Bench to Biomarker: Applications of the immunoSEQ® Assay in Clinical Research

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    The path to success in clinical drug/vaccine development or biomarker assessment is lined with potential obstacles. Fortunately, Adaptive Biotechnologies has the tools to help you succeed, no matter where you are in the clinical research pipeline. Our advanced immunosequencing technology enables in-depth studies of the T and B cells that make up the adaptive immune system. In this article, we’ll take a look at the immunoSEQ Technology and how it can be used to support and accelerate projects at any stage of clinical development, from early academic research to advanced clinical trial research (Figure 1).

    Figure 1. The immunoSEQ Assay can help accelerate research at all stages of drug discovery and development.

    There are significant challenges throughout both the discovery and the development stages of the clinical development pipeline. In the discovery stage, these include performing initial candidate screening, pharmacokinetic and pharmacodynamic studies, pre-clinical dosing, and identifying predictive biomarkers of disease. Between the discovery and development stages, scaling up from small academic studies to more extensive confirmatory trials can present a significant obstacle.

    In the development stage, further stumbling blocks include confirming drug safety and mitigating risk, establishing biomarker endpoints, optimizing patient selection, and monitoring adverse events. The immunoSEQ Assays can help you overcome these hurdles. We have the experience and expertise to support you at every clinical development stage to propel your research forward.

    What is the immunoSEQ Assay?

    Our immunoSEQ Assay is a quantitative, flexible, robust, and scalable multiplex PCR-bias controlled assay for immune repertoire sequencing (Figure 2). Using the highly variable genomic complementarity determining region 3 (CDR3) of T-cell receptors (TCRs) and B-cell receptors (BCRs) as a unique barcode for each cell, the immunoSEQ Assay captures the depth and breadth of the adaptive immune system and eliminates the problem of amplification bias commonly associated with multiplex PCR. For more details on how this technology works, view our webinar on Exploring Repertoire Development and Dynamics.

    Figure 2. Recombination of the V(D)J region of TCRs and BCRs creates a unique barcode for each cell, allowing the immunoSEQ Assay to profile the adaptive immune system.

    One of the strengths of the immunoSEQ Assay is that it can be adapted to suit a wide variety of research applications. Sample input requirements are flexible; the immunoSEQ Assay can be performed on almost any biological sample that contains lymphocyte genomic DNA. This includes sorted T and B cells, peripheral blood mononucleated cells (PBMCs), whole blood, bone marrow, and fresh, frozen, or even formalin-fixed, paraffin-embedded (FFPE) tissue.

    How can the immunoSEQ Assay be used in clinical development?

    The immunoSEQ Assay can be used throughout the clinical development pipeline, from early-stage discovery to large-scale clinical trials research, for various disease states. Data generated include measures of diversity, clonal expansion, and T-cell fraction (TCFr) within a sample or between samples and how these change over time, and allows tracking of individual clones over time (Figure 3).

    Figure 3. Insights from the immunoSEQ Assay on various elements of the adaptive immune system.

    Examples of the immunoSEQ Assay in the clinical development pipeline

    The immunoSEQ Assay has been used in >600 trials by more than 165 biopharmaceutical partners, spanning the entire clinical development pipeline. Our end-to-end support has enabled this research to be published in >600 peer-reviewed papers, across various research fields, including basic immunology, autoimmune diseases, infectious diseases, transplantation, hematology, and oncology. For an overview of the immunoSEQ Assay and its clinical development applications, watch our recent webinar: From Bench to Biomarker.

    In this section, we’ll take a closer look at several key examples of how the immunoSEQ Assay has contributed to drug discovery research by identifying immune-related markers of treatment efficacy and enabling drug safety monitoring (see Table 1 for an overview).

