Additional File 1. Overlap between genes displaying a significant (p < 0.01) changes of expression in OVCAR-3 after 5-aza-dC treatment and genes down-regulated in ovarian cancer tissue samples. Fold change in gene expression is shown for 5-aza-dC treated

Table 2. Downregulated genes after 5-aza-dC treatment of OVCAR cells. Chromosomal location and fold change in gene expression are shown for 5-aza-dC treated/untreated OVCAR 3 cells.

Table 1. Upregulated genes after 5-aza-dC treatment of OVCAR cells. Chromosomal location and fold change in gene expression are shown for 5-aza-dC treated/untreated OVCAR 3 cells.

Table 1. Genes differently expressed in LNM35 vs. N15

Supplement Table 1b: List of annotated genes down-regulated in at least two of three CAF populations.

Supplement Table 1a: List of 42 annotated genes up-regulated in at least two of three CAF populations. The 13 genes encoding secreted proteins are marked in italic.

Table 4. ABC transporter genes highly expressed in drug-resistant cell line NCI-H460/PTX250 relative to parental NCI-H460

Table 3. Genes with highly increased and decreased expression in drug-resistant cell line NCI-H460/PTX250 relative to parental NCI-H460

Table S4. Comparison of the gene-expression profile of 15 PTCL-u samples (6 CD30+ and 9 CD30?) according to the CD30+ versus CD30? distinction

Table 3. Genes overexpressed in PTCL-u compared to AITL

Table S1. Top 2.5% most varying probe sets

Table S2. Comparison of the gene expression profile of the 33 tumor tissue samples (17 AITLs and 16 PTCLs-u) according to the AITL versus PTCL-u distinction

Table 2. Genes overexpressed in AITL compared to PTCL-u

Table 3: Genes up-regulated in Parp-1-/- ES cells

Table 4: Genes down- and up-regulated in Parp-1-/- livers

Table 2: Genes down-regulated in Parp-1-/- ES cells

Supplementary Table 1B. Genes that were relatively over expressed in CD38- CLL cells.

Supplementary Table 1A. Genes that were relatively over expressed in CD38+ CLL cells.

Table 2. Highest Weighted Genes in the Platinum Prediction Response Models Using 83-Sample Training Set and Validated in 36-Sample Validation Set