PDF Output of CLIC (Clustering by Inferred Co-Expression)

PDF Output of CLIC (clustering by inferred co-expression)

Dataset: Num of genes in input gene set: 6 Total number of genes: 16493

CLIC PDF output has three sections:

1) Overview of Co-Expression Modules (CEMs) Heatmap shows pairwise correlations between all genes in the input query gene set.

Red lines shows the partition of input genes into CEMs, ordered by CEM strength.

Each row shows one gene, and the brightness of squares indicates its correlations with other genes.

Gene symbols are shown at left side and on the top of the heatmap.

2) Details of each CEM and its expansion CEM+ Top panel shows the posterior selection probability (dataset weights) for top GEO series datasets.

Bottom panel shows the CEM genes (blue rows) as well as expanded CEM+ genes (green rows).

Each column is one GEO series dataset, sorted by their posterior probability of being selected.

The brightness of squares indicates the gene's correlations with CEM genes in the corresponding dataset.

CEM+ includes genes that co-express with CEM genes in high-weight datasets, measured by LLR score.

3) Details of each GEO series dataset and its expression profile: Top panel shows the detailed information (e.g. title, summary) for the GEO series dataset.

Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Chtf18 Num ofGenesinQueryGeneset:6.CEMs:1. Overview ofCo-ExpressionModules(CEMs) with DatasetWeighting Pcna Rfc2 Rfc3 Rfc4 Rfc5

Rfc5 Rfc4 Rfc3 Pcna Rfc2 Chtf18 CEM 1(641datasets) 0.0 Scale ofaveragePearsoncorrelations 0.2 0.4 0.6 0.8 1.0 Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page1 Rad51ap1 Ncapd2 Chaf1b Cenph Chtf18 Cenpk Ncaph Cdc20 Cks1b Kif20a Cdca8 Cdca5 Cdc45 Rad51 Spc24 Fignl1 Aurkb Gmnn Mcm4 Mcm2 Mcm6 Mcm7 Mcm5 Gins1 Prim1 Prim2 Gins2 Asf1b Uhrf1 Rrm1 Birc5 Bub1 Kif22 Cdc6 Rpa2 Cdk1 Exo1 Pcna Tipin Fen1 Melk Hat1 Rfc2 Rfc3 Rfc4 Rfc5 Pole Lig1 Pbk Tk1 0.0 1.0

GSE38031 [8] GSE40513 [6]

GSE31028 [6] Only showingfirst200datasets-Seetxtoutputforfulldetails. GSE54215 [13] GSE20954 [14] GSE23200 [6] GSE18135 [18] GSE27605 [8] GSE15741 [6] GSE4694 [6] GSE12498 [12] GSE39449 [6] GSE20100 [15] GSE6998 [32] GSE51883 [30] GSE12454 [13] GSE21393 [6] GSE21379 [10] GSE12465 [14] GSE13302 [30] GSE48204 [6] GSE17794 [44] GSE57543 [6] GSE51628 [15] GSE21900 [12] GSE28093 [6] GSE38257 [14] GSE28457 [24] GSE13225 [6] GSE48397 [10] GSE13693 [9] GSE16073 [6] GSE31313 [22] GSE33308 [10] GSE51243 [7] GSE51075 [12] GSE23833 [12] GSE32386 [13] GSE46797 [6] GSE54490 [12] GSE19004 [9] GSE24628 [16] GSE17796 [39] GSE44260 [10] GSE14004 [9] GSE13873 [27] GSE50813 [24] GSE17266 [59] GSE31359 [8] GSE22180 [60] GSE51385 [8] GSE21309 [9] GSE20696 [8] GSE54653 [6] GSE38693 [8] GSE6875 [8] GSE13874 [14] GSE46209 [21] GSE30160 [6] GSE46090 [12] GSE16925 [15] GSE29241 [6] GSE12993 [6] GSE5041 [8] GSE44101 [6] GSE11220 [44] GSE45895 [27] GSE51608 [6] GSE17316 [12] GSE18660 [10] GSE51804 [10] GSE10176 [6] GSE6689 [12] GSE15155 [12] GSE53951 [10] GSE13692 [8] GSE24512 [29] GSE25257 [6] GSE9763 [20] GSE28621 [21] GSE7503 [6] GSE46091 [8] GSE15872 [18] GSE5891 [6] GSE9287 [8] GSE6065 [100] GSE48203 [9] GSE39034 [9] GSE17462 [8] GSE16675 [72] GSE46942 [7] GSE13563 [6] GSE9247 [15] GSE11358 [8] GSE39621 [51] GSE52474 [154] GSE21278 [48] GSE11222 [42] GSE7694 [12] GSE40655 [6] GSE51213 [16] GSE30192 [6] GSE19436 [8] GSE15541 [12] GSE1435 [27] GSE41342 [26] GSE46970 [15] GSE28389 [20] GSE20426 [35] GSE21299 [12] GSE23845 [15] GSE12464 [23] GSE16110 [16] GSE32598 [11] GSE4768 [18] GSE19403 [12] GSE6837 [8] GSE48004 [6] GSE51365 [28] GSE16679 [8] GSE22005 [23] GSE26355 [6] GSE38277 [18] GSE42047 [24] GSE7020 [8] GSE19925 [6] GSE10895 [8] GSE7875 [16] GSE24210 [16] GSE29632 [42] GSE21224 [16] GSE20620 [22] GSE27901 [23] GSE10525 [18] GSE14012 [24] GSE16874 [12] GSE30962 [16] GSE18042 [18] GSE18326 [8] GSE44175 [18] GSE39984 [18] GSE28593 [9] GSE14308 [12] GSE40230 [15] GSE51483 [45] GSE4260 [6] GSE30485 [15] GSE13493 [6] GSE47967 [18] GSE11775 [12] GSE33156 [18] GSE14753 [6] GSE14769 [24] GSE10192 [24] CEM+ CEM GSE5332 [12] GSE39766 [6] GSE30488 [52] GSE15267 [8] GSE15580 [14] GSE25423 [10] 0.0 GSE34729 [6] GSE19517 [6]

GSE45465 [39] Scale ofaveragePearsoncorrelations GSE13044 [59] GSE23925 [6] GSE36814 [20] GSE55705 [10] GSE27114 [6] GSE54207 [9] 0.2 GSE55855 [6] GSE39897 [36] GSE17513 [12] GSE30138 [51] GSE5245 [16] GSE8678 [6] GSE4518 [12] GSE45143 [6] GSE58307 [20] 0.4 GSE11759 [6] GSE43419 [20] GSE19885 [9] GSE18534 [15] GSE5976 [12] GSE14406 [54] GSE42049 [8] GSE16992 [48] GSE23496 [9] 0.6 GSE23502 [8] GSE13259 [10] GSE21606 [6] GSE56777 [8] GSE29318 [9] GSE31598 [12] GSE20500 [6] GSE16684 [6] GSE32277 [33] 0.8 GSE18136 [12] GSE46185 [6] GSE21568 [12] GSE46242 [12] Score 1122.54 1128.94 1129.73 1131.22 1134.96 1145.55 1153.29 1161.31 1169.33 1173.82 1179.42 1182.92 1186.72 1188.05 1193.93 1198.91 1198.94 1209.80 1211.97 1214.64 1225.42 1227.00 1234.16 1259.79 1267.00 1272.46 1274.57 1279.29 1292.98 1311.22 1316.52 1319.16 1337.66 1338.09 1343.70 1349.66 1351.20 1374.93 1409.46 1429.05 1472.49 1479.41 1504.07 1531.32 1.0 Notes Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page2 BC055324 Racgap1 Mms22l Shcbp1 Topbp1 Wdhd1 Dnajc9 Cenpw Incenp Zwilch Cenpu Cenpp Cenpn Dnmt1 Apitd1 Bub1b Dtymk Nup85 Ccnb2 Ncapg Ercc6l Spag5 Ndc80 Trip13 Ube2c Ccna2 Fbxo5 Hirip3 Aurka Brca1 Ube2t Cenpi Kntc1 Spdl1 Sgol1 Espl1 Eme1 Pola1 Pole2 Rrm2 Kif11 Ppil1 Hells Tpx2 Orc6 Dbf4 Nuf2 Cdt1 Plk4 Plk1 0.0 1.0

GSE38031 [8] GSE40513 [6]

