DNA-barcoded signal amplification for imaging mass cytometry enables sensitive and highly multiplexed tissue imaging

From surfing to diving into the tumor microenvironment through multiparametric imaging mass cytometry

The tumor microenvironment (TME) is a complex ecosystem where malignant and non-malignant cells cooperate and interact determining cancer progression. Cell abundance, phenotype and localization within the TME vary over tumor development and in response to therapeutic interventions. Therefore, increasing our knowledge of the spatiotemporal changes in the tumor ecosystem architecture is of importance to better understand the etiologic development of the neoplastic diseases. Imaging Mass Cytometry (IMC) represents the elective multiplexed imaging technology enabling the in-situ analysis of up to 43 different protein markers for in-depth phenotypic and spatial investigation of cells in their preserved microenvironment. IMC is currently applied in cancer research to define the composition of the cellular landscape and to identify biomarkers of predictive and prognostic significance with relevance in mechanisms of drug resistance. Herein, we describe the general principles and experimental workflow of IMC raising the informative potential in preclinical and clinical cancer research.

In-depth and high-throughput spatial proteomics for whole-tissue slice profiling by deep learning-facilitated sparse sampling strategy

Mammalian organs and tissues are composed of heterogeneously distributed cells, which interact with each other and the extracellular matrix surrounding them in a spatially defined way. Therefore, spatially resolved gene expression profiling is crucial for determining the function and phenotypes of these cells. While genome mutations and transcriptome alterations act as drivers of diseases, the proteins that they encode regulate essentially all biological functions and constitute the majority of biomarkers and drug targets for disease diagnostics and treatment. However, unlike transcriptomics, which has a recent explosion in high-throughput spatial technologies with deep coverage, spatial proteomics capable of reaching bulk tissue-level coverage is still rare in the field, due to the non-amplifiable nature of proteins and sensitivity limitation of mass spectrometry (MS). More importantly, due to the limited multiplexing capability of the current proteomics methods, whole-tissue slice mapping with high spatial resolution requires a formidable amount of MS matching time. To achieve spatially resolved, deeply covered proteome mapping for centimeter-sized samples, we developed a sparse sampling strategy for spatial proteomics (S4P) using computationally assisted image reconstruction methods, which is potentially capable of reducing the number of samples by tens to thousands of times depending on the spatial resolution. In this way, we generated the largest spatial proteome to date, mapping more than 9000 proteins in the mouse brain, and discovered potential new regional or cell type markers. Considering its advantage in sensitivity and throughput, we expect that the S4P strategy will be applicable to a wide range of tissues in future studies.

From morphology to single-cell molecules: high-resolution 3D histology in biomedicine

High-resolution three-dimensional (3D) tissue analysis has emerged as a transformative innovation in the life sciences, providing detailed insights into the spatial organization and molecular composition of biological tissues. This review begins by tracing the historical milestones that have shaped the development of high-resolution 3D histology, highlighting key breakthroughs that have facilitated the advancement of current technologies. We then systematically categorize the various families of high-resolution 3D histology techniques, discussing their core principles, capabilities, and inherent limitations. These 3D histology techniques include microscopy imaging, tomographic approaches, single-cell and spatial omics, computational methods and 3D tissue reconstruction (e.g. 3D cultures and spheroids). Additionally, we explore a wide range of applications for single-cell 3D histology, demonstrating how single-cell and spatial technologies are being utilized in the fields such as oncology, cardiology, neuroscience, immunology, developmental biology and regenerative medicine. Despite the remarkable progress made in recent years, the field still faces significant challenges, including high barriers to entry, issues with data robustness, ambiguous best practices for experimental design, and a lack of standardization across methodologies. This review offers a thorough analysis of these challenges and presents recommendations to surmount them, with the overarching goal of nurturing ongoing innovation and broader integration of cellular 3D tissue analysis in both biology research and clinical practice.

