Transcriptional program of ex vivo expanded T cells

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DESCRIPTION (provided by applicant): Cellular immunotherapies with ex vivo expanded T cells (with or without genetic modifications) are promising tools for the treatment of otherwise untreatable cancers and viral infections, including iatrogenic ones (such as Epstein-Barr virus or Cytomegalovirus infections). In all cases, immune cells are isolated from the patient or an allogeneic donor, genetically modified if necessary, and expanded ex vivo before a large number of cells (10e9 -10e11) are infused into the patient. Thus, optimization of culture parameters with respect to cell proliferation and function is critical for successful immunotherapy. The majority of current protocols culture T cells in 5% C02 and ambient air (~20% 02 tension, p02). However, in vivo the mean pO2 in hematopoietic and lymphoid-organ tissues is closer to 40 mmHg (or 5% of the 02 in the gas atmosphere). We have shown that pO2 affects T-cell proliferation (by 4.8 to 13-fold), receptor expression and density, apoptosis, and metabolic rates. Similarly, we found that autologous plasma has a profound effect (43 to 74-fold over non-plasma cultures) on total cellular expansion. However, little is known about the underlying molecular biology of these profound effects, and specifically, about the large-scale gene expression patterns (transcriptome) during the activation and expansion process of T cells ex vivo. Thus, we propose to examine the large-scale transcriptome of ex vivo expanded human primary T cells using DNA arrays, whereby up to 8,500 genes will be examined for differential expression. Both T-cell selected and unselected peripheral blood mononuclear cells (PBMC) will be used to examine: (1) the temporal differential transcriptional program of T cells cultured under 5% or 20% pO2, and with or without autologous plasma; (2) the "relative" differential transcriptional program of cells cultured under 5% versus 20% pO2, and with versus without autologous plasma; (3) the differential transcriptional program of T cells cultured in the presence versus absence of an antioxidant; and (4) the differential transcriptional program of selected T cells vs. unselected cells under both low and high pO2. Analysis of DNA-array data will be used to test the following hypotheses as to whether these effects result from large transcriptional effects on: (i) The cell-cycle machinery; (ii) the apoptosis machinery; (iii) signal transduction/transcription factor networks; (iv) glycolysis/TCA cycle; and (v) stress and oxidative damage responses. In order to achieve these objectives, we will purse advanced clustering methods and new bioinformatic approaches that may allow us to examine if the collected DNA array expression data are consistent with existing pathway and regulatory networks models.