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.

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.

mTORC2 contributes to the metabolic reprogramming in EGFR tyrosine-kinase inhibitor resistant cells in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) patients with activating EGFR mutations are often successfully treated with EGFR tyrosine kinase inhibitor (TKI) such as erlotinib; however, treatment resistance inevitably occurs. Given tumor metabolism of glucose and therapeutic response are intimately linked, we explored the metabolic differences between isogenic erlotinib-sensitive and -resistant NSCLC cell lines. We discovered that the growth of erlotinib-resistant cells is more sensitive to glucose deprivation. Seahorse metabolic assay revealed erlotinib-resistant cells have lower spare respiratory capacity (SRC), an indicator of metabolic flexibility, compared to erlotinib-sensitive cells. Additionally, we found downstream components of mTORC2 signaling to be phosphorylated in erlotinib-resistant cells. Knockdown of an mTORC2 component, Rictor, enhanced the SRC and rescued the growth rate of erlotinib-resistant cells during glucose deprivation. Among NSCLCs with activating EGFR mutations, gene sets involved in glucose metabolism were enriched in patients with high expression of p-NDGR1, a readout of mTORC2 activity. Furthermore, overall survival was negatively correlated with p-NDRG1. Our work uncovers a link between mTORC2 and metabolic reprogramming in EGFR TKI-resistant cells and highlights the significance of mTORC2 in the progression of EGFR-mutated NSCLC.