Culture Adaptation Alters Transcriptional Hierarchies among Single Human Embryonic Stem Cells Reflecting Altered Patterns of Differentiation

We have used single cell transcriptome analysis to re-examine the substates of early passage, karyotypically Normal, and late passage, karyotypically Abnormal (‘Culture Adapted’) human embryonic stem cells characterized by differential expression of the cell surface marker antigen, SSEA3. The results confirmed that culture adaptation is associated with alterations to the dynamics of the SSEA3(+) and SSEA3(-) substates of these cells, with SSEA3(-) Adapted cells remaining within the stem cell compartment whereas the SSEA3(-) Normal cells appear to have differentiated. However, the single cell data reveal that these substates are characterized by further heterogeneity that changes on culture adaptation. Notably the Adapted population includes cells with a transcriptome substate suggestive of a shift to a more naïve-like phenotype in contrast to the cells of the Normal population. Further, a subset of the Normal SSEA3(+) cells expresses genes typical of endoderm differentiation, despite also expressing the undifferentiated stem cell genes, POU5F1 (OCT4) and NANOG, whereas such apparently lineage-primed cells are absent from the Adapted population. These results suggest that the selective growth advantage gained by genetically variant, culture adapted human embryonic stem cells may derive in part from a changed substate structure that influences their propensity for differentiation

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Unsupervised two-way cluster analysis of single cells analyzed by Taqman stem cell pluripotency assays

<p>. Samples are plotted horizontally and Taqman probe sets used to interrogate the single cells are displayed vertically. The vertical red line separates the two major clusters identified in the dataset. Green on the heat map indicates high Delta Ct values i.e. low gene expression.</p

Two-way scatter plots of <i>POU5F1</i> (<i>OCT4</i>) expression versus <i>NANOG</i> expression in the SSEA3 positive and negative assayed fractions from the Normal and Adapted H7 human ES cells.

<p>The genes plotted are <i>DNMT3B</i>, <i>GATA4</i>, <i>GATA6</i> and <i>SOX17</i>. Each cell is represented by an individual dot and colored according to the Delta Ct value of the genes indicated in the legend appended to each graph. Increasing Delta Ct indicates decreasing expression. Note that, in contrast to the relatively uniform expression of DNMT3B in all cells in each sorted population, the expression of GATA4, GATA6 and SOX17 is quite distinct in most cells of the SSEA3(+) Normal population but in almost no cells in the SSEA(3+) Adapted population.</p

Simultanious gene expression in normal and abnormal SSEA3 + and − fractions.

<p>Visualization of simultaneous gene expression in single Normal H7.s14 cells from the SSEA3 positive and negative fractions (N3⁺, N3^- respectively) and Adapted H7.s6 cells from the SSEA3 positive and negative fractions (A3⁺ A3^- respectively) for selected genes from the Human Stem Cell Pluripotency assays associated with (i) the undifferentiated pluripotent state (<i>CD9</i>, <i>DNMT3B</i>, <i>GABRB3</i>, <i>GBX2</i>, <i>GDF3</i>, <i>NANOG</i>, <i>POU5F1</i>, <i>SOX2</i>, <i>TDGF1</i>, <i>ZFP42</i>), (ii) gastrulation (<i>FGF5</i>, <i>LEFTY1</i>, <i>LEFTY2</i>, <i>NODAL</i>, <i>EOMES</i>), (iii) trophoectoderm (<i>CDX2</i>), (iv) Endoderm (<i>GATA4</i>, <i>GATA6</i>, <i>SOX17</i>) (v) Mesoderm (<i>MYF5</i>, <i>MYOD1</i>, <i>BRACHYURY</i>) and (vi) Neural (<i>NEUROD1</i>, <i>PAX6</i>). The color of each square represents a single genes’ expression (Delta Ct) in a particular cell. Green indicates high Delta Ct values i.e. low gene expression.</p