Figure 6
Figure 6. Gene expression profiling identifies gene functions and signaling pathways altered in MLL-AF4 and MLL-AF4/FLT3-TKD hESCs-derived CD45+ hematopoietic cells. (A) Heatmap diagram depicting the global gene expression profiling for EV-, MLL-AF4-, and MLL-AF4/FLT3-TKD hESC-CD45+ blood cells. The upper color bar codifies the gene expression in a log2 scale. Expression levels vary from highly expressed (red) to nonexpressed (green) genes. (B-D) After gene expression microarray analysis, the groups of genes differentially expressed (P value < .01; 2-fold regulation) in MLL-AF4 vs EV and MLL-AF4/FLT3-TKD vs MLL-AF4 hESC-CD45+ cells were compared, and the lists of gene functions and canonic pathways significantly altered were generated using the IPA software. IPA software–based data mining generated a list of significantly modulated gene functions (B) and canonic pathways (C) in MLL-AF4 vs EV hESC-CD45+ cells and MLL-AF4/FLT3-TKD vs MLL-AF4 hESC-CD45+ cells. (D) A more profound analysis was then performed for all of the genes classified by the IPA software as involved in hematopoietic system development and function/hematopoiesis. The IPA analysis–based z score is an estimation of the activation/inhibition status of a given category within an altered gene function.

Gene expression profiling identifies gene functions and signaling pathways altered in MLL-AF4 and MLL-AF4/FLT3-TKD hESCs-derived CD45+ hematopoietic cells. (A) Heatmap diagram depicting the global gene expression profiling for EV-, MLL-AF4-, and MLL-AF4/FLT3-TKD hESC-CD45+ blood cells. The upper color bar codifies the gene expression in a log2 scale. Expression levels vary from highly expressed (red) to nonexpressed (green) genes. (B-D) After gene expression microarray analysis, the groups of genes differentially expressed (P value < .01; 2-fold regulation) in MLL-AF4 vs EV and MLL-AF4/FLT3-TKD vs MLL-AF4 hESC-CD45+ cells were compared, and the lists of gene functions and canonic pathways significantly altered were generated using the IPA software. IPA software–based data mining generated a list of significantly modulated gene functions (B) and canonic pathways (C) in MLL-AF4 vs EV hESC-CD45+ cells and MLL-AF4/FLT3-TKD vs MLL-AF4 hESC-CD45+ cells. (D) A more profound analysis was then performed for all of the genes classified by the IPA software as involved in hematopoietic system development and function/hematopoiesis. The IPA analysis–based z score is an estimation of the activation/inhibition status of a given category within an altered gene function.

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