    Table 1: Overview of immunoSEQ Assay applications in clinical development

    Disease state  System/model DataApplicationReference
    Non-small cell lung cancerHumanClonalityCandidate selectionForde et al. (1)
    Zika virusMouseClonalityCandidate selectionHassert et al. (2)
    Metastatic cancerMouseT-cell infiltrationPre-clinical drug trialDovedi et al. (3)
    OrthopoxvirusMouseClonalityPre-clinical vaccine trialWolf et al. (4)
    Crohn’s diseaseHumanClonality/ repertoire overlapBiomarker discoveryAllez et al. (5)
    MelanomaHumanT-cell fractionBiomarker discoveryPruessman et al. (6)
    PsoriasisHumanClonalityDrug efficacyMatos et al. (7)
    Alopecia areataHumanClonalityDrug efficacyde Jong et al. (8)
    Prostate cancerHumanClonality/clonal expansionDrug efficacyPhillips et al. (9)
    Melanoma/fatal encephalitisHumanClonality/
    T-cell fraction
    Adverse event monitoringJohnson et al. (10)
    GVHD/drug hypersensitivityHumanClonalityAdverse event monitoringChang et al. (11)
    COVID-19HumanClonality/ repertoire overlapBiomarker endpointSnyder et al. (12)

    GVHD, graft-versus-host disease.

    The immunoSEQ Assay in drug discovery

    Identifying immunogenic peptides

    One application of the immunoSEQ Assay in drug discovery is identifying immunogenic peptides. In a study by Forde et al. (1), researchers screened mutation-associated neoantigens from a patient with non-small cell lung cancer. The authors identified one neoantigen that elicited a T-cell response in vitro (Figure 4A). Using the immunoSEQ Assay, they tracked these neoantigen-specific T-cell clones in different tissues and over time (Figure 4B). In drug development, the ability to track the T-cell response to antigens can be useful in identifying vaccine candidates.

    Figure 4. T-cell clonality in non-small cell lung cancer tumors. A) Expansion of T-cell clones after peptide stimulation. B) Frequency of three T-cell clones in tumor and resected tissue. Adapted from Forde et al. (1)

    Understanding the immune response to infection

    The immunoSEQ Assay can also provide insight into the types of immune responses that are most effective against a pathogen, thereby providing insight on the goals of vaccine strategies.

    After the emergence of the Zika virus, the immunoSEQ Assay was used in a mouse model to identify elements of the adaptive immune system that arise in response to infection. The results demonstrated a key role for polyfunctional and polyclonal CD4+ T cells in protecting the central nervous system from damage during severe Zika virus infection.

    More severe neurological damage and significant increases in viral load and replication were observed in mice depleted of CD4+ T cells (Figure 5). These results highlight the necessity of developing vaccines for the Zika virus that elicit a robust CD4+ T-cell response. (2)

    Figure 5. A) Survival rates of mice depleted of CD4+ T cells and B) TCRB CDR3 region diversity among CD4+ T cells responding to ZIKV-specific epitopes. Adapted from Hassert et al. (2)

    More recently, we’ve leveraged our technology and proprietary platforms to identify SARS-CoV-2-specific TCR sequences. Our immunoSEQ® T-MAP™ COVID tools give you the resources to study and analyze the T-cell response to SARS-CoV-2 (Figure 6). Several lines of evidence suggest that measuring the T-cell immune response can provide a more comprehensive, robust picture of immunity than measuring antibodies in individuals infected with SARS-CoV-2.

    With immunoSEQ T-MAP COVID, researchers can access the underlying technology that powers the first and only EUA-approved T-cell-based test for COVID-19. You can assess past T-cell immune response to COVID-19, access virus-specific antigen–TCR sequence-level data, and track COVID-19-specific TCR sequences longitudinally over time.

    Figure 6. Insights available via immunoSEQ T-MAP COVID.

    Understanding immune-related markers of treatment efficacy with the immunoSEQ Assay

    Late-stage clinical trials are expensive and time-consuming. Analyzing efficacy endpoints such as disease progression or survival, which are needed for regulatory approval, can take years in fields like oncology. Therefore, gaining insights on shorter-term treatment effects in early-stage trials can help to identify the most promising drug candidates or combinations to pursue in larger efficacy trials.

    Dovedi et al. (3) used the immunoSEQ Assay to analyze tumor-infiltrating lymphocytes in response to radiotherapy. Mice were injected with murine colon carcinoma cells in two separate locations and received (i) no treatment, (ii) anti-programmed cell death protein 1 (PD-1) therapy alone, (iii) radiotherapy (RT) alone, or (iv) anti-PD-1 therapy plus RT. The group treated with anti-PD-1 therapy alone showed no significant T-cell infiltration. The group that received RT alone showed T-cell infiltration in RT-targeted tumors but none in shielded tumors.

