Renal Cell Carcinoma (RCC) Tumors Display Large Expansion of Double Positive (DP) CD4+CD8+ T Cells With Expression of Exhaustion Markers

Checkpoint inhibitors target the inhibitory receptors expressed by tumor-infiltrating T cells in order to reinvigorate an anti-tumor immune response. Therefore, understanding T cell composition and phenotype in human tumors is crucial. We analyzed by flow cytometry tumor-infiltrating lymphocytes (TILs) from two independent cohorts of patients with different cancer types, including RCC, lung, and colon cancer. In healthy donors, peripheral T cells are usually either CD4+ or CD8+ with a small percentage of CD4+ CD8+ DP cells (<5%). Compared to several other cancer types, including lung, and colorectal cancers, TILs from about a third of RCC patients showed an increased proportion of DP CD4+CD8+ T cells (>5%, reaching 30–50% of T cells in some patients). These DP T cells have an effector memory phenotype and express CD38, 4-1BB, and HLA-DR, suggesting antigen-driven expansion. In fact, TCR sequencing analysis revealed a high degree of clonality in DP T cells. Additionally, there were high levels of PD-1 and TIM-3 expression on DP T cells, which correlated with higher expression of PD-1 and TIM-3 in conventional single positive CD8 T cells from the same patients. These results suggest that DP T cells could be dysfunctional tumor-specific T cells with the potential to be reactivated by checkpoint inhibitors

Transcriptional Profiling of the Dose Response: A More Powerful Approach for Characterizing Drug Activities

The dose response curve is the gold standard for measuring the effect of a drug treatment, but is rarely used in genomic scale transcriptional profiling due to perceived obstacles of cost and analysis. One barrier to examining transcriptional dose responses is that existing methods for microarray data analysis can identify patterns, but provide no quantitative pharmacological information. We developed analytical methods that identify transcripts responsive to dose, calculate classical pharmacological parameters such as the EC50, and enable an in-depth analysis of coordinated dose-dependent treatment effects. The approach was applied to a transcriptional profiling study that evaluated four kinase inhibitors (imatinib, nilotinib, dasatinib and PD0325901) across a six-logarithm dose range, using 12 arrays per compound. The transcript responses proved a powerful means to characterize and compare the compounds: the distribution of EC50 values for the transcriptome was linked to specific targets, dose-dependent effects on cellular processes were identified using automated pathway analysis, and a connection was seen between EC50s in standard cellular assays and transcriptional EC50s. Our approach greatly enriches the information that can be obtained from standard transcriptional profiling technology. Moreover, these methods are automated, robust to non-optimized assays, and could be applied to other sources of quantitative data

Discovery of a Highly Selective JAK2 Inhibitor, BMS-911543, for the Treatment of Myeloproliferative Neoplasms

JAK2 kinase inhibitors are a promising new class of agents for the treatment of myeloproliferative neoplasms and have potential for the treatment of other diseases possessing a deregulated JAK2-STAT pathway. X-ray structure and ADME guided refinement of C-4 heterocycles to address metabolic liability present in dialkylthiazole <b>1</b> led to the discovery of a clinical candidate, BMS-911543 (<b>11</b>), with excellent kinome selectivity, <i>in vivo</i> PD activity, and safety profile