Different stages of differentiation of CD8 T cells based on the expression of costimulatory receptors - CD28 and CD27 has been previously described (

Nature Medicine
8
:
379
,
2002
). Specifically, CD8 T cells that are CD28CD27 are designated as the “Late” stage, while those that are CD27+ CD28 belong to the “Intermediate” stage. We have previously demonstrated that in a total of 39 total patients with multiple myeloma that had expanded T cell receptor Vβ (TCRVβ) clones, 78% of patients had clonally expanded CD8+CD57+TCRVβ+ T cells of the “Late” subset while the remaining 22% were of the “Intermediate” subset. It was also demonstrated that patients whose expanded T cells expressed a “Late” T cell phenotype had a significantly improved survival over those with an “Intermediate” T cell phenotype (
Blood
102
:
927a
,
2003
). The survival of patients with an “Intermediate” phenotype was not significantly better than those who had no detectable T cell clones. It was suggested that the expanded CD8+CD57+ cells clones with late memory/effector phenotype are associated with good prognosis in patients with myeloma. Hence gene expression profiles of these clinically significant late stage T cells will be very useful for the understanding of the anti-tumor mechanisms of these cells. Our laboratory has previously demonstrated that only the CD57+ CD8+ cells in patients with myeloma are monoclonal or biclonal, while the CD57 counterparts are polyclonal. Based on this finding, we performed an Affymetrix array analysis on these “Late” expanded T cell clones and “Intermediate” T cell clones from each of 2 patients. Eventually we aim to select for individual TCRVβ clone rather than from total CD8+CD57+. We have optimised the procedure for RNA extraction of small number of sorted cells (n=1000), RNA amplification and subsequent labelling for Affymetrix array analysis using U133Plus 2.0 GeneChips. Patient’s peripheral blood mononuclear cells were sorted using 6-color flow sorting with the phenotypes of DAPICD3+CD4CD57+CD28CD27+ (Intermediate) and DAPICD3+CD4CD57+CD28CD27 (Late). The RNA extracted from these two populations were then individually amplified and labeled for the array analysis. We implemented an algorithm called Rank Product (RP) to calculate the most significantly up-regulated genes in “Late” stage T cells in both patients’ samples. The top 2 of the Rank Product value list were: i.) KLCRs, killer cell lectin like receptor members that were associated with increased cell lysis and ii.) IGFBP7, insulin-like growth factor binding protein 7 that were associated with tumor suppression activity. Granulysin, a protein present in cytotoxic granules of cytotoxic T lymphocytes, was shown to be highly up-regulated in one of the patients but not in the other. Furthermore, we used Gene Spring software (Silicon Genetics) as an alternative data analytical approach. KLCRs were also found to be significantly up-regulated by more than 2 fold in both patients’ samples. To further validate our observation, more patients will be included in the future study and the up-regulation of these genes will be verified by real time PCR. (This work is supported by the Cancer Institute NSW)

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