Cancer immunotherapy encompasses classes of treatments designed to attack cancer via activating or suppressing the tumor-associated immune response. Immunotherapies range from adoptive cell transfer (ACT) therapies to administered immuno-modulators such as IL-2 or anti-CTLA-4. Significant progress has been made in demonstrating the efficacy of immunotherapies for some patients, but responses are often transient, and pre-selecting likely responders, or modifying immunotherapies to improve response durabilities, is challenging. For many immunotherapies, traditional molecular or cellular biomarker assays rarely provide correlates with clinical outcomes. This situation will likely be further exacerbated as the field towards trials in which multiple immunotherapies are combined. We propose to address PQ20 through the use of advanced immune monitoring techniques that will initially be deployed retrospectively, and then integrated into well-designed immunotherapy clinical trials. Our specific focus is on late-stage melanoma patients participating in a variety of ACT trials. Our hypothesis is more general: We hypothesize that a comprehensive functional analysis of key, tumor-associated compartments of the immune system, measured across an immunotherapy regimen, can help answer PQ20. To test this hypothesis, we bring together three recently developed, highly multiplex immune monitoring tools to permit an unprecedented level of analysis of cancer patient immune system function: (1) The Single Cell Barcode Chip (SCBC) is designed to quantitate a panel of ~20 functional proteins from single cells, with >103-104 cells profiled in parallel, thus permitting a full functinal analysis of, for example, key T cell phenotypes associated with a given immunotherapy. (2) Nucleic Acid Cell Sorting (NACS), is a tetramer library approach for quantitating the populations of ~50 antigen specific T cells. (3) DNA-encoded antibody libraries (DEAL) integrated onto microfluidic chips; permit the quantitation of a large panel of blood-based biomarker proteins for surveying immune system functions and tumor markers. These assay results, plus additional (traditional) assays, patient demographics, etc., will be incorporated into algorithms for the analysis, dimensional reduction, integration, and visualization of the resultant data, which we anticipate will lead to a resolution of PQ20. We describe the recent application of our technologies towards analyzing the time-dependent responses of late-stage metastatic melanoma patients participating in an engineered T Cell Receptor (TCR) ACT immunotherapy trial. That trial involves multiple immunotherapies, including lymphodepletion of the host immune system, engineered TCR lymphocytes, dendritic cell vaccines, and IL-2. Traditional molecular diagnostic results did not correlate with clinical outcomes. However, application of the new immune monitoring tools yielded clear insights that strongly correlated with clinical outcomes, and those results have informed a clear direction for designing the proposed program.

Public Health Relevance

Cancer immunotherapy describes treatments that attack cancer via activating or suppressing the tumor- associated immune response. While immunotherapies show great promise, most patient responses are transient, and it is challenging to stratify potential responders from non-responders. We propose to address this challenge by broadly applying of a new class of immune diagnostic tools designed to reveal the detailed functional performance of a patient's anti-tumor immune response.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA170689-04
Application #
8865575
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Welch, Anthony R
Project Start
2012-09-01
Project End
2016-06-30
Budget Start
2015-07-01
Budget End
2016-06-30
Support Year
4
Fiscal Year
2015
Total Cost
Indirect Cost
Name
California Institute of Technology
Department
Type
Schools of Arts and Sciences
DUNS #
009584210
City
Pasadena
State
CA
Country
United States
Zip Code
91125
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