GSE45465 [39] Scale ofaveragePearsoncorrelations GSE13044 [59] GSE23925 [6] GSE36814 [20] GSE55705 [10] GSE27114 [6] GSE54207 [9] 0.2 GSE55855 [6] GSE39897 [36] GSE17513 [12] GSE30138 [51] GSE5245 [16] GSE8678 [6] GSE4518 [12] GSE45143 [6] GSE58307 [20] 0.4 GSE11759 [6] GSE43419 [20] GSE19885 [9] GSE18534 [15] GSE5976 [12] GSE14406 [54] GSE42049 [8] GSE16992 [48] GSE23496 [9] 0.6 GSE23502 [8] GSE13259 [10] GSE21606 [6] GSE56777 [8] GSE29318 [9] GSE31598 [12] GSE20500 [6] GSE16684 [6] GSE32277 [33] 0.8 GSE18136 [12] GSE46185 [6] GSE21568 [12] GSE46242 [12] Score 906.01 907.52 913.88 916.92 919.95 922.71 936.32 939.71 942.30 949.93 950.67 952.89 954.42 957.95 962.01 967.04 972.23 980.34 983.71 987.12 991.52 992.76 995.93 1019.15 1020.81 1025.69 1029.59 1031.45 1031.94 1032.11 1034.87 1040.91 1041.29 1045.19 1053.91 1055.68 1065.19 1072.81 1086.83 1089.16 1089.36 1094.65 1095.16 1096.99 1102.37 1103.51 1105.27 1110.72 1112.74 1115.09 1.0 Notes Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page3 Rnaseh2b Mis18bp1 Timeless Suv39h1 Ranbp1 Nup133 Nup107 Ncapg2 Nusap1 Rad54b Cdc25c Cenpm Dnaaf2 Cenpe Kif18b Kpna2 Haus5 Ckap2 Cdca2 Haus1 Poc1a Esco2 Mybl2 Cenpf Mki67 Gins4 Atad5 Atad2 Pold2 Pold1 H2afx Tfdp1 Lsm2 Tcf19 Lsm3 Gsg2 Rpa3 Cks2 Nek2 Ska3 Ezh2 Orc1 Oip5 Ccnf Prc1 Ect2 Dhfr Blm Kif4 Ttf2 0.0 1.0

GSE38031 [8] GSE40513 [6]

GSE45465 [39] Scale ofaveragePearsoncorrelations GSE13044 [59] GSE23925 [6] GSE36814 [20] GSE55705 [10] GSE27114 [6] GSE54207 [9] 0.2 GSE55855 [6] GSE39897 [36] GSE17513 [12] GSE30138 [51] GSE5245 [16] GSE8678 [6] GSE4518 [12] GSE45143 [6] GSE58307 [20] 0.4 GSE11759 [6] GSE43419 [20] GSE19885 [9] GSE18534 [15] GSE5976 [12] GSE14406 [54] GSE42049 [8] GSE16992 [48] GSE23496 [9] 0.6 GSE23502 [8] GSE13259 [10] GSE21606 [6] GSE56777 [8] GSE29318 [9] GSE31598 [12] GSE20500 [6] GSE16684 [6] GSE32277 [33] 0.8 GSE18136 [12] GSE46185 [6] GSE21568 [12] GSE46242 [12] Score 722.95 725.27 728.79 730.23 730.80 731.54 733.15 738.65 739.11 742.86 749.77 752.45 756.24 763.67 765.36 766.86 770.01 771.14 775.21 776.34 776.64 776.99 777.27 777.84 779.98 791.54 793.70 796.11 796.56 800.23 807.56 809.07 809.14 813.80 814.23 836.15 838.11 845.12 846.48 856.06 864.17 870.18 872.88 883.82 894.68 894.90 896.53 897.02 897.83 903.69 1.0 Notes 2700029M09Rik 4930579G24Rik 2700094K13Rik Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page4 Arhgap11a Psmc3ip Hnrnpab Snrnp40 Nup155 Parpbp Dctpp1 Nudt21 Mis18a Ckap2l Rad54l Lmnb1 Whsc1 Cenpq Rqcd1 Nup93 Dpy30 Ccne1 Actl6a Kif18a Cdca7 Cep55 Ddx39 Rfwd3 Alyref Mcm8 Brca2 Cenpl Aspm Sgol2 Sf3a3 Cse1l Fanci Mastl Brip1 Dsn1 Cdc7 Rpa1 Mtfr2 Rcc1 Skp2 Anln Rbl1 Nxt1 E2f8 E2f7 Stil 0.0 1.0

GSE38031 [8] GSE40513 [6]

GSE45465 [39] Scale ofaveragePearsoncorrelations GSE13044 [59] GSE23925 [6] GSE36814 [20] GSE55705 [10] GSE27114 [6] GSE54207 [9] 0.2 GSE55855 [6] GSE39897 [36] GSE17513 [12] GSE30138 [51] GSE5245 [16] GSE8678 [6] GSE4518 [12] GSE45143 [6] GSE58307 [20] 0.4 GSE11759 [6] GSE43419 [20] GSE19885 [9] GSE18534 [15] GSE5976 [12] GSE14406 [54] GSE42049 [8] GSE16992 [48] GSE23496 [9] 0.6 GSE23502 [8] GSE13259 [10] GSE21606 [6] GSE56777 [8] GSE29318 [9] GSE31598 [12] GSE20500 [6] GSE16684 [6] GSE32277 [33] 0.8 GSE18136 [12] GSE46185 [6] GSE21568 [12] GSE46242 [12] Score 554.91 559.74 560.44 563.86 568.87 569.00 569.57 570.66 570.68 571.46 572.80 579.37 580.07 580.13 584.88 596.61 598.33 604.49 608.49 611.17 614.35 622.92 623.33 625.74 638.54 638.72 638.96 644.46 644.75 645.78 646.20 652.30 653.99 655.86 660.79 661.53 666.35 666.60 676.05 676.43 683.59 695.70 702.94 704.97 708.23 710.48 713.54 715.70 718.64 722.66 1.0 Notes 2810417H13Rik Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page5 BC030867 Rnaseh2a Arhgef39 Depdc1b Depdc1a Tamm41 Fam64a Anp32b Rbmxl1 Sapcd2 Pkmyt1 Hmgb3 Rbmx2 Recql4 Iqgap3 Magoh Lrrc40 Stmn1 Cdkn3 Nup62 Rpp30 Nup43 Cdca4 Pbdc1 Haus4 Ccne2 Tubg1 Fancb Sass6 Syce2 Fanca Nudt1 Ssrp1 Gtse1 Banf1 Larp7 Clhc1 Phf5a H2afz Siva1 Msh6 Gen1 Uba2 Aaas Mtbp Pask Hn1l Nrm Ung 0.0 1.0

GSE38031 [8] GSE40513 [6]

GSE45465 [39] Scale ofaveragePearsoncorrelations GSE13044 [59] GSE23925 [6] GSE36814 [20] GSE55705 [10] GSE27114 [6] GSE54207 [9] 0.2 GSE55855 [6] GSE39897 [36] GSE17513 [12] GSE30138 [51] GSE5245 [16] GSE8678 [6] GSE4518 [12] GSE45143 [6] GSE58307 [20] 0.4 GSE11759 [6] GSE43419 [20] GSE19885 [9] GSE18534 [15] GSE5976 [12] GSE14406 [54] GSE42049 [8] GSE16992 [48] GSE23496 [9] 0.6 GSE23502 [8] GSE13259 [10] GSE21606 [6] GSE56777 [8] GSE29318 [9] GSE31598 [12] GSE20500 [6] GSE16684 [6] GSE32277 [33] 0.8 GSE18136 [12] GSE46185 [6] GSE21568 [12] GSE46242 [12] Score 398.54 399.83 400.94 401.68 401.99 402.70 403.27 405.19 407.18 410.57 418.22 425.43 427.86 440.59 445.70 450.75 455.38 458.83 459.59 467.46 474.04 474.40 479.43 482.35 484.93 486.87 493.40 493.98 496.52 496.74 499.27 508.27 511.53 511.87 512.78 517.84 524.88 526.23 528.01 528.77 531.18 533.12 535.65 537.32 537.76 538.07 540.17 543.75 544.24 547.30 1.0 Notes Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page6 Nsmce4a Zmynd19 Anapc15 Tubgcp2 Suv39h2 Snrnp25 Ncaph2 Nup160 Cep192 Ccdc34 Exosc2 Snrpa1 Dlgap5 Ruvbl2 Ruvbl1 Ankle1 Smc1a Mrpl18 Prpf31 Wdr90 Nup35 Chek2 Rad18 Enkd1 Naa10 Casc5 Snrpb Tex30 Gmps Snrpc Gins3 Xrcc6 Uchl5 Pold3 Palb2 Tonsl Lsm4 Snrpf Prr11 Msh2 Nelfe Nde1 Tdp1 Ska2 Rfc1 Lyar Dis3 Eri1 Pif1 Fxn 0.0 1.0

GSE38031 [8] GSE40513 [6]

