Multiplexed ion beam imaging of human breast tumors

Multiplexed Single-Cell Imaging: Past, Present, and Future

Jia-Ren Lin from the Laboratory of Systems Pharmacology at Harvard Medical School was awarded best poster at the annual Society of Biomolecular Imaging and Informatics meeting held in Boston, September 2016. His work focuses on single-cell imaging, especially on developing new methods for simultaneously detecting many antigens, named cyclic immunofluorescence (CycIF). This method could be applied in different stages of drug development, from discovery phase, preclinical research to clinical research. The current works and future directions of CycIF method are summarized in the following overview.

Cyclic Immunofluorescence (CycIF), A Highly Multiplexed Method for Single-cell Imaging

Cyclic Immunofluorescence (CycIF) is a public-domain method for performing highly multiplexed immunofluorescence imaging using a conventional epifluorescence microscope. It uses simple reagents and existing antibodies to construct images with up to 30 channels by sequential 4- to 6-channel imaging followed by fluorophore inactivation. Three variant methods are described, the most generally useful of which involves staining fixed cells with antibodies directly conjugated to Alexa Fluor dyes and imaging in four colors, inactivating fluorophores using a mild base in the presence of hydrogen peroxide and light, and then performing another round of staining and imaging. Cell morphology is preserved through multiple rounds of CycIF, and signal-to-noise ratios appear to increase. Unlike antibody-stripping methods, CycIF is gentle and optimized for monolayers of cultured cells. A second protocol involves indirect immunofluorescence and a third enables chemical inactivation of genetically encoded fluorescent proteins, allowing multiplex immunofluorescence to be combined with live-cell analysis of cells expressing fluorescent reporter proteins. © 2016 by John Wiley & Sons, Inc.

The Cohesive Metastasis Phenotype in Human Prostate Cancer

A critical barrier for the successful prevention and treatment of recurrent prostate cancer is detection and eradication of metastatic and therapy-resistant disease. Despite the fall in diagnoses and mortality, the reported incidence of metastatic disease has increased 72% since 2004. Prostate cancer arises in cohesive groups as intraepithelial neoplasia, migrates through muscle and leaves the gland via perineural invasion for hematogenous dissemination. Current technological advances have shown cohesive-clusters of tumor (also known as microemboli) within the circulation. Circulating tumor cell (CTC) profiles are indicative of disseminated prostate cancer, and disseminated tumor cells (DTC) are found in cohesive-clusters, a phenotypic characteristic of both radiation- and drug-resistant tumors. Recent reports in cell biology and informatics, coupled with mass spectrometry, indicate that the integrin adhesome network provides an explanation for the biophysical ability of cohesive-clusters of tumor cells to invade thorough muscle and nerve microenvironments while maintaining adhesion-dependent therapeutic resistance. Targeting cohesive-clusters takes advantage of the known ability of extracellular matrix (ECM) adhesion to promote tumor cell survival and represents an approach that has the potential to avoid the progression to drug- and radiotherapy-resistance. In the following review we will examine the evidence for development and dissemination of cohesive-clusters in metastatic prostate cancer.

Let There Be Light!

The invention of the microscope has been fundamental for the understanding of tissue architecture and subcellular structures. With the advancement of higher magnification microscopes came the development of various molecular biology tools such as Förster resonance energy transfer (FRET) and in situ proximity ligation assay (in situ PLA) to monitor protein interactions. Microscopy has become a commonly used method for the investigation of molecular events within the cell, for the identification of key players in signaling networks, and the activation of these pathways. Multiple approaches are available for functional analyses in single cells. They provide information not only on the localization of proteins at a given time point, but also on their expression levels and activity states, allowing us to pinpoint hallmarks of different cellular identities within tissues in health and disease. Clever solutions to increase the sensitivity of molecular tools, the possibilities for multiplexing, as well as image resolution have recently been introduced; however, these methods have their pros and cons. Therefore, one needs to carefully consider the biological question of interest along with the nature of the sample before choosing the most suitable method or combination of methods. Herein, we review a few of the most exciting microscopy-based molecular techniques for proteomic analysis and cover the benefits as well as the disadvantages of their use.

Validation of biomarkers to predict response to immunotherapy in cancer: Volume I - pre-analytical and analytical validation

Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, there have been many clinical successes using checkpoint receptor blockade, including T cell inhibitory receptors such as cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death-1 (PD-1). Despite demonstrated successes in a variety of malignancies, responses only typically occur in a minority of patients in any given histology. Additionally, treatment is associated with inflammatory toxicity and high cost. Therefore, determining which patients would derive clinical benefit from immunotherapy is a compelling clinical question.

