Whether researchers are following the immune response to treatments for cancer, infection or autoimmune disease, or searching for biomarkers of disease onset and progression, they need a comprehensive, reliable method to monitor changes in immune cell populations.

Mass cytometry has proven to be a uniquely empowering platform for immune profiling and biomarker discovery. Now, Fluidigm makes this powerful technology more accessible than ever with the Maxpar^® Human Immune Monitoring Panel Kit designed for use on Helios™, a CyTOF^® system.

The Maxpar Human Immune Monitoring Panel Kit

This 29-marker panel kit maximizes the information obtained from every drop of precious sample, enabling identification of over 25 key immune cell populations, all in a single tube (Figure 1).

Figure 1. Cell subsets that can be identified with the single-tube Maxpar Human Immune Monitoring Panel Kit.

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Panel Kit Contents and Workflow

Whether you are new to mass cytometry or are a seasoned pro, the Maxpar Human Immune Monitoring Panel Kit provides the most convenient and efficient approach to identifying all major immune subsets in peripheral blood mononuclear cells (PBMC).

This kit contains all reagents needed to prepare PBMC samples for mass cytometric analysis on Helios, plus:

• 29 individually packaged, pre-titrated antibodies ready to use straight from the kit to prepare the antibody cocktail
• A detailed, kit-specific protocol for sample preparation, instrument setup and sample collection on Helios systems
• A Helios acquisition template pre-populated with the appropriate parameter names and metals required

Table 1. The 29 anti-human antibodies included in the Maxpar Human Immune Monitoring Panel Kit. The eight open channels are 145Nd, 150Nd, 156Gd, 159Tb, 161Dy, 170Er, 172Yb, 209Bi.

Figure 2. Workflow for the Maxpar Human Immune Monitoring Panel Kit. No panel design or antibody titrations need to be performed. Stain PBMC samples according to the custom protocol provided, collect data on a Helios or CyTOF 2-to-Helios instrument using the customized kit acquisition template, and analyze samples.

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Data analysis options are flexible

FCS 3.0 data files are generated when acquiring samples with the Maxpar Human Immune Monitoring Panel Kit on Helios and can be analyzed by any capable third-party software tool. Manual gating can be performed with third-party software tools such as Cytobank.

Automated analysis software such as GemStone™ can also be used, providing the following features:

• Automated gating of viable single cells
• 2D dot plot and cell stage progression profiles
• High-dimensional Cen-se’™ map of identified populations
• Sample report for each population, with cell number, percent of total cells and percent of parent population

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Complete the form below to receive more information on the new Maxpar Human Immune Monitoring Panel Kit.

For Research Use Only. Not for use in diagnostic procedures.

The heart of the single-cell community at fluidigm.com, Script Hub™ provides a growing selection of innovative single-cell omics applications for researchers to browse and download for free to use with C1™.

Ansuman Satpathy, MD, PhD, is an Instructor in the Department of Pathology at Stanford University School of Medicine. As a postdoctoral fellow in Howard Chang’s lab, he studies immune system function and dysfunction in cancer patients. He spoke with Fluidigm recently about developing genome sequencing methods, specifically his new transcript-indexed single-cell ATAC-seq (T-ATAC-seq) application available at Script Hub for pairing TCR-seq with ATAC-seq.

His research focuses on investigating single-cell and three-dimensional genome sequencing tools to study epigenetic regulation of tumor-specific T cells. Taking advantage of C1 flexibility, he used Script Builder™ software to develop the method for co-detecting two key cellular components: RNA and DNA. Satpathy highlighted the ability to flow any enzymes or chemistries to the C1 integrated fluidic circuit (IFC) inlets and then to the chamber. He pointed out that there is really no restriction to designing applications through Script Builder. “The key is that Script Builder software is easy to use,” he said. “You can design things in silico using computer modeling and then easily implement them in Script Builder.”

T-ATAC-seq application

A tool for analyzing epigenomic landscapes in clonal T cells, T-ATAC-seq has the potential to advance studies of T cell malignancy, immunity and immunotherapy. Satpathy—in collaboration with Naresha Saligrama, PhD; Jason Buenrostro, PhD; Mark Davis, PhD; and Howard Chang, MD, PhD, at Stanford University—developed the T-ATAC-seq app to sequence open chromatin sites in clonal T cells by combining targeted RNA sequencing and epigenomic sequencing. As an immunologist, he sought to pair ATAC-seq epigenome information with immune transcripts of interest. By pairing two pieces of information, he learned the sequence of the specific T cell receptor in each individual cell, and the epigenomic state of that cell.