GSE45465 [39] Scale ofaveragePearsoncorrelations GSE13044 [59] GSE23925 [6] GSE36814 [20] GSE55705 [10] GSE27114 [6] GSE54207 [9] 0.2 GSE55855 [6] GSE39897 [36] GSE17513 [12] GSE30138 [51] GSE5245 [16] GSE8678 [6] GSE4518 [12] GSE45143 [6] GSE58307 [20] 0.4 GSE11759 [6] GSE43419 [20] GSE19885 [9] GSE18534 [15] GSE5976 [12] GSE14406 [54] GSE42049 [8] GSE16992 [48] GSE23496 [9] 0.6 GSE23502 [8] GSE13259 [10] GSE21606 [6] GSE56777 [8] GSE29318 [9] GSE31598 [12] GSE20500 [6] GSE16684 [6] GSE32277 [33] 0.8 GSE18136 [12] GSE46185 [6] GSE21568 [12] GSE46242 [12] Score 263.11 263.28 264.65 273.73 278.41 279.23 279.98 280.02 281.46 281.78 284.55 285.77 287.95 289.86 290.91 291.15 294.40 298.71 298.71 305.42 307.42 309.31 312.55 313.45 314.38 317.14 324.25 327.51 329.06 330.22 331.67 333.15 335.28 335.38 335.49 336.80 340.13 340.74 341.44 342.05 345.00 346.09 349.75 352.34 364.70 364.92 370.20 371.02 380.82 383.72 1.0 Notes 4632434I11Rik Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page7 Fam111a Fam83d Fam72a Anp32e Tubb4b Sephs1 Cdc123 Rad51c Ppp1r8 Aarsd1 Hmgb2 Rbm8a Stoml2 Cdca7l Trim59 Cmss1 Lmnb2 Nubp1 Dnph1 Nelfcd Nop56 Haus3 Apex1 Ddx11 Haus8 Lrwd1 Snrpg Prmt1 Snrpe Dars2 Rnf26 U2af1 Emg1 Diap3 Pole3 Pms2 Lsm6 Fancl Mns1 Myg1 Nhp2 Usp1 Dcps Neil3 Ints7 Tcp1 E2f1 Gart Eri2 0.0 1.0

GSE38031 [8] GSE40513 [6]

GSE45465 [39] Scale ofaveragePearsoncorrelations GSE13044 [59] GSE23925 [6] GSE36814 [20] GSE55705 [10] GSE27114 [6] GSE54207 [9] 0.2 GSE55855 [6] GSE39897 [36] GSE17513 [12] GSE30138 [51] GSE5245 [16] GSE8678 [6] GSE4518 [12] GSE45143 [6] GSE58307 [20] 0.4 GSE11759 [6] GSE43419 [20] GSE19885 [9] GSE18534 [15] GSE5976 [12] GSE14406 [54] GSE42049 [8] GSE16992 [48] GSE23496 [9] 0.6 GSE23502 [8] GSE13259 [10] GSE21606 [6] GSE56777 [8] GSE29318 [9] GSE31598 [12] GSE20500 [6] GSE16684 [6] GSE32277 [33] 0.8 GSE18136 [12] GSE46185 [6] GSE21568 [12] GSE46242 [12] Score 138.77 141.51 146.20 147.04 148.98 149.91 152.48 154.66 155.82 156.61 165.92 167.08 173.06 173.52 176.99 180.39 181.02 185.93 186.49 188.88 193.62 195.74 197.89 198.91 199.72 203.92 204.38 206.55 208.18 211.22 213.74 213.80 215.59 217.38 217.95 222.12 222.27 230.80 233.99 236.23 246.38 249.42 249.82 252.08 252.48 255.15 256.61 257.15 259.34 262.20 1.0 Notes 4930427A07Rik Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page8 Ebna1bp2 Cdk2ap1 Donson Gemin2 Prpf38a Nucks1 Cep128 Mthfd1l Exosc3 Ppp1r7 Rnf168 Ppm1g Mrpl40 G3bp1 Rbbp7 Rbbp8 Aimp2 Cpsf3l Cep57 Usp39 Znhit3 Pa2g4 Parp2 Parp1 Hmbs Asf1a Nme1 Sf3b5 Defa3 Noc4l Smc3 Etaa1 Paics Mnd1 Mxd3 Nop9 Xpo1 Pmf1 Cct7 Cct5 Eif3l Pfas Ipo5 Lrr1 Dck Lbr Ncl Ilf2 Cit 0.0 1.0

GSE38031 [8] GSE40513 [6]

GSE45465 [39] Scale ofaveragePearsoncorrelations GSE13044 [59] GSE23925 [6] GSE36814 [20] GSE55705 [10] GSE27114 [6] GSE54207 [9] 0.2 GSE55855 [6] GSE39897 [36] GSE17513 [12] GSE30138 [51] GSE5245 [16] GSE8678 [6] GSE4518 [12] GSE45143 [6] GSE58307 [20] 0.4 GSE11759 [6] GSE43419 [20] GSE19885 [9] GSE18534 [15] GSE5976 [12] GSE14406 [54] GSE42049 [8] GSE16992 [48] GSE23496 [9] 0.6 GSE23502 [8] GSE13259 [10] GSE21606 [6] GSE56777 [8] GSE29318 [9] GSE31598 [12] GSE20500 [6] GSE16684 [6] GSE32277 [33] 0.8 GSE18136 [12] GSE46185 [6] GSE21568 [12] GSE46242 [12] Score 60.87 60.95 61.90 63.09 63.66 65.39 68.65 70.63 73.84 78.31 79.78 81.45 81.56 83.75 84.74 84.80 85.85 85.89 86.48 89.54 90.33 91.88 92.93 95.47 96.63 97.87 98.04 100.08 100.63 101.03 102.14 102.83 102.87 104.90 106.65 107.21 107.82 108.61 109.72 111.02 112.13 113.46 116.78 117.24 125.87 126.77 127.73 128.03 132.58 138.28 1.0 Notes 4930422G04Rik 2610318N02Rik Symbol Num ofCEMGenes:6.Predicted424.SelectedDatasets:641.Strength:10.9 CEM 1,Geneset"[C]PCNA-CHL12-RFC2-5complex",Page9 Efcab11 Magohb Mrps22 Mcmbp Trim28 Psmg1 Psma1 Zfp367 Mcph1 Polr2d Kpnb1 Nup54 Cops3 Ddx20 Thoc6 Psip1 Smc2 Gtf3a Nudc Ndc1 Ddx1 Dkc1 Bora Adsl Lin9 Isy1 Itpa Dut 0.0 1.0

GSE38031 [8] GSE40513 [6]

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38031 Status: Public on Jul 25 2013 Title: DNA damage-induced differentiation of NSC Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24052948 Summary & Design: Summary: Murine ES-derived neural stem cells (NSC) were not irradiated (ctrl) or irradiated with 10Gy and cultured for 7 days (irr).

The goal was to study the gene expression changes in NSC at d7 after irradiation.

Overall design: Total RNA was extracted from 4 ctrl and 4 irr samples (biological quadruplicates).

Background corr dist: KL-Divergence = 0.0114, L1-Distance = 0.0339, L2-Distance = 0.0011, Normal std = 0.9128

0.456 Kernel fit Pairwise Correlations Normal fit

Density 0.228

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

ctrl_rep1ctrl_rep2 (0.129602)ctrl_rep3 (0.106583)ctrl_rep4 (0.151327)irr_rep1 (0.113984)irr_rep2 (0.128277)irr_rep3 (0.124589)irr_rep4 (0.123065) (0.122572) [ min ] [ medium ] [ max ] CEM 1 Rfc5 652.0 2451.5 2743.4 P ( S | Z, I ) = 1.00 Rfc4 776.0 2752.2 3105.3 Mean Corr = 0.99331 Rfc3 891.6 2193.2 2383.4 Pcna 11062.8 18043.1 18449.4 Rfc2 1280.9 3037.2 3281.4 Chtf18 96.4 276.8 304.9 Prim1 786.6 2927.5 3263.0 Mcm5 750.9 2682.6 2962.9 Rad51 471.9 1195.3 1346.1 Mcm7 1563.0 5383.1 5851.4 Gins1 248.2 1413.1 1578.5 CEM 1 + Lig1 1069.2 3389.5 3955.5 Top 10 Genes Mcm6 1582.3 4899.7 5399.0 Mcm2 963.1 2465.0 2773.9 Tipin 2352.1 5157.3 5731.0 Tk1 512.4 3298.8 3534.6

Null module GEO Series "GSE40513" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE40513 Status: Public on Oct 16 2012 Title: Gene expression profile of mouse breast cancer V720 cells treated with vehicle or PD 0332991 Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23079655 Summary & Design: Summary: D-cyclins represent components of cell cycle machinery. To test the efficacy of targeting D-cyclins in cancer treatment, we engineered mouse strains which allow acute and global ablation of individual D-cyclins in a living animal. Ubiquitous shutdown of cyclin D1 or inhibition of cyclin D associated kinase activity in mice bearing ErbB2-driven mammary carcinomas halted cancer progression and triggered tumor-specific senescence, without compromising the animals' health. Ablation of cyclin D3 in mice bearing T-cell acute lymphoblastic leukemias (T-ALL) triggered tumorspecific apoptosis. Such selective killing of leukemic cells can be also achieved by inhibiting cyclin D associated kinase activity in mouse and human T-ALL models. Hence, contrary to what one might expect from ablation of a cell cycle protein, acute shutdown of a D-cyclin leads not only to cell cycle arrest, but it also triggers tumor cell senescence or apoptosis, and it affects different tumor types through distinct cellular mechanisms. Inhibiting cyclin D-activity represents a highly-selective anticancer strategy which specifically targets cancer cells without significantly affecting normal tissues.