Although numerous candidate biomarkers have been described, there are currently three FDA-approved assays based on PD-1 ligand expression (PD-L1) that have been clinically validated to identify patients who are more likely to benefit from a single-agent anti-PD-1/PD-L1 therapy. Because of the complexity of the immune response and tumor biology, it is unlikely that a single biomarker will be sufficient to predict clinical outcomes in response to immune-targeted therapy. Rather, the integration of multiple tumor and immune response parameters, such as protein expression, genomics, and transcriptomics, may be necessary for accurate prediction of clinical benefit. Before a candidate biomarker and/or new technology can be used in a clinical setting, several steps are necessary to demonstrate its clinical validity. Although regulatory guidelines provide general roadmaps for the validation process, their applicability to biomarkers in the cancer immunotherapy field is somewhat limited. Thus, Working Group 1 (WG1) of the Society for Immunotherapy of Cancer (SITC) Immune Biomarkers Task Force convened to address this need. In this two volume series, we discuss pre-analytical and analytical (Volume I) as well as clinical and regulatory (Volume II) aspects of the validation process as applied to predictive biomarkers for cancer immunotherapy. To illustrate the requirements for validation, we discuss examples of biomarker assays that have shown preliminary evidence of an association with clinical benefit from immunotherapeutic interventions. The scope includes only those assays and technologies that have established a certain level of validation for clinical use (fit-for-purpose). Recommendations to meet challenges and strategies to guide the choice of analytical and clinical validation design for specific assays are also provided.

Atmospheric pressure MALDI mass spectrometry imaging of tissues and cells at 1.4-μm lateral resolution

We report an atmospheric pressure (AP) matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) setup with a lateral resolution of 1.4 μm, a mass resolution greater than 100,000, and accuracy below ±2 p.p.m. We achieved this by coupling a focusing objective with a numerical aperture (NA) of 0.9 at 337 nm and a free working distance of 18 mm in coaxial geometry to an orbitrap mass spectrometer and optimizing the matrix application. We demonstrate improvement in image contrast, lateral resolution, and ion yield per unit area compared with a state-of-the-art commercial MSI source. We show that our setup can be used to detect metabolites, lipids, and small peptides, as well as to perform tandem MS experiments with 1.5-μm² sampling areas. To showcase these capabilities, we identified subcellular lipid, metabolite, and peptide distributions that differentiate, for example, cilia and oral groove in Paramecium caudatum.

In-Field, In Situ, and In Vivo 3-Dimensional Elemental Mapping for Plant Tissue and Soil Analysis Using Laser-Induced Breakdown Spectroscopy

Sensing and mapping element distributions in plant tissues and its growth environment has great significance for understanding the uptake, transport, and accumulation of nutrients and harmful elements in plants, as well as for understanding interactions between plants and the environment. In this study, we developed a 3-dimensional elemental mapping system based on laser-induced breakdown spectroscopy that can be deployed in- field to directly measure the distribution of multiple elements in living plants as well as in the soil. Mapping is performed by a fast scanning laser, which ablates a micro volume of a sample to form a plasma. The presence and concentration of specific elements are calculated using the atomic, ionic, and molecular spectral characteristics of the plasma emission spectra. Furthermore, we mapped the pesticide residues in maize leaves after spraying to demonstrate the capacity of this method for trace elemental mapping. We also used the system to quantitatively detect the element concentrations in soil, which can be used to further understand the element transport between plants and soil. We demonstrate that this method has great potential for elemental mapping in plant tissues and soil with the advantages of 3-dimensional and multi-elemental mapping, in situ and in vivo measurement, flexible use, and low cost.

Precision targeted therapy of ovarian cancer

The review is aimed at describing modern approaches to detection as well as precision and personalized treatment of ovarian cancer. Modern methods and future directions of nanotechnology-based targeted and personalized therapy are discussed.

Impaired coordination between signaling pathways is revealed in human colorectal cancer using single-cell mass cytometry of archival tissue blocks

Cellular heterogeneity poses a substantial challenge to understanding tissue-level phenotypes and confounds conventional bulk analyses. To analyze signaling at the single-cell level in human tissues, we applied mass cytometry using cytometry time of flight to formalin-fixed, paraffin-embedded (FFPE) normal and diseased intestinal specimens. This technique, called FFPE-DISSECT (disaggregation for intracellular signaling in single epithelial cells from tissue), is a single-cell approach to characterizing signaling states in embedded tissue samples. We applied FFPE-DISSECT coupled to mass cytometry and found differential signaling by tumor necrosis factor-α in intestinal enterocytes, goblet cells, and enteroendocrine cells, implicating the downstream RAS-RAF-MEK pathway in determining goblet cell identity. Application of this technique and computational analyses to human colon specimens confirmed the reduced differentiation in colorectal cancer (CRC) compared to normal colon and revealed increased intratissue and intertissue heterogeneity in CRC with quantitative changes in the regulation of signaling pathways. Specifically, coregulation of the kinases p38 and ERK, the translation regulator 4EBP1, and the transcription factor CREB in proliferating normal colon cells was lost in CRC. Our data suggest that this single-cell approach, applied in conjunction with genomic annotation, enables the rapid and detailed characterization of cellular heterogeneity from clinical repositories of embedded human tissues. This technique can be used to derive cellular landscapes from archived patient samples (beyond CRC) and as a high-resolution tool for disease characterization and subtyping.

