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Revealing the 3D composition of intact tissue specimens is essential for understanding cell and organ biology in health and disease. State-of-the-art 3D microscopy techniques aim to capture tissue volumes on an ever-increasing scale, while also retaining sufficient resolution for single-cell analysis. Furthermore, spatial profiling through multi-marker imaging is fast developing, providing more context and better distinction between cell types. Following these lines of technological advance, we here present a protocol based on FUnGI (fructose, urea and glycerol clearing solution for imaging) optical clearing of tissue before multispectral large-scale single-cell resolution 3D (mLSR-3D) imaging, which implements 'on-the-fly' linear unmixing of up to eight fluorophores during a single acquisition. Our protocol removes the need for repetitive illumination, thereby allowing larger volumes to be scanned with better image quality in less time, also reducing photo-bleaching and file size. To aid in the design of multiplex antibody panels, we provide a fast and manageable intensity equalization assay with automated analysis to design a combination of markers with balanced intensities suitable for mLSR-3D. We demonstrate effective mLSR-3D imaging of various tissues, including patient-derived organoids and xenografted tumors, and, furthermore, describe an optimized workflow for mLSR-3D imaging of formalin-fixed paraffin-embedded samples. Finally, we provide essential steps for 3D image data processing, including shading correction that does not require pre-acquired shading references and 3D inhomogeneity correction to correct fluorescence artefacts often afflicting 3D datasets. Together, this provides a one-week protocol for eight-fluorescent-marker 3D visualization and exploration of intact tissue of various origins at single-cell resolution.Multispectral large-scale single-cell resolution 3D imaging allows up to eight fluorophores to be captured in a single acquisition. This protocol enables the visualization and exploration of large intact tissue volumes.

Extending the success of cellular immunotherapies against blood cancers to the realm of solid tumors will require improved in vitro models that reveal therapeutic modes of action at the molecular level. Here we describe a system, called BEHAV3D, developed to study the dynamic interactions of immune cells and patient cancer organoids by means of imaging and transcriptomics. We apply BEHAV3D to live-track >150,000 engineered T cells cultured with patient-derived, solid-tumor organoids, identifying a ‘super engager’ behavioral cluster comprising T cells with potent serial killing capacity. Among other T cell concepts we also study cancer metabolome-sensing engineered T cells (TEGs) and detect behavior-specific gene signatures that include a group of 27 genes with no previously described T cell function that are expressed by super engager killer TEGs. We further show that type I interferon can prime resistant organoids for TEG-mediated killing. BEHAV3D is a promising tool for the characterization of behavioral-phenotypic heterogeneity of cellular immunotherapies and may support the optimization of personalized solid-tumor-targeting cell therapies.

Despite advances in three-dimensional (3D) imaging, it remains challenging to profile all the cells within a large 3D tissue, including the morphology and organization of the many cell types present. Here, we introduce eight-color, multispectral, large-scale single-cell resolution 3D (mLSR-3D) imaging and image analysis software for the parallelized, deep learning–based segmentation of large numbers of single cells in tissues, called segmentation analysis by parallelization of 3D datasets (STAPL-3D). Applying the method to pediatric Wilms tumor, we extract molecular, spatial and morphological features of millions of cells and reconstruct the tumor’s spatio-phenotypic patterning. In situ population profiling and pseudotime ordering reveals a highly disorganized spatial pattern in Wilms tumor compared to healthy fetal kidney, yet cellular profiles closely resembling human fetal kidney cells could be observed. In addition, we identify previously unreported tumor-specific populations, uniquely characterized by their spatial embedding or morphological attributes. Our results demonstrate the use of combining mLSR-3D and STAPL-3D to generate a comprehensive cellular map of human tumors. An imaging software for large-scale microscopy data shows how cells are organized in tissues.

Our understanding of the cellular composition and architecture of cancer has primarily advanced using 2D models and thin slice samples. This has granted spatial information on fundamental cancer biology and treatment response. However, tissues contain a variety of interconnected cells with different functional states and shapes, and this complex organization is impossible to capture in a single plane. Furthermore, tumours have been shown to be highly heterogenous, requiring large‐scale spatial analysis to reliably profile their cellular and structural composition. Volumetric imaging permits the visualization of intact biological samples, thereby revealing the spatio‐phenotypic and dynamic traits of cancer. This review focuses on new insights into cancer biology uniquely brought to light by 3D imaging and concomitant progress in cancer modelling and quantitative analysis. 3D imaging has the potential to generate broad knowledge advance from major mechanisms of tumour progression to new strategies for cancer treatment and patient diagnosis. We discuss the expected future contributions of the newest imaging trends towards these goals and the challenges faced for reaching their full application in cancer research.