Satpathy describes his combinatorial T-ATAC-seq method as an experimental pipeline integrating single-cell ATAC-seq with targeted TCR-seq in the same single cell. Applying T-ATAC-seq to clinical samples from T cell leukemia tissues enabled him to identify cancer clone-specific epigenomic signatures unobservable from ensemble measurements, demonstrating the value of T-ATAC-seq as a new tool for single-cell epigenomic characterization of T cells in research and future clinical applications.

Nature Medicine paper

In an April 2018 Nature Medicine paper entitled, “Transcript-indexed ATAC-seq for precision immune profiling,” Satpathy et al. describe how they combined single-cell T cell receptor (TCR) sequencing and an assay for transposase-accessible chromatin analysis to collect data on TCR specificity and the epigenomic state of individual T cells. In T cell leukemia patients, T-ATAC-seq enabled the researchers to identify leukemic and non-leukemic regulatory pathways in T cells from the same individual, separating signals arising from the malignant clone from background T cell noise.

T-ATAC-seq pairs epigenomic data with high-fidelity RNA sequence of TCR loci to provide a platform for multi-omic investigation of T cell diversity. Noting that they were able to define epigenomic signatures of clonal cancer cells missed by standard fluorescence-activated cell sorting-based (FACS) separation methods, the authors demonstrated the promise of this approach: “T-ATAC-seq represents an important technical advance towards achieving an atlas of human cell types and states in that it is able to generate genome-wide chromatin accessibility maps, while simultaneously preserving and measuring RNA sequence.”

The report characterizes T-ATAC-seq as complementary to approaches for unbiased identification of TCR ligands, enabling integration of T cell epigenomic state, TCR sequence and TCR ligands. Satpathy et al. concluded: “The application of this strategy to human diseases such as cancer and autoimmune disease, particularly in the context of immunotherapy, could be invaluable in generating comprehensive profiles of beneficial and harmful T cell responses, the regulatory networks underlying either response and the antigens that drive these networks.”

“This method opens up a lot of possibilities in single-cell genomics, pairing different types of information with epigenetic states. We’re describing one application of TCR sequencing, but in the future, there are applications such as CRISPR guide sequencing or other cell-identifying transcripts like B cell receptors or non-coding RNAs, marrying information from different systems and developing those technologies. That’s the immediate goal from the perspective of technology and development.”
—Ansuman Satpathy, MD, PhD, Stanford University

Publication findings

Satpathy et al. decided to study human T cells since it has been difficult historically to examine epigenetic states, particularly at the single-cell level in human tissues. After sorting different human CD4 T cell subtypes as defined by classical FACS markers, they used this single-cell method to gauge epigenetic variation. They found extensive variation within subtypes. For example, a small number of classically defined naive T cells—5% or 10%—look similar to subpopulations of memory or stem cell T cells. This supports prior findings suggesting that there might be a small population of stem memory cells that live in the FACS gate. The investigators reported identifying formal proof that on the epigenome-wide level, those cells had a distinct chromatin state within the rest of the naive cells.

“That’s one of the major findings we saw in healthy T cells,” Satpathy said. “In the last part of the paper we took that to a malignant T cell cancer setting where only a fraction of CD4 T cells represent the putative cancer clone. Now we can use this combined TCR-seq and ATAC-seq method to identify the epigenetic state of only the clonal cancer cells.”

Broad implications

Satpathy’s results show the wide applicability of the T-ATAC-seq method for cancer immunotherapy research. Asking specific questions at the single-cell level about a T cell clone that is reacting against that tumor can reveal why that particular T cell clone might be working well in one subject but not in another. “The key is isolating the signal of the clonal T cell from the background T cells,” he explained. “Amplifying the TCR is the perfect approach. In the case of other non-immunology-related cell types or systems, you might use a different transcript that marks a certain cell subpopulation or cell function.”

According to Satpathy, looking at the RNA but not the ATAC, or the ATAC but not the RNA, leaves out important information. The RNA sequence is useful for particular parts of the question, and the chromatin state or the ATAC-seq is useful for others. He noted that in certain cases, both pieces are helpful. Moving forward, combining these and other types of sequencing methods from the same single cell is a strong application area for him. “Researchers can gather valuable information from chromatin, protein and RNA and then integrate it all in the same single cell,” he explained. “T-ATAC-seq is a first step toward achieving that goal.”