Toward spatial glycomics and glycoproteomics: Innovations and applications

In this mini review, we provide an overview of the challenging field of spatial glycomics/glycoproteomics. Owing to their complexity, sophisticated analytical methods and innovative technologies are needed to advance this field. An agile development approach enables unraveling aberrant glycosylations, glycobiomarkers, and glycotargets for spatial imaging, diagnosis, and therapeutic purposes. We discuss glycopathology and tissue glycomic profiling using highly sensitive lectin-based analyses and introduce deep visual proteomics for glycomic/glycoproteomic sample preparation. Additionally, we highlight the importance of leveraging laser microdissection and artificial intelligence-driven visual software for cell-type assignment and automation techniques, which are crucial for advancing glycomics/glycoproteomics.

Multiparameter quantitative analyses of diagnostic cells in brain tissues from tuberous sclerosis complex

The advent of high-dimensional imaging offers new opportunities to molecularly characterize diagnostic cells in disorders that have previously relied on histopathological definitions. One example case is found in tuberous sclerosis complex (TSC), a developmental disorder characterized by systemic growth of benign tumors. Within resected brain tissues from patients with TSC, detection of abnormally enlarged balloon cells (BCs) is pathognomonic for this disorder. Though BCs can be identified by an expert neuropathologist, little is known about the specificity and broad applicability of protein markers for these cells, complicating classification of proposed BCs identified in experimental models of this disorder. Here, we report the development of a customized machine learning pipeline (BAlloon IDENtifier; BAIDEN) that was trained to prospectively identify BCs in tissue sections using a histological stain compatible with high-dimensional cytometry. This approach was coupled to a custom 36-antibody panel and imaging mass cytometry (IMC) to explore the expression of multiple previously proposed BC marker proteins and develop a descriptor of BC features conserved across multiple tissue samples from patients with TSC. Here, we present a modular workflow encompassing BAIDEN, a custom antibody panel, a control sample microarray, and analysis pipelines-both open-source and in-house-and apply this workflow to understand the abundance, structure, and signaling activity of BCs as an example case of how high-dimensional imaging can be applied within human tissues.

Highly Multiplexed Tissue Imaging in Precision Oncology and Translational Cancer Research

Precision oncology tailors treatment strategies to a patient's molecular and health data. Despite the essential clinical value of current diagnostic methods, hematoxylin and eosin morphology, immunohistochemistry, and gene panel sequencing offer an incomplete characterization. In contrast, highly multiplexed tissue imaging allows spatial analysis of dozens of markers at single-cell resolution enabling analysis of complex tumor ecosystems; thereby it has the potential to advance our understanding of cancer biology and supports drug development, biomarker discovery, and patient stratification. We describe available highly multiplexed imaging modalities, discuss their advantages and disadvantages for clinical use, and potential paths to implement these into clinical practice. Significance: This review provides guidance on how high-resolution, multiplexed tissue imaging of patient samples can be integrated into clinical workflows. It systematically compares existing and emerging technologies and outlines potential applications in the field of precision oncology, thereby bridging the ever-evolving landscape of cancer research with practical implementation possibilities of highly multiplexed tissue imaging into routine clinical practice.

Multiplexed and Quantitative Imaging of Live-Cell Membrane Proteins by a Precise and Controllable DNA-Encoded Amplification Reaction

Amplifying DNA conjugated affinity ligands can improve the sensitivity and multiplicity of cell imaging and play a crucial role in comprehensively deciphering cellular heterogeneity and dynamic changes during development and disease. However, the development of one-step, controllable, and quantitative DNA amplification methods for multiplexed imaging of live-cell membrane proteins is challenging. Here, we introduce the template adhesion reaction (TAR) method for assembling amplifiable DNA sequences with different affinity ligands, such as aptamers or antibodies, for amplified and multiplexed imaging of live-cell membrane proteins with high quantitative fidelity. The precisely controllable TAR enables proportional amplification of membrane protein targets with variable abundances by modulating the concentration ratios of hairpin templates and primers, thus allowing sensitive visualization of multiple membrane proteins with enhanced signal-to-noise ratios (SNRs) without disturbing their original ratios. Using TAR, we achieved signal-enhanced imaging of six proteins on the same live-cell within 1-2 h. TAR represents an innovative and programmable molecular toolkit for multiplexed profiling of membrane proteins in live-cells.

