Normalization of RNA-Seq data has proven essential to ensure accurate inferences and replication of findings. Hence, various normalization methods have been proposed for various technical artifacts that can be present in high-throughput sequencing transcriptomic studies. In this study, we set out to compare the widely used library size normalization methods (UQ, TMM, and RLE) and across sample normalization methods (SVA, RUV, and PCA) for RNA-Seq data using publicly available data from The Cancer Genome Atlas (TCGA) cervical cancer study. Additionally, an extensive simulation study was completed to compare the performance of the across sample normalization methods in estimating technical artifacts. Lastly, we investigated the effect of reduction in degrees of freedom in the normalized data and their impact on downstream differential expression analysis results. Based on this study, the TMM and RLE library size normalization methods give similar results for CESC dataset. In addition, the simulated datasets results show that the SVA (“BE”) method outperforms the other methods (SVA “Leek”, PCA) by correctly estimating the number of latent artifacts. Moreover, ignoring the loss of degrees of freedom due to normalization results in an inflated type I error rates. We recommend adjusting not only for library size differences but also the assessment of known and unknown technical artifacts in the data, and if needed, complete across sample normalization. In addition, we suggest that one includes the known and estimated latent artifacts in the design matrix to correctly account for the loss in degrees of freedom, as opposed to completing the analysis on the post-processed normalized data.

Immunosuppression by adenosine is an important cancer immune checkpoint. Extracellular adenosine signals through specific receptors and can be transported across the cell membrane through nucleoside transporters. Although adenosine receptors are well-known to regulate tumor immunity, the impact of adenosine transporters remains unexplored. In this study, we investigated the effect on tumor immunity of equilibrative nucleoside transporter-1 (ENT1), the major regulator of extracellular adenosine concentrations. Blocking or deleting host ENT1 significantly enhanced CD8+ T-cell–dependent antitumor responses. Tumors inoculated into ENT1-deficient mice showed increased infiltration of effector CD8+ T cells with an enhanced cytotoxic transcriptomic profile and significant upregulation of granzyme B, IFNγ, IL2, TNFα, and CXCL10. ENT1 deficiency was further associated with decreased tumor-infiltrating T regulatory cells and CD206high macrophages and suppressed CCL17 production. ENT1 deficiency notably potentiated the therapeutic activity of PD-1 blockade. T cells upregulated ENT1 upon activation, and blocking ENT1 enhanced their function when cocultured with cognate antigen/HLA-matched melanoma cells. Mechanistically, ENT1-mediated adenosine uptake inhibited the activity of phosphoribosyl pyrophosphate synthetase in activated T cells, thereby suppressing production of uridine 5′-monophosphate and its derivatives required for DNA and RNA synthesis. In summary, this study identified ENT1-mediated adenosine uptake as an important mechanism of adenosine-mediated immunosuppression and pyrimidine starvation that can be targeted to enhance antitumor T-cell responses. Significance: ENT1 is a potential therapeutic target to overcome immunosuppression induced by extracellular adenosine and to increase the activity of PD-1 blockade.