Overall design: Mouse breast cancer V720 cells were cultured in the presence of the CDK4/6 inhibitor PD 0332991 (PD; 1 microM) or vehicle (VO) for 24 hrs. Experiment was done in biological triplicate. A total of 6 RNA samples (3 vehicle treated and 3 PD 0332991 treated samples) were used for microarray expression analysis.

Background corr dist: KL-Divergence = 0.0313, L1-Distance = 0.0429, L2-Distance = 0.0022, Normal std = 0.7225

0.600 Kernel fit Pairwise Correlations Normal fit

Density 0.300

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

V720_vehicle_rep1V720_vehicle_rep2V720_vehicle_rep3 (0.157815)V720_PD0332991_rep1 (0.173426)V720_PD0332991_rep2 (0.170227)V720_PD0332991_rep3 (0.173627) (0.172286) (0.152619)[ min ] [ medium ] [ max ] CEM 1 Rfc5 930.7 1949.3 2056.9 P ( S | Z, I ) = 1.00 Rfc4 668.8 1420.9 1498.5 Mean Corr = 0.98762 Rfc3 579.5 1025.5 1108.9 Pcna 7203.4 10720.6 10824.0 Rfc2 1106.3 1676.6 1805.4 Chtf18 41.4 166.9 183.5 Prim1 899.3 2790.0 2839.9 Mcm5 571.6 1393.0 1469.6 Rad51 510.3 1583.3 1602.5 Mcm7 1084.3 2097.5 2222.0 Gins1 310.1 814.4 868.8 CEM 1 + Lig1 644.0 1820.4 1877.1 Top 10 Genes Mcm6 3155.7 5573.2 5786.2 Mcm2 618.3 1273.0 1420.1 Tipin 905.8 1847.0 1939.6 Tk1 612.2 1857.8 1958.1

Null module GEO Series "GSE31028" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31028 Status: Public on Sep 02 2011 Title: Genome-wide maps of histone modifications unwind in vivo chromatin states of the hair follicle lineage Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21885018 Summary & Design: Summary: Mouse hair follicles (HFs) undergo synchronized cycles. Cyclical regeneration and hair growth is fueled by stem cells (SCs). During the rest phase, the HF-SCs remain quiescent due to extrinsic inhibitory signals within the niche. As activating cues accumulate, HF-SCs become activated, proliferate, and grow downward to form transient-amplifying matrix progenitor cells. We used microarrays to detect the relative levels of global gene expression underlying the states of hair follicle stem cells and their transient-amplifying progeny before differentiation.

Overall design: Quiescent hair follicle stem cells (qHF-SCs), activated hair follicle stem cells (aHF-SCs) and transient-amplifying matrix cells (HF-TACs) were FACS-purified for RNA extraction and hybridization on Affymetrix microarrays. To obtain homogeneous populations of expression profiles, we applied the FACS technique to purify SC and TACs according to their cell surface markers.

Background corr dist: KL-Divergence = 0.0298, L1-Distance = 0.0230, L2-Distance = 0.0006, Normal std = 0.6841

0.594 Kernel fit Pairwise Correlations Normal fit

Density 0.297

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

QuiescentQuiescent hair Activatedfollicle hair Activatedstemfollicle hair cells, follicleTransient-amplifyingstem hair rep1 cells, stemfollicleTransient-amplifying (0.144454) rep2 cells, stem (0.106159) rep1 cells, matrix (0.0236647) rep2 cells,matrix (0.0753238) rep1 cells,[ (0.208176)min rep2 (0.442222) ] [ medium ] [ max ] CEM 1 Rfc5 651.1 977.3 2598.6 P ( S | Z, I ) = 1.00 Rfc4 826.6 1484.0 4426.7 Mean Corr = 0.98211 Rfc3 446.5 661.5 1214.1 Pcna 9946.9 15044.2 35622.7 Rfc2 947.7 1306.4 1917.3 Chtf18 41.4 87.1 285.9 Prim1 1085.1 1403.6 4791.0 Mcm5 146.4 553.0 2279.5 Rad51 131.3 523.1 2337.2 Mcm7 791.2 1218.4 4473.8 Gins1 250.0 452.4 2485.3 CEM 1 + Lig1 646.3 904.4 2814.7 Top 10 Genes Mcm6 1829.2 4101.2 8173.2 Mcm2 309.9 1010.6 2532.5 Tipin 879.0 2022.1 4304.1 Tk1 231.0 1065.6 3628.4

Null module GEO Series "GSE54215" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 13 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE54215 Status: Public on Mar 02 2014 Title: Comparison of gene expression profiles of naÃ¯ve and in vitro effector CD8+ T cells from wild-type and BATF-/- mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24584090 Summary & Design: Summary: The transcription factor BATF is required for Th17 and TFH differentiation. Here, we show that BATF also has a fundamental role in regulating effector CD8+ T cell differentiation. BATF-deficient CD8+ T cells show profound defects in effector expansion and undergo proliferative and metabolic catastrophe early after antigen encounter. BATF, together with IRF4 and Jun proteins, binds to and promotes early expression of genes encoding lineage-specific transcription-factors (T-bet and Blimp-1) and cytokine receptors, while paradoxically repressing genes encoding effector molecules (IFNg and granzyme B). Thus, BATF amplifies TCR-dependent transcription factor expression and augments inflammatory signal propagation but restrains effector gene expression. This checkpoint prevents irreversible commitment to an effector fate until a critical threshold of downstream transcriptional activity has been achieved.

Overall design: P14 TCR transgenic CD8+ T cells from wild-type or BATF-/- mice were examined either as naÃ¯ve cells or after 3 days of in vitro stimulation with antibodies to CD3 and CD28 in the presence of IL-2

Background corr dist: KL-Divergence = 0.0486, L1-Distance = 0.0713, L2-Distance = 0.0070, Normal std = 0.6584

0.695 Kernel fit Pairwise Correlations Normal fit

Density 0.348

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

WT_P14_Naive_rep1WT_P14_Naive_rep2BATF_KO_P14_Naive_rep1 (0.148325)BATF_KO_P14_Naive_rep2 (0.131787)BATF_KO_P14_Naive_rep3WT_P14_D3_Effector_rep1 (0.0395078)WT_P14_D3_Effector_rep2 (0.172989)WT_P14_D3_Effector_rep3 (0.126714)WT_P14_D3_Effector_rep4 (0.0356122)BATF_KO_P14_D3_Effector_rep1 (0.0379696)BATF_KO_P14_D3_Effector_rep2 (0.0462641)BATF_KO_P14_D3_Effector_rep3 (0.0429838)BATF_KO_P14_D3_Effector_rep4 (0.0656828) (0.0521304) (0.0566356)[ min (0.0433997) ] [ medium ] [ max ] CEM 1 Rfc5 1041.9 2641.6 3005.8 P ( S | Z, I ) = 1.00 Rfc4 713.7 2091.0 2271.4 Mean Corr = 0.98054 Rfc3 265.7 835.0 963.0 Pcna 12462.9 25989.7 27044.4 Rfc2 1730.3 3238.2 3481.6 Chtf18 74.3 278.6 327.0 Prim1 1188.0 3742.7 4262.9 Mcm5 655.8 2135.7 2552.1 Rad51 235.5 1727.4 1911.3 Mcm7 1910.4 4860.2 5329.9 Gins1 323.0 1649.7 1864.8 CEM 1 + Lig1 1218.4 6585.5 6773.2 Top 10 Genes Mcm6 4592.5 10466.5 11317.8 Mcm2 1043.0 1704.3 2003.3 Tipin 2061.7 5158.9 5844.3 Tk1 277.7 2243.9 2493.0

Null module GEO Series "GSE20954" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 14 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20954 Status: Public on Aug 17 2010 Title: mRNA expression profile in mouse lung development Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20520778 Summary & Design: Summary: We performed miRNA and mRNA profiling over a 7-point time course, encompassing all recognized stages of lung development and explore dynamically regulated miRNAs and potential miRNA-mRNA interaction networks specific to mouse lung development

Overall design: replicated time course of mouse lung development in 7 time points

Background corr dist: KL-Divergence = 0.0229, L1-Distance = 0.0372, L2-Distance = 0.0026, Normal std = 0.7245

0.551 Kernel fit Pairwise Correlations Normal fit

Density 0.275

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Mouse lung-embryoMouse lung-embryoMouse day lung-embryoMouse 12-rep1 day lung-embryoMouse 12-rep2 (0.121644) day lung-embryoMouse 14-rep1 (0.142485) day lung-embryoMouse 14-rep2 (0.108376) day lung-embryoMouse 16-rep1 (0.098161) day lung-embryoMouse 16-rep2 (0.0445243) day lung-postnatalMouse 18-rep1 (0.0595221) day lung-postnatalMouse 18-rep2 (0.0595788) lung-postnatalMouseday (0.0583394) 2-rep1 lung-postnatalMouseday (0.0261462)2-rep2 lung-postnatalMouseday (0.0284946)10-rep1 lung-postnatalday 10-rep2 (0.0507003) day 30-rep1 (0.0444574) day 30-rep2 (0.0743749)[ min (0.0831961) ] [ medium ] [ max ] CEM 1 Rfc5 284.7 623.3 2180.0 P ( S | Z, I ) = 1.00 Rfc4 147.1 415.0 2250.0 Mean Corr = 0.97729 Rfc3 199.0 543.0 1943.8 Pcna 5105.7 9740.1 18650.5 Rfc2 1032.9 1483.6 3388.7 Chtf18 39.0 73.1 331.4 Prim1 301.8 748.3 3315.5 Mcm5 189.8 586.8 3589.7 Rad51 80.1 359.5 2385.6 Mcm7 715.3 1487.2 6920.8 Gins1 85.3 272.1 1305.7 CEM 1 + Lig1 485.6 939.0 3445.8 Top 10 Genes Mcm6 666.6 2086.7 6853.6 Mcm2 301.0 748.5 3497.5 Tipin 817.7 1824.9 5003.6 Tk1 135.3 649.9 2333.3