Advances in spatial proteomics: Mapping proteome architecture from protein complexes to subcellular localizations

Proteins are responsible for most intracellular functions, which they perform as part of higher-order molecular complexes, located within defined subcellular niches. Localization is both dynamic and context specific and mislocalization underlies a multitude of diseases. It is thus vital to be able to measure the components of higher-order protein complexes and their subcellular location dynamically in order to fully understand cell biological processes. Here, we review the current range of highly complementary approaches that determine the subcellular organization of the proteome. We discuss the scale and resolution at which these approaches are best employed and the caveats that should be taken into consideration when applying them. We also look to the future and emerging technologies that are paving the way for a more comprehensive understanding of the functional roles of protein isoforms, which is essential for unraveling the complexities of cell biology and the development of disease treatments.

Leveraging preclinical models of metastatic breast cancer

Women that present to the clinic with established breast cancer metastases have limited treatment options. Yet, the majority of preclinical studies are actually not directed at developing treatment regimens for established metastatic disease. In this review we will discuss the current state of preclinical macro-metastatic breast cancer models, including, but not limited to syngeneic GEMM, PDX and xenografts. Challenges within these models which are often overlooked include fluorophore-immunogenic neoantigens, differences in experimental vs spontaneous metastasis and tumor heterogeneity. Furthermore, due to cell plasticity in the tumor immune microenvironment (TIME) of the metastatic landscape, the treatment efficacy of newly approved immune checkpoint blockade (ICB) may differ in metastatic sites as compared to primary localized tumors.

Spatial immunophenotyping of FFPE tissues by imaging mass cytometry

The immune compartment of a tissue is dynamic, changing to respond to infections, tumors, or therapeutic interventions. Within tissues, local microenvironments provide interaction partners and cytokines that can gear immune cells into distinct functional states. Thus, it is not just the immune composition of a tissue, but also the relative localization of immune cells that determines the outcome of a response. Conventional techniques like immunohistochemistry (IHC) have been used to describe infiltration of immune cells and their relative position within tissues. However, these technologies are limited on the number of targets that can be simultaneously imaged. Here, we describe a simple protocol using imaging mass cytometry (IMC) for immunophenotyping formalin-fixed, paraffin-embedded (FFPE) tissues. IMC has a 1-μm resolution and allows simultaneous detection of up to 40 targets, overcoming limitations of traditional methods. In this protocol, we detail the staining procedure, offer an example of a murine FFPE antibody panel for immunophenotyping, and additionally provide suggestions for initial image analysis. The herein presented workflow facilitates the characterization of immune niches and can be used to assess their alterations throughout immune responses or therapeutic interventions. With minimal alterations, this approach can be used on clinically relevant samples or animal models to investigate specific immune responses and better understand disease progression or treatment dynamics.

Spatiotemporal omics for biology and medicine

The completion of the Human Genome Project has provided a foundational blueprint for understanding human life. Nonetheless, understanding the intricate mechanisms through which our genetic blueprint is involved in disease or orchestrates development across temporal and spatial dimensions remains a profound scientific challenge. Recent breakthroughs in cellular omics technologies have paved new pathways for understanding the regulation of genomic elements and the relationship between gene expression, cellular functions, and cell fate determination. The advent of spatial omics technologies, encompassing both imaging and sequencing-based methodologies, has enabled a comprehensive understanding of biological processes from a cellular ecosystem perspective. This review offers an updated overview of how spatial omics has advanced our understanding of the translation of genetic information into cellular heterogeneity and tissue structural organization and their dynamic changes over time. It emphasizes the discovery of various biological phenomena, related to organ functionality, embryogenesis, species evolution, and the pathogenesis of diseases.

