Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue

Fully automated 5-plex fluorescent immunohistochemistry with tyramide signal amplification and same species antibodies

The ability to simultaneously visualize the presence, abundance, location and functional state of many targets in cells and tissues has been described as a true next-generation approach in immunohistochemistry (IHC). A typical requirement for multiplex IHC (mIHC) is the use of different animal species for each primary (1°Ab) and secondary (2°Ab) antibody pair. Although 1°Abs from different species have been used with differently labeled species-specific 2°Abs, quite often the appropriate combination of antibodies is not available. More recently, sequential detection of multiple antigens using 1°Abs from the same species used a microwaving treatment between successive antigen detection cycles to elute previously bound 1°Ab/2°Ab complex and therefore to prevent the cross-reactivity of anti-species 2°Abs used in subsequent detection cycles. We present here a fully automated 1°Ab/2°Ab complex heat deactivation (HD) method on Ventana's BenchMark ULTRA slide stainer. This method is applied to detection using fluorophore-conjugated tyramide deposited on the tissue and takes advantage of the strong covalent bonding of the detection substrate to the tissue, preventing its elution in the HD process. The HD process was characterized for (1) effectiveness in preventing Ab cross-reactivity, (2) impact on the epitopes and (3) impact on the fluorophores. An automated 5-plex fluorescent IHC assay was further developed using the HD method and rabbit 1°Abs for CD3, CD8, CD20, CD68 and FoxP3 immune biomarkers in human tissue specimens. The fluorophores were carefully chosen and the narrow-band filters were designed to allow visualization of the staining under fluorescent microscope with minimal bleed through. The automated 5-plex fluorescent IHC assay achieved staining results comparable to the respective single-plex chromogenic IHC assays. This technology enables automated mIHC using unmodified 1°Abs from same species and the corresponding anti-species 2°Ab on a clinically established automated platform to ensure staining quality, reliability and reproducibility.

Highly Multiplexed, Super-resolution Imaging of T Cells Using madSTORM

Imaging heterogeneous cellular structures using single molecule localization microscopy has been hindered by inadequate localization precision and multiplexing ability. Using fluorescent nano-diamond fiducial markers, we describe the drift correction and alignment procedures required to obtain high precision in single molecule localization microscopy. In addition, a new multiplexing strategy, madSTORM, is described in which multiple molecules are targeted in the same cell using sequential binding and elution of fluorescent antibodies. madSTORM is demonstrated on an activated T cell to visualize the locations of different components within a membrane-bound, multi-protein structure called the T cell receptor microcluster. In addition, application of madSTORM as a general tool for visualization of multi-protein structures is discussed.

The CA19-9 and Sialyl-TRA Antigens Define Separate Subpopulations of Pancreatic Cancer Cells

Molecular markers to detect subtypes of cancer cells could facilitate more effective treatment. We recently identified a carbohydrate antigen, named sTRA, that is as accurate a serological biomarker of pancreatic cancer as the cancer antigen CA19-9. We hypothesized that the cancer cells producing sTRA are a different subpopulation than those producing CA19-9. The sTRA glycan was significantly elevated in tumor tissue relative to adjacent pancreatic tissue in 3 separate tissue microarrays covering 38 patients. The morphologies of the cancer cells varied in association with glycan expression. Cells with dual staining of both markers tended to be in well-to-moderately differentiated glands with nuclear polarization, but exclusive sTRA staining was present in small clusters of cells with poor differentiation and large vacuoles, or in small and ill-defined glands. Patients with higher dual-staining of CA19-9 and sTRA had statistically longer time-to-progression after surgery. Patients with short time-to-progression (<2 years) had either low levels of the dual-stained cells or high levels of single-stained cells, and such patterns differentiated short from long time-to-progression with 90% (27/30) sensitivity and 80% (12/15) specificity. The sTRA and CA19-9 glycans define separate subpopulations of cancer cells and could together have value for classifying subtypes of pancreatic adenocarcinoma.