Null module GEO Series "GSE23200" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE23200 Status: Public on Jun 23 2011 Title: Immunoprotective properties of sertoli cells: potential genes and pathways that confer immune privilege for sertoli cell transplantation and in the testis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21900683 Summary & Design: Summary: Immune privileged Sertoli cells (SC) survive when transplanted across immunological barriers and prolong the survival of co-transplanted allogeneic and xenogeneic cells in rodent models. However, the mechanism for this survival and protection remains unresolved. We have recently identified a mouse Sertoli cell line (MSC-1) that lacks some of the immunoprotective abilities associated with primary SC. The objective of this study was to compare the survival and gene expression profiles of primary SC and MSC-1 cells to identify factors or immune-related pathways potentially important for SC immune privilege. Primary SC or MSC-1 cells were transplanted as allografts to the renal subcapsular area of naÃ¯ve BALB/c mice and cell survival was analyzed by immunohistochemistry. Additionally, transcriptome differences were investigated by microarray and pathway analyses. While primary SC were detected within the grafts with 100% graft survival throughout the 20-day study, MSC-1 cells w ere rejected between 11 and 14 days with 0% graft survival at 20 days post-transplantation. Microarray analysis identified 3198 genes that were differentially expressed with a Â± 4-fold or higher level in primary SC. Cluster and pathway analyses indicate that the mechanism of SC immune privilege is likely complex with multiple immune modulators being involved such as immunosuppressive cytokines and complement inhibitors, lipid mediators for controlling inflammation, and junctional molecules that control leukocyte movement in and out of the immune privileged space. Further study of these immune modulators will increase our understanding of SC immune privilege and in the long-term lead to improvements in transplantation success.

Overall design: Aggregated 19 to 20-day mice primary Sertoli cells and MSC-1 cell line were used to determine the global transcriptome differences important for the survival and protection of transplanted cells.

Background corr dist: KL-Divergence = 0.0095, L1-Distance = 0.0345, L2-Distance = 0.0013, Normal std = 0.9520

0.445 Kernel fit Pairwise Correlations Normal fit

Density 0.222

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

apSC_Rep1apSC_Rep2 (0.228675)apSC_Rep3 (0.106928)aMSC_1_Rep1 (0.164971)aMSC_1_Rep2 aMSC_1_Rep3(0.229008) (0.100548) (0.169869) [ min ] [ medium ] [ max ] CEM 1 Rfc5 383.2 2634.2 2880.6 P ( S | Z, I ) = 1.00 Rfc4 1371.3 2801.3 3269.5 Mean Corr = 0.97557 Rfc3 496.0 2569.4 2753.1 Pcna 9721.6 20986.7 24099.7 Rfc2 1997.4 4022.4 4128.1 Chtf18 82.1 350.4 479.1 Prim1 674.1 3725.1 4725.1 Mcm5 684.4 3579.6 4538.2 Rad51 599.4 2444.6 2619.7 Mcm7 3301.6 8805.8 9624.6 Gins1 948.4 1651.6 1939.4 CEM 1 + Lig1 760.3 3027.8 3605.0 Top 10 Genes Mcm6 1524.9 10587.5 11549.6 Mcm2 389.4 4525.8 5834.1 Tipin 1544.9 5817.1 6158.6 Tk1 148.8 2243.6 2671.0

Null module GEO Series "GSE18135" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 18 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE18135 Status: Public on Jan 15 2010 Title: Gene Expression Profile of Androgen Modulated Genes in the Murine Fetal Developing Lung Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20064212 Summary & Design: Summary: Accumulating evidences suggest that sex affects lung development. During the fetal period, male lung maturation is delayed compared with female and surfactant production appears earlier in female than in male fetal lungs.

We analyzed by microarrays the expression of genes showing a sexual difference and those modulated by endogenous androgens (flutamide).

Overall design: Following flutamide or vehicle administration to pregnant mothers, fetal mouse lungs were studied at gestational day 17 (GD17) and GD18. RNA was extracted and hybridized on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0822, L1-Distance = 0.0567, L2-Distance = 0.0049, Normal std = 0.5081

0.862 Kernel fit Pairwise Correlations Normal fit

Density 0.431

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

FlutamideFlutamide treatedFlutamide treatedmaleVehicule at treatedmaleGD 17,Vehicule at (control) malebiologicalGD 17,Vehicule at (control) biologicalfemaleGD rep1 17,Vehicule (control) at biologicalfemale(0.0211631) GD rep2Vehicule (control)17, at female(0.0285989) biologicalGD rep3Vehicule (control)17, at male(0.0237726) biologicalGDFlutamide rep1 at(control)17, maleGD biological(0.0967625) Flutamide17, rep2at treated malebiologicalGD (0.0821223) Flutamide17, rep3at treated malebiologicalGD (0.0862909)rep1 Vehicule17, at treatedmaleGD biological(0.0656288) rep2 18,Vehicule at (control) malebiologicalGD (0.0400446) rep3 18,Vehicule at (control) biologicalfemaleGD (0.0422447) rep1 18,Vehicule (control) at biologicalfemale(0.0745313) GD rep2Vehicule (control)18, at female(0.0407145) biologicalGD rep3Vehicule (control)18, at male(0.0712631) biologicalGD rep1 at(control)18, maleGD biological(0.108393) 18, rep2at malebiologicalGD (0.0459282) 18, rep3at biologicalGD (0.0713669)rep1 [18, min biological(0.00550665) rep2 (0.0182776)] rep3 (0.07739)[ medium ] [ max ] CEM 1 Rfc5 683.9 1486.0 1831.7 P ( S | Z, I ) = 1.00 Rfc4 816.8 1782.9 2111.7 Mean Corr = 0.97448 Rfc3 418.7 839.0 1010.7 Pcna 7086.4 14976.6 17634.9 Rfc2 1265.4 1985.9 2372.7 Chtf18 105.4 215.6 273.8 Prim1 979.1 2304.4 2776.3 Mcm5 538.6 1679.3 2113.4 Rad51 390.8 1238.9 1497.5 Mcm7 1404.9 3626.6 4322.3 Gins1 188.9 534.8 722.3 CEM 1 + Lig1 1191.1 2332.8 2764.8 Top 10 Genes Mcm6 1712.8 3982.9 4700.1 Mcm2 874.7 2235.4 2665.6 Tipin 1619.8 3418.7 4272.2 Tk1 490.0 1036.7 1414.1

Null module GEO Series "GSE27605" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE27605 Status: Public on Mar 14 2011 Title: The intestinal stem cell signature identifies colorectal cancer stem cells and predicts disease relapse Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21419747 Summary & Design: Summary: Using EphB2 or the ISC marker Lgr5, we have FACS-purified and profiled intestinal stem cells (ISCs), crypt proliferative progenitors and late transient amplifying cells to define a gene expression program specific for normal ISCs.

A frequent complication in colorectal cancer (CRC) is regeneration of the tumor after therapy. The intestinal stem cell signature predicts disease relapse in CRC and identifies a stem cell-like population that displays robust tumor- initiating capacity in immunodeficient mice as well as long-term self-renewal potential.

Overall design: We FACS purified mouse intestinal crypt cells according to their EphB2 or Lgr5 contents. We used Affymetrix chips to hybridize 2 samples from EphB2 high, 2 samples from EphB2 medium and 2 samples from EphB2 low cells (one sample from each group in a first hybridization on February 2009 plus an additional sample from each group on March 2009). Additionally, we hybridized one sample from Lgr5-EGFP high and one sample from Lgr5-EGFP low cells, obtained from Lgr5-EGFP knock-in mice (Barker et al., 2007).