Zero-Background Dual-Mode Closed Bipolar Electrode Electrochemiluminescence Biosensor Based on ZnCoN-C Potential Regulation for Ultrasensitive Detection of Ochratoxin A

In this work, the relationship between electrochemiluminescence (ECL) signal and driving voltage was first studied by self-made reduced and oxidized closed bipolar electrodes (CBPEs). It was found that when the driving voltage was large enough, the maximum ECL signals for the two kinds of CBPEs were the same but their required drive voltages were different. Zinc cobalt nitrogen doped carbon material (ZnCoN-C) had an outstanding electric double layer (EDL) property and conductivity. Therefore, it could significantly reduce the driving voltage of two kinds of CBPE systems, reaching the maximum ECL signal of Ru(bpy)32+. Interestingly, when the ZnCoN-C modified electrode reached the maximum ECL signal, the bare electrode signal was zero. As a proof-of-concept application, a zero-background dual-mode CBPE-ECL biosensor was constructed for the ultrasensitive detection of ochratoxin A (OTA) in beer. Considering that beer samples contained a large number of reducing substances, a reduced CBPE system was selected to build the biosensor. Furthermore, a convenient ECL imaging platform using a smartphone was built for the detection of OTA. This work used a unique EDL material ZnCoN-C to regulate the driving voltage of CBPE for the first time; thus, a novel zero-background ECL sensor was constructed. Further, this work provided a deeper understanding of the CBPE-ECL system and opened a new door for zero-background detection.

Signal amplification by cyclic extension enables high-sensitivity single-cell mass cytometry

Mass cytometry uses metal-isotope-tagged antibodies to label targets of interest, which enables simultaneous measurements of ~50 proteins or protein modifications in millions of single cells, but its sensitivity is limited. Here, we present a signal amplification technology, termed Amplification by Cyclic Extension (ACE), implementing thermal-cycling-based DNA in situ concatenation in combination with 3-cyanovinylcarbazole phosphoramidite-based DNA crosslinking to enable signal amplification simultaneously on >30 protein epitopes. We demonstrate the utility of ACE in low-abundance protein quantification with suspension mass cytometry to characterize molecular reprogramming during the epithelial-to-mesenchymal transition as well as the mesenchymal-to-epithelial transition. We show the capability of ACE to quantify the dynamics of signaling network responses in human T lymphocytes. We further present the application of ACE in imaging mass cytometry-based multiparametric tissue imaging to identify tissue compartments and profile spatial aspects related to pathological states in polycystic kidney tissues.

Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes

Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.

Improvement in the sensitivity of LA-ICP-MS bioimaging by addition of nitrogen to the argon carrier gas

Elemental bioimaging of low abundant elements via laser ablation-inductively coupled plasma mass spectrometry (LA-ICP-MS) is hampered by a lack of sensitivity. Novel solutions for specific applications have been developed, however there is a need for more universal approaches. Here we investigated the addition of N2 to the ICP carrier gas to increase sensitivity, defined as signal-to-background, for the majority of biologically relevant elements. A gelatine standard that contained 38 elements across the mass range was ablated with increasing amounts of N2 added to the carrier gas post-ablation. The results show that while all elements examined had an increase in signal intensity, some elements did not have a resultant increase in signal-to-background. Sc, V, Mn, Fe, and Se all exhibited a reduction in signal-to-background ratios across all N2 flow rates examined, with the remaining elements experiencing signal-to-background increases from 1.2-7.8x, depending on the N2 flow rate and element. A compromised optimum N2 flow rate was determined for the analysis all elements and used to image endogenous elements in a mouse brain, and antibody-conjugated elements in a quadriceps muscle section. These images confirmed that the addition of N2 to the carrier gas increased the signal-to-background of the analysis, improving image resolution for endogenous elements and low abundant analytes used for immuno-mass spectrometry imaging of biomarkers. These findings offer a promising avenue for advancing the capabilities of LA-ICP-MS in bio-imaging applications.

Two-layer cascaded catalytic hairpin assemblies based on locked nucleic acids for one-step and highly sensitive ctDNA detection

