Biology subjects

Cadavid, J. L.

Publications and source records attributed to Cadavid, J. L..

6 recordsLinked to original sources

bioRxiv2025

Systems biology framework for rational design of operational conditions for in vitro / in vivo translation of microphysiological systems

Preclinical models are used extensively to study diseases and potential therapeutic treatments. Complex in vitro platforms incorporating human cellular components, known as microphysiological systems (MPS), can model cellular and microenvironmental features of diseased tissues. However, determining experimental conditions -- particularly biomolecular cues such as growth factors, cytokines, and matrix proteins -- providing the most effective translatability of MPS-generated information to in vivo human subject contexts is a major challenge. Here, using metabolic dysfunction-associated fatty liver disease (MAFLD) studied using the CNBio PhysioMimix as a case study, we developed a machine learning framework called Latent In Vitro to In Vivo Translation (LIV2TRANS) to ascertain how MPS data map to in vivo data, first sharpening translation insights and consequently elucidating experimental conditions that can further enhance translation capability. Our findings in this case study highlight TGF{beta} as a crucial cue for MPS translatability and indicate that adding JAK-STAT pathway perturbations via interferon stimuli could increase the predictive performance of this MPS in MAFLD studies. Finally, we developed an optimization approach that identified androgen and EGFR signaling as key for maximizing the capacity of this MPS to capture in vivo human biological information germane to MAFLD. More broadly, this work establishes a mathematically principled approach for identifying experimental conditions most beneficially capturing in vivo human-relevant molecular pathways and processes, generalizable to preclinical studies for a wide range of diseases and potential treatments.

systems biology↗

bioRxiv2024

Single-cell analysis of an engineered organoid-based model of pancreatic cancer identifies hypoxia as a contributing factor in the determination of transcriptional subtypes

Pancreatic ductal adenocarcinoma (PDAC) is a high-mortality cancer characterized by its aggressive, treatment-resistant phenotype and a complex tumour microenvironment (TME) featuring significant hypoxia. Bulk transcriptomic analysis has identified the "classical" and "basal-like" transcriptional subtypes which have prognostic value in PDAC; however, it remains unclear how microenvironmental heterogeneity contributes to the expression of these transcriptional signatures. Here, we used single cell transcriptome analysis of the organoid TRACER platform to explore the effect of oxygen and other microenvironmental gradients on PDAC organoid cells. We found that the microenvironmental gradients present in TRACER significantly impact the distribution of organoid transcriptional phenotypes and the enrichment of gene sets linked to cancer progression and treatment resistance. More significantly, we found that microenvironmental gradients drive changes in the expression of the classical and basal-like transcriptional subtype gene signatures. This effect is likely dominated by the oxygen gradients in TRACER, as hypoxia alone induced decreases in the expression of classical marker GATA6 at both the gene and protein level in PDAC cells. This work suggests that hypoxia contributes to determining transcriptional subtypes in PDAC and broadly underscores the importance of considering microenvironmental gradients in organoid-based transcriptomic studies of PDAC.

cancer biology↗

bioRxiv2023

An Engineered 3D Co-culture Model of Primary Macrophages and Patient-Derived Tumour Cells to Explore Cellular Responses in the Graded Hypoxic Microenvironment of Pancreatic Cancer

In pancreatic ductal adenocarcinoma (PDAC), tumour associated macrophages (TAMs) are a heterogeneous immune cell population that interact with cancer cells to promote malignancy, chemo-resistance, and immunosuppression. Aside from TAMs, hypoxia is a prominent feature of PDAC that can rewire cells to survive and enhance malignancy in the tumour microenvironment (TME). Deciphering the interactions between macrophages, cancer cells and hypoxia could lead to the development of effective immune-targeted therapies for PDAC. However, there are only a few models that physiologically recapitulate the PDAC TME and allow for meaningful interrogation of cancer-immune cell interactions in hypoxia. Here, we develop a model of primary macrophages and PDAC patient organoid-derived cells by adapting TRACER, a paper-based, engineered 3D model that allows snapshot analysis of cellular response in hypoxia. In this study, we establish a direct co-culture method of primary macrophages and PDAC organoid cells in TRACER and demonstrate that TRACER co-cultures generate hypoxic gradients and show expected phenotypic responses to this hypoxic gradient. Moreover, we report for the first time in a human in vitro model that hypoxic macrophages exert a graded chemoprotective effect on gemcitabine-treated PDAC organoid cells, and that interactions between cancer cells and macrophages from the inner layers of TRACER indirectly attenuate the inflammatory response of donor-derived T-cells. Overall, the TRACER co-culture system is a novel, fully human 3D in vitro cancer-immune model for evaluating the response of macrophages and cancer cells in a hypoxic gradient.

