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Review
. 2023 Oct;12(26):e2300903.
doi: 10.1002/adhm.202300903. Epub 2023 Aug 27.

Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid-Based 3D In Vitro Models

Natalie Landon-Brace  1 , Nancy T Li  2 , Alison P McGuigan  3
Affiliations
Review

Exploring New Dimensions of Tumor Heterogeneity: The Application of Single Cell Analysis to Organoid-Based 3D In Vitro Models

Natalie Landon-Brace et al. Adv Healthc Mater. 2023 Oct.

Abstract

Modeling the heterogeneity of the tumor microenvironment (TME) in vitro is essential to investigating fundamental cancer biology and developing novel treatment strategies that holistically address the factors affecting tumor progression and therapeutic response. Thus, the development of new tools for both in vitro modeling, such as patient-derived organoids (PDOs) and complex 3D in vitro models, and single cell omics analysis, such as single-cell RNA-sequencing, represents a new frontier for investigating tumor heterogeneity. Specifically, the integration of PDO-based 3D in vitro models and single cell analysis offers a unique opportunity to explore the intersecting effects of interpatient, microenvironmental, and tumor cell heterogeneity on cell phenotypes in the TME. In this review, the current use of PDOs in complex 3D in vitro models of the TME is discussed and the emerging directions in the development of these models are highlighted. Next, work that has successfully applied single cell analysis to PDO-based models is examined and important experimental considerations are identified for this approach. Finally, open questions are highlighted that may be amenable to exploration using the integration of PDO-based models and single cell analysis. Ultimately, such investigations may facilitate the identification of novel therapeutic targets for cancer that address the significant influence of tumor-TME interactions.

Keywords: 3D in vitro models; single cell transcriptomics; tissue engineering; tumor heterogeneity; tumor microenvironments.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Biological complexity in the tumor microenvironment (TME) arises from the intersection of several levels of heterogeneity, which can be partially captured in vitro with patient‐derived organoids (PDOs). A) Interpatient heterogeneity results from differences between patients in their unique genetics and other host factors. B) Intertumor heterogeneity exists between tumor sites in the same patient and is influenced by factors such as tumor location and the presence of distinct clones in each lesion. Microenvironmental heterogeneity arises due to tumor cell extrinsic factors, such as stromal cell composition and hypoxia in the TME. C) Tumor cell heterogeneity reflects the co‐existence of multiple tumor cell clones and phenotypes in a single tumor.
Figure 2
Figure 2
PDO‐based 3D in vitro models (left) can integrate multiple sources of tumor heterogeneity and are valuable for exploring various tumor‐microenvironment interactions (right) using single‐cell analysis tools and conventional experimental approaches. A) Schematic representation of hydrogel‐free models, which are well‐suited to investigations of cell–cell interactions. PDO‐derived cells can be cultured independently or with other cell types i) as a monolayer on a plastic substrate, ii) in an ultra‐low attachment (ULA) plates or iii) individual hanging droplets, or iv) using a Transwell insert to form an air‐liquid interface or facilitate indirect interaction between two cell populations. B) Schematic representation of hydrogel‐based models, which adapt conventional PDO culture methods to facilitate investigation of the impact of physical and chemical cues on cell phenotype, including those from stromal cell populations. PDOs can be cultured in 3D within a i) specialized bio‐matrix formulation and can be added to the well to form a ii) hydrogel dome (convex) or hydrogel plug (concave) with iii) defined culture conditions to simulate the tumor microenvironment. C) Schematic representation of spatially‐resolved models that enable investigation of the effect of spatial architecture on cell phenotypes, including the effect of molecular gradients in the TME in select models. i) Patterned hydrogels, such as the GLAnCE model (pictured), allow for live‐imaging of cell invasion at the interface before cell retrieval. ii) Microfluidic devices enable perfusion and real‐time monitoring of cell populations cultured in the device. iii) Paper‐supported models, such as TRACER (pictured), allow patterning of cells in paper scaffolds which can be assembled in single or multi‐layered constructs. In the multi‐layered constructs, cells establish molecular gradients across the layers through consumption; disassembly allows correlation of cell phenotypes with cell location in the microenvironmental gradient. iv) Bioprinted models allow highly customizable tissue architecture and precise fabrication for PDOs in both monoculture and co‐culture with stromal cells.
Figure 3
Figure 3
Bulk and single cell technologies can be used to investigate tumor heterogeneity in vivo and in vitro. A) Both bulk and single cell analysis can be used to effectively characterize interpatient heterogeneity and identify broad differences in tumor phenotypes. Single cell analysis is particularly impactful for exploring (B) microenvironmental and (C) tumor cell heterogeneity. B) Single cell analysis at the microenvironment level can provide insight into tumor composition and variation between patients or sample sites. C) Single cell analysis at the tumor cell level can reveal subpopulations of tumor cells with distinct phenotypes due to the co‐existence of multiple clones and variable exposure to both cellular (e.g., stromal cells) and non‐cellular (e.g., hypoxia) microenvironmental features.
Figure 4
Figure 4
A possible workflow for multiomic single‐cell analysis of PDO‐based models to explore tumor heterogeneity in vitro. Formulation of the biological question (A) guides the appropriate selection of a tissue engineered model system (B). Quality control (C) is essential to ensuring validity of the results. Once established, the PDO‐based model can be used to generate samples for multiomic single cell analysis (D). Data from single cell analysis should be interpreted in the context of model features and known information from in vivo tumors to decipher important aspects of tumor biology (E).
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