Enzyme-free signal amplification of catalytic hairpin assembly (CHA) has enabled sensitive detection of circulating tumor DNA (ctDNA) in early clinical diagnosis. Conventional CHA strategies are restrained by the limited amplification efficiency of the single-stage system, and signal leakage from "breathing" influence and nuclease degradation. Here, we introduced two-layer cascaded locked nucleic acid (LNA)-assisted CHA circuits with the intelligent incorporation of LNA in the hairpins and reporter for the highly sensitive one-step detection of scarce ctDNA. The target-triggered upstream CHA reaction continuously generates hybrid products to catalyze the downstream CHA reaction for transducing the primary sensing event, and the released target and the produced hybrid product trigger the next catalytic reaction round at the same time and finally cascade to amplify the target ctDNA fluorescence output signal. Meanwhile, the stronger binding affinity of the LNA-DNA duplex endows the two-layer LNA-assisted CHA system with thermodynamic stability and nuclease resistance, and thus our designed system exhibits an excellent detection performance for target ctDNA in the range from 2 pM to 5 nM with a low detection limit of 0.6 pM. Significantly, the two-layer LNA-assisted CHA circuits have been successfully implemented for the feasible analysis of clinical samples. This two-layer cascaded LNA-assisted CHA strategy provides a promising high sensitivity tool for one-step detection of scarce ctDNA from complex clinical samples and would facilitate the reconfiguration of DNA circuit-based DNA nanotechnology for the precise analysis of other biomarkers in clinical research fields.

Advancements in technology for characterizing the tumor immune microenvironment

Immunotherapy plays a key role in cancer treatment, however, responses are limited to a small number of patients. The biological basis for the success of immunotherapy is the complex interaction between tumor cells and tumor immune microenvironment (TIME). Historically, research on tumor immune constitution was limited to the analysis of one or two markers, more novel technologies are needed to interpret the complex interactions between tumor cells and TIME. In recent years, major advances have already been made in depicting TIME at a considerably elevated degree of throughput, dimensionality and resolution, allowing dozens of markers to be labeled simultaneously, and analyzing the heterogeneity of tumour-immune infiltrates in detail at the single cell level, depicting the spatial landscape of the entire microenvironment, as well as applying artificial intelligence (AI) to interpret a large amount of complex data from TIME. In this review, we summarized emerging technologies that have made contributions to the field of TIME, and provided prospects for future research.

Explore & actuate: the future of personalized medicine in oncology through emerging technologies

PURPOSE OF REVIEW

The future of medicine is aimed to equip the physician with tools to assess the individual health of the patient for the uniqueness of the disease that separates it from the rest. The integration of omics technologies into clinical practice, reviewed here, would open new avenues for addressing the spatial and temporal heterogeneity of cancer. The rising cancer burden patiently awaits the advent of such an approach to personalized medicine for routine clinical settings.

RECENT FINDINGS

To weigh the translational potential, multiple technologies were categorized based on the extractable information from the different types of samples used, to the various omic-levels of molecular information that each technology has been able to advance over the last 2 years. This review uses a multifaceted classification that helps to assess translational potential in a meaningful way toward clinical adaptation.

SUMMARY

The importance of distinguishing technologies based on the flow of information from exploration to actuation puts forth a framework that allows the clinicians to better adapt a chosen technology or use them in combination to enhance their goals toward personalized medicine.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy

Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683 + GZMB + CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.

Multielement Z-tag imaging by X-ray fluorescence microscopy for next-generation multiplex imaging

Rapid, highly multiplexed, nondestructive imaging that spans the molecular to the supra-cellular scale would be a powerful tool for tissue analysis. However, the physical constraints of established imaging methods limit the simultaneous improvement of these parameters. Whole-organism to atomic-level imaging is possible with tissue-penetrant, picometer-wavelength X-rays. To enable highly multiplexed X-ray imaging, we developed multielement Z-tag X-ray fluorescence (MEZ-XRF) that can operate at kHz speeds when combined with signal amplification by exchange reaction (SABER)-amplified Z-tag reagents. We demonstrated parallel imaging of 20 Z-tag or SABER Z-tag reagents at subcellular resolution in cell lines and multiple human tissues. We benchmarked MEZ-XRF against imaging mass cytometry and demonstrated the nondestructive multiscale repeat imaging capabilities of MEZ-XRF with rapid tissue overview scans, followed by slower, more sensitive imaging of low-abundance markers such as immune checkpoint proteins. The unique multiscale, nondestructive nature of MEZ-XRF, combined with SABER Z-tags for high sensitivity or enhanced speed, enables highly multiplexed bioimaging across biological scales.