Stanford University

Human Immune Monitoring Core

This core is responsible for providing standardized, state-of the art immune monitoring assays at the RNA, protein, and cellular level; testing and developing new technologies for immune monitoring that may be useful in the context of the HIPC projects; and efficiently archiving, reporting, and mining data from immune monitoring studies, so as to increase the value of the data and to assist In biomarker discovery. Standardized, state-of-the-art immune monitoring assays include genome-wide RNA microarrays, multiplex Luminex cytokine assays, immunophenotyping, phosphoepitope flow cytometry, CFSE dye dilution assays for proliferation, and intracellular cytokine staining. An ELISPOT reader is also available. It is also creating and testing metal-labeled antibody panels for cell phenotyping using the new Cytometry by Time of Flight (CyTOF) technology, which can measure at least 35 parameters simultaneously.

http://iti.stanford.edu/research/human_immune_monitoring.html

Genomic Core

This core is responsible for providing high-throughput sequencing support to the program using a number of high throughput DNA sequencing instruments to determine the sequence variability in Human Leukocyte Antigen related genes (HLA/MIC) and to interrogate the repertoire of rearranged immunoglobulin (Ig) and T cell receptor (TcR) loci in samples isolated from the vaccine studies. Specifically, this core will amplify and sequence HLA Class I and II exons from patients, analyze exon sequences to determine the haplotype, and analyze the sequences of VDJ recombination.

Biostatistics Core for Vaccination and Infection

This core will provide high level statistical consulting to investigators. Efforts will be made to provide statistical support across multiple different immunophenotyping platforms, including FACS; phosphoflow cytometry; Luminex cytokine/chemokine assays; tetramer studies; protein microarrays; DNA arrays; genotyping of MHC, antigen receptors, and other SNP studies; functional assays; antibody neutralization studies; and clinical datasets including outcome measurements. Open source computer programs written in the popular R language http://www.r-project.org/ will be made available to investigators.