NanoSIMS chemical imaging combined with correlative microscopy for biological sample analysis

Nano-scale Secondary Ion Mass Spectrometry (NanoSIMS) is one of the most powerful in situ elemental and isotopic analysis techniques available to biologists. The combination of stable isotope probing with NanoSIMS (nanoSIP) has opened up new avenues for biological studies over the past decade. However, due to limitations inherent with any analytical methodology, additional information from correlative techniques is usually required to address real biological questions. Here we review recent developments in correlative analysis applied to complex biological systems: first, high-resolution tracking of molecules (e.g. peptides, lipids) by correlation with electron microscopy and atomic force microscopy; second, identification of a specific microbial taxon with fluorescence in situ hybridization and quantification of its metabolic capacities; and, third, molecular specific imaging with new probes.

Lanthanides: Applications in Cancer Diagnosis and Therapy

Lanthanide complexes are of increasing importance in cancer diagnosis and therapy, owing to the versatile chemical and magnetic properties of the lanthanide-ion 4f electronic configuration. Following the first implementation of gadolinium(III)-based contrast agents in magnetic resonance imaging in the 1980s, lanthanide-based small molecules and nanomaterials have been investigated as cytotoxic agents and inhibitors, in photodynamic therapy, radiation therapy, drug/gene delivery, biosensing, and bioimaging. As the potential utility of lanthanides in these areas continues to increase, this timely review of current applications will be useful to medicinal chemists and other investigators interested in the latest developments and trends in this emerging field.

Tumour heterogeneity: principles and practical consequences

Two major reasons compel us to study tumour heterogeneity: firstly, it represents the basis of acquired therapy resistance, and secondly, it may be one of the major sources of the low level of reproducibility in clinical cancer research. The present review focuses on the heterogeneity of neoplastic disease, both within the primary tumour and between primary tumour and metastases. We discuss different levels of heterogeneity and the current understanding of the phenomenon, as well as imminent developments relevant for clinical research and diagnostic pathology. It is necessary to develop new tools to study heterogeneity and new biomarkers for heterogeneity. Established and new in situ methods will be very useful. In future studies, not only clonal heterogeneity needs to be addressed but also non-clonal phenotypic heterogeneity which might be important for therapy resistance. We also review heterogeneity established in major tumour types, in order to explore potential similarities that might help to define new strategies for targeted therapy.

Biology of lung cancer: genetic mutation, epithelial-mesenchymal transition, and cancer stem cells

At present, most cases of unresectable cancer cannot be cured. Genetic mutations, EMT, and cancer stem cells are three major issues linked to poor prognosis in such cases, all connected by inter- and intra-tumor heterogeneity. Issues on inter-/intra-tumor heterogeneity of genetic mutation could be resolved with recent and future technologies of deep sequencers, whereas, regarding such issues as the "same genome, different epigenome/phenotype", we expect to solve many of these problems in the future through further research in stem cell biology. We herein review and discuss the three major issues in the biology of cancers, especially from the standpoint of stem cell biology.

Systems immune monitoring in cancer therapy

Treatments that successfully modulate anti-cancer immunity have significantly improved outcomes for advanced stage malignancies and sparked intense study of the cellular mechanisms governing therapy response and resistance. These responses are governed by an evolving milieu of cancer and immune cell subpopulations that can be a rich source of biomarkers and biological insight, but it is only recently that research tools have developed to comprehensively characterize this level of cellular complexity. Mass cytometry is particularly well suited to tracking cells in complex tissues because >35 measurements can be made on each of hundreds of thousands of cells per sample, allowing all cells detected in a sample to be characterized for cell type, signalling activity, and functional outcome. This review focuses on mass cytometry as an example of systems level characterization of cancer and immune cells in human tissues, including blood, bone marrow, lymph nodes, and primary tumours. This review also discusses the state of the art in single cell tumour immunology, including tissue collection, technical and biological quality controls, computational analysis, and integration of different experimental and clinical data types. Ex vivo analysis of human tumour cells complements both in vivo monitoring, which generally measures far fewer features or lacks single cell resolution, and laboratory models, which incur cell type losses, signalling alterations, and genomic changes during establishment. Mass cytometry is on the leading edge of a new generation of cytomic tools that work with small tissue samples, such as a fine needle aspirates or blood draws, to monitor changes in rare or unexpected cell subsets during cancer therapy. This approach holds great promise for dissecting cellular microenvironments, monitoring how treatments affect tissues, revealing cellular biomarkers and effector mechanisms, and creating new treatments that productively engage the immune system to fight cancer and other diseases.