bioengineering↗

bioRxiv2022

An automation workflow for high-throughput manufacturing and analysis of scaffold-supported 3D tissue arrays

The success rate of bringing novel cancer therapies to the clinic remains extremely low due to the lack of relevant pre-clinical culture models that capture the complexity of human tumours. Patient-derived organoids have emerged as a useful tool to model patient and tumour heterogeneity to begin addressing this need. Scaling these complex culture models while enabling stratified analysis of different cellular sub-populations remains a challenge, however. One strategy to enable higher throughput organoid cultures that also enables easy image-based analysis is the Scaffold-supported Platform for Organoid-based Tissues (SPOT) platform. SPOT allows the generation of flat, thin and dimensionally-defined microtissues in both 96- and 384-well plate footprints and is compatible with tumour organoid culture and downstream image-based readouts. SPOT manufacturing is currently a manual process however, limiting the use of SPOT to perform larger-scale screening. In this study, we integrate and optimize an automation approach to generate tumour-mimetic 3D engineered microtissues in SPOT using a liquid handler, and show comparable within-sample and between-sample variation as the standard manual manufacturing process. Furthermore, we develop a liquid handler-supported whole-cell extraction protocol and as a proof-of-value demonstration, we generate 3D complex tissues containing different proportions of tumour and stromal cells and perform single-cell-based end-point analysis to demonstrate the impact of co-culture on the tumour cell population specifically. We also demonstrate we can incorporate primary patient-derived organoids into the pipeline to capture patient-level tumour heterogeneity. We envision that this automated workflow integrated with 96/384-SPOT and multiple cell types and patient-derived organoid models will provide opportunities for future applications in high-throughput screening for novel personalized therapeutic targets. This pipeline also allows the user to assess dynamic cell responses using high-content longitudinal imaging or downstream single-cell-based analyses.

bioengineering↗

bioRxiv2022

An off-the-shelf multi-well scaffold-supported platform for tumour organoid-based tissues

Complex 3D bioengineered tumour models provide the opportunity to better capture the heterogeneity of patient tumours. Patient-derived organoids are emerging as a useful tool to study tumour heterogeneity and variation in patient responses. Organoid cultures typically require a 3D microenvironment that can be manufactured easily to facilitate screening. Here we set out to create a high-throughput, "off-the-shelf" platform which permits the generation of organoid-containing microtissues for standard phenotypic bioassays and image-based readings. To achieve this, we developed the Scaffold-supported Platform for Organoid-based Tissues (SPOT) platform. SPOT is a 3D gel-embedded in vitro platform that can be produced in a 96- or 384-well plate format and enables the generation of flat, thin and dimensionally-defined microgels. SPOT has high potential for adoption due to its reproducible manufacturing methodology, compatibility with existing instrumentation, and reduced within-sample and between-sample variation, which can pose challenges to both data analysis and interpretation. Using SPOT we generate cultures from patient derived pancreatic ductal adenocarcinoma organoids and assess the cellular response to standard-of-care chemotherapeutic compounds, demonstrating our platforms usability for drug screening. We envision 96/384-SPOT will provide a useful tool to assess drug sensitivity of patient-derived organoids and easily integrate into the drug discovery pipeline.

bioengineering↗

bioRxiv2019

Gels for Live Analysis of Compartmentalized Environments (GLAnCE): A Tissue Model to Probe Tumour Phenotypes at Tumour-Stroma Interfaces

The interface between a tumour and the adjacent stroma is a site of great importance for tumour development. At this site, carcinoma cells are highly proliferative, undergo invasive phenotypic changes, and directly interact with surrounding stromal cells, such as cancer-associated fibroblasts (CAFs) which further exert pro-tumorigenic effects. Here we describe the development of GLAnCE (Gels for Live Analysis of Compartmentalized Environments), an easy-to-use hydrogel-culture platform for investigating CAF-tumour cell interaction dynamics in vitro at a tumour-stroma interface. GLAnCE enables observation of CAF-mediated enhancement of both tumour cell proliferation and invasion at the tumour-stroma interface in real time, as well as stratification between phenotypes at the interface versus in the bulk tumour tissue compartment. We found that CAF presence resulted in the establishment of an invasion-permissive, interface-specific matrix environment, that leads to carcinoma cell movement outwards from the tumour edge and tumour cell invasion. Furthermore, the spatial stratification capability of GLAnCE was leveraged to discern differences between tumour cell epithelial-to-mesenchymal (EMT) transition genes induced by paracrine signaling from CAFs versus genes induced by interface-specific, CAF-mediated microenvironment. GLAnCE combines high usability and tissue complexity, to provide a powerful in vitro platform to probe mechanisms of tumour cell movement specific to the microenvironment at the tumour-stroma interface.

bioengineering↗