Table S4 Total analysis of genes differently expressed between CD34+ cells

Supplementary Table 4a. Ingenuity networks generated by 345 genes over-expressed in cancer SP (using q-value 0.05 and 1.5 log2 fold change

Supplementary Table 1. genes  differentially expressed by at least 2-fold compared with control cells after normalization to both hactin and myosin

Supplementary Table 2. STAT3 mRNA was increased 2.5- to 3.1-fold in cells overexpressing HMGA1a and 2.9-to 3.0-fold in fibroblasts overexpressing HMGA1b

Supplemental Table 3. Biological processes for genes down-regulated in HCC-infiltrating mononuclear inflammatory cells.

Supplemental Table 4. Biological processes for genes down-regulated in PBMCs of HCC patients

Table 1. Biological processes for genes up-regulated in HCC-infiltrating mononuclear inflammatory cells

Table 3. Biological processes for genes up-regulated in PBMCs of HCC patients

Table 4 ? List of genes differentially expressed in gastric cancers with and without MSI.

Consistent MSI-associated candidate genes identified by at least two Affymetrix probe sets and one IMAGE clone

Supplementary Table 2: The 829 and 192 genes (probesets) consistently changed between MSI and MSS cases across multiple studies of primary CRCs and across primary CRCs and CRC cell lines  respectively.

Table S2. 501 probe sets associated with clinical outcome within the 61 adult classical Hodgkin lymphoma (cHL) samples, associated with outcome, corresponding to 450 unique genes comprising 47 genes (52 probe sets) associated with unfavorable outcome and 403 genes (449 probe sets) associated with favorable outcome

Table S3. Genes differentially expressed between the 18 EBV+ cHL samples and the 35 EBV? cHL samples (XLS  99.5 KB)

Table S5. Genes differentially expressed between the 5H/TCRBCL samples and the 63 cHL samples (XLS  146 KB)

Table S4. Genes differentially expressed between the 42 nodular sclerosis cHL samples and the 17 mixed cellularity cHL samples (XLS  27 KB)

Table 1. Fifteen probe sets consistently identified among the random forest classifiers as being important both with respect to the mean decrease in accuracy and the mean decrease in the Gini index.