Multiplexed ion beam imaging of human breast tumors

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.

High-resolution high-sensitivity elemental imaging by secondary ion mass spectrometry: from traditional 2D and 3D imaging to correlative microscopy

Secondary ion mass spectrometry (SIMS) constitutes an extremely sensitive technique for imaging surfaces in 2D and 3D. Apart from its excellent sensitivity and high lateral resolution (50 nm on state-of-the-art SIMS instruments), advantages of SIMS include high dynamic range and the ability to differentiate between isotopes. This paper first reviews the underlying principles of SIMS as well as the performance and applications of 2D and 3D SIMS elemental imaging. The prospects for further improving the capabilities of SIMS imaging are discussed. The lateral resolution in SIMS imaging when using the microprobe mode is limited by (i) the ion probe size, which is dependent on the brightness of the primary ion source, the quality of the optics of the primary ion column and the electric fields in the near sample region used to extract secondary ions; (ii) the sensitivity of the analysis as a reasonable secondary ion signal, which must be detected from very tiny voxel sizes and thus from a very limited number of sputtered atoms; and (iii) the physical dimensions of the collision cascade determining the origin of the sputtered ions with respect to the impact site of the incident primary ion probe. One interesting prospect is the use of SIMS-based correlative microscopy. In this approach SIMS is combined with various high-resolution microscopy techniques, so that elemental/chemical information at the highest sensitivity can be obtained with SIMS, while excellent spatial resolution is provided by overlaying the SIMS images with high-resolution images obtained by these microscopy techniques. Examples of this approach are given by presenting in situ combinations of SIMS with transmission electron microscopy (TEM), helium ion microscopy (HIM) and scanning probe microscopy (SPM).

Cytometry-based single-cell analysis of intact epithelial signaling reveals MAPK activation divergent from TNF-α-induced apoptosis in vivo

Understanding heterogeneous cellular behaviors in a complex tissue requires the evaluation of signaling networks at single-cell resolution. However, probing signaling in epithelial tissues using cytometry-based single-cell analysis has been confounded by the necessity of single-cell dissociation, where disrupting cell-to-cell connections inherently perturbs native cell signaling states. Here, we demonstrate a novel strategy (Disaggregation for Intracellular Signaling in Single Epithelial Cells from Tissue-DISSECT) that preserves native signaling for Cytometry Time-of-Flight (CyTOF) and fluorescent flow cytometry applications. A 21-plex CyTOF analysis encompassing core signaling and cell-identity markers was performed on the small intestinal epithelium after systemic tumor necrosis factor-alpha (TNF-α) stimulation. Unsupervised and supervised analyses robustly selected signaling features that identify a unique subset of epithelial cells that are sensitized to TNF-α-induced apoptosis in the seemingly homogeneous enterocyte population. Specifically, p-ERK and apoptosis are divergently regulated in neighboring enterocytes within the epithelium, suggesting a mechanism of contact-dependent survival. Our novel single-cell approach can broadly be applied, using both CyTOF and multi-parameter flow cytometry, for investigating normal and diseased cell states in a wide range of epithelial tissues.

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.

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.

Transition from identity to bioactivity-guided proteomics for biomarker discovery with focus on the PF2D platform

Proteomic strategies provide a valuable tool kit to identify proteins involved in diseases. With recent progress in MS technology, high throughput proteomics has accelerated protein identification for potential biomarkers. Numerous biomarker candidates have been identified in several diseases, and many are common among pathologies. An overall strategy that could complement and strengthen the search for biomarkers is combining protein identity with biological outcomes. This review describes an emerging framework of bridging bioactivity to protein identity, exploring the possibility that some biomarkers will have a mechanistic role in the disease process. A review of pulmonary, cardiovascular, and CNS biomarkers will be discussed to demonstrate the utility of combining bioactivity with identification as a means to not only find meaningful biomarkers, but also to uncover functional mediators of disease.

