycine substitutions engineered into the hinge region. Surfactants used specifically to increase wettability, such as those used in agricultural applications would benefit from this new proteosurfactant since foamed liquid has greater wind resistance and decreased dispersal. Indeed, given growing concern of organsilicone surfactant effects on declining bee populations, biological surfactant proteins have several unique advantages over more common amphiphiles in that they can be renewably sourced, are environmentally friendly, degrade readily into non-toxic byproducts, and reduce surface tension without deleterious effects on cell membranes.