A representative sample was shown Original magnification 100x A

A representative sample was shown. Original magnification 100x. Additionally, 6 surrounding non-tumoural pancreatic control samples, 7 LM and 4 PM fulfilled the quality criteria and were used for microarray analysis. Gene expression profiling of ‘Good’ PDAC Akt inhibitor versus control

Analysis of ‘Good’ versus control samples revealed 3265 differentially expressed probe sets, of which 2806 could be mapped to genes in the Ingenuity Knowledge Base. IPA analysis generated networks, including ‘Cell morphology’, with TGFβ1 (fold 2.6, p < 0.001) central to this network. ‘Cancer’, ‘Cellular growth and proliferation’, ‘DNA repair’, and ‘Cellular movement’ were differentially expressed STI571 cost functions. Differentially expressed canonical pathways (p < 0.01) are shown in Table 2. The Integrin pathway (including Integrin β4 (ITGB4): fold 5.5, Integrin β5 (ITGB5): fold 5.9, and Integrin α6 (ITGA6): fold 4.6; all p < 0.001) was most significant, followed by the Ephrin pathway (including Ephrin receptor A2 (EPHA2): fold 5.9, Ephrin receptor B2 (EPHB2): fold 3.3, Ephrin A1 (EFNA1): fold 3.4, Ephrin A4 (EFNA4): fold 2.0 and Ephrin B2 (EFNB2): fold 3.4; all p < 0.001). KEGG pathway analysis of genes overexpressed in ‘Good’ samples showed SGC-CBP30 upregulation of elements of the p53 signalling, Wnt/β-catenin signalling, Notch, MAPK, and Hedgehog signalling pathways (Table

2). Table 2 Differentially expressed canonical pathways (IPA) and upregulated KEGG pathways (GENECODIS) in ‘Good’ and ‘Bad’ PDAC

  Goodversuscontrol Badversuscontrol Canonical pathways a P-value Upregulated genesc P-value Upregulated genesc Integrin signalling 5.62E-7 RAC1, RAC2, ITGB4, ITGB5, ITGA6, ACTN1, MAP2K2, GSK3B, PPP1R12A, ARF1, ACTG2 4.79E-6 RAC1, ITGA2, ITGA3, ITGA6, ITGB1, ITGB4, ITGB5, ITGB6, ACTN1, ARF1 Ephrin receptor signalling 0.00002 RAC1, RAC2, EPHA2, EPHB2, EFNA4, EFNB2, MAP4K4, MAP2K2, STAT3, RHOA, ADAM10, VEGFA 0.00001 RAC1, EFNA5, EFNB2, EPHA2, EPHB4, STAT3, ADAM10, FGF1, VEGFA, PDGFC Molecular mechanism of cancer 0.00063 RAC1, RAC2, CCND1, MAP2K2, TGFβ1, GSK3B, BRCA1, CDH1, BMP2, SMAD6, BAX, CTNNB1     P53 signalling 0.00089 TP53, PIK3C2A, RAC1, BAX, BIRC5, SERPINB5, GSK3B, BRCA1 0.02757 PRKDC, RAC1, BAX, CCND1, BIRC5, SERPINB5, CTNNB1, CDK2 Wnt/β-catenin 4-Aminobutyrate aminotransferase 0.00550 RAC2, CSNK1A1, CSNK1E, SOX9, TGFβ1, SOX4, LRP5, CTNNB1, WNT10A 0.00323 CSNK1A1, TGFβ1, DKK1, DKK3, WNT5A, WNT10A, SOX4, SOX11, TCF7L2, TCF3 Pancreatic adenocarcinoma     0.00776 JAK1, RAC1, STAT3, CCND1, BIRC5, VEGF, TGFβ1, ERBB2, CDK2 PI3K/AKT Signaling 0.00933 RAC1, RAC2, JAK1, MAP2K2, PPP2R5     KEGG pathways b         P53 Signaling 2.20E-12 TP53, CDKN6, CCND1, CDK1, CDK2, SFN 3,03E-8 CDK1, CDK2, BAX, SERPINB5, CCND1, SFN Wnt signalling 2,67E-07 WNT10A, CTNNB1, CTBP1, LRP5, TCF7L2, FZD8, GSK3B, PPP3R1, RAC1 0.00011 WNT5A, WNT10A, DKK1, DVL1, CTNNB1, CSNK1A1, CSNK1E, LRP5, RAC1, TCF7L2 Pancreatic cancer 3.

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