    The surprising result of the study was that the combination of RT and anti-PD-1 treatment elicited significant T-cell infiltration not only in the targeted tumor but also in the secondary, shielded tumors, showing that anti-PD-1 treatment may replicate the immune effects of RT at a distant tumor that received no radiation (Figure 7). This study demonstrates how the immunoSEQ Assay can help determine effective combination therapies and strategies for cancer treatment.

    Figure 7. T-cell infiltration in response to treatment with anti-PD-1 and/or RT on tumors in mice. A) Study strategy. B) Percentage of tumor-infiltrating lymphocytes in primary and secondary tumors by treatment. Adapted from Dovedi et al. (3)*

    Another mouse study demonstrates the utility of sequencing the peripheral T-cell repertoire in determining prior virus exposure and the effectiveness of vaccines in eliciting strong immune responses. Researchers used the immunoSEQ Assay to identify and track virus-associated T-cell clonotypes after vaccination or infection with orthopoxvirus. (4) The immunoSEQ Assay identified virus and vaccine-specific clones. Longitudinal sampling was able to describe the kinetics of clone expansion over eight weeks. The data were used to construct an algorithm that could predict prior virus exposure with 97% accuracy.

    immunoSEQ T-MAP COVID has a similar feature, called the Classifier, which allows you to determine whether your samples demonstrate evidence of prior T-cell immune response to SARS-CoV-2 (Figure 8).

    Figure 8. Example of output from the Classifier feature.

    Monitoring the immune repertoire is essential to understanding and treating autoimmune diseases. Psoriatic lesions can resolve upon treatment with anti-TNF therapy or ultraviolet light but often come back when treatment is discontinued. One explanation is that residual pathogenic T cells remain in the region and can trigger disease recurrence.

    In a 2017 study (7), the immunoSEQ Assay was used to sequence T-cell clones from pre- and post-treatment biopsies of psoriatic lesions. The results revealed that 6.7% of T-cell clones are conserved between resolved and active lesions, and 19 clonal signatures not present in control (healthy) samples or other (non-psoriasis) samples of inflammatory skin disease were identified (Figure 9). These data suggest that durable disease control may be assisted by controlling these pathogenic T-cell clones.

    Figure 9. T-cell clonality in active and resolved psoriatic lesions. A) The number of unique T-cell clones for 14 patients in active and resolved lesions. B) The total number of T cells per 100 ng of skin DNA in the top 20 most frequent clones. Adapted from Matos et al. (7)

    In a similar example, immune repertoire profiling was undertaken on pre- and post-treatment scalp biopsies from patients with alopecia areata (AA) using the immunoSEQ Assay to provide insights into the T-cell response following treatment with the drug tofacitinib. (8) Patients with AA typically have higher T-cell clonality (Figure 10A), which decreases with tofacitinib treatment (Figure 10B).

    The immunoSEQ Assay identified several T-cell clones that persist following treatment, including public clones that were present in multiple patients (Figure 10C). Similar to the T-cell clones identified in psoriatic lesions, the clones that persist at higher frequencies post treatment may be pathogenic clones that could be targeted to control the disease.

    Figure 10. T-cell clonality in pre- and post-treatment scalp biopsies from patients with alopecia. The clonality of the scalp T-cell repertoire and the number of expanded CD8+ T-cell clones in the top 100 most abundant clones in A) controls, alopecia areata (AAP), and alopecia totalis and alopecia universalis (AT/AU) scalps; B) before and after 24 weeks of tofacitinib treatment. C) Identification of expanded clones that persist following treatment. Adapted from de Jong et al. (8)

    The immunoSEQ Assay in biomarker discovery

    Identifying predictive biomarkers of response is another key application of the immunoSEQ Assay in clinical development. In a phase 2 randomized clinical trial by Phillips et al. (9), immunosequencing was performed on blood samples from patients with oligometastatic prostate cancer treated with stereotactic ablative radiotherapy (SABR). Higher baseline T-cell clonality was associated with a lack of disease progression in the SABR group but not in the control group (Figure 11A). The immunoSEQ Assay showed both expansion and contraction of T-cell clones following SABR (Figure 11B), characterizing the immunomodulatory effect of SABR.