High-throughput genomic profiling of tumor-infiltrating leukocytes

Tumors are complex ecosystems comprised of diverse cell types including malignant cells, mesenchymal cells, and tumor-infiltrating leukocytes (TILs). While TILs are well known to play important roles in many aspects of cancer biology, recent developments in immuno-oncology have spurred considerable interest in TILs, particularly in relation to their optimal engagement by emerging immunotherapies. Traditionally, the enumeration of TIL phenotypic diversity and composition in solid tumors has relied on resolving single cells by flow cytometry and immunohistochemical methods. However, advances in genome-wide technologies and computational methods are now allowing TILs to be profiled with increasingly high resolution and accuracy directly from RNA mixtures of bulk tumor samples. In this review, we highlight recent progress in the development of in silico tumor dissection methods, and illustrate examples of how these strategies can be applied to characterize TILs in human tumors to facilitate personalized cancer therapy.

In-situ Isotopic Analysis at Nanoscale using Parallel Ion Electron Spectrometry: A Powerful New Paradigm for Correlative Microscopy

Isotopic analysis is of paramount importance across the entire gamut of scientific research. To advance the frontiers of knowledge, a technique for nanoscale isotopic analysis is indispensable. Secondary Ion Mass Spectrometry (SIMS) is a well-established technique for analyzing isotopes, but its spatial-resolution is fundamentally limited. Transmission Electron Microscopy (TEM) is a well-known method for high-resolution imaging down to the atomic scale. However, isotopic analysis in TEM is not possible. Here, we introduce a powerful new paradigm for in-situ correlative microscopy called the Parallel Ion Electron Spectrometry by synergizing SIMS with TEM. We demonstrate this technique by distinguishing lithium carbonate nanoparticles according to the isotopic label of lithium, viz. ⁶Li and ⁷Li and imaging them at high-resolution by TEM, adding a new dimension to correlative microscopy.

In-depth tissue profiling using multiplexed immunohistochemical consecutive staining on single slide

Despite remarkable recent achievements of immunotherapy strategies in cancer treatment, clinical responses remain limited to subsets of patients. Predictive markers of disease course and response to immunotherapy are urgently needed. Recent results have revealed the potential predictive value of immune cell phenotype and spatial distribution at the tumor site, prompting the need for multidimensional immunohistochemical analyses of tumor tissues. To address this need, we developed a sample-sparing, highly multiplexed immunohistochemistry technique based on iterative cycles of tagging, image scanning, and destaining of chromogenic substrate on a single slide. This assay, in combination with a newly developed automated digital landscaping solution, democratizes access to high-dimensional immunohistochemical analyses by capturing the complexity of the immunome using routine pathology standards. Applications of the method extend beyond cancer to screen and validate comprehensive panels of tissue-based prognostic and predictive markers, perform in-depth in situ monitoring of therapies, and identify targets of disease.

Cross-Platform DNA Encoding for Single-Cell Imaging of Gene Expression

Integration of imaging data across different molecular target types can provide in-depth insight into cell physiology and pathology, but remains challenging owing to poor compatibility between target-type-specific labeling methods. We show that cross-platform imaging analysis can be readily achieved through DNA encoding of molecular targets, which translates the molecular identity of various target types into a uniform in situ array of ssDNA tags for subsequent labeling with complementary imaging probes. The concept was demonstrated through multiplexed imaging of mRNAs and their corresponding proteins with multicolor quantum dots. The results reveal heterogeneity of cell transfection with siRNA and outline disparity in RNA interference (RNAi) kinetics at the level of both the mRNA and the encoded protein.

Monitoring immune responses in the tumor microenvironment

Immune monitoring in the tumor microenvironment allows for important insights into immune mechanisms of response and resistance to various cancer treatments; however clinical challenges exist using current strategies. Significant questions remain regarding monitoring of archival versus fresh tissue, assessment of static versus dynamic markers, evaluation of limited tissue samples, and the translation of insights gained from immunologically 'hot' tumors such as melanoma to other 'cold' tumor microenvironments prevalent in other cancer types. Current and emerging immune monitoring strategies will be examined herein, and genomic-based assays complementing these techniques will also be discussed. Finally, host genomic and external environmental factors influencing anti-tumor immune responses will be considered, including the role of the gut microbiome. Though optimal immune monitoring techniques are in evolution, great promise exists in recent advances that will help guide patient selection as far as type, sequence, and combination of therapeutic regimens to enhance anti-tumor immunity and clinical responses.

