Down syndrome iPSC model: endothelial perspective on tumor development

Figure 1. Characterization of disomic and trisomic iPSCs and iECs. (A) (i) Phase contrast microscopy images of the trisomic and isogenic pair: DSV-iPSCs and isoDSV-iPSCs. (ii) Immunocytochemistry images showing TRA-1-60 [green] and OCT4 [red] co-expression in DSV-iPSCs and isoDSV-iPSCs. (B) Representative images: (1) flow cytometric analysis of iECs demonstrating homogeneity of CD31 and CD144 co-expression; (2) Cobblestone endothelial morphology; (3) Immunocytochemistry showing positive expression of cell-surface marker VE-Cadherin (CD144); (4) Immunocytochemistry data confirming positive expression of von Willebrand factor (VWF). Cell nuclei were stained with DAPI [blue]. (C) Heatmap showing vascular-related gene expression correlation and cell line clustering amongst HUVEC, disomic SR2-iECs, isoDSV-iECs, DSV-iECs, isoDSV-iPSCs, and DSV-iPSCs. FB1 and FB2 cell lines are fibroblasts. The microarray expression data has been log-transformed. (D) Venn diagram generated via Network Analyst showing the number of microarray genes unique to and shared between DSV-iPSC, isoDSV-iPSC, DSV-iEC, and isoDSV-iEC cell lines. (E) Statistically significant functional processes that incorporate the genes in…

Figure 2. DS endothelial perspective on tumor development: chromosome 21 cancer-related genes, leukemia-associated genes, solid tumor-associated genes. (A) Significantly expressed leukemia-associated [red] and solid tumor-associated [grey] genes mapped along Chromosome 21. The blue star represents a tumor suppressor, and the red star highlights an oncogene. Red arrows symbolize up-regulation, and green arrows are representative of down-regulation. (B and C) Top 5 significantly expressed, genome-wide leukemia and solid tumor-associated oncogenes [red stars] and tumor suppressors [blue stars] per most frequent alteration type (mutations, CNAs, fusions). Red arrows show up-regulated expression, and green arrows represent down-regulated expression. The p-value, fold change, and expression data for all gene panels was obtained from RNA-Seq analysis. Additionally, every gene panel shows DSV-iEC expression values compared to isogenic control (isoDSV-iECs).

Figure 3. Bioinformatic pathway analysis and gene verification. (A and B) Schematic representations of proliferation + inflammation pathways [left] and cytoskeletal rearrangement + ECM remodeling pathways [right]. Genes of interest are highlighted in blue. Red stars symbolize pathway starting points. The dotted lines refer to activation [green arrows] and inhibition [red bar-headed lines] mechanisms. (C) Volcano plot showing the statistical significance of the selected genes of interest. In relation to DSV-iECs, the down-regulated genes are toward the right, and up-regulated genes are on the left. (D) Chromosome plot showing locations of selected genes. Chromosome locations were obtained via RNA-Seq analysis and the UCSC Genome Browser. (E) rtPCR verification of both microarray and RNA-Seq data with regard to APOE, HAPLN1, and CCL2 expression. (F) rtPCR data table with CCL2 removed to improve visualization of APOE and HAPLN1 expression. The rtPCR tables include data, presented as mean ± SEM, from three experimental replicates.

Figure 4. Endothelial differentiation efficiency, VEGF response sensitivity, and proliferative potential of disomic and trisomic iECs. (A) Flow cytometry results of DSV-iEC and SR2-iEC differentiation in the presence of VEGF. The endothelial differentiation efficiency table incorporates expression data from three replicates. (B) DSV-iEC and HUVEC cell counts following 0.5 ng/mL, 2 ng/mL, and 20 ng/mL VEGF addition. The cell counts incorporated three replicates. (C) Flow cytometry data from the EdU Proliferation Assay. For the SR2-iEC cell line, the data shows the G0/G1 cell percentage consistently decreasing as more cells are transitioning into the S/G2 cell cycles. DSV-iECs, despite showing a growing cell percentage in the S/G2 cell cycle phases, have a significantly larger percentage of cells in the G0/G1 phases. (D) All EdU flow cytometry data compiled into a histogram. Four replicates were included in the assay. (E) RNA-Seq data showing up-regulated expression of three VEGF receptors in DSV-iECs. All statistical data in the figure is presented as mean ± SEM.

Figure 5. Tube formation, spheroid sprouting, and inflammatory response of disomic and trisomic iECs. (A) (i, ii) SR2-iEC and DSV-iEC phase contrast microscopy images of the Tube Formation Assay: prior to and following WimTube software analysis; (iii) SR2-iECs and DSV-iECs stained with cell-permeant dye Calcein-AM. The numerical values, reported in pixels (px), refer to total tube length; (iv) Tube Formation data table showing mean values for loops, branching points, and total number of tubes; (B) (i, ii) Phase contrast microscopy images of the Spheroid Assay: prior to and following WimSprout software analysis; (iii) Spheroid Assay data table showing mean values, which are reported in pixels (px), for total spheroid area, total sprout area, and total sprout length. (C) Representative image: flow cytometry results of iEC response to TNF-α stimulation. The sensitivity of the response was evaluated on the basis of VCAM-1 (CD106) and E-selectin (CD62E) cell surface expression. (D) Inflammatory Assay data incorporating four experimental replicates. Unlike the SR2-iEC line, DSV-iECs have VCAM-1 and E-selectin moderately expressed prior to TNF-α activation. Following the addition of TNF-α,…