Revealing the 3D composition of intact tissue specimens is essential for understanding cell and organ biology in health and disease. State-of-the-art 3D microscopy techniques aim to capture tissue volumes on an ever-increasing scale, while also retaining sufficient resolution for single-cell analysis. Furthermore, spatial profiling through multi-marker imaging is fast developing, providing more context and better distinction between cell types. Following these lines of technological advance, we here present a protocol based on FUnGI (fructose, urea and glycerol clearing solution for imaging) optical clearing of tissue before multispectral large-scale single-cell resolution 3D (mLSR-3D) imaging, which implements 'on-the-fly' linear unmixing of up to eight fluorophores during a single acquisition. Our protocol removes the need for repetitive illumination, thereby allowing larger volumes to be scanned with better image quality in less time, also reducing photo-bleaching and file size. To aid in the design of multiplex antibody panels, we provide a fast and manageable intensity equalization assay with automated analysis to design a combination of markers with balanced intensities suitable for mLSR-3D. We demonstrate effective mLSR-3D imaging of various tissues, including patient-derived organoids and xenografted tumors, and, furthermore, describe an optimized workflow for mLSR-3D imaging of formalin-fixed paraffin-embedded samples. Finally, we provide essential steps for 3D image data processing, including shading correction that does not require pre-acquired shading references and 3D inhomogeneity correction to correct fluorescence artefacts often afflicting 3D datasets. Together, this provides a one-week protocol for eight-fluorescent-marker 3D visualization and exploration of intact tissue of various origins at single-cell resolution.

Organoid technology, in vitro 3D culturing of miniature tissue, has opened a new experimental window for cellular processes that govern organ development and function as well as disease. Fluorescence microscopy has played a major role in characterizing their cellular composition in detail and demonstrating their similarity to the tissue they originate from. In this article, we present a comprehensive protocol for high-resolution 3D imaging of whole organoids upon immunofluorescent labeling. This method is widely applicable for imaging of organoids differing in origin, size and shape. Thus far we have applied the method to airway, colon, kidney, and liver organoids derived from healthy human tissue, as well as human breast tumor organoids and mouse mammary gland organoids. We use an optical clearing agent, FUnGI, which enables the acquisition of whole 3D organoids with the opportunity for single-cell quantification of markers. This three-day protocol from organoid harvesting to image analysis is optimized for 3D imaging using confocal microscopy.

Despite advances in three-dimensional (3D) imaging, it remains challenging to profile all the cells within a large 3D tissue, including the morphology and organization of the many cell types present. Here, we introduce eight-color, multispectral, large-scale single-cell resolution 3D (mLSR-3D) imaging and image analysis software for the parallelized, deep learning-based segmentation of large numbers of single cells in tissues, called segmentation analysis by parallelization of 3D datasets (STAPL-3D). Applying the method to pediatric Wilms tumor, we extract molecular, spatial and morphological features of millions of cells and reconstruct the tumor's spatio-phenotypic patterning. In situ population profiling and pseudotime ordering reveals a highly disorganized spatial pattern in Wilms tumor compared to healthy fetal kidney, yet cellular profiles closely resembling human fetal kidney cells could be observed. In addition, we identify previously unreported tumor-specific populations, uniquely characterized by their spatial embedding or morphological attributes. Our results demonstrate the use of combining mLSR-3D and STAPL-3D to generate a comprehensive cellular map of human tumors.

Direct targeting of the downstream mitogen-activated protein kinase (MAPK) pathway to suppress extracellular-regulated kinase (ERK) activation in KRAS and BRAF mutant colorectal cancer (CRC) has proven clinically unsuccessful, but promising results have been obtained with combination therapies including epidermal growth factor receptor (EGFR) inhibition. To elucidate the interplay between EGF signalling and ERK activation in tumours, we used patient-derived organoids (PDOs) from KRAS and BRAF mutant CRCs. PDOs resemble in vivo tumours, model treatment response and are compatible with live-cell microscopy. We established real-time, quantitative drug response assessment in PDOs with single-cell resolution, using our improved fluorescence resonance energy transfer (FRET)-based ERK biosensor EKAREN5. We show that oncogene-driven signalling is strikingly limited without EGFR activity and insufficient to sustain full proliferative potential. In PDOs and in vivo, upstream EGFR activity rigorously amplifies signal transduction efficiency in KRAS or BRAF mutant MAPK pathways. Our data provide a mechanistic understanding of the effectivity of EGFR inhibitors within combination therapies against KRAS and BRAF mutant CRC. Ponsioen et al. use a FRET‐based ERK biosensor EKAREN5 in patient‐derived organoids to show that EGFR activity amplifies signal transduction efficiency in KRAS or BRAF mutant MAPK pathways.