Background corr dist: KL-Divergence = 0.0298, L1-Distance = 0.0338, L2-Distance = 0.0014, Normal std = 0.6870

0.614 Kernel fit Pairwise Correlations Normal fit

Density 0.307

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

intestine-Lgr5High-R1intestine-Lgr5Low-R1intestine-EphB2High-R1 intestine-EphB2Medium-R1(0.0649856) (0.00337505)intestine-EphB2Low-R1intestine-EphB2High-R2 (0.137785)intestine-EphB2Medium-R2 (0.00735609)intestine-EphB2Low-R2 (0.238203) (0.111942) (0.0205749) (0.415779)[ min ] [ medium ] [ max ] CEM 1 Rfc5 411.5 1109.1 1454.5 P ( S | Z, I ) = 1.00 Rfc4 643.5 2590.5 3231.0 Mean Corr = 0.97185 Rfc3 299.8 1158.9 1467.8 Pcna 6162.6 8346.7 9040.5 Rfc2 1183.0 2399.3 2838.3 Chtf18 174.1 767.0 1000.8 Prim1 652.1 3311.5 4139.1 Mcm5 259.1 1561.4 2101.3 Rad51 180.4 885.6 1163.0 Mcm7 324.9 1773.4 2400.3 Gins1 291.8 1816.9 2267.2 CEM 1 + Lig1 421.5 1891.5 2296.6 Top 10 Genes Mcm6 1139.2 4121.2 4728.5 Mcm2 249.4 1451.9 1880.4 Tipin 179.4 1125.4 1385.6 Tk1 780.0 3422.4 3993.3

Null module GEO Series "GSE15741" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15741 Status: Public on Nov 10 2009 Title: Gene expression profiles of forced miR-200 expression in 344SQ lung adenocarcinoma cells with high metastatic potential Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19759262 Summary & Design: Summary: Metastatic disease is a primary cause of cancer-related death, and factors governing tumor cell metastasis have not been fully elucidated. Here we addressed this question by using tumor cell lines derived from mice that develop metastatic lung adenocarcinoma owing to expression of mutant K-ras and p53. A feature of metastasis-prone tumor cells that distinguished them from metastasis-incompetent tumor cells was plasticity in response to changes in their microenvironment. They transited reversibly between epithelial and mesenchymal states, forming highly polarized epithelial spheres in 3-dimensional culture that underwent epithelial-mesenchymal transition (EMT) following treatment with transforming growth factor-beta or injection into syngeneic mice. This plasticity was entirely dependent upon the microRNA-200 family, which decreased during EMT. Forced expression of miR-200 abrogated the capacity of these tumor cells to undergo EMT, invade, and metastasize and conferred transcriptional features of metastasis-incompetent tumor cells. We conclude that microenvironmental cues direct tumor metastasis by regulating miR-200 expression.

Overall design: Cell lines from p53R172Hg/+ K-rasLA1/+ mice were derived from tumor tissues removed at autopsy from two different mice (#344 and #393). The tissues were minced, placed in culture, and passed serially in RPMI 1640 supplemented with 10% fetal bovine serum (FBS), which yielded mass populations of tumor cells derived from primary lung tumors (344P and 393P), mediastinal lymph nodes (344LN and 393LN), and a subcutaneous site (344SQ). Stable 344SQ cell lines expressing the miR-200b-200a-429 cluster or control vector were generated by transduction with lentivirus vectors. GFP positive transfectant pools were selected by growth in RPMI 1640 with 10% FBS and puromycin. RNA samples of miR-200b-200a-429 knockup versus control (from triplicate cultures of each) were processed and analyzed on Affymetrix Mouse Expression Array 430A 2.0 chips.

Background corr dist: KL-Divergence = 0.0327, L1-Distance = 0.0246, L2-Distance = 0.0007, Normal std = 0.6647

0.624 Kernel fit Pairwise Correlations Normal fit

Density 0.312

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

ControlControl A (0.0793539)Control B (0.31168)429 C (0.0653867) B (0.10667)429 A (0.342699)429 C (0.0942104) [ min ] [ medium ] [ max ] CEM 1 Rfc5 752.8 2900.3 3111.5 P ( S | Z, I ) = 1.00 Rfc4 598.8 2034.8 2210.6 Mean Corr = 0.96917 Rfc3 357.7 825.7 923.9 Pcna 6230.4 10089.4 10366.1 Rfc2 739.5 2184.7 2351.2 Chtf18 24.8 216.8 240.0 Prim1 786.8 2612.7 4036.8 Mcm5 228.6 1372.4 2058.3 Rad51 145.5 1754.4 2289.9 Mcm7 397.2 1802.7 2206.7 Gins1 148.0 1370.7 1537.5 CEM 1 + Lig1 262.2 1245.8 1519.5 Top 10 Genes Mcm6 717.9 2925.1 4288.6 Mcm2 240.7 1020.8 1386.4 Tipin 1147.9 3373.8 3637.8 Tk1 159.5 2375.3 2702.9

Null module GEO Series "GSE4694" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4694 Status: Public on Apr 30 2006 Title: Expression data from myogenesis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17062158 Summary & Design: Summary: During muscle differentiation, myogenesis sepcific genes are differentially regulated, including Lamins that function at least in maintenance of nuclear architecture and regulation of gene expression.

We used microarrays to detail the global changes of gene expression in lamins and nuclear envelope assoicated proteins during myogenesis.

Keywords: comparative, myogenesis

Overall design: C2C12 were cultured either in 20% serum (undifferentiated) or in 2% horse serum (differentiated). Differentiated C2C12 cells were harvested on day 6 after induction of myogenesis in low serum. Affymetirx microarray raw data were further processed by GCRMA to globally normalized signal values and then subjected to analysis of Bayesian regularized t-test. Gene expression, that has a p-value less than 0.05 in the t-test and has more than 1.5 fold change, was considered siginificant.

Background corr dist: KL-Divergence = 0.0380, L1-Distance = 0.0307, L2-Distance = 0.0010, Normal std = 0.6550

0.633 Kernel fit Pairwise Correlations Normal fit

Density 0.316

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

myoblastmyoblast undifferentiatedmyoblast undifferentiatedmyotubes, undifferentiated C2C12,myotubes, differentiatedC2C12,biologicalmyotubes, differentiatedC2C12,biological rep1 C2C12, differentiated biological(0.15977) rep2 C2C12,biological (0.21813) rep3 C2C12,biological (0.136015) rep1[ min biological(0.182909) rep2 (0.15546)] rep3 (0.147715)[ medium ] [ max ] CEM 1 Rfc5 80.5 1391.0 1596.1 P ( S | Z, I ) = 1.00 Rfc4 278.7 900.3 997.8 Mean Corr = 0.96701 Rfc3 261.2 664.3 1035.5 Pcna 5875.0 20022.3 21373.2 Rfc2 566.4 1337.1 1542.0 Chtf18 11.6 317.7 383.7 Prim1 412.3 2377.5 2738.5 Mcm5 109.4 2394.8 2872.9 Rad51 75.5 1140.1 1419.3 Mcm7 585.4 5110.8 5432.6 Gins1 37.6 657.2 993.7 CEM 1 + Lig1 365.9 1732.4 1948.2 Top 10 Genes Mcm6 1329.3 4624.9 5114.6 Mcm2 657.6 3446.7 4132.6 Tipin 496.7 1894.8 2214.6 Tk1 206.6 3838.7 4380.6

Null module GEO Series "GSE12498" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12498 Status: Public on Nov 21 2008 Title: Gene expression profiles regulated by Tead2 mutants, Yap, and cell density in NIH3T3 cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19004856 Summary & Design: Summary: Regulation of organ size is important for development and tissue homeostasis. In Drosophila, Hippo signaling controls organ size by regulating the activity of a TEAD transcription factor, Scalloped, through modulation of its coactivator protein Yki. The role of mammalian Tead proteins in growth regulation, however, remains unknown. Here we examined the role of mouse Tead proteins in growth regulation. In NIH3T3 cells, cell density and Hippo signaling regulated the activity of Tead proteins by modulating nuclear localization of a Yki homologue, Yap, and the resulting change in Tead activity altered cell proliferation. Tead2-VP16 mimicked Yap overexpression, including increased cell proliferation, reduced cell death, promotion of EMT, lack of cell contact inhibition, and promotion of tumor formation. Growth promoting activities of various Yap mutants correlated with their Tead-coactivator activities. Tead2-VP16 and Yap regulated largely overlapping sets of genes. However, only a few of the Tead/Yapregulated genes in NIH3T3 cells were affected in Tead1-/-;Tead2-/- or Yap-/- embryos. Most of the previously identified Yap-regulated genes were not affected in NIH3T3 cells or mutant mice. In embryos, levels of nuclear Yap and Tead1 varied depending on cell types. Strong nuclear accumulation of Yap and Tead1 were seen in myocardium, correlating with requirements of Tead1 for proliferation. However, their distribution did not always correlate with proliferation. Taken together, mammalian Tead proteins regulate cell proliferation and contact inhibition as a transcriptional mediator of Hippo signaling, but the mechanisms by which Tead/Yap regulate cell proliferation differ depending on cell types, and Tead, Yap and Hippo signaling may play multiple roles in mouse embryos.

We used microarrays to know the gene expression profiles regurated by Tead2-VP16, Tead2-EnR, Yap, and cell density in NIH3T3 cells.