    Figure 11. A) Clonality and B) clonal expansion in prostate cancer patients. Adapted from Phillips et al. (9)

    The immunoSEQ Assay has also been used to identify immune-related prognostic biomarkers. An oncology study by Pruessmann et al. (6) used the immunoSEQ Assay to show that T-cell fraction (TCFr) is an indicator of progression-free survival (PFS) in patients with melanoma. Higher TCFr correlated with better PFS; a cutoff of >20% TCFr was determined to be a positive marker of survival. When TCFr data were combined with tumor thickness measurements, they predicted PFS better than any other combination of histopathological variables.

    Immunosequencing can also identify key biomarkers of response to treatment and disease recurrence in autoimmune diseases. A 2019 study of patients with ileal Crohn’s disease used the immunoSEQ Assay to assess clonal expansion in resected bowel tissue from patients experiencing either recurring or non-recurring disease. (5)

    The data demonstrated that the T-cell repertoire is a strong predictor of recurrent Crohn’s disease, with patients who had higher T-cell diversity being more likely to experience recurrence. Interestingly, patients who displayed similar TCR repertoires six months post resection were found to have the highest chance of disease recurrence, indicating that T cells play a critical role in Crohn’s disease and have the potential for diagnostic use in this context (Figure 12).

    Figure 12. A) Clonal diversity and B) repertoire overlap in patients with Crohn’s disease as a prediction of disease recurrence. Adapted from Allez et al. (5)

    Monitoring and understanding drug safety with the immunoSEQ Assay

    Immunotherapies have been associated with severe, or even fatal, immune-related adverse events. Understanding the underlying mechanisms of these events and identifying immune characteristics that predispose patients to serious events is imperative to managing patients on immunotherapies.

    A key example from Johnson et al. (10) used the immunoSEQ Assay to understand the role of T cells in patients with metastatic melanoma who experienced severe immune-related adverse events following anti-PD-1 treatment. In a patient who experienced fatal encephalitis, the immunoSEQ Assay was performed on inflamed and non-inflamed brain tissue, revealing that inflamed tissue had an extremely high TCFr; 70% of the tissue was made up of infiltrating T cells with increased clonality compared with non-inflamed tissue (Figure 13).

    Surprisingly, the most dominant clone displayed high sequence homology with an Epstein–Barr virus (EBV)-associated clone. These results suggest that the checkpoint blockade treatment triggered the EBV-associated clone to expand in brain tissue, leading to fatal encephalitis.

    Figure 13. A) T-cell expansion in uninfected (U) and inflamed (I) brain tissue of a patient with melanoma after treatment. B) TCR tracking over time and across tissues of EBV-specific clonotypes and non-EBV-specific clonotypes. Adapted from Johnson et al. (10)

    In the transplant setting, one challenge in patient management and monitoring drug safety can be distinguishing drug hypersensitivity from other conditions. Graft-versus-host disease (GVHD), for example, typically displays similar features to drug hypersensitivity. Chang et al. used the immunoSEQ Assay to show that patients with GVHD have higher T-cell clonality in skin biopsies than those with drug hypersensitivity. (11) This could be useful in clinical research to help distinguish between these two types of events (Figure 14).

    Figure 14. Clonality in patients with GVHD vs. those with drug hypersensitivity. Adapted from Chang et al. (11)

    Why partner with Adaptive Biotechnologies?

    Support throughout the entire clinical development pipeline

    We provide end-to-end support through the entire clinical development pipeline, from experimental design to providing publication-ready data, so you’re never left in the dark. Our commitment to providing expert support to researchers at every step has led to our technology being used in >600 peer-reviewed publications. With broad experience across a variety of disease states, we can provide advice on sample and time point selection, biomarker endpoint selection, review of clinical trial manuals, liaising with clinical research organizations (CROs), statistical analyses, and retrospective studies (Figure 15).

    Figure 15. A summary of publications in various research fields utilizing immunoSEQ Data and the support offered by Adaptive Biotechnologies.

    Using the immunoSEQ® Analyzer, our online, cloud-based software platform, you can visualize data and download them for off-platform use, with experts to help you navigate every step. We also provide computational biology services to assist with sorting immunoSEQ Data, correlating results with existing metadata for retrospective studies, and preparing publication-ready graphs and images.