Metal Stable Isotope Tagging: Renaissance of Radioimmunoassay for Multiplex and Absolute Quantification of Biomolecules

The unambiguous quantification of biomolecules is of great significance in fundamental biological research as well as practical clinical diagnosis. Due to the lack of a detectable moiety, the direct and highly sensitive quantification of biomolecules is often a "mission impossible". Consequently, tagging strategies to introduce detectable moieties for labeling target biomolecules were invented, which had a long and significant impact on studies of biomolecules in the past decades. For instance, immunoassays have been developed with radioisotope tagging by Yalow and Berson in the late 1950s. The later languishment of this technology can be almost exclusively ascribed to the use of radioactive isotopes, which led to the development of nonradioactive tagging strategy-based assays such as enzyme-linked immunosorbent assay, fluorescent immunoassay, and chemiluminescent and electrochemiluminescent immunoassay. Despite great success, these strategies suffered from drawbacks such as limited spectral window capacity for multiplex detection and inability to provide absolute quantification of biomolecules. After recalling the sequences of tagging strategies, an apparent question is why not use stable isotopes from the start? A reasonable explanation is the lack of reliable means for accurate and precise quantification of stable isotopes at that time. The situation has changed greatly at present, since several atomic mass spectrometric measures for metal stable isotopes have been developed. Among the newly developed techniques, inductively coupled plasma mass spectrometry is an ideal technique to determine metal stable isotope-tagged biomolecules, for its high sensitivity, wide dynamic linear range, and more importantly multiplex and absolute quantification ability. Since the first published report by our group, metal stable isotope tagging has become a revolutionary technique and gained great success in biomolecule quantification. An exciting research highlight in this area is the development and application of the mass cytometer, which fully exploited the multiplexing potential of metal stable isotope tagging. It realized the simultaneous detection of dozens of parameters in single cells, accurate immunophenotyping in cell populations, through modeling of intracellular signaling network and undoubted discrimination of function and connection of cell subsets. Metal stable isotope tagging has great potential applications in hematopoiesis, immunology, stem cells, cancer, and drug screening related research and opened a post-fluorescence era of cytometry. Herein, we review the development of biomolecule quantification using metal stable isotope tagging. Particularly, the power of multiplex and absolute quantification is demonstrated. We address the advantages, applicable situations, and limitations of metal stable isotope tagging strategies and propose suggestions for future developments. The transfer of enzymatic or fluorescent tagging to metal stable isotope tagging may occur in many aspects of biological and clinical practices in the near future, just as the revolution from radioactive isotope tagging to fluorescent tagging happened in the past.

Multiplexed immunofluorescence delineates proteomic cancer cell states associated with metabolism

The phenotypic diversity of cancer results from genetic and nongenetic factors. Most studies of cancer heterogeneity have focused on DNA alterations, as technologies for proteomic measurements in clinical specimen are currently less advanced. Here, we used a multiplexed immunofluorescence staining platform to measure the expression of 27 proteins at the single-cell level in formalin-fixed and paraffin-embedded samples from treatment-naive stage II/III human breast cancer. Unsupervised clustering of protein expression data from 638,577 tumor cells in 26 breast cancers identified 8 clusters of protein coexpression. In about one-third of breast cancers, over 95% of all neoplastic cells expressed a single protein coexpression cluster. The remaining tumors harbored tumor cells representing multiple protein coexpression clusters, either in a regional distribution or intermingled throughout the tumor. Tumor uptake of the radiotracer 18F-fluorodeoxyglucose was associated with protein expression clusters characterized by hormone receptor loss, PTEN alteration, and HER2 gene amplification. Our study demonstrates an approach to generate cellular heterogeneity metrics in routinely collected solid tumor specimens and integrate them with in vivo cancer phenotypes.

Multiplexed Epitope-Based Tissue Imaging for Discovery and Healthcare Applications

The study of organs and tissues on a molecular level is necessary as we seek an understanding of health and disease. Over the last few years, powerful highly multiplexed epitope-based imaging approaches that rely on the serial imaging of tissues with fluorescently labeled antibodies and the simultaneous analysis using metal-labeled antibodies have emerged. These techniques enable analysis of dozens of epitopes in thousands of cells in a single experiment providing a systems level view of normal and disease processes at the single-cell level with spatial resolution in tissues. In this Review, I discuss, first, the highly multiplexed epitope-based imaging approaches and the generated data. Second, I describe challenges that must be overcome to implement these imaging methods from bench to bedside, including issues with tissue processing and analyses of the large amounts of data generated. Third, I discuss how these methods can be integrated with readouts of genome, transcriptome, metabolome, and live cell information, and fourth, the novel applications possible in tissue biology, drug development, and biomarker discovery. I anticipate that highly multiplexed epitope-based imaging approaches will broadly complement existing imaging methods and will become a cornerstone of tissue biology and biomedical research and of precision medical applications.

