Background: T-cell activation is an essential step of the immune response and relies on the tightly controlled orchestration of hundreds of genes/proteins, yet the cellular and molecular events underlying this complex process are not fully understood, especially at the genome-scale. Significantly, a comparative genome-scale transcriptional analysis of two T-cell subsets (CD4+ and CD8+) against each other and against the naturally mixed population (CD3+ cells) remains unexplored.

BackgroundT-cell activation is an essential step of immune response. The process of proper T-cell activation is strictly monitored and regulated by apoptosis signaling. Yet, regulation of apoptosis, an integral and crucial facet during the process of T-cell activation, is not well understood.MethodsIn this study, a Gene-Ontology driven global gene expression analysis coupled with protein abundance and activity assays identified genes and pathways associated with regulation of apoptosis in primary human CD3+ T cells and separately CD4+ and CD8+ T cells.ResultsWe identified significantly regulated apoptotic genes in several protein families, such as BCL2 proteins, CASPASE proteins, and TNF receptors, and detailed their transcriptional kinetics during the T-cell activation process. Transcriptional patterns of a few select genes (BCL2A1, BBC3 and CASP3) were validated at the protein level. Many of these apoptotic genes are involved in NF-κB signaling pathway, including TNFRSF10A, TNFRSF10B, TRAF4, TRAF1, TRAF3, and TRAF6. Upregulation of NF-κB and IκB family genes (REL, RELA, and RELB, NFKBIA, NFKBIE and NFKB1) at 48 to 96 hours, supported by the increase of phosphorylated RELA (p65), suggests that the involvement of the NF-κB complex in the process of T-cell proliferation is not only regulated at the protein level but also at the transcriptional level. Examination of genes involved in MAP kinase signalling pathway, important in apoptosis, suggests an induction of p38 and ERK1 cascades in T-cell proliferation (at 48 to 96 hours), which was explored using phosphorylation assays for p38 (MAPK14) and ERK1 (MAPK3). An immediate and short-lived increase of AP-1 activity measured by DNA-binding activity suggests a rapid and transient activation of p38 and/or JNK cascades upon T-cell activation.ConclusionThis comparative genome-scale, transcriptional analysis of T-cell activation in the CD4+ and CD8+ subsets and the mixed CD3+ population identified many apoptosis genes not previously identified in the context of T-cell activation. Furthermore, it provided a comprehensive temporal analysis of the transcriptional program of apoptosis associated with T-cell activation.

Immunotherapy with ex vivo cultured T cells depends on a large supply of biologically active cells. Understanding the effects of culture parameters is essential for improving the proliferation and efficacy of the expanded cells. Low oxygen tension (5% pO(2)) was previously reported to improve T-cell expansion and alter cellular phenotypic characteristics compared to T cells cultured at 20% pO(2). Here we report the use of DNA-array based transcriptional analysis coupled with protein-level analysis to provide molecular insights into pO(2) and patient-variability effects on expanded primary human T cells. Analysis of seven blood samples showed that reduced pO(2) results in higher expression of genes important in lymphocyte biology, immune function, and cell-cycle progression. 20% pO(2) resulted in higher expression of genes involved in stress response, cell death, and cellular repair. Expression of granzyme A (gzmA) was found to be significantly regulated by oxygen tension with cells at 5% pO(2) having greater gzmA expression than at 20% pO(2). Protein-level analysis of gzmA was consistent with transcriptional analysis. Granzyme K (gzmK) was coexpressed with gzmA, whereas Granzyme B (gzmB) expression was found to precede the expression of both gzmA and gzmK in 15-day cultures. Temporal gene expression patterns for seven blood samples demonstrate that most genes are expressed by all patient samples in similar temporal patterns. However, several patient-specific gene clusters were identified, and one cluster was found to correlate well with cell proliferation and may potentially be used to predict patient-specific T-cell expansion.

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