Future applications

“This method opens up a lot of possibilities in single-cell genomics, pairing different types of cellular information with epigenetic states,” Satpathy said. “We’re describing one application of TCR sequencing, but in the future, there are approaches such as CRISPR guide sequencing or other cell-identifying transcripts like B cell receptors or non-coding RNAs, marrying information from different systems and developing those technologies. That’s the immediate goal from the perspective of technology and development.”

Satpathy believes that researchers involved in Human Cell Atlas, Chan Zuckerberg Biohub and other similar consortiums also stand to benefit from this technology. “The Human Cell Atlas and CZ Biohub focus predominantly on single RNA-seq,” he said, “but looking at the epigenetic state using the methods we’ve developed in collaboration with Fluidigm, and other similar approaches, will be complementary and useful.”

Maximize the power of your single-cell analysis on the C1 system with access to the industry’s largest collection of single-cell genomics applications. Download the T-ATAC-seq script developed by Satpathy’s group, and find other innovative protocols on Script Hub for use with Open App™ IFCs to advance your single-cell studies.

Sign up to receive more information about new applications coming soon to C1 Script Hub.

For Research Use Only. Not for use in diagnostic procedures.

Improving care is a mission that drives us all. Translating new discoveries into better clinical outcomes takes dedication and new approaches to asking the most difficult questions. At Fluidigm, we believe that changing the course of how diseases are treated and ultimately cured requires a comprehensive understanding of complex cellular phenotypes and their interrelationships within the tissue microenvironment. To meet this great challenge, we developed the Hyperion™ Imaging System.

“The impact of this first-in-class technology stands to be especially profound in oncology, immunology and immunotherapy research. With more than 30 systems enabled globally, progress in applying this innovative technology to ask new questions across a number of disease research areas is truly impressive .”
—Chris Linthwaite, President and CEO, Fluidigm

The Hyperion Imaging System brings imaging capability together with proven CyTOF® technology to set a new standard in highly multiplexed protein detection. Surpassing the inherent limitations of fluorescence detection, this system enables researchers to simultaneously image 4 to 37 protein markers in tissues and tumors by Imaging Mass Cytometry™. Ideal for deep profiling of precious formalin-fixed, paraffin-embedded (FFPE) and fresh frozen tissue samples, the Hyperion Imaging System empowers researchers to uncover new biomarker correlations and cellular social networks in the context of the tissue microenvironment—all from a single slide.

As with any new research application, having access to optimized reagents, analytical tools and training is essential for success. We designed the Hyperion Imaging System workflow with this in mind. It is accompanied by a pathologist-verified Maxpar® imaging antibody portfolio, antibody labeling kits, a software suite for image acquisition and data analysis, and experienced Fluidigm service and support. With the ability to utilize up to 135 channels to detect additional parameters, the system is well-suited to meet researchers needs today and well into the future.

A step jump of this magnitude doesn’t happen every day in life sciences. The impact of this first-in-class technology stands to be especially profound in oncology, immunology and immunotherapy research. With more than 30 systems enabled globally, truly impressive progress is being made in applying this innovative technology to ask new questions across a number of disease research areas.

I invite you to join with us and the growing scientific community in powering this revolution in tissue imaging to create breakthroughs today that will enable the development of better diagnostics and more effective therapies for tomorrow.

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For Research Use Only. Not for use in diagnostic procedures.

The Hyperion™ Imaging System received first place in The Analytical Scientist Innovation Awards, or TASIAs. Judges named it the top innovation of 2017, commending the platform that “combines tissue imaging with cytometry, allowing correlation between biomarkers and cell interactions. This technology has the potential to be truly transformative.”

Editor Charlotte Barker of The Analytical Scientist said, “Now in year five, The Innovation Awards continue to shine a light on the instruments and technologies that are having a big impact across the analytical sciences. We had a record number of entries this year and the final 15 reflect the full spectrum of analytical advances, from ingenious software for managing impurity data, to transformative MS imaging technology.”

The Hyperion Imaging System has the potential to revolutionize disease research by providing unprecedented visualization of complex cellular phenotypes and their relationships in the context of cancer, immuno-oncology and a range of immune mediated diseases. The potential ability to develop better diagnostics and more effective therapies stands to change the future of health care.