Comprehensive Immunohistochemistry: Digital, Analytical and Integrated

Immunohistochemistry (IHC) is widely used in contemporary pathology as a diagnostic and, increasingly, as a prognostic and predictive tool. The main value of the method today comes from a sensitive and specific detection of a protein of interest in the context of tissue architecture and cell populations. One of the major limitations of conventional IHC is related to the fact that the results are usually obtained by visual qualitative or semiquantitative evaluation. While this is sufficient for diagnostic purposes, measurement of prognostic and predictive biomarkers requires better accuracy and reproducibility. Also, objective evaluation of the spatial heterogeneity of biomarker expression as well as the development of combined/integrated biomarkers are in great demand. On the other end of the scale, the rapid development of tissue proteomics accounting for 2D spatial aspects has led to a disruptive concept of next-generation IHC, promising high multiplexing and broad dynamic range quantitative/spatial data on tissue protein expression. This 'evolutionary gap' between conventional and next-generation IHC can be filled by comprehensive IHC based on digital technologies (empowered by quantification and spatial and multiparametric analytics) and integrated into the pathology workflow and information systems. In this paper, we share our perspectives on a comprehensive IHC road map as a multistep development process.

Single-Cell Analysis in Cancer Genomics

Genetic changes and environmental differences result in cellular heterogeneity among cancer cells within the same tumor, thereby complicating treatment outcomes. Recent advances in single-cell technologies have opened new avenues to characterize the intra-tumor cellular heterogeneity, identify rare cell types, measure mutation rates, and, ultimately, guide diagnosis and treatment. In this paper we review the recent single-cell technological and computational advances at the genomic, transcriptomic, and proteomic levels, and discuss their applications in cancer research.

Simple, Scalable Proteomic Imaging for High-Dimensional Profiling of Intact Systems

Combined measurement of diverse molecular and anatomical traits that span multiple levels remains a major challenge in biology. Here, we introduce a simple method that enables proteomic imaging for scalable, integrated, high-dimensional phenotyping of both animal tissues and human clinical samples. This method, termed SWITCH, uniformly secures tissue architecture, native biomolecules, and antigenicity across an entire system by synchronizing the tissue preservation reaction. The heat- and chemical-resistant nature of the resulting framework permits multiple rounds (>20) of relabeling. We have performed 22 rounds of labeling of a single tissue with precise co-registration of multiple datasets. Furthermore, SWITCH synchronizes labeling reactions to improve probe penetration depth and uniformity of staining. With SWITCH, we performed combinatorial protein expression profiling of the human cortex and also interrogated the geometric structure of the fiber pathways in mouse brains. Such integrated high-dimensional information may accelerate our understanding of biological systems at multiple levels.

Multiscale analysis of the murine intestine for modeling human diseases

When functioning properly, the intestine is one of the key interfaces between the human body and its environment. It is responsible for extracting nutrients from our food and excreting our waste products. It provides an environment for a host of healthful microbes and serves as a first defense against pathogenic ones. These processes require tight homeostatic controls, which are provided by the interactions of a complex mix of epithelial, stromal, neural and immune cells, as well as the resident microflora. This homeostasis can be disrupted by invasive microbes, genetic lesions, and carcinogens, resulting in diseases such Clostridium difficile infection, inflammatory bowel disease (IBD) and cancer. Enormous strides have been made in understanding how this important organ functions in health and disease using everything from cell culture systems to animal models to human tissue samples. This has resulted in better therapies for all of these diseases, but there is still significant room for improvement. In the United States alone, 14,000 people per year die of C. difficile, up to 1.6 million people suffer from IBD, and more than 50,000 people die every year from colon cancer. Because these and other intestinal diseases arise from complex interactions between the different components of the gut ecosystem, we propose that systems approaches that address this complexity in an integrative manner may eventually lead to improved therapeutics that deliver lasting cures. This review will discuss the use of systems biology for studying intestinal diseases in vivo with particular emphasis on mouse models. Additionally, it will focus on established experimental techniques that have been used to drive this systems-level analysis, and emerging techniques that will push this field forward in the future.

Single-cell states versus single-cell atlases - two classes of heterogeneity that differ in meaning and method

Recent advances have created new opportunities to dissect cellular heterogeneity at the omics level. The enthusiasm for deep single-cell profiling has obscured a discussion of different types of heterogeneity and the most-appropriate techniques for studying each type. Here, I distinguish heterogeneity in regulation from heterogeneity in lineage. Snapshots of lineage heterogeneity provide a cell atlas that catalogs cellular diversity within complex tissues. Profiles of regulatory heterogeneity seek to interrogate one lineage deeply to capture an ensemble of single-cell states. Single-cell atlases require molecular signatures from many cells at a throughput afforded by mass cytometry-based, microfluidic-based, and microencapsulation-based methods. Single-cell states are more dependent on time, microenvironment, and low-abundance transcripts, emphasizing in situ methods that stress depth of profiling and quantitative accuracy.

