The profound metabolic reprogramming that occurs in cancer cells has been investigated primarily in two-dimensional cell cultures, which fail to recapitulate spatial aspects of cell-to-cell interactions as well as tissue gradients present in three-dimensional (3D) tumours. Here, we describe an engineered model to assemble 3D tumours by rolling a scaffold-tumour composite strip. By unrolling the strip, the model can be rapidly disassembled for snap-shot analysis, allowing spatial mapping of cell metabolism in concert with cell phenotype. We also show that the establishment of oxygen gradients within samples are shaped by oxygen-dependent signalling pathways, as well as the consequential variations in cell growth, response to hypoxic gradients extending from normoxia to severe hypoxia, and therapy responsiveness, are consistent with tumours in vivo. Moreover, by using liquid chromatography tandem mass spectrometry, we mapped cellular metabolism and identified spatially defined metabolic signatures of cancer cells to reveal both known and novel metabolic responses to hypoxia.

Cancer prognosis remains a lottery dependent on cancer type, disease stage at diagnosis, and personal genetics. While investment in research is at an all-time high, new drugs are more likely to fail in clinical trials today than in the 1970s. In this review, a summary of current survival statistics in North America is provided, followed by an overview of the modern drug discovery process, classes of models used throughout different stages, and challenges associated with drug development efficiency are highlighted. Then, an overview of the cancer hallmarks that drive clinical progression is provided, and the range of available clinical therapies within the context of these hallmarks is categorized. Specifically, it is found that historically, the development of therapies is limited to a subset of possible targets. This provides evidence for the opportunities offered by novel disease-relevant in vitro models that enable identification of novel targets that facilitate interactions between the tumor cells and their surrounding microenvironment. Next, an overview of the models currently reported in literature is provided, and the cancer biology they have been used to explore is highlighted. Finally, four priority areas are suggested for the field to accelerate adoption of in vitro tumour models for cancer drug discovery.

Patient-derived organoids (PDOs) are emerging as powerful models to capture the genetic heterogeneity of human tumors. However, the self-assembling nature of PDOs limits their use in studies of the impact of microenvironmental heterogeneity on tumor cell function. Here, a paper-based model, the Tissue Roll for Analysis of Cellular Environment and Response (TRACER) is adapted, using patterned polymer infiltration, to enable controlled assembly and disassembly of organoid structures to study the impact of both genetic and microenvironmental heterogeneity on tumor cell behavior. In the adapted platform (TRACER2), pancreatic cancer PDOs establish oxygen gradients across the tissue and in response exhibit graded cell viability, proliferation, hypoxiaresponse gene transcription, and response to gemcitabine therapy. Further, PDOs retrieved from the hypoxic regions of the TRACER2 cultures show graded transcriptional changes in immunosuppression-related genes and upon co-culture, after TRACER2 disassembly, induce graded functional changes in Jurkat cells and macrophage cells. Therefore, TRACER2 offers a novel platform to dissect the effects of microenvironmental parameters on tumor cell function.

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The tumour microenvironment is heterogeneous and consists of multiple cell types, variable extracellular matrix (ECM) composition, and contains cell-defined gradients of small molecules, oxygen, nutrients and waste. Emerging in vitro cell culture systems that attempt to replicate these features often fail to incorporate design strategies to facilitate efficient data collection and stratification. The tissue roll for analysis of cellular environment and response (TRACER) is a novel strategy to assemble layered, three-dimensional tumours with cell-defined, graded heterogeneous microenvironments that also facilitates cellular separation and stratification of data from different cell populations from specific microenvironments. Here we describe the materials selection and development of TRACER. We find that cellulose fibre scaffolding is an ideal support to generate tissue constructs having homogenous cell seeding and consistent properties. We explore ECM remodeling and long-term cell growth in the scaffold, and characterize the tumour microenvironment in assembled TRACERs using multiple established analysis methods. Finally, we confirm that TRACERs replicate small molecule gradients of glucose and lactate, and explore cell phenotype associated with these gradients using confocal microscopy, flow cytometry, and quantitative PCR analysis. We envision this technology will provide a platform to create complex, yet controlled tumour microenvironments that can be easily disassembled for snapshot analysis of cell phenotype and response to therapy in relation to microenvironment properties.