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Cellular Microarrays for Analysis of the T Cell Response to Tumors

A life sciences technician at the Stanford Functional Genomics Facility works at a printer spotting small slides with samples of DNA sequences taken from thousands of known genes. The facility uses these slides, known as microarrays, to analyze gene expression in tissue samples as part of its support services for school clinicians and researchers.

Immune based therapies that evoke a T cell response against tumor-specific antigens represent an attractive therapeutic approach. However, the ongoing development of such therapies, which include vaccines, immune modulators, DC therapy and adoptive immunotherapy, is hampered by difficulty in assessing the quantity, breadth and functional activity of the T cell response to a given treatment.

Peptide-MHC Tetramers

Peptide-MHC tetramers, originally developed by Mark Davis , have become an invaluable tool to rapidly identify, enumerate and isolate antigen-specific T cells directly from patient samples without the need for in vitro expansion.

In the cancer setting, peptide-MHC tetramers have been successfully used to identify and study T cells specific for tumor-associated antigens that develop endogenously or after vaccination in patients. Tetramers have also been used to isolate and expand tumor antigen-specific T cells for adoptive cellular immunotherapy.

However, a disadvantage of such tetramer assays, as compared with other assays such as enzyme-linked immunospot or cytokine flow cytometry is the fact that only a few different specificities can be assessed at one time and difficulties in assigning functionality to the T cells identified.

Advances in Cellular Microarrays

Recently, Daniel Chen and colleagues in the Davis and Brown laboratories has described a novel, high-throughput method to profile different populations of tumor-specific T cells for specific functional defects post-peptide vaccine therapy. This method offers the potential for not only identifying a very large number of peptide-specific T cells simultaneously but also for determining their functional profile at a single-cell resolution.

Cellular microarrays comprised of printed peptide-MHC spots, co-printed with anti-cytokine antibodies and other factors, on a single microarray, have been produced for the rapid capture of antigen-specific T cell populations and functional analysis in geographically distinct regions. Viable peripheral blood mononuclear cell samples taken from patients with malignant melanoma at different time points during ongoing peptide-vaccination protocols were analyzed on the microarray. 

Functionally active tumor-specific T cells secrete factors or cytokines such as Interferon- g , TNF- a , IL-2, or granzyme B, which are captured and detected next to the cell. Peptide-pulsed target cells may also be added to the captured T cells, and target cell killing ascertained.

To date, the results of this work are extremely promising. The peptide-MHC/cytokine cellular microarray appears to be capable of rapidly identifying several different peptide-specific T cell populations emerging following peptide-vaccination. However, the majority of tumor-specific T cells from patients that experienced disease recurrence expressed a functionally defective profile, lacking the ability to specifically secrete certain cytokines, such as IFN- g or TNF- a.

This was in contrast to viral-specific T cells from the same patients, which expressed a functional profile. Further development of the peptide-MHC cellular microarray will lead to increased peptide-MHC representation, and functional profiling of specific T cell populations. Once completed, application of this technology will lead to an improved understanding of the natural history of immune responses to malignancy and tumor immunotherapy, as well as serve as a tool to effectively monitor responses to treatment.

Novel Genomic Technologies and Clinical Informatics

Hanlee Ji is focused on developing novel genomic technologies and integrating them with clinical bioinformatics. These systems are used for identifying and validating molecular signatures as prognostic and predictive biomarkers in cancer. Currently, Dr. Ji is collaborating with Dr. Engleman in this Program and Dr. Levy (Program 6) to utilize gene and protein microarray technology to identify and characterize factors that are predictive of both clinical outcome and response to therapy, including dendritic cell vaccination. In addition to these efforts, Dr. Ji also uses functional comparative genomics for studying molecular mechanisms of cancer development.


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