Read the full article in The Analytical Scientist for more on the TASIAs. To learn more about Imaging Mass Cytometry™ and be informed about news and events, fill out the form below.

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For Research Use Only. Not for use in diagnostic procedures.

Take a moment to remember your favorite painting, a classic that brings you comfort and fills you with introspective thought. Something like Starry Night by van Gogh or Guernica by Picasso. Now imagine that instead of showing the full image, we break it all down inch by inch, pixel by pixel into a collection of dots grouped by color. Does knowing that 80% of Starry Night is blue or that 10% of Guernica is white convey the same message as seeing the image as the artist intended? Even though all the colors are represented, the work of art disappears in the absence of spatial organization. For David L. Rimm, MD, PhD, Professor of Pathology and of Medicine at the Yale School of Medicine, spatial information brings everything together for a better understanding of the cellular environment. That is the power of imaging in scientific studies. The new Hyperion™ Imaging System brings together imaging with proven CyTOF^® technology, pushing highly multiplexed immunohistochemistry-based imaging to the forefront of translational research. Rimm and colleagues are leading the way.

Recognizing early potential

Rimm’s familiarity with highly multiplexed imaging technology began in 2014 when he was writing a commentary on two groundbreaking Nature papers on novel imaging methods. Based on two different techniques, the publications coalesced on the same theme: the need for higher-order imaging technology using metal-tagged antibodies. Rimm recalled that the techniques “were similar approaches but they had some subtle differences in the mechanism.” Rimm recognized the value of these techniques and saw this as the future path for his lab. He saw great potential in the Hyperion Imaging System, where a precisely directed laser beam collects biological samples stained with metal-tagged antibodies and CyTOF technology enables the detection of different metal tags based on mass rather than on wavelength, which is the basis of relatively low-plex immunofluorescence.

For Rimm, this highly multiplexed imaging technology, Imaging Mass Cytometry™, represents the future of pathology-based studies. “A key current clinical problem in pathology,” said Rimm, “is the ability to define levels of protein in tissue so that we are maintaining the spatial information and the localization of different cell types.”

He added, “Research in my lab is related to biomarkers that either predict outcome or response to therapy or to a drug. I see the Hyperion Imaging System as a valuable discovery tool that can provide information about which molecules are most important to predict response to therapy. It gives you information that few other tools can provide: the ability to look at 30 different things at once yet maintain the two dimensional spatial information, giving us the power to discriminate biology beyond a single point measurement.”

Developing biomarker signatures

Rimm’s lab focused on applying Imaging Mass Cytometry technology to two innovative initiatives. The first was discerning key signaling pathways regulating biological effects of targeted therapies in breast cancer. Using banked samples from cancer patients treated with trastuzumab (Herceptin®), Rimm’s group simultaneously analyzed the expression levels of 17 protein markers using Imaging Mass Cytometry. By concurrently staining with a multitude of markers, he said, we can examine “the signaling molecules themselves, the receptors and the molecules in the signaling cascade that occur after the receptors are bound.”

For the second effort, they used Imaging Mass Cytometry to better understand the tumor microenvironment of lung cancer, with a particular emphasis on tumor infiltrating immune cells. This project used Imaging Mass Cytometry to develop a protein-based signature associated with patient response to therapy, with an ultimate goal to more precisely tailor therapy for cancer patients receiving immunotherapy.

The Hyperion Imaging System requires relatively small quantities of tissue to detect large numbers of proteins while maintaining spatial context. This is a key benefit when analyzing small biopsies or relatively rare or precious specimens. Rimm’s training set of tissues for the Herceptin study consisted of tumors from more than 61 patients.

Examining 17 markers simultaneously offered the advantage of identifying a wide variety of cells and activation states without the need for serial sections. Speaking to this point, Rimm said that when using serial sections, it’s unclear if the markers are actually in the same cell. It’s then necessary to take a population approach comparing expression of markers 100 µm apart. Imaging Mass Cytometry on the Hyperion Imaging System provides “unequivocal evidence that they are in the same cell, because they co-localize to the same pixel.”