Regulation of macrophage development and function in peripheral tissues

Macrophages are immune cells of haematopoietic origin that provide crucial innate immune defence and have tissue-specific functions in the regulation and maintenance of organ homeostasis. Recent studies of macrophage ontogeny, as well as transcriptional and epigenetic identity, have started to reveal the decisive role of the tissue stroma in the regulation of macrophage function. These findings suggest that most macrophages seed the tissues during embryonic development and functionally specialize in response to cytokines and metabolites that are released by the stroma and drive the expression of unique transcription factors. In this Review, we discuss how recent insights into macrophage ontogeny and macrophage-stroma interactions contribute to our understanding of the crosstalk that shapes macrophage function and the maintenance of organ integrity.

Edge effects in game-theoretic dynamics of spatially structured tumours

Cancer dynamics are an evolutionary game between cellular phenotypes. A typical assumption in this modelling paradigm is that the probability of a given phenotypic strategy interacting with another depends exclusively on the abundance of those strategies without regard for local neighbourhood structure. We address this limitation by using the Ohtsuki-Nowak transform to introduce spatial structure to the go versus grow game. We show that spatial structure can promote the invasive (go) strategy. By considering the change in neighbourhood size at a static boundary--such as a blood vessel, organ capsule or basement membrane--we show an edge effect that allows a tumour without invasive phenotypes in the bulk to have a polyclonal boundary with invasive cells. We present an example of this promotion of invasive (epithelial-mesenchymal transition-positive) cells in a metastatic colony of prostate adenocarcinoma in bone marrow. Our results caution that pathologic analyses that do not distinguish between cells in the bulk and cells at a static edge of a tumour can underestimate the number of invasive cells. Although we concentrate on applications in mathematical oncology, we expect our approach to extend to other evolutionary game models where interaction neighbourhoods change at fixed system boundaries.

Advancing biomedical imaging

Imaging reveals complex structures and dynamic interactive processes, located deep inside the body, that are otherwise difficult to decipher. Numerous imaging modalities harness every last inch of the energy spectrum. Clinical modalities include magnetic resonance imaging (MRI), X-ray computed tomography (CT), ultrasound, and light-based methods [endoscopy and optical coherence tomography (OCT)]. Research modalities include various light microscopy techniques (confocal, multiphoton, total internal reflection, superresolution fluorescence microscopy), electron microscopy, mass spectrometry imaging, fluorescence tomography, bioluminescence, variations of OCT, and optoacoustic imaging, among a few others. Although clinical imaging and research microscopy are often isolated from one another, we argue that their combination and integration is not only informative but also essential to discovering new biology and interpreting clinical datasets in which signals invariably originate from hundreds to thousands of cells per voxel.

Robust normalization protocols for multiplexed fluorescence bioimage analysis

study of mapping and interaction of co-localized proteins at a sub-cellular level is important for understanding complex biological phenomena. One of the recent techniques to map co-localized proteins is to use the standard immuno-fluorescence microscopy in a cyclic manner (Nat Biotechnol 24:1270–8, 2006; Proc Natl Acad Sci 110:11982–7, 2013). Unfortunately, these techniques suffer from variability in intensity and positioning of signals from protein markers within a run and across different runs. Therefore, it is necessary to standardize protocols for preprocessing of the multiplexed bioimaging (MBI) data from multiple runs to a comparable scale before any further analysis can be performed on the data. In this paper, we compare various normalization protocols and propose on the basis of the obtained results, a robust normalization technique that produces consistent results on the MBI data collected from different runs using the Toponome Imaging System (TIS). Normalization results produced by the proposed method on a sample TIS data set for colorectal cancer patients were ranked favorably by two pathologists and two biologists. We show that the proposed method produces higher between class Kullback-Leibler (KL) divergence and lower within class KL divergence on a distribution of cell phenotypes from colorectal cancer and histologically normal samples.

Single-cell analysis tools for drug discovery and development

The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed.

Eliminating Size-Associated Diffusion Constraints for Rapid On-Surface Bioassays with Nanoparticle Probes

Nanoparticle probes enable implementation of advanced on-surface assay formats, but impose often underappreciated size-associated constraints, in particular on assay kinetics and sensitivity. The present study highlights substantially slower diffusion-limited assay kinetics due to the rapid development of a nanoprobe depletion layer next to the surface, which static incubation and mixing of bulk solution employed in conventional assay setups often fail to disrupt. In contrast, cyclic solution draining and replenishing yields reaction-limited assay kinetics irrespective of the probe size. Using common surface bioassays, enzyme-linked immunosorbent assays and immunofluorescence, this study shows that this conceptually distinct approach effectively "erases" size-dependent diffusion constraints, providing a straightforward route to rapid on-surface bioassays employing bulky probes and procedures involving multiple labeling cycles, such as multicycle single-cell molecular profiling. For proof-of-concept, the study demonstrates that the assay time can be shortened from hours to minutes with the same probe concentration and, at a typical incubation time, comparable target labeling can be achieved with up to eight times lower nanoprobe concentration. The findings are expected to enable realization of novel assay formats and stimulate development of rapid on-surface bioassays with nanoparticle probes.