Recent advances in in vitro culture technologies, such as adult stem cell-derived organoids, have opened up new avenues for the development of novel, more physiologic human cancer models. Such preclinical models are essential for efficient translation of basic cancer research into novel treatment regimens. We succeeded in growing organoids from a range of pediatric solid tumors, including Wilms’ tumors, renal cell carcinomas, and different types of rhabdoid tumors (i.e., AT/RT, MRT). Tumor organoids retain many characteristics of parental tumor tissue. For instance, Wilms’ tumor organoids retain the cellular heterogeneity of tumors, as they are composed of an intricate network of different cell types. Moreover, we demonstrate that tumor organoids are amenable to gene editing and high-throughput drug screens. In conclusion, our pediatric cancer organoids capture disease and tissue heterogeneity and provide a platform for basic cancer research, drug screening, and personalized medicine. Citation Format: Camilla Calandrini, Frans Schutgens, Rurika Oka, Thanasis Margaritis, Tito Candelli, Luka Mathijsen, Carola Ammerlaan, Ravian van Ineveld, Sepideh Derakhshan, Lars Custers, Philip Lijnzaad, Harry Begthel, Hinri Kerstens, Maarten Rookmaker, Marianne Verhaar, Patrick Kemmeren, Ronald de Krijger, Kathy Pritchard-Jones, Anne Rios, Marry van den Heuvel-Eibrink, Frank Holstege, Ruben van Boxtel, Hans Clevers, Jarno Drost. Patient-derived organoids in pediatric cancer research [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA27.

Breast tumors are inherently heterogeneous, but the evolving cellular organization through neoplastic progression is poorly understood. Here we report a rapid, large-scale single-cell resolution 3D imaging protocol based on a one-step clearing agent that allows visualization of normal tissue architecture and entire tumors at cellular resolution. Imaging of multicolor lineage-tracing models of breast cancer targeted to either basal or luminal progenitor cells revealed profound clonal restriction during progression. Expression profiling of clones arising in Pten/Trp53-deficient tumors identified distinct molecular signatures. Strikingly, most clones harbored cells that had undergone an epithelial-to-mesenchymal transition, indicating widespread, inherent plasticity. Hence, an integrative pipeline that combines lineage tracing, 3D imaging, and clonal RNA sequencing technologies offers a comprehensive path for studying mechanisms underlying heterogeneity in whole tumors.

Background Nephron progenitor cells (NPCs) undergo a stepwise process to generate all mature nephron structures. Mesenchymal to epithelial transition (MET) is considered a multistep process of NPC differentiation to ensure progressive establishment of new nephrons. However, despite this important role, to date, no marker for NPCs undergoing MET in the nephron exists. Results Here, we identify LGR6 as a NPC marker, expressed in very early cap mesenchyme, pre‐tubular aggregates, renal vesicles, and in segments of S‐shaped bodies, following the trajectory of MET. By using a lineage tracing approach in embryonic explants in combination with confocal imaging and single‐cell RNA sequencing, we provide evidence for the multiple fates of LGR6+ cells during embryonic nephrogenesis. Moreover, by using long‐term in vivo lineage tracing, we show that postnatal LGR6+ cells are capable of generating the multiple lineages of the nephrons. Conclusions Given the profound early mesenchymal expression and MET signature of LGR6+ cells, together with the lineage tracing of mesenchymal LGR6+ cells, we conclude that LGR6+ cells contribute to all nephrogenic segments by undergoing MET. LGR6+ cells can therefore be considered an early committed NPC population during embryonic and postnatal nephrogenesis with potential regenerative capability., Key Findings Lgr6 is expressed in the earliest cap mesenchyme pool, a niche where nephrogenic progenitor cells (NPCs) are found.Lgr6 marks NPCs undergoing mesenchymal to epithelial transition, following the main process of nephron development.Using ex vivo and vivo lineage tracing, we show that mesenchymal Lgr6 expressing cells give rise to multiple types of mesenchymal derived nephron segments, including specialized glomerular epithelium, such as podocytes.