Multifunctional T-cell Analyses to Study Response and Progression in Adoptive Cell Transfer Immunotherapy

1NanoSystems Biology Cancer Center, 2Division of Chemistry and Chemical Engineering, 3Division of Physics, Mathematics, and Astronomy, and 4Division of Biology, California Institute of Technology, Pasadena
Cancer Discovery (Impact Factor: 19.45). 03/2013; 3(4). DOI: 10.1158/2159-8290.CD-12-0383
Source: PubMed


Adoptive cell transfer (ACT) of genetically engineered T cells expressing cancer-specific T-cell receptors (TCR) is a promising cancer treatment. Here, we investigate the in vivo functional activity and dynamics of the transferred cells by analyzing samples from 3 representative patients with melanoma enrolled in a clinical trial of ACT with TCR transgenic T cells targeted against the melanosomal antigen MART-1. The analyses included evaluating 19 secreted proteins from individual cells from phenotypically defined T-cell subpopulations, as well as the enumeration of T cells with TCR antigen specificity for 36 melanoma antigens. These analyses revealed the coordinated functional dynamics of the adoptively transferred, as well as endogenous, T cells, and the importance of highly functional T cells in dominating the antitumor immune response. This study highlights the need to develop approaches to maintaining antitumor T-cell functionality with the aim of increasing the long-term efficacy of TCR-engineered ACT immunotherapy.

A longitudinal functional study of adoptively transferred TCR–engineered lymphocytes yielded revealing snapshots for understanding the changes of antitumor responses over time in ACT immunotherapy of patients with advanced melanoma.

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    • "Ma's team assayed a panel of 12 secreted proteins and found a large (albeit not statistically random) range of functional phenotypes within a tightly defined T-cell phenotype [4]. A follow-up kinetic study [5] helped define some of this functional diversity (Figure 2). The authors [5] studied three melanoma cancer patients participating in the same ACT trial and combined 19-plex SCBC functional (secreted) protein assays with 10-color FACS to measure the functional evolution of specific T-cell phenotypes at 5 to 10 time points over a 90-day trial (Figure 2a). "
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    ABSTRACT: Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing approaches for directly elucidating phosphoprotein signaling networks in cancer cells or for capturing high-resolution snapshots of immune system function in patients with various disease conditions. We discuss advances in single-cell proteomics platforms, with an emphasis on microchip methods. These methods can provide a direct correlation of morphological, functional and molecular signatures at the single-cell level. We also provide examples of how those platforms are being applied to both fundamental biology and clinical studies, focusing on immune-system monitoring and phosphoprotein signaling networks in cancer.
    Genome Medicine 08/2013; 5(8):75. DOI:10.1186/gm479 · 5.34 Impact Factor
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    • "They also secreted each of these cytokines in large amounts (Betts et al., 2006; Darrah et al., 2007; Seder et al., 2008; Ma et al., 2011, 2013). Thus, they produced a predominant amount of cytokine in an immune response (Ma et al., 2013). One explanation of this phenomenon is that the cytokine functions are coordinated at the level of single cells and new parameters have been defined to summarize this information of polyfunctionality (Figure 1Cvi) (Darrah et al., 2007; Seder et al., 2008; Ma et al., 2013). "
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    ABSTRACT: In the past decade, significant progresses have taken place in the field of cancer immunotherapeutics, which are being developed for most human cancers. New immunotherapeutics, such as Ipilimumab (anti-CTLA-4), have been approved for clinical treatment; cell-based immunotherapies such as adoptive cell transfer (ACT) have either passed the final stage of human studies (e.g., Sipuleucel-T) for the treatment of selected neoplastic malignancies or reached the stage of phase II/III clinical trials. Immunotherapetics has become a sophisticated field. Multimodal therapeutic regimens comprising several functional modules (up to five in the case of ACT) have been developed to provide focused therapeutic responses with improved efficacy and reduced side-effects. However, a major challenge remains: the lack of effective and clinically applicable immune assessment methods. Due to the complexity of antitumor immune responses within patients, it is difficult to provide comprehensive assessment of therapeutic efficacy and mechanism. To address this challenge, new technologies have been developed to directly profile the cellular immune functions and the functional heterogeneity. With the goal to measure the functional proteomics of single immune cells, these technologies are informative, sensitive, high-throughput, and highly multiplex. They have been used to uncover new knowledge of cellular immune functions and have been utilized for rapid, informative, and longitudinal monitoring of immune response in clinical anti-cancer treatment. In addition, new computational tools are required to integrate high-dimensional data sets generated from the comprehensive, single cell level measurements of patient's immune responses to guide accurate and definitive diagnostic decision. These single cell immune function assessment tools will likely contribute to new understanding of therapy mechanism, pre-treatment stratification of patients, and ongoing therapeutic monitoring and assessment.
    Frontiers in Oncology 05/2013; 3:133. DOI:10.3389/fonc.2013.00133
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    ABSTRACT: Adoptive cell transfer (ACT) of T cells has great clinical potential, but the numerous variables of this therapy make choices difficult. A new study takes advantage of a novel technology for characterizing the T-cell responses of patients. If applied systematically, this approach may identify biomedical correlates of protection, thereby supporting treatment optimization. Cancer Discov; 3(4); 379-81. ©2013 AACR.
    Cancer Discovery 04/2013; 3(4):379-81. DOI:10.1158/2159-8290.CD-13-0064 · 19.45 Impact Factor
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