Optimized multiplex immunofluorescence single-cell analysis reveals tuft cell heterogeneity

Intestinal tuft cells are a rare, poorly understood cell type recently shown to be a critical mediator of type 2 immune response to helminth infection. Here, we present advances in segmentation algorithms and analytical tools for multiplex immunofluorescence (MxIF), a platform that enables iterative staining of over 60 antibodies on a single tissue section. These refinements have enabled a comprehensive analysis of tuft cell number, distribution, and protein expression profiles as a function of anatomical location and physiological perturbations. Based solely on DCLK1 immunoreactivity, tuft cell numbers were similar throughout the mouse small intestine and colon. However, multiple subsets of tuft cells were uncovered when protein coexpression signatures were examined, including two new intestinal tuft cell markers, Hopx and EGFR phosphotyrosine 1068. Furthermore, we identified dynamic changes in tuft cell number, composition, and protein expression associated with fasting and refeeding and after introduction of microbiota to germ-free mice. These studies provide a foundational framework for future studies of intestinal tuft cell regulation and demonstrate the utility of our improved MxIF computational methods and workflow for understanding cellular heterogeneity in complex tissues in normal and disease states.

Microchip-based single-cell functional proteomics for biomedical applications

Cellular heterogeneity has been widely recognized but only recently have single cell tools become available that allow characterizing heterogeneity at the genomic and proteomic levels. We review the technological advances in microchip-based toolkits for single-cell functional proteomics. Each of these tools has distinct advantages and limitations, and a few have advanced toward being applied to address biological or clinical problems that traditional population-based methods fail to address. High-throughput single-cell proteomic assays generate high-dimensional data sets that contain new information and thus require developing new analytical frameworks to extract new biology. In this review article, we highlight a few biological and clinical applications in which microchip-based single-cell proteomic tools provide unique advantages. The examples include resolving functional heterogeneity and dynamics of immune cells, dissecting cell-cell interaction by creating a well-controlled on-chip microenvironment, capturing high-resolution snapshots of immune system functions in patients for better immunotherapy and elucidating phosphoprotein signaling networks in cancer cells for guiding effective molecularly targeted therapies.

Universal Super-Resolution Multiplexing by DNA Exchange

Super-resolution microscopy allows optical imaging below the classical diffraction limit of light with currently up to 20× higher spatial resolution. However, the detection of multiple targets (multiplexing) is still hard to implement and time-consuming to conduct. Here, we report a straightforward sequential multiplexing approach based on the fast exchange of DNA probes which enables efficient and rapid multiplexed target detection with common super-resolution techniques such as (d)STORM, STED, and SIM. We assay our approach using DNA origami nanostructures to quantitatively assess labeling, imaging, and washing efficiency. We furthermore demonstrate the applicability of our approach by imaging multiple protein targets in fixed cells.

A Stepwise Integrated Approach to Personalized Risk Predictions in Stage III Colorectal Cancer

Purpose: Apoptosis is essential for chemotherapy responses. In this discovery and validation study, we evaluated the suitability of a mathematical model of apoptosis execution (APOPTO-CELL) as a stand-alone signature and as a constituent of further refined prognostic stratification tools.Experimental Design: Apoptosis competency of primary tumor samples from patients with stage III colorectal cancer (n = 120) was calculated by APOPTO-CELL from measured protein concentrations of Procaspase-3, Procaspase-9, SMAC, and XIAP. An enriched APOPTO-CELL signature (APOPTO-CELL-PC3) was synthesized to capture apoptosome-independent effects of Caspase-3. Furthermore, a machine learning Random Forest approach was applied to APOPTO-CELL-PC3 and available molecular and clinicopathologic data to identify a further enhanced signature. Association of the signature with prognosis was evaluated in an independent colon adenocarcinoma cohort (TCGA COAD, n = 136).Results: We identified 3 prognostic biomarkers (P = 0.04, P = 0.006, and P = 0.0004 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively) with increasing stratification accuracy for patients with stage III colorectal cancer.The APOPTO-CELL-PC3 signature ranked highest among all features. The prognostic value of the signatures was independently validated in stage III TCGA COAD patients (P = 0.01, P = 0.04, and P = 0.02 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively). The signatures provided further stratification for patients with CMS1-3 molecular subtype.Conclusions: The integration of a systems-biology-based biomarker for apoptosis competency with machine learning approaches is an appealing and innovative strategy toward refined patient stratification. The prognostic value of apoptosis competency is independent of other available clinicopathologic and molecular factors, with tangible potential of being introduced in the clinical management of patients with stage III colorectal cancer. Clin Cancer Res; 23(5); 1200-12. ©2016 AACR.

