Table 3. Molecular functionalities associated with TKI-resistant expression profiles.
Typea | Functional annotationb | Gene size | P-valuec | Genesd |
---|---|---|---|---|
Upregulated | GO/ATPase activity, coupled to transmembrane movement of substances | 22 | 1.7E-06 | ABCA8, ABCB1, TAP1, ABCC1, ABCB9, ABCD4 |
GO/amino-acid transport | 28 | 1.2E-05 | SLC12A7, SLC38A6, XK, SLC38A1, SLC43A1, MGC15523, SLC7A8 | |
GO/immune response | 163 | 0.0001 | IFITM3, TAP1, IFIH1, TNFRSF9, AIM2, PSMB9, IL18RAP, IFITM2, PSME1, IFI16, IFIT3, CD97, DAF, CNIH, CCL5, ISGF3G, IL18R1, PSME2, MR1, EBI2, TNFSF10, LIF, IKBKE, FCGR2B, ACSL1 | |
GO/amino-acid-polyamine transporter activity | 23 | 0.0002 | SLC12A7, SLC38A6, SLC38A1, MGC15523, SLC7A8 | |
GenMAPP/Integrin-mediated cell adhesion | 55 | 0.0005 | FYN, SEPP1, ITGB5, RAP1B, CAPN2, RAC2, CAV1, TLN1, AKT1, ITGA4, CAV2, VCL, PAK1 | |
GO/cell adhesion | 189 | 0.0006 | CD44, TPBG, MCAM, LAMA4, LAMB1, CD36, ITGB5, CPXM, CD9, TNXB, PTPRF, CD97, SELPLG, CD47, PCDH10, CCL5, IGSF1, PCDH17, FAT, URP2, ITGA4, NELL2, FEZ1, C16orf9, VCL, PKP2, CASK | |
GenMAPP/Smooth_muscle_contraction | 81 | 0.0007 | RGS20, PRKCH, IGFBP4, TNXB, ADM, ITPR2, PRKCZ, GSTO1, CREB3, ACTA2, GJA1, NOS3, ATF5, ATP2A3, NFKB1 | |
GO/non-membrane spanning protein tyrosine kinase activity | 11 | 0.0009 | SYK, FYN | |
Downregulated | GO/sterol biosynthesis | 19 | 0.0002 | FDFT1, SC4MOL, NSDHL, MVK, HMGCR, IDI1, CYP51A1, DHCR24, SC5DL |
GenMAPP/Cholesterol_Biosynthesis | 14 | 0.0003 | FDFT1, SC4MOL, NSDHL, MVK, HMGCR, IDI1, LSS, CYP51A1, SC5DL | |
GO/steroid biosynthesis | 30 | 0.0003 | HSD17B7, HSD17B8, FDFT1, SC4MOL, HSD17B1, NSDHL, MVK, HMGCR, IDI1, LSS, CYP51A1, DHCR24, SC5DL | |
GO/cholesterol biosynthesis | 16 | 0.0006 | FDFT1, NSDHL, MVK, HMGCR, IDI1, CYP51A1, DHCR24 |
Abbreviation: TKI, tyrosine kinase inhibitors.
The signatures were distinguished for upregulated and downregulated gene sets in TKI-resistant sublines.
Three databases (GO, KEGG and GenMAPP) used to collect the gene sets are denoted in the respective gene sets.
The significance for enrichment is calculated using parametric gene set enrichment analysis algorithm based on z-statistics, and unadjusted P<0.10 was considered significance.
Among the genes belonging to the gene set, the ‘leading edge subset' are listed for genes whose corresponding signal-to-noise ratio is above mean+s.d. (upregulated) or below mean−s.d. (downregulated).