Keywords: Cell density, genetic modification

Overall design: Tead2-VP16-, Tead2-EnR-, Yap- and control vector-expressing cells were cultured at low or high density for RNA extraction and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0711, L1-Distance = 0.0551, L2-Distance = 0.0045, Normal std = 0.5445

0.805 Kernel fit Pairwise Correlations Normal fit

Density 0.402

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

ctrl-low-1ctrl-low-2 (0.277881)tead2VP16-conf-1 (0.241329)tead2VP16-conf-2yap-conf-1 (0.0373966)yap-conf-2 (0.040305)(0.0285965)tead2EnR-low-1 (0.0277954)tead2EnR-low-2ctrl-over-1 (0.0804986)ctrl-over-2 (0.0839638) (0.0455588)tead2VP16-over-1 (0.0407459)tead2VP16-over-2 (0.0469496) (0.0489797) [ min ] [ medium ] [ max ] CEM 1 Rfc5 382.5 484.3 2149.4 P ( S | Z, I ) = 1.00 Rfc4 458.6 509.7 1597.7 Mean Corr = 0.96673 Rfc3 282.5 369.0 1125.0 Pcna 5428.9 8680.2 19569.6 Rfc2 842.4 961.5 2178.6 Chtf18 164.1 186.4 868.6 Prim1 674.0 836.5 3433.2 Mcm5 416.5 774.5 5949.3 Rad51 329.1 456.5 3226.3 Mcm7 888.4 1027.0 4949.6 Gins1 126.9 172.5 1120.9 CEM 1 + Lig1 507.0 696.1 3048.7 Top 10 Genes Mcm6 1199.4 1594.1 7143.7 Mcm2 608.7 855.4 3734.0 Tipin 1218.8 1462.1 3413.9 Tk1 345.8 389.1 3557.6

Null module GEO Series "GSE39449" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39449 Status: Public on Feb 25 2014 Title: Differentially activated CD8 T cells in liver and gut Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19265543 Summary & Design: Summary: NaÃ¯ve, liver- and gut-activated CD8 OT-I T cells show differential migration behaviour. To analyze which genes could be responsible for different migration patterns, naÃ¯ve, liver-activated and gut-activated CD8 T cells were isolated and compared for their gene expression profile.

Overall design: After total RNA extraction, reverse transcription, cDNA extraction, the biotinylated cRNA was transcribed, fragmented, and 15 ´g cRNA hybridized in duplicates for each of the three groups to the GeneChip arrays. Group1: naÃ¯ve, Group2: liver-activated Group3: gut-activated. Lists of differentially regulated genes were created using High Performance Chip Data Analysis (HPCDA) with Bioretis database (http://www.bioretis-analysis.de). Worldwide data sharing is possible via Bioretis, please ask the authors.

Background corr dist: KL-Divergence = 0.0358, L1-Distance = 0.0497, L2-Distance = 0.0032, Normal std = 0.6979

0.630 Kernel fit Pairwise Correlations Normal fit

Density 0.315

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

DifferentiallyDifferentially activatedDifferentially activatedDifferentially CD8 Tactivated cellsDifferentially CD8 in Tactivated cellsDifferentially liverCD8 andin Tactivated cells liverCD8 gut: andin Tactivated Liver-activated cells liverCD8 gut: andinT Liver-activated cells liverCD8 gut: andinT Gut-activated CD8cells[liver gut:min OT-I andin Gut-activated CD8liver Tgut: cells OT-I ]and CD8 NaÃ¯ve (liver)Tgut: OT-I cells CD8 NaÃ¯veCD8 ChipT (liver) cells [OT-I OT-I 1medium CD8 (0.0726937)(mes)ChipT T cells cells OT-I 2 Chip (0.16608)(mes) (naÃ¯ve)T cells 1 (0.0644481)Chip (naÃ¯ve)] Chip 2 (0.0569468) 1 (0.265694)Chip[ 2 (0.374138)max ] CEM 1 Rfc5 1096.8 4303.3 4457.6 P ( S | Z, I ) = 1.00 Rfc4 1294.4 4038.4 4740.1 Mean Corr = 0.96629 Rfc3 299.4 1077.0 1390.8 Pcna 12477.1 24422.3 26058.3 Rfc2 1286.5 2813.5 2891.5 Chtf18 34.5 263.1 346.6 Prim1 1356.5 5762.0 6487.7 Mcm5 976.4 3872.9 4114.8 Rad51 330.8 3851.1 4167.8 Mcm7 2398.4 6988.5 8290.0 Gins1 297.6 2190.4 2969.2 CEM 1 + Lig1 785.0 5932.0 6792.3 Top 10 Genes Mcm6 4517.5 12231.2 13959.2 Mcm2 1991.2 3352.0 3795.4 Tipin 1591.6 7043.8 8458.9 Tk1 210.3 3703.3 4232.3

Null module GEO Series "GSE20100" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 15 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20100 Status: Public on Jul 01 2010 Title: Expression data from primary MEF lacking either HDAC1, HDAC2 or both Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20194438 Summary & Design: Summary: Previously published data suggested some redundant functions between HDAC1 and HDAC2 in mouse. To test this hypothesis, we used microarrays to have a genome wide analysis at the transcription level of primary MEFs lacking HDAC1, HDAC2.

Overall design: MEF HDAC1 F/F were were transduced with two different retroviruses: one virus expresses the Tamoxifen-inducible cre recombinase Cre-ERT2 and the second virus expresses either a small hairpin micro-RNA against HDAC2 or a scrambled version. HDAC1F/F MEFs expressing either a scrambled micro-RNA or a micro-RNA against HDAC2 can be induced by addition of Tamoxifen to delete HDAC1, thereby generating four different genotypes: WT, HDAC1 KO, HDAC2 knockdown (Kd) and HDAC1/2 KO/Kd.

Background corr dist: KL-Divergence = 0.0906, L1-Distance = 0.0823, L2-Distance = 0.0115, Normal std = 0.5232

0.888 Kernel fit Pairwise Correlations Normal fit

Density 0.444

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

MEF HDAC1MEF HDAC1+/+MEF + Tamoxien HDAC1+/+MEF + Tamoxien HDAC1+/+ rep1MEF + Tamoxien(0.0219159) HDAC1fl/fl rep2MEF + siRNA(0.0151298) HDAC1fl/fl rep3MEF + scrambled siRNA(0.010776) HDAC1fl/flMEF + scrambledsiRNA HDAC1fl/fl +MEF EtOH + scrambledsiRNA HDAC1fl/fl +rep1MEF EtOH + scrambledsiRNA (0.0760104) HDAC1fl/fl +rep2MEF EtOH + scrambledsiRNA (0.0754523) HDAC1fl/fl +rep3MEF Tamoxifen + scrambledsiRNA (0.0594678) HDAC1fl/fl +MEF Tamoxifen + +siRNA rep1EtOH HDAC1fl/fl +MEF Tamoxifen +(0.0113448) +rep1siRNA rep2EtOH HDAC1fl/flMEF (0.0323585) +(0.0180549) +rep2siRNA rep3EtOH HDAC1fl/fl (0.0250029) +(0.00138402) +rep3siRNA Tamoxifen fl/fl (0.017417) + +siRNA Tamoxifen rep1 + Tamoxifen (0.225679)[ rep2 min (0.170704) rep3 ] (0.239303) [ medium ] [ max ] CEM 1 Rfc5 302.2 1455.6 1795.9 P ( S | Z, I ) = 1.00 Rfc4 435.7 2525.5 3104.0 Mean Corr = 0.96348 Rfc3 475.5 1041.8 1236.3 Pcna 7348.9 18065.8 21134.7 Rfc2 772.3 1812.6 2139.8 Chtf18 26.8 110.5 167.1 Prim1 507.9 2278.4 2688.6 Mcm5 262.9 2118.4 3763.2 Rad51 332.6 1764.2 2156.1 Mcm7 1064.4 3471.8 4622.4 Gins1 257.2 1037.9 1376.9 CEM 1 + Lig1 297.6 1360.9 1965.8 Top 10 Genes Mcm6 2027.1 4825.9 6137.5 Mcm2 611.5 1751.0 2398.8 Tipin 2418.7 6067.1 7264.9 Tk1 174.0 1907.7 2551.0

Null module GEO Series "GSE6998" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 32 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE6998 Status: Public on Feb 09 2007 Title: Expression profiling of developmental and regenerating liver in mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17227769 Summary & Design: Summary: Normal adult liver is uniquely capable of renewal

and repair after injury. Whether this response

represents simple hyperplasia of various liver elements

or requires recapitulation of the genetic program of

the developing liver is not known. To study these possibilities,

we examined transcriptional programs of

adult liver after partial hepatectomy and contrasted

these with developing embryonic liver. Principal component

analysis demonstrated that the time series of

gene expression during liver regeneration does not segregate

according to developmental transcription patterns.

Gene ontology analysis revealed that liver restoration

after hepatectomy and liver development differ

dramatically with regard to transcription factors

and chromatin structure modification. In contrast, the

tissues are similar with regard to proliferationassociated

genes. Consistent with these findings, realtime

polymerase chain reaction showed transcription

factors known to be important in liver development

are not induced during liver regeneration. These three

lines of evidence suggest that at a transcriptional level,

restoration of liver mass after injury is best described

as hepatocyte hyperplasia and not true regeneration.

We speculate this novel pattern of gene expression may

underlie the unique capacity of the liver to repair itself

after injury.