Resistance to mTORC1 Inhibitors in Cancer Therapy: From Kinase Mutations to Intratumoral Heterogeneity of Kinase Activity

Targeting mTORC1 has been thoroughly explored in cancer therapy. Following encouraging preclinical studies, mTORC1 inhibitors however failed to provide substantial benefits in cancer patients. Several resistance mechanisms have been identified including mutations of mTOR and activation of alternate proliferation pathways. Moreover, emerging evidence discloses intratumoral heterogeneity of mTORC1 activity that further contributes to a reduced anticancer efficacy of mTORC1 inhibitors. Genetic heterogeneity as well as heterogeneous conditions of the tumor environment such as hypoxia profoundly modifies mTORC1 activity in tumors and hence influences the response of tumors to mTORC1 inhibitors. Intriguingly, the heterogeneity of mTORC1 activity also occurs towards its substrates at the single cell level, as mutually exclusive pattern of activation of mTORC1 downstream effectors has been reported in tumors. After briefly describing mTORC1 biology and the use of mTORC1 inhibitors in patients, this review will give an overview on concepts of resistance to mTORC1 inhibition in cancer with a particular focus on intratumoral heterogeneity of mTORC1 activity.

Versatile tissue lasers based on high-Q Fabry-Pérot microcavities

Biolasers are an emerging technology for next generation biochemical detection and clinical applications. Progress has recently been made to achieve lasing from biomolecules and single living cells. Tissues, which consist of cells embedded in an extracellular matrix, mimic more closely the actual complex biological environment in a living body and therefore are of more practical significance. Here, we developed a highly versatile tissue laser platform, in which tissues stained with fluorophores are sandwiched in a high-Q Fabry-Pérot microcavity. Distinct lasing emissions from muscle and adipose tissues stained respectively with fluorescein isothiocyanate (FITC) and boron-dipyrromethene (BODIPY), and hybrid muscle/adipose tissue with dual staining were achieved with a threshold of only ∼10 μJ mm-2. Additionally, we investigated how the tissue structure/geometry, tissue thickness, and staining dye concentration affect the tissue laser. Lasing emission from FITC conjugates (FITC-phalloidin) that specifically target F-actin in muscle tissues was also realized. It is further found that, despite the large fluorescence spectral overlap between FITC and BODIPY in tissues, their lasing emissions could be clearly distinguished and controlled due to their narrow lasing bands and different lasing thresholds, thus enabling highly multiplexed detection. Our tissue laser platform can be broadly applicable to various types of tissues/diseases. It provides a new tool for a wide range of biological and biomedical applications, such as diagnostics/screening of tissues and identification/monitoring of biological transformations in tissue engineering.

Highly Multiplexed Single-Cell In Situ Protein Analysis with Cleavable Fluorescent Antibodies

Limitations on the number of proteins that can be quantified in single cells in situ impede advances in our deep understanding of normal cell physiology and disease pathogenesis. Herein, we present a highly multiplexed single-cell in situ protein analysis approach that is based on chemically cleavable fluorescent antibodies. In this method, antibodies tethered to fluorophores through a novel azide-based cleavable linker are utilized to detect their protein targets. After fluorescence imaging and data storage, the fluorophores coupled to the antibodies are efficiently cleaved without loss of protein target antigenicity. Upon continuous cycles of target recognition, fluorescence imaging, and fluorophore cleavage, this approach has the potential to quantify over 100 different proteins in individual cells at optical resolution. This single-cell in situ protein profiling technology will have wide applications in signaling network analysis, molecular diagnosis, and cellular targeted therapies.