A contamination-insensitive probe for imaging specific biomolecules by secondary ion mass spectrometry

Imaging techniques should differentiate between specific signals, from the biomolecules of interest, and non-specific signals, from the background. We present a probe containing (15)N and (14)N isotopes in approximately equal proportion, for secondary ion mass spectrometry imaging. This probe designed for a precise biomolecule analysis is insensitive to background signals.

Highly multiplexed simultaneous detection of RNAs and proteins in single cells

Precise gene expression measurement has been fundamental to developing an advanced understanding of the roles of biological networks in health and disease. To enable detection of expression signatures specific to individual cells we developed PLAYR (Proximity Ligation Assay for RNA). PLAYR enables highly multiplexed quantification of transcripts in single cells by flow- and mass-cytometry and is compatible with standard antibody staining of proteins. With mass cytometry, this currently enables simultaneous quantification of more than 40 different mRNAs and proteins. The technology was demonstrated in primary cells to be capable of quantifying multiple gene expression transcripts while the identity and the functional state of each analyzed cell was defined based on the expression of other transcripts or proteins. PLAYR now enables high throughput deep phenotyping of cells to readily expand beyond protein epitopes to include RNA expression, thereby opening a new venue on the characterization of cellular metabolism.

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century's work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

Novel technologies and emerging biomarkers for personalized cancer immunotherapy

The culmination of over a century’s work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

Comprehensive Immune Profiling of Lung Adenocarcinomas Reveals Four Immunosubtypes with Plasma Cell Subtype a Negative Indicator

Neoplastic cancer cells and cancer stroma (including infiltrating immune cells) determine the biology and prognosis of cancer. Various types of adaptive and innate immune cells are known to infiltrate the cancer stroma. However, the patterns and spatial distribution of immune cell infiltration as well as its association with tumor histology remain poorly understood. To address these issues, we comprehensively analyzed the infiltrating immune cells present in lung adenocarcinoma. The principal types of both adaptive and innate infiltrating immune cells were immunohistochemically evaluated in the predominant histologic components of 111 lung adenocarcinomas. The same analysis was also carried out on 143 samples of histologic subtypes making up more than 20% of tumors. As a result, plasma cells and B cells with interfollicular distribution were almost exclusively observed in invasive histologic subtypes, while an increased number of mast cells were observed in noninvasive histologic subtypes. Cluster analysis revealed four distinct immunosubtypes (CD8, mast cell, macrophage/dendritic cell, and plasma cell subtypes) based on the infiltrating immune cell profiles. These immunosubtypes correlated with histologic subtypes, and univariate and multivariate analyses identified the plasma cell subtype as an independent negative prognostic factor. These plasma cells may be one of the major producers of the immunosuppressive cytokine IL35 in cancer stroma.

The niche in single-cell technologies

The niche is the microenvironment in which each cell exists and is able to keep its own peculiar characteristics. The importance of the niche has been intensively studied especially in the context of stem cells, as it is responsible for both the maintenance of stemness and activation of differentiation. In the past few years, a variety of single-cell technologies have shed light on the extraordinary variability that characterizes different stem cell populations both in vitro and in vivo, but in most cases positional information is lost. Recent developments of new technologies aim to integrate both the transcriptomic profiling of cells and their spatial location. In this review I will discuss the state of the art of these technologies and the integration with others approaches that will be important in the study of stem cell populations.

Immunocapture strategies in translational proteomics

Aiming at clinical studies of human diseases, antibody-assisted assays have been applied to biomarker discovery and toward a streamlined translation from patient profiling to assays supporting personalized treatments. In recent years, integrated strategies to couple and combine antibodies with mass spectrometry-based proteomic efforts have emerged, allowing for novel possibilities in basic and clinical research. Described in this review are some of the field's current and emerging immunocapture approaches from an affinity proteomics perspective. Discussed are some of their advantages, pitfalls and opportunities for the next phase in clinical and translational proteomics.

Rethinking ovarian cancer II: reducing mortality from high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSOC) accounts for 70-80% of ovarian cancer deaths, and overall survival has not changed significantly for several decades. In this Opinion article, we outline a set of research priorities that we believe will reduce incidence and improve outcomes for women with this disease. This 'roadmap' for HGSOC was determined after extensive discussions at an Ovarian Cancer Action meeting in January 2015.