“I see the Hyperion Imaging System as a valuable discovery tool that can provide information about which molecules are most important to predict response to therapy. It gives you information that few other tools can provide.”
—David Rimm, MD, PhD, Yale

Looking ahead

For Rimm, the real power of this technique will come from uncovering unanticipated correlations between large numbers of protein markers and patient outcome. Imaging Mass Cytometry enables simultaneous analysis of large numbers of protein markers to more efficiently discover new predictive signatures composed of smaller numbers of markers that may ultimately have clinical utility.

Scientists can also use Imaging Mass Cytometry to identify relevant biomarkers of disease progression and to better understand how cancer arises. When faced with the complexities of a heterogeneous disease state, looking at as many markers as possible can create insightful results that could ultimately lead to improved prognosis and therapies—and by extension improved care for cancer patients.

Going forward, Rimm hopes that Imaging Mass Cytometry will “enable us to answer key biological questions.” Moving away from the one-dimensional data of mass cytometry experiments into two or three-dimensional spatial data will advance future biological exploration. With a sense of reserved excitement, Rimm said he believes that “we’re just at the very beginning of finding out what the Hyperion Imaging System can do.”

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For Research Use Only. Not for use in diagnostic procedures.

The innovative Hyperion™ Imaging System by Fluidigm was born out of a dedicated effort to advance translational research toward a more comprehensive understanding of the complex cellular relationships and tissue microenvironment. It is the first commercially available platform to empower simultaneous interrogation of 4 to 37 protein markers in spatial context at subcellular resolution. A lead developer and longtime champion of Imaging Mass Cytometry™, Bernd Bodenmiller, PhD, Assistant Professor for Quantitative Biology at the University of Zurich (UZH), shares his experiences using the Hyperion Imaging System.

In a Nature Methods paper published in 2014, Giesen and Wang et al. first reported on an approach they developed in the Bodenmiller Lab to simultaneously image 32 protein markers and protein modifications at subcellular resolution. They detailed an Imaging Mass Cytometry approach they believed would greatly advance the understanding of cancer and other disease states through improved tissue characterization. Imaging Mass Cytometry now brings game-changing technology to immuno-oncology researchers, with the realm of possibilities extending to autoimmune diseases, neuroscience, precision medicine and other disease areas.

At his systems biomedicine lab at the north end of Lake Zurich in Switzerland’s largest city, Bodenmiller sets his sights on understanding the workings of tumor ecosystems. The Bodenmiller Lab researches cell types present in solid tumors to better grasp how the cellular elements of the ecosystems influence each other through cell-to-cell communication to drive tumor development. Modeling the tumors as multidimensionally resolved cellular networks, Bodenmiller studies cancer biology in the context of precision medicine, hoping to inform future treatment approaches for cancer. His comprehensive investigational research encompasses development of experimental and bioinformatics methods for highly multiplexed, spatially resolved subcellular tissue analysis.

The Imaging Mass Cytometry workflow pairs immunohistochemical methods with proven CyTOF® technology to record cellular markers, transcripts and signaling to generate an image of the tissue. Having already published a paper demonstrating how Imaging Mass Cytometry enables the simultaneous imaging of 32 protein markers at subcellular resolution in breast cancer tissues, the team has also shown the simultaneous imaging of proteins and transcripts, expanding the possibilities for analyzing aspects of cancer biology.

Images generated using the Hyperion Imaging System could reveal how cells respond to oxygen levels, factors contributing to immune cell exhaustion, and which conditions within the tumor environment relate to clinical features. Put into the context of translational research, the Imaging Mass Cytometry workflow using the Hyperion Imaging System empowers scientists to gain comprehensive insights into solving questions relevant to clinical treatment and global health initiatives underway at the University of Zurich.

Analyzing the tumor ecosystem

While all of his group’s research is based on mass cytometry, Bodenmiller estimates that around two-thirds of their projects now rely on Imaging Mass Cytometry. “The Hyperion Imaging System is a key method in my lab,” he said. “Within the tumor ecosystem it is informative to reveal cell type identity and the functional state of individual cells. It is important to also add spatial information for those cells. This is highly relevant because then we can study how cellular environments might actually shape a cellular phenotype or influence treatment response.”

Imaging Mass Cytometry can provide translational data on the status of the immune repertoire within a tumor. Bodenmiller anticipates that targeted modulation of the tumor ecosystem will eventually empower researchers to interrupt and halt tumor growth. “Immune checkpoint blockade therapies are a nice example of targeting interactions within the tumor ecosystem,” he explained, “as it’s really the cell-to-cell interaction and modulation that are responsible for dampening and reactivating the immune response.”