Keywords: time course

Overall design: Each experimental time point is represented by two separate samples, each consisting of at least 3 pooled tissues from different animals. For example, 6 hepatectomies were performed for the 1 hour post-hepatectomy time point. Time 0 is used as control.

Background corr dist: KL-Divergence = 0.0534, L1-Distance = 0.0220, L2-Distance = 0.0006, Normal std = 0.5487

0.727 Kernel fit Pairwise Correlations Normal fit

Density 0.364

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

baselinebaseline sampleregeneration sampleat T0,regeneration rep1 at T0, (0.0183443)sampleregeneration rep2 (0.0219091) sampleatregeneration T1, rep1 sampleatregeneration T1, (0.0228434) rep2 sampleatregeneration T2, (0.020302) rep1 sampleatregeneration T2, (0.0190857) rep2 sampleatregeneration T6, (0.0222151) rep1 sampleatregeneration T6, (0.0224425) rep2 sampleatregeneration T12, (0.0196183) samplerep1atregeneration T12, (0.0210458) samplerep2atregeneration T18, (0.0217794) samplerep1atregeneration T18, (0.0155094) samplerep2atregeneration T24, (0.0182364) samplerep1atregeneration T24, (0.020432) samplerep2atregeneration T30, (0.019882) samplerep1atregeneration T30, (0.0197946) samplerep2atregeneration T48, (0.0211501) samplerep1atdevelopmental T48, (0.0173731) samplerep2atdevelopmental T72, (0.0138457) rep1at developmentalsample T72, (0.00880069) rep2 developmental sampleat T105,(0.00810963) developmental sampleat rep1 T105, (0.0341454) developmental sampleat rep2 T115, (0.0407138) developmental sampleat rep1 T115, (0.053334) developmental sampleat rep2 T125, (0.0435409) developmental sampleat rep1 T125, (0.0573773) developmental sampleat rep2 T135, (0.0483336) developmental sampleat rep1 T135, (0.0657626) developmental sampleat rep2 T145, (0.0652321) sampleat rep1 T145, (0.0568018) sampleat rep2 T165, (0.0513343) at rep1 T165, (0.0608195)[ rep2min (0.0498853) ] [ medium ] [ max ] CEM 1 Rfc5 3.5 204.4 1971.1 P ( S | Z, I ) = 1.00 Rfc4 440.3 778.1 3388.0 Mean Corr = 0.96228 Rfc3 15.9 178.9 1505.3 Pcna 714.6 1326.0 18268.6 Rfc2 449.9 858.8 2449.8 Chtf18 3.3 3.8 406.6 Prim1 198.8 430.6 3120.7 Mcm5 426.7 677.6 5708.9 Rad51 3.3 6.1 1413.0 Mcm7 226.1 435.0 7638.5 Gins1 24.5 165.9 1454.6 CEM 1 + Lig1 88.6 232.2 3838.6 Top 10 Genes Mcm6 213.6 703.3 9709.1 Mcm2 106.0 264.0 4563.1 Tipin 42.9 254.1 4312.1 Tk1 79.7 644.8 2774.4

Null module GEO Series "GSE51883" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 30 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51883 Status: Public on Jan 28 2014 Title: Effect of Mirn378 overexpression on gene expression during C2C12 myogenic and BMP2-induced osteogenic differentiation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Background: MicroRNAs (miRNAs) are a family of small, non-coding single-stranded RNA molecules involved in post-transcriptional regulation of gene expression. As such, they are believed to play a role in regulating the step-wise changes in gene expression patterns that occur during cell fate specification of multipotent stem cells. Here, we have studied whether terminal differentiation of C2C12 myoblasts is indeed controlled by lineage-specific changes in miRNA expression.

Results: Using a previously generated RNA polymerase II (Pol-II) ChIP-on-chip dataset, we show differential Pol-II occupancy at the promoter regions of six miRNAs during C2C12 myogenic versus BMP2-induced osteogenic differentiation. Overexpression of one of these miRNAs, miR-378, enhances Alp activity, calcium deposition and mRNA expression of osteogenic marker genes in the presence of BMP2.

Conclusions: Our results demonstrate a previously unknown role for miR-378 in promoting BMP2-induced osteogenic differentiation. #!#

Overall design: Stable C2C12 cell lines C2C12-pMirn0 and C2C12-pMirn378 were generated by lentiviral transduction of C2C12 myoblasts with a Mirn378-overexpression construct and its parent vector, respectively. C2C12-pMirn0 and C2C12-pMirn378 cells were plated at 2.5 x 10^4 cells/cm2 (day -1), cultured for 1 day in DMEM 10%NCS, then (d0) treated with or without 300 ng/ml bone morphogenetic protein 2 (BMP2) for 6 days. RNA was extracted on d0, d3 and d6 and hybridized to GeneChip Mouse Genome 430 2.0 array (Affymetrix).

Background corr dist: KL-Divergence = 0.1521, L1-Distance = 0.0728, L2-Distance = 0.0106, Normal std = 0.4058

1.104 Kernel fit Pairwise Correlations Normal fit

Density 0.552

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

C2C12-pMirn0_d0_rep1C2C12-pMirn0_d0_rep2C2C12-pMirn0_d0_rep3C2C12-pMirn0_day (0.137994)C2C12-pMirn0_day (0.13465)C2C12-pMirn0_day (0.121611) 3_untreated_rep1C2C12-pMirn0_day 3_untreated_rep2C2C12-pMirn0_day 3_untreated_rep3 C2C12-pMirn0_day(0.0197142) 6_untreated_rep1 C2C12-pMirn0_day(0.0178224) 6_untreated_rep2 C2C12-pMirn0_day(0.0151127) 6_untreated_rep3 C2C12-pMirn0_day(0.0103897) 3_BMP2 C2C12-pMirn0_day(0.0117946) 3_BMP2 treated_rep1 C2C12-pMirn0_day(0.0136712) 3_BMP2 treated_rep2C2C12-pMirn0_day (0.00573469)6_BMP2 treated_rep3C2C12-pMirn378_d0_rep1 (0.00951667)6_BMP2 treated_rep1C2C12-pMirn378_d0_rep2 (0.0069537)6_BMP2 treated_rep2C2C12-pMirn378_d0_rep3 (0.00757182) treated_rep3C2C12-pMirn378_day (0.128406)(0.0092732)C2C12-pMirn378_day (0.125462)(0.00934358)C2C12-pMirn378_day (0.0985869) 3_untreated_rep1C2C12-pMirn378_day 3_untreated_rep2C2C12-pMirn378_day 3_untreated_rep3C2C12-pMirn378_day (0.0123175) 6_untreated_rep1C2C12-pMirn378_day (0.0125073) 6_untreated_rep2C2C12-pMirn378_day (0.0127345) 6_untreated_rep3C2C12-pMirn378_day (0.0101028) 3_BMP2C2C12-pMirn378_day (0.00999967) 3_BMP2C2C12-pMirn378_day treated_rep1 (0.00940409) 3_BMP2C2C12-pMirn378_day treated_rep2 (0.00412816)6_BMP2 treated_rep3 (0.00266258)6_BMP2 treated_rep1 (0.00258006)6_BMP2 treated_rep2 (0.0150061)[ treated_rep3 min (0.0126447) ] (0.0123033)[ medium ] [ max ] CEM 1 Rfc5 232.9 388.7 2275.1 P ( S | Z, I ) = 1.00 Rfc4 495.6 718.4 1858.5 Mean Corr = 0.96140 Rfc3 260.3 358.3 1275.6 Pcna 3652.4 5934.7 15336.6 Rfc2 510.3 608.8 1462.5 Chtf18 2.7 21.4 230.7 Prim1 433.6 666.2 3609.3 Mcm5 87.1 181.5 1962.0 Rad51 78.3 201.2 1734.0 Mcm7 644.5 831.6 3548.7 Gins1 98.4 193.1 1238.5 CEM 1 + Lig1 161.9 311.2 1473.6 Top 10 Genes Mcm6 656.4 1183.6 5376.5 Mcm2 243.7 488.4 2417.0 Tipin 651.0 1315.0 2965.2 Tk1 88.7 251.3 3165.1

Null module GEO Series "GSE12454" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 13 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12454 Status: Public on Aug 01 2009 Title: The SWI/SNF protein ATRX co-regulates pseudoautosomal genes that have translocated to autosomes in the mouse genome Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 18842153 Summary & Design: Summary: Pseudoautosomal regions (PAR1 and PAR2) in eutherians retain homologous regions between the X and Y chromosomes that play a critical role in the obligatory X-Y crossover during male meiosis. Genes that reside in the PAR1 are exceptional in that they are rich in repetitive sequences and undergo a very high rate of recombination. Remarkably, murine PAR1 homologs have translocated to various autosomes, reflecting the complex recombination history during the evolution of the mammalian X chromosome. We now report that the SNF2-type chromatin remodeling protein ATRX controls the expression of eutherians ancestral PAR1 genes that have translocated to autosomes in the mouse. In addition, we have identified two potentially novel mouse PAR