Superresolution Imaging of Clinical Formalin Fixed Paraffin Embedded Breast Cancer with Single Molecule Localization Microscopy

Millions of archived formalin-fixed, paraffin-embedded (FFPE) specimens contain valuable molecular insight into healthy and diseased states persevered in their native ultrastructure. To diagnose and treat diseases in tissue on the nanoscopic scale, pathology traditionally employs electron microscopy (EM), but this platform has significant limitations including cost and painstaking sample preparation. The invention of single molecule localization microscopy (SMLM) optically overcame the diffraction limit of light to resolve fluorescently labeled molecules on the nanoscale, leading to many exciting biological discoveries. However, applications of SMLM in preserved tissues has been limited. Through adaptation of the immunofluorescence workflow on FFPE sections milled at histological thickness, cellular architecture can now be visualized on the nanoscale using SMLM including individual mitochondria, undulations in the nuclear lamina, and the HER2 receptor on membrane protrusions in human breast cancer specimens. Using astigmatism imaging, these structures can also be resolved in three dimensions to a depth of ~800 nm. These results demonstrate the utility of SMLM in efficiently uncovering ultrastructural information of archived clinical samples, which may offer molecular insights into the physiopathology of tissues to assist in disease diagnosis and treatment using conventional sample preparation methods.

Biologically Relevant Heterogeneity: Metrics and Practical Insights

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

Phenotyping Multiple Subsets of Immune Cells In Situ in FFPE Tissue Sections: An Overview of Methodologies

The recent clinical success of new cancer immunotherapy agents and methods is driving the need to understand the role of immune cells in solid tissues, especially tumors. Immune cell phenotyping via flow cytometry, while a cornerstone of immunology, is not spatially resolved and cannot analyze immune cell subsets in situ in clinical biopsy sections or to determine their interrelationships. To address this problem, a number of methodologies have been developed in attempts to phenotype immune and other cells in images acquired from tissue sections and to assess their organization in the tumor and its microenvironment. This chapter review the staining and multiplex image analysis methods that have been developed for phenotyping immune and other cells in formalin-fixed, paraffin-embedded (FFPE) tissue sections.

Analysis of the Germinal Center Reaction in Tissue Sections

Germinal centers are short-lived microanatomical compartments with essential roles in adaptive immunity. These lymphoid structures can be identified in secondary lymphoid organs using both flow cytometry and immunohistological analyses, but only the latter provides useful architectural and spatial information. Here we describe how to use immunofluorescence and immunohistochemistry with specific antibodies to precisely highlight the cellular and architectural features of germinal centers, both in human and mouse secondary lymphoid organs, and to study their normal development and disturbance in disease.

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.

Pointwise mutual information quantifies intratumor heterogeneity in tissue sections labeled with multiple fluorescent biomarkers

BACKGROUND

Measures of spatial intratumor heterogeneity are potentially important diagnostic biomarkers for cancer progression, proliferation, and response to therapy. Spatial relationships among cells including cancer and stromal cells in the tumor microenvironment (TME) are key contributors to heterogeneity.

METHODS

We demonstrate how to quantify spatial heterogeneity from immunofluorescence pathology samples, using a set of 3 basic breast cancer biomarkers as a test case. We learn a set of dominant biomarker intensity patterns and map the spatial distribution of the biomarker patterns with a network. We then describe the pairwise association statistics for each pattern within the network using pointwise mutual information (PMI) and visually represent heterogeneity with a two-dimensional map.

RESULTS

We found a salient set of 8 biomarker patterns to describe cellular phenotypes from a tissue microarray cohort containing 4 different breast cancer subtypes. After computing PMI for each pair of biomarker patterns in each patient and tumor replicate, we visualize the interactions that contribute to the resulting association statistics. Then, we demonstrate the potential for using PMI as a diagnostic biomarker, by comparing PMI maps and heterogeneity scores from patients across the 4 different cancer subtypes. Estrogen receptor positive invasive lobular carcinoma patient, AL13-6, exhibited the highest heterogeneity score among those tested, while estrogen receptor negative invasive ductal carcinoma patient, AL13-14, exhibited the lowest heterogeneity score.