Comparing the way Imaging Mass Cytometry uses metal isotopes as reporters to the way enzymatic immunohistochemistry uses enzymes to stain tissue, and immunofluorescent microscopy uses fluorophore as a reporter for antibodies, Bodenmiller said, “What makes Imaging Mass Cytometry special is that it enables us to perform multiplexed measurements.” When detecting isotopes on the Hyperion Imaging System, the proven CyTOF technology offers 135 channels to measure many metal-tagged antibodies at once in a single tissue.

“I see enormous potential for Imaging Mass Cytometry in assessing immune checkpoint inhibitor status and deregulated cellular pathways and determining best treatments for precision medicine.”
—Bernd Bodenmiller, PhD, University of Zurich

Unprecedented pathology possibilities

Imaging Mass Cytometry stands to benefit many different areas of medicine, health and life sciences. With a nod to translational and potential clinical applications, Bodenmiller pointed to Switzerland and countries with centralized state-run health care systems that store anonymous clinical and long-term patient data and tissue samples. He cited Zurich as an example housing a half-million tissue specimens that scientists could use for additional research under governance by the institutional and state ethics board.

“There are untold answers in the millions of biobank tumor samples stored in hospitals around the world—many with densely annotated disease and patient features or treatment data,” he remarked, adding that there is an unprecedented amount of information to explore from tissue samples. “If we analyze large cohorts using Imaging Mass Cytometry and apply computational tools and machine learning to improve patient classification, we could learn about marker relationships that translate to established clinical techniques in the future. The potential is enormous.”

Toward precision medicine

Knowledge about tumor biology could be translated to patients in the future, Bodenmiller observed. “I see enormous potential for Imaging Mass Cytometry in assessing immune checkpoint inhibitor status and deregulated cellular pathways and determining best treatments for precision medicine. With Imaging Mass Cytometry, we gain an unprecedented detailed view of tissue biology. We have the ability to determine T cell status and which markers they express, suggesting how to modulate them within the tumor ecosystem. Our ability to comprehensively measure tumor tissues—from single-cell pathways to cell-to-cell interactions and tissue morphology—will reveal which aspects of the tumor ecosystem to target.”

Bodenmiller envisions the development of applications on the Hyperion Imaging System that could potentially optimize clinical workflows. A comprehensive understanding of tissue biology stands to benefit the development of new treatments and decisions about the right drug for the right patient. He contends that such precision medicine is close at hand. Using an example of analyzing melanoma samples with highly activated signaling pathways, he noted that it would be possible to target those pathways with appropriate inhibitors.

Nature Methods on histoCAT

In September 2017, the Bodenmiller Lab’s Denis Schapiro, Hartland Jackson and the UZH team published a Nature Methods paper describing the computational toolbox they call histoCAT™ (histology topography cytometry analysis toolbox) and documenting the processing of Imaging Mass Cytometry data to analyze cellular phenotypes and spatial relationships of these cells with neighboring ones. Fluidigm recently announced a distribution agreement with UZH to offer histoCAT software for high-parameter tissue analysis.

Bodenmiller expects other publications using histoCAT software analysis to follow: “We plan to show how to relate these Imaging Mass Cytometry results to clinical data, and in an additional extension of histoCAT, how we can analyze three-dimensional representation of tumors.” Advancing from two-dimensional tissue representations to reconstructing three-dimensional tumor volumes will provide an even more comprehensive understanding of cell-to-cell interactions.

Challenges and successes

There are many obstacles ahead in immuno-oncology research. We can answer more questions faster with Imaging Mass Cytometry to achieve our common goals for better human health, but developing this remarkable technology calls for the power of committed and engaged researchers focusing together on that shared objective. As with other big data, data-driven medicine analyzes massive sets of medical records and images for patterns that can reveal previously hidden connections to advance learning and inform researchers’ decisions. The answers are out there, and the tissue samples are out there, Bodenmiller concludes.

Bodenmiller reiterated the value of Imaging Mass Cytometry using the powerful Hyperion Imaging System and the potential it holds for researchers studying human health and disease. “My lab is part of the Cancer Research UK (CRUK) Grand Challenge. Imaging Mass Cytometry is one of the main pillars of this whole project with regard to comprehensively measuring the tumor ecosystem,” he said. “It is a Grand Challenge because the grant aims to comprehensively map a high number of tumors on a molecular and cellular level in 3D. About 10 labs in the US, UK and Switzerland are involved, and we’re attempting to build the whole pipeline and data analysis to enable this.”

