Fig 1.
Validation of the cell type origin of (non-)hematopoietic samples.
Probe fluorescence as measured by microarray gene expression analysis is depicted on the x-axis in logarithmic scale. (A) Gene expression for various cell type-associated genes as determined by microarray gene expression analysis is shown. Hepatocyte-specific expression is shown for APOA2, ORM1, FGA and ALB and melanocyte-specific expression is shown for MLANA, SILV, TYRP1 and TYR. Fibroblasts-associated expression as defined by detectable expression in fibroblasts as well as a limited number of other non-hematopoietic cell types is shown for FBLN2, CD248, ITGA11 and THY1 and keratinocyte-associated expression is demonstrated for KRT14, LAMA3, KLK5 and DSG3. Fibroblasts, FB; keratinocytes, KC. (B) Gene expression for monocytes and dendritic cells (DC) is shown (left graph) as well as for immature and mature DC (right graph). Down-regulation of CD14 and up-regulation of CD86, CD209 and CCL22 is shown for DC (filled bars) cultured from monocytes (open bars) with GM-CSF and IL-4 (left graph). To validate maturation of DC, down-regulation of markers for immature DC (CCL13 and CD36) and up-regulation of markers for mature DC (LAMP3, HLA-DOB, FLT3, CD80, CD83 and HLA-DQA1) was checked (right graph). Immature DC (imDC) are depicted by squares and mature DC (matDC) are indicated by circles. Red symbols indicate samples which have been excluded from the dataset for incomplete maturation. (C) Various non-hematopoietic cell types (fibroblasts, keratinocytes, PTEC, melanocytes and HUVEC) were cultured in the presence of IFN-γ (100 IU/ml) for 4 days to mimic inflammation. Expression of various genes that are known to be induced by IFN-γ is shown (GBP2, IFITM1), including genes that are involved in HLA processing and presentation (TAP1, CD74, PSMB9 and HLA-DRA). Circles represent samples cultured without IFN-γ, while squares indicate samples after IFN-γ treatment. Red symbols indicate samples which have been excluded from the dataset for incomplete maturation.
Table 1.
Characteristics of leukemic cells selected for microarray gene expression analysis.
Table 2.
R2 values for regression analysis between microarray and q-PCRa.
Fig 2.
Effect of IFN-γ on gene expression in non-hematopoietic cell types.
Microarray gene expression analysis was performed on fibroblasts, keratinocytes, PTEC, melanocytes and HUVEC cultured in the presence of IFN-γ and probe fluorescence was compared with the same cell samples cultured in the absence of IFN-γ. All probes that were >10-fold up-regulated after IFN-γ treatment in one or more cell types are depicted. Probe fluorescence is shown on the y-axis in logarithmic scale. Circles show gene expression in the absence of IFN-γ, while squares indicate expression in the presence of IFN-γ. For each cell type, the number of probes that are >10-fold up-regulated by IFN-γ is shown.
Table 3.
Gene expression in skin fibroblasts as induced by IFN-γ and T-cell supernatant.
Fig 3.
Gene expression profiles for potential targets for immunotherapy of hematological malignancies.
Gene expression profiles were generated for hematopoiesis-restricted minor histocompatibility antigens and B-cell specific surface antigens as potential targets for immunotherapy of hematological malignancies. (A) Gene expression profiles for minor histocompatibility antigens HA-1 (HMHA1), LB-ARHGDIB-1R (ARHGDIB) and LB-ITGB2-1 (ITGB2). (B) Gene expression profiles for B-cell specific antigens CD19, CD79B and ROR1. Probe fluorescence intensity is shown on the x-axis in logarithmic scale. On the y-axis malignant and healthy (non-)hematopoietic cell types as included in the microarray dataset are shown. Each dot represents a different sample and the mean and standard deviation of gene expression is shown for each cell type.