CONCLUSIONS

This paper presents an approach for describing intratumor heterogeneity, in a quantitative fashion (via PMI), which departs from the purely qualitative approaches currently used in the clinic. PMI is generalizable to highly multiplexed/hyperplexed immunofluorescence images, as well as spatial data from complementary in situ methods including FISSEQ and CyTOF, sampling many different components within the TME. We hypothesize that PMI will uncover key spatial interactions in the TME that contribute to disease proliferation and progression.

Microfluidic Tissue Mesodissection in Molecular Cancer Diagnostics

We present a mesodissection platform that retains the advantages of laser-based dissection instrumentation with the speed and ease of manual dissection. Tissue dissection in clinical laboratories is often performed by manually scraping a physician-selected region from standard glass slide mounts. In this manner, costs associated with dissection remain low, but spatial resolution is compromised. In contrast, laser microdissection methods maintain spatial resolution that matches the requirements for analysis of important tissue heterogeneity but remains costly and labor intensive. We demonstrate a microfluidic tool for rapid extraction of histological regions of interest from formalin-fixed paraffin-embedded tissue, which uses a simple and automated method that is compatible with most downstream enzymatic reactions, including protocols used for next-generation DNA sequencing.

Deciphering tumor heterogeneity from FFPE tissues: Its promise and challenges

An impediment to the understanding of cancer is the heterogeneous nature of cell populations within a tumor microenvironment. We reported a method to query protein signaling in single epithelial cells from formalin-fixed paraffin-embedded (FFPE) colorectal cancer tissues. Here, we discuss the feasibility and limitations of this approach for investigating signaling state heterogeneity.

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.

madSTORM: a superresolution technique for large-scale multiplexing at single-molecule accuracy

A highly multiplexed superresolution imaging strategy with single-molecule accuracy enabled by fluorescent nanodiamonds called madSTORM affords the ability to define spatial relationships among constituent molecules within structures. It makes it possible to probe the molecular topology of complex signaling cascades and other heterogeneous networks.

Investigation of heterogeneous cellular structures using single-molecule localization microscopy has been limited by poorly defined localization accuracy and inadequate multiplexing capacity. Using fluorescent nanodiamonds as fiducial markers, we define and achieve localization precision required for single-molecule accuracy in dSTORM images. Coupled with this advance, our new multiplexing strategy, madSTORM, allows accurate targeting of multiple molecules using sequential binding and elution of fluorescent antibodies. madSTORM is used on an activated T-cell to localize 25 epitopes, 14 of which are on components of the same multimolecular T-cell receptor complex. We obtain an average localization precision of 2.6 nm, alignment error of 2.0 nm, and <0.01% cross-talk. Combining these technical advances affords the ability to move beyond obtaining superresolved structures to defining spatial relationships among constituent molecules within structures. Probing the molecular topology of complex signaling cascades and other heterogeneous networks is feasible with madSTORM.

Diagnostics based on nucleic acid sequence variant profiling: PCR, hybridization, and NGS approaches

Nucleic acid sequence variations have been implicated in many diseases, and reliable detection and quantitation of DNA/RNA biomarkers can inform effective therapeutic action, enabling precision medicine. Nucleic acid analysis technologies being translated into the clinic can broadly be classified into hybridization, PCR, and sequencing, as well as their combinations. Here we review the molecular mechanisms of popular commercial assays, and their progress in translation into in vitro diagnostics.

High sensitivity isoelectric focusing to establish a signaling biomarker for the diagnosis of human colorectal cancer

BACKGROUND

The progression of colorectal cancer (CRC) involves recurrent amplifications/mutations in the epidermal growth factor receptor (EGFR) and downstream signal transducers of the Ras pathway, KRAS and BRAF. Whether genetic events predicted to result in increased and constitutive signaling indeed lead to enhanced biological activity is often unclear and, due to technical challenges, unexplored. Here, we investigated proliferative signaling in CRC using a highly sensitive method for protein detection. The aim of the study was to determine whether multiple changes in proliferative signaling in CRC could be combined and exploited as a "complex biomarker" for diagnostic purposes.