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For Research Use Only. Not for use in diagnostic procedures.

Tumor gene expression has proven effective in measuring immune response during cancer progression and therapeutic response. As emerging therapies reveal new biomarkers and expand the need for samples, the costs and labor required to complete this important work also rise. Cancer researchers now have a reliable, sensitive and cost-effective tool for identifying gene expression signatures from immune and cancer cells: the new Advanta™ Immuno-Oncology Gene Expression Assay, used with the Biomark™ HD system.

A powerful immuno-oncology focused assay

The Advanta Immuno-Oncology Gene Expression Assay was developed in collaboration with leading academic and biopharma researchers to provide the right balance of biomarker breadth, assay flexibility and workflow efficiency.

The panel consists of 170 genes, including 91 reported in Nature, where Roy Herbst et al. defined a gene set representing tumor and immune response. The panel includes markers for:

• Immune cell identification
• Immune and cancer cell function
• Immune regulation and cell fate
• Checkpoint therapy response

Optimized for FFPE and fresh frozen tumor samples, the Advanta Immuno-Oncology Gene Expression Assay uses TaqMan® chemistry to sensitively measure gene expression, with five reference genes serving as analysis controls. Combined with Fluidigm microfluidics technology, the assay uniquely offers significant workflow efficiencies over traditional gene expression profiling methods. Each reaction is miniaturized to nanoliter volume and controlled using precise automation to empower accurate and cost-effective qPCR analysis across a large dynamic range. Since assay introduction into the integrated fluidic circuit (IFC) is under user control, researchers also have the flexibility to add up to 17 new assays or exchange gene assays within the panel to achieve experimental goals—all without affecting the original panel content, protocol or workflow.

Immuno-Oncology Expression Assay

Table 1. The Advanta Immuno-Oncology Gene Expression Assay panels A and B. This two-panel set includes 91 target genes and 5 housekeeping genes on Panel A and 74 target genes and the same 5 housekeeping genes on Panel B. Panel B reserves 17 open assay inlets, so you have the added flexiblity to add new assays over time for customization. Each panel is available in packs of 2 or 10 (192 or 960 samples, respectively)

Sample case study

In a 2016 paper published by The Lancet for the POPLAR study, “Atezolizumab versus docetaxel for patients with previously treated non-small-cell lung cancer,” Louis Fehrenbacher et al. detailed how they “assessed efficacy and safety of atezolizumab versus docetaxel in previously treated NSCLC, analyzed by PD-L1 expression levels on tumor cells and tumor-infiltrating immune cells and in the intention-to-treat population.” The team showed that “patients with pre-existing immunity, defined by high T-effector–interferon-γ-associated gene expression, had improved overall survival with atezolizumab.”

Fehrenbacher’s group noted that atezolizumab “significantly improved survival compared with docetaxel in patients with previously treated NSCLC. Improvement correlated with PD-L1 immunohistochemistry expression on tumor ce/p>lls and tumor-infiltrating immune cells,” leading them to conclude: “PD-L1 expression is predictive for atezolizumab benefit. Atezolizumab was well tolerated, with a safety profile distinct from chemotherapy.”

The researchers performed the clinical trial using immunohistochemistry, and also ran a gene expression panel of 91 genes featured in the Herbst paper. These genes are included in the Advanta Immuno-Oncology Gene Expression Assay. The team subsequently used these results to develop a gene signature based on a subset of the panel, effectively predicting therapeutic response that provides data that could potentially be used for developing future diagnostics tests.

Achieve greater overall productivity

The Advanta Immuno-Oncology Gene Expression Assay is optimized to run on the industry-proven Biomark HD system. This automated system enables researchers to easily run up to 96 samples at once with limited hands-on time, while delivering trusted performance. Together with the capability to sensitively detect biomarkers across defined T cell subsets, immune regulation, immune cell fate, cytokines, chemokines and more with exceptional cost-efficiency, this new assay offers an ideal solution to meet the rigorous demands of translational research studies.

Advanta IO Gene Expression Assay ordering information

Contact us to learn more about the Biomark HD system and the Advanta Immuno-Oncology Gene Expression Assay.

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For Research Use Only. Not for use in diagnostic procedures.