Cell-based immunotherapies hold great promise for treatment of malignancies, yet they are among the greatest challenges to develop and implement in modern medicine. There are typically no or few markers such as distinct clinical features, specific morphological changes by imaging, or serological identifiers, which can predict efficacy or even therapeutic potential of these biologic therapies. Despite these hurdles, and the challenge of generating cell-based immunotherapies from within not-for-profit academic institutions, immune- based therapies are being developed and tested in humans based on the premise and promise of their specificity and ability to eradicate tumor using effector mechanisms that are non-overlapping with conventional therapies. The Center for Cancer Immunology Research (CCIR) at University of Texas (UT) M.D. Anderson Cancer Center (MDACC) has an active program in designing and implementing clinical-grade immunotherapies based on enhancing passive and active immunity. Currently, the phenotype of cells infused and cells recovered from patients (and animals) are characterized by flow cytometry for protein expression and a limited analysis of expressed genes. However, it is vital to be able to classify immune genes that are differentially expressed before and after immunotherapy to gauge the therapeutic potential of the treatment and to undertake the rational design of next generation immunotherapeutics with predicted improved biologic effect. The two current approaches to profiling immune gene expression, microanalysis and Q-PCR, have a limited role in enhancing the potential of immunotherapy due to the large amount of material needed, with the resultant bias that occurs when mRNA is limiting and does not cover the array's dynamic concentration range, or the bias occurring with enzymatic amplification. Simply put, comprehensive mRNA expression profiling to assess activation status, homing potential, and immunophenotype, is not possible on the immune cells recovered after infusion due to the small amount of recovered tissue. Fortunately, new technology is now available using the nCounter Analysis System from NanoString Technologies, Inc. (Seattle, WA). This system uses no enzymes or amplification steps, yet can analyze hundreds of genes in a single assay with high precision, even at low expression levels using samples directly obtained from cell culture, tissue, or whole blood lysates without sample purification and significantly can assay total purified RNA derived from formalin- fixed paraffin-embedded (FFPE) tissue samples. This system employs a novel digital technology to enable direct multiplexed measurement of gene expression while offering a high level of sensitivity and precision, including detection of fractional fold-change differences. The technology uses molecular barcodes and single molecule imaging to detect and count hundreds of unique transcripts in a single reaction. The fully automated system is easy to use and is ideally suited for researchers on this grant application who wish to validate gene expression signatures, working with small amounts of starting material and studying defined gene sets.