METHODS

We used robotized capillary isoelectric focusing as well as conventional immunoblotting for the comprehensive analysis of epidermal growth factor receptor signaling pathways converging on extracellular regulated kinase 1/2 (ERK1/2), AKT, phospholipase Cγ1 (PLCγ1) and c-SRC in normal mucosa compared with CRC stage II and IV. Computational analyses were used to test different activity patterns for the analyzed signal transducers.

RESULTS

Signaling pathways implicated in cell proliferation were differently dysregulated in CRC and, unexpectedly, several were downregulated in disease. Thus, levels of activated ERK1 (pERK1), but not pERK2, decreased in stage II and IV while total ERK1/2 expression remained unaffected. In addition, c-SRC expression was lower in CRC compared with normal tissues and phosphorylation on the activating residue Y418 was not detected. In contrast, PLCγ1 and AKT expression levels were elevated in disease. Immunoblotting of the different signal transducers, run in parallel to capillary isoelectric focusing, showed higher variability and lower sensitivity and resolution. Computational analyses showed that, while individual signaling changes lacked predictive power, using the combination of changes in three signaling components to create a "complex biomarker" allowed with very high accuracy, the correct diagnosis of tissues as either normal or cancerous.

CONCLUSIONS

We present techniques that allow rapid and sensitive determination of cancer signaling that can be used to differentiate colorectal cancer from normal tissue.

Intratumor Heterogeneity in Breast Cancer

Intratumor heterogeneity is the main obstacle to effective cancer treatment and personalized medicine. Both genetic and epigenetic sources of intratumor heterogeneity are well recognized and several technologies have been developed for their characterization. With the technological advances in recent years, investigators are now elucidating intratumor heterogeneity at the single cell level and in situ. However, translating the accumulated knowledge about intratumor heterogeneity to clinical practice has been slow. We are certain that better understanding of the composition and evolution of tumors during disease progression and treatment will improve cancer diagnosis and the design of therapies. Here we review some of the most important considerations related to intratumor heterogeneity. We discuss both genetic and epigenetic sources of intratumor heterogeneity and review experimental approaches that are commonly used to quantify it. We also discuss the impact of intratumor heterogeneity on cancer diagnosis and treatment and share our perspectives on the future of this field.

Single cell-resolution western blotting

This protocol describes how to perform western blotting on individual cells to measure cell-to-cell variation in protein expression levels and protein state. Like conventional western blotting, single-cell western blotting (scWB) is particularly useful for protein targets that lack selective antibodies (e.g., isoforms) and in cases in which background signal from intact cells is confounding. scWB is performed on a microdevice that comprises an array of microwells molded in a thin layer of a polyacrylamide gel (PAG). The gel layer functions as both a molecular sieving matrix during PAGE and a blotting scaffold during immunoprobing. scWB involves five main stages: (i) gravity settling of cells into microwells; (ii) chemical lysis of cells in each microwell; (iii) PAGE of each single-cell lysate; (iv) exposure of the gel to UV light to blot (immobilize) proteins to the gel matrix; and (v) in-gel immunoprobing of immobilized proteins. Multiplexing can be achieved by probing with antibody cocktails and using antibody stripping/reprobing techniques, enabling detection of 10+ proteins in each cell. We also describe microdevice fabrication for both uniform and pore-gradient microgels. To extend in-gel immunoprobing to gels of small pore size, we describe an optional gel de-cross-linking protocol for more effective introduction of antibodies into the gel layer. Once the microdevice has been fabricated, the assay can be completed in 4-6 h by microfluidic novices and it generates high-selectivity, multiplexed data from single cells. The technique is relevant when direct measurement of proteins in single cells is needed, with applications spanning the fundamental biosciences to applied biomedicine.

PD-L1 Expression in Lung Cancer

Immunotherapies targeted against programmed death ligand 1 (PD-L1) and its receptor (PD-1) have improved survival in a subset of patients with advanced lung cancer. PD-L1 protein expression has emerged as a biomarker that predicts which patients are more likely to respond to immunotherapy. The understanding of PD-L1 as a biomarker is complicated by the history of use of different immunohistochemistry platforms with different PD-L1 antibodies, scoring systems, and positivity cut-offs for immunotherapy clinical trials with different anti-PD-L1 and anti-PD-1 drugs. Herein, we summarize the brief history of PD-L1 as a biomarker and describe the challenges remaining to harmonize PD-L1 detection and interpretation for best patient care.

