The outstanding clinical success of immune checkpoint blockade has revived the interest in underlying mechanisms of the immune system that are capable of eliminating tumors even in advanced stages. In this scenario, CD4 and CD8 T cell responses are part of the cancer immune cycle and both populations significantly influence the clinical outcome. In general, the immune system has evolved several mechanisms to protect the host against cancer. Each of them has to be undermined or evaded during cancer development to enable tumor outgrowth. In this review, we give an overview of T lymphocyte-driven control of tumor growth and discuss the involved tumor-suppressive mechanisms of the immune system, such as senescence surveillance, cancer immunosurveillance, and cancer immunoediting with respect to recent clinical developments of immunotherapies. The main focus is on the currently existing knowledge about the CD4 and CD8 T lymphocyte interplay that mediates the control of tumor growth.

Reference genes (RG) as sample internal controls for gene transcript level analyses by quantitative RT-PCR (RT-qPCR) must be stably expressed within the experimental range. A variety of in vitro cell culture settings with primary human hepatocytes, and Huh-7 and HepG2 cell lines, were used to determine candidate RG expression stability in RT-qPCR analyses. Employing GeNorm, BestKeeper and Normfinder algorithms, this study identifies PSMB6, MDH1 and some more RG as sufficiently unregulated, thus expressed at stable levels, in hepatocyte-like cells in vitro. Inclusion of multiple RG, quenching occasional regulations of single RG, greatly stabilises gene expression level calculations from RT-qPCR data. To further enhance validity and reproducibility of relative RT-qPCR quantifications, the ΔCT calculation can be extended (e-ΔCT) by replacing the CT of a single RG in ΔCT with an averaged CT-value from multiple RG. The use of two or three RG - here identified suited for human hepatocyte-like cells - for normalisation with the straightforward e-ΔCT calculation, should improve reproducibility and robustness of comparative RT-qPCR-based gene expression analyses.

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