    Scalable technology, from basic research to clinical trials

    There’s a critical element that gives us such an edge in clinical development: scalability. Our immunoSEQ Technology can be utilized from early, discovery-based projects aimed at narrowing down possible drug candidates to much larger-scale confirmation studies and high-throughput screens. With support at every stage, nothing is standing in the way of success.

    Clinical development and the immunoSEQ Assay in a nutshell

    If you need a powerful, accurate, and quantitative method to study the adaptive immune response to disease or treatment, with support at every step along the way, the immunoSEQ Assay is the tool for you.

    Our flexible and sophisticated technology captures the depth and breadth of the immune repertoire. It can be used throughout the entire clinical development pipeline, including candidate selection, identification of immune-related markers of treatment efficacy, biomarker discovery, and monitoring for adverse events.

    The immunoSEQ Assay is not only for expert immunologists and clinical researchers but also for scientists studying the adaptive immune response at any level of research. We’re here to help you accelerate your research – for more information, visit our immunoSEQ Assays page. If you have questions about how to get started, please get in touch with our product team.

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

    *Research collaboration and/or financial support provided by Adaptive Biotechnologies.


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    2.      Hassert M, Wolf KJ, Schwetye KE, DiPaolo RJ, Brien JD, Pinto AK. CD4+T cells mediate protection against Zika associated severe disease in a mouse model of infection. PLoS Pathog 2018;14(9):e1007237.

    3.      Dovedi SJ, Cheadle EJ, Popple AL, Poon E, Morrow M, Stewart R, et al. Fractionated radiation therapy stimulates antitumor immunity mediated by both resident and infiltrating polyclonal T-cell populations when combined with PD-1 blockade. Clin Cancer Res 2017;23(18):5514.

    4.      Wolf K, Hether T, Gilchuk P, Kumar A, Rajeh A, Schiebout C, et al. Identifying and tracking low-frequency virus-specific TCR clonotypes using high-throughput sequencing. Cell Rep 2018;25(9):2369–78.e4.

    5.      Allez M, Auzolle C, Ngollo M, Bottois H, Chardiny V, Corraliza AM, et al. T cell clonal expansions in ileal Crohn’s disease are associated with smoking behaviour and postoperative recurrence. Gut 2019;68(11):1961.

    6.      Pruessmann W, Rytlewski J, Wilmott J, Mihm MC, Attrill GH, Dyring-Andersen B, et al. Molecular analysis of primary melanoma T cells identifies patients at risk for metastatic recurrence. Nat Cancer 2020;1(2):197–209.

    7.      Matos TR, O’Malley JT, Lowry EL, Hamm D, Kirsch IR, Robins HS, et al. Clinically resolved psoriatic lesions contain psoriasis-specific IL-17-producing αβ T cell clones. J Clin Invest 2017;127(11):4031–41.

    8.      de Jong A, Jabbari A, Dai Z, Xing L, Lee D, Li MM, et al. High-throughput T cell receptor sequencing identifies clonally expanded CD8+ T cell populations in alopecia areata. JCI Insight 2018;3(19):e121949.

    9.      Phillips R, Shi WY, Deek M, Radwan N, Lim SJ, Antonarakis ES, et al. Outcomes of observation vs stereotactic ablative radiation for oligometastatic prostate cancer: the ORIOLE phase 2 randomized clinical trial. JAMA Oncol 2020;6(5):650–9.

    10.    Johnson DB, McDonnell WJ, Gonzalez-Ericsson PI, Al-Rohil RN, Mobley BC, Salem J-E, et al. A case report of clonal EBV-like memory CD4+ T cell activation in fatal checkpoint inhibitor-induced encephalitis. Nat Med 2019;25(8):1243–50.

    11. Chang L-W, Doan LT, Fields P, Vignali M, Akilov OE. The utility of T-cell clonality in differential diagnostics of acute graft-versus-host disease from drug hypersensitivity reaction. J Invest. Dermatol. 2020;140(6):1282–5.

    12.    Snyder TM, Gittelman RM, Klinger M, May DH, Osborne EJ, Taniguchi R, et al. Magnitude and dynamics of the T-cell response to SARS-CoV-2 infection at both individual and population levels. medRxiv 2020.07.31.20165647.

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