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.

A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine

Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)-driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point.

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.

Dense transcript profiling in single cells by image correlation decoding

Sequential barcoded fluorescent in situ hybridization (seqFISH) allows large numbers of molecular species to be accurately detected in single cells, but multiplexing is limited by the density of barcoded objects. We present correlation FISH (corrFISH), a method to resolve dense temporal barcodes in sequential hybridization experiments. Using corrFISH, we quantified highly expressed ribosomal protein genes in single cultured cells and mouse thymus sections, revealing cell-type-specific gene expression.

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.

High-acceleration whole body vibration stimulates cortical bone accrual and increases bone mineral content in growing mice

Whole body vibration (WBV) is a promising tool for counteracting bone loss. Most WBV studies on animals have been performed at acceleration <1g and frequency between 30 and 90Hz. Such WBV conditions trigger bone growth in osteopenia models, but not in healthy animals. In order to test the ability of WBV to promote osteogenesis in young animals, we exposed seven-week-old male mice to vibration at 90Hz and 2g peak acceleration for 15min/day, 5 days/week. We examined the effects on skeletal tissues with micro-computed tomography and histology. We also quantified bone vascularization and mechanosensitive osteocyte proteins, sclerostin and DMP1. Three weeks of WBV resulted in an increase of femur cortical thickness (+5%) and area (+6%), associated with a 25% decrease of sclerostin expression, and 35% increase of DMP1 expression in cortical osteocytes. Mass-structural parameters of trabecular bone were unaltered in femur or vertebra, while osteoclastic parameters and bone formation rate were increased at both sites. Three weeks of WBV resulted in higher blood vessel numbers (+23%) in the distal femoral metaphysis. After 9-week WBV, we have not observed the difference in structural cortical or trabecular parameters. However, the tissue mineral density of cortical bone was increased by 2.5%. Three or nine weeks of 2g/90Hz WBV treatment did not affect longitudinal growth rate or body weight increase under our experimental conditions, indicating that these are safe to use. These results validate a potential of 2g/90Hz WBV to stimulate trabecular bone cellular activity, accelerate cortical bone growth, and increase bone mineral density.

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.

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.

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.

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.

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.

Atypical Phenotypes in Classical Hodgkin Lymphoma

Classical Hodgkin lymphoma has a characteristic immunophenotype in most cases, with expression of CD30, CD15, and PAX-5, and absence of CD45 and T-lineage markers. However, in a significant subset of cases, atypical staining patterns may be seen for one or more antigens, particularly negative staining for CD15 or staining for one or more B-lineage markers, such as CD20, CD79a, OCT-2, or BOB.1. The greatest pitfall is in the misinterpretation of other cells, such as immunoblasts or histiocytes, as Hodgkin cells.

Kinetics of Reactive Modules Adds Discriminative Dimensions for Selective Cell Imaging

Living cells are chemical mixtures of exceptional interest and significance, whose investigation requires the development of powerful analytical tools fulfilling the demanding constraints resulting from their singular features. In particular, multiplexed observation of a large number of molecular targets with high spatiotemporal resolution appears highly desirable. One attractive road to address this analytical challenge relies on engaging the targets in reactions and exploiting the rich kinetic signature of the resulting reactive module, which originates from its topology and its rate constants. This review explores the various facets of this promising strategy. We first emphasize the singularity of the content of a living cell as a chemical mixture and suggest that its multiplexed observation is significant and timely. Then, we show that exploiting the kinetics of analytical processes is relevant to selectively detect a given analyte: upon perturbing the system, the kinetic window associated to response read-out has to be matched with that of the targeted reactive module. Eventually, we introduce the state-of-the-art of cell imaging exploiting protocols based on reaction kinetics and draw some promising perspectives.

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.