Getting controls under control: the time is now for immunohistochemistry

For several decades, immunohistochemistry (IHC), more specifically diagnostic IHC (dIHC), has been considered an art rather than a laboratory test. There was no clarity about what test performance characteristics are relevant to dIHC, test performance characteristics were not fully defined for dIHC and partly as a consequence of that, there were no standardised controls or reference standards. Herein, we discuss the role of standardisation of external controls for test performance characteristics and the role of standardised controls and reference standards for overall standardisation of IHC.

Cancer-associated fibroblasts as target and tool in cancer therapeutics and diagnostics

Cancer-associated fibroblasts (CAFs) are drivers of tumour progression and are considered as a target and a tool in cancer diagnostic and therapeutic applications. An increased abundance of CAFs or CAF signatures are recognized as a bad prognostic marker in several cancer types. Tumour-environment biomimetics strongly improve our understanding of the communication between CAFs, cancer cells and other host cells. Several experimental drugs targeting CAFs are in clinical trials for multiple tumour entities; alternatively, CAFs can be exploited as a tool to characterize the functionality of circulating tumour cells or to capture them as a tool to prevent metastasis. The continuous interaction between tissue engineers, biomaterial experts and cancer researchers creates the possibility to biomimic the tumour-environment and provides new opportunities in cancer diagnostics and management.

Toward understanding and exploiting tumor heterogeneity

The extent of tumor heterogeneity is an emerging theme that researchers are only beginning to understand. How genetic and epigenetic heterogeneity affects tumor evolution and clinical progression is unknown. The precise nature of the environmental factors that influence this heterogeneity is also yet to be characterized. Nature Medicine, Nature Biotechnology and the Volkswagen Foundation organized a meeting focused on identifying the obstacles that need to be overcome to advance translational research in and tumor heterogeneity. Once these key questions were established, the attendees devised potential solutions. Their ideas are presented here.

Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging

Studying the neuroanatomy of the mouse brain using imaging mass spectrometry and chemometric analysis.

Metals have a number of important roles within the brain. We used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to map the three-dimensional concentrations and distributions of transition metals, in particular iron (Fe), copper (Cu) and zinc (Zn) within the murine brain. LA-ICP-MS is one of the leading analytical tools for measuring metals in tissue samples. Here, we present a complete data reduction protocol for measuring metals in biological samples, including the application of a pyramidal voxel registration technique to reproducibly align tissue sections. We used gold (Au) nanoparticle and ytterbium (Yb)-tagged tyrosine hydroxylase antibodies to assess the co-localisation of Fe and dopamine throughout the entire mouse brain. We also examined the natural clustering of metal concentrations within the murine brain to elucidate areas of similar composition. This clustering technique uses a mathematical approach to identify multiple ‘elemental clusters’, avoiding user bias and showing that metal composition follows a hierarchical organisation of neuroanatomical structures. This work provides new insight into the distinct compartmentalisation of metals in the brain, and presents new avenues of exploration with regard to region-specific, metal-associated neurodegeneration observed in several chronic neurodegenerative diseases.

Paradoxical changes in innate immunity in aging: recent progress and new directions

Immunosenescence, describing alterations, including decline of immune responses with age, is comprised of inappropriate elevations, decreases, and dysregulated immune responses, leading to more severe consequences of bacterial and viral infections and reduced responses to vaccination. In adaptive immunity, these changes include increased proportions of antigen-experienced B and T cells at the cost of naïve cell populations. Innate immune changes in aging are complex in spanning multiple cell types, activation states, and tissue context. Innate immune responses are dampened in aging, yet there is also a paradoxical increase in certain signaling pathways and cytokine levels. Here, we review recent progress and highlight novel directions for expected advances that can lead the aging field to a new era of discovery that will embrace the complexity of aging in human populations.

Automated Analysis and Classification of Histological Tissue Features by Multi-Dimensional Microscopic Molecular Profiling

Characterization of the molecular attributes and spatial arrangements of cells and features within complex human tissues provides a critical basis for understanding processes involved in development and disease. Moreover, the ability to automate steps in the analysis and interpretation of histological images that currently require manual inspection by pathologists could revolutionize medical diagnostics. Toward this end, we developed a new imaging approach called multidimensional microscopic molecular profiling (MMMP) that can measure several independent molecular properties in situ at subcellular resolution for the same tissue specimen. MMMP involves repeated cycles of antibody or histochemical staining, imaging, and signal removal, which ultimately can generate information analogous to a multidimensional flow cytometry analysis on intact tissue sections. We performed a MMMP analysis on a tissue microarray containing a diverse set of 102 human tissues using a panel of 15 informative antibody and 5 histochemical stains plus DAPI. Large-scale unsupervised analysis of MMMP data, and visualization of the resulting classifications, identified molecular profiles that were associated with functional tissue features. We then directly annotated H&E images from this MMMP series such that canonical histological features of interest (e.g. blood vessels, epithelium, red blood cells) were individually labeled. By integrating image annotation data, we identified molecular signatures that were associated with specific histological annotations and we developed statistical models for automatically classifying these features. The classification accuracy for automated histology labeling was objectively evaluated using a cross-validation strategy, and significant accuracy (with a median per-pixel rate of 77% per feature from 15 annotated samples) for de novo feature prediction was obtained. These results suggest that high-dimensional profiling may advance the development of computer-based systems for automatically parsing relevant histological and cellular features from molecular imaging data of arbitrary human tissue samples, and can provide a framework and resource to spur the optimization of these technologies.

Introduction of Zinc-salt Fixation for Effective Detection of Immune Cell-related Markers by Immunohistochemistry

Tissue localization of immune cells is critical to the study of disease processes in mouse models of human diseases. However, immunohistochemistry (IHC) for immune cell phenotyping in mouse tissue sections presents specific technical challenges. For example, CD4 and CD8 have been difficult to detect using IHC on formalin-fixed and paraffin-embedded mouse tissue, prompting alternative methods. We investigated the use of formalin-free zinc-salt fixation (ZN) and optimized IHC protocols for detecting a panel of immune cell-related markers (CD3, CD4, CD8, Foxp3, B220, F4/80, CD68, and major histocompatibility complex [MHC] class-I, MHC class-II, and Gr-1). The IHC results for these markers were compared on mouse spleen tissue treated with neutral buffered formalin (NBF) or ZN with or ZN without antigen retrieval (AR). Whereas CD4 and CD8 were not detected in NBF-treated tissue, all markers were detected in ZN-treated tissue without AR. Thus, the use of ZN treatment for IHC staining can be a good tool for studying immunoreactive lesions in tissues.

Extensive rewiring of epithelial-stromal co-expression networks in breast cancer

BACKGROUND

Epithelial-stromal crosstalk plays a critical role in invasive breast cancer pathogenesis; however, little is known on a systems level about how epithelial-stromal interactions evolve during carcinogenesis.

RESULTS

We develop a framework for building genome-wide epithelial-stromal co-expression networks composed of pairwise co-expression relationships between mRNA levels of genes expressed in the epithelium and stroma across a population of patients. We apply this method to laser capture micro-dissection expression profiling datasets in the setting of breast carcinogenesis. Our analysis shows that epithelial-stromal co-expression networks undergo extensive rewiring during carcinogenesis, with the emergence of distinct network hubs in normal breast, and estrogen receptor-positive and estrogen receptor-negative invasive breast cancer, and the emergence of distinct patterns of functional network enrichment. In contrast to normal breast, the strongest epithelial-stromal co-expression relationships in invasive breast cancer mostly represent self-loops, in which the same gene is co-expressed in epithelial and stromal regions. We validate this observation using an independent laser capture micro-dissection dataset and confirm that self-loop interactions are significantly increased in cancer by performing computational image analysis of epithelial and stromal protein expression using images from the Human Protein Atlas.

CONCLUSIONS

Epithelial-stromal co-expression network analysis represents a new approach for systems-level analyses of spatially localized transcriptomic data. The analysis provides new biological insights into the rewiring of epithelial-stromal co-expression networks and the emergence of epithelial-stromal co-expression self-loops in breast cancer. The approach may facilitate the development of new diagnostics and therapeutics targeting epithelial-stromal interactions in cancer.

The use of virtual microscopy and a wiki in pathology education: Tracking student use, involvement, and response

Background:

The pathology laboratory course at the New York College of Podiatric Medicine involves the use of Virtual Microscopy. The students can scan the whole slide, section by section, and zoom in or out.

Methods:

Using the advantages of digital pathology, the students can, in addition, access the slide collections from other medical schools and put up normal histology (control) slides side-by-side with the pathology. They can cut and paste and preserve the region of interest that they find. They can edit and annotate their slides. A wiki was created (http://pathlab2014.wikifoundry.com)for the Class of 2014. The students saved, edited and uploaded their slides. In the wiki format, other students could comment, further edit, and even delete the slides.

Results:

The students studied Basic Mechanisms and System Pathology. During this time, they saved, edited, shared, and uploaded their slides to the wiki. These were available in one full presentation and were also grouped into 16 albums. They were available to all. Student access was followed by Google analytics. At the end of the course, a questionnaire was distributed, assessing their impression of the wiki format and soliciting strengths and weaknesses.

Conclusions:

The use of a wiki has a number of important advantages in pathology education. It trains the students in the more sophisticated skills that they will use as professional pathologists or as clinicians: (1) Telepathology-it enables them to share slides and discuss observations. (2) Archiving and retrieval - It models the challenge faced by hospitals, diagnostic labs and physicians in maintaining a collection of slides in a form that is easily accessible. (3) Image analysis-familiarity with the wiki format allows them to jump easily to capturing and storing images found in the literature or in a pathologist's report. Experience with the use of a wiki in pathology education has been quite satisfactory from both the faculty and the student's point of view.

Integrative network modeling approaches to personalized cancer medicine

The ability to collect millions of molecular measurements from patients is a now a reality for clinical medicine. This reality has created the challenge of how to integrate these vast amounts of data into models that accurately predict complex pathophysiology and can translate this complexity into clinically actionable outputs. Integrative informatics and data-driven approaches provide a framework for analyzing large-scale datasets and combining them into multiscale models that can be used to determine the key drivers of disease and identify optimal therapies for treating tumors. In this perspective we discuss how an integrative modeling approach is being used to inform individual treatment decisions, highlighting a recent case report that illustrates the challenges and opportunities for personalized oncology.

Mass cytometry as a platform for the discovery of cellular biomarkers to guide effective rheumatic disease therapy

The development of biomarkers for autoimmune diseases has been hampered by a lack of understanding of disease etiopathogenesis and of the mechanisms underlying the induction and maintenance of inflammation, which involves complex activation dynamics of diverse cell types. The heterogeneous nature and suboptimal clinical response to treatment observed in many autoimmune syndromes highlight the need to develop improved strategies to predict patient outcome to therapy and personalize patient care. Mass cytometry, using CyTOF®, is an advanced technology that facilitates multiparametric, phenotypic analysis of immune cells at single-cell resolution. In this review, we outline the capabilities of mass cytometry and illustrate the potential of this technology to enhance the discovery of cellular biomarkers for rheumatoid arthritis, a prototypical autoimmune disease.

Secondary-ion mass spectrometry of genetically encoded targets

Secondary ion mass spectrometry (SIMS) is generally used in imaging the isotopic composition of various materials. It is becoming increasingly popular in biology, especially for investigations of cellular metabolism. However, individual proteins are difficult to identify in SIMS, which limits the ability of this technology to study individual compartments or protein complexes. We present a method for specific protein isotopic and fluorescence labeling (SPILL), based on a novel click reaction with isotopic probes. Using this method, we added (19) F-enriched labels to different proteins, and visualized them by NanoSIMS and fluorescence microscopy. The (19) F signal allowed the precise visualization of the protein of interest, with minimal background, and enabled correlative studies of protein distribution and cellular metabolism or composition. SPILL can be applied to biological systems suitable for click chemistry, which include most cell-culture systems, as well as small model organisms.

Quantitative measurement of cancer tissue biomarkers in the lab and in the clinic

Detection of biomolecules in tissues provides contextual information and the possibility to assess the interaction of different cell types and markers. Routine qualitative assessment of immune- and oligonucleotide-based methods in research and the clinic has been associated with assay variability because of lack of stringent validation and subjective interpretation of results. As a result, the vast majority of in situ assays in clinical usage are nonquantitative and, although useful, often of questionable scientific validity. Here, we revisit the reporters and methods used for single- and multiplexed in situ visualization of protein and RNA. Then we examine methods for the use of quantitative platforms for in situ measurement of protein and mRNA levels. Finally, we discuss the challenges of the transition of these methods to the clinic and their potential role as tools for development of companion diagnostic tests.

Immunohistochemistry and mass spectrometry for highly multiplexed cellular molecular imaging

The role of immunohistochemistry (IHC) in the management of cancer has expanded to provide improved diagnostic classification, as well as guidance on disease prognosis, therapy, and relapse. These new tasks require evaluation of an increasing number of protein targets; however, conventional multiplexing, usually achieved using serial tissue sections stained for a single analyte per slide, can exhaust small biopsy specimens, complicate slide-to-slide protein expression correlation, and leave insufficient material for additional molecular assays. A new approach, mass spectrometry immunohistochemistry (MSIHC), compatible with high levels of target multiplexing and suitable for use on formalin-fixed, paraffin-embedded samples can circumvent many of these issues. The strategy employs antibodies that are labeled with elemental mass tags, such as isotopically pure lanthanides not typically found in biological specimens, rather than with typical fluorophores or chromogens. The metal-labeled antibodies are then detected in tissue using lasers or ion beams to liberate the tags for subsequent mass spectrometry detection. Within a given multiplexed IHC panel, the metal labels are selected so that their respective masses do not overlap. More than 30 antibodies have been imaged simultaneously, and up to 100 antibodies could potentially be detected at once if the full available mass spectrum is deployed. MSIHC has a number of advantages over conventional IHC techniques. Background due to autofluorescence is absent and the dynamic range is 10(5), exceeding immunofluorescence and chromogenic IHC by 100-fold and 1000-fold, respectively. Detection of labeled primary antibodies improves assay linearity over both chromogenic and fluorescent IHC. Multiplexed mass-tagged antibodies incubated simultaneously with tissue do not appear to cross-interfere, and because the mass tags do not degrade, samples are stable indefinitely. The imaging resolution of multiplexed ion-beam imaging can be better than light microscopy. With appropriate instrumentation, MSIHC has the potential to transform research and clinical pathology practice.

Open access to large scale datasets is needed to translate knowledge of cancer heterogeneity into better patient outcomes

In this guest editorial, Andrew Beck discusses the importance of open access to big data for translating knowledge of cancer heterogeneity into better outcomes for cancer patients.

Super-resolution imaging for cell biologists: concepts, applications, current challenges and developments

The recent 2014 Nobel Prize in chemistry honored an era of discoveries and technical advancements in the field of super-resolution microscopy. However, the applications of diffraction-unlimited imaging in biology have a long road ahead and persistently engage scientists with new challenges. Some of the bottlenecks that restrain the dissemination of super-resolution techniques are tangible, and include the limited performance of affinity probes and the yet not capillary diffusion of imaging setups. Likewise, super-resolution microscopy has introduced new paradigms in the design of projects that require imaging with nanometer-resolution and in the interpretation of biological images. Besides structural or morphological characterization, super-resolution imaging is quickly expanding towards interaction mapping, multiple target detection and live imaging. Here we review the recent progress of biologists employing super-resolution imaging, some pitfalls, implications and new trends, with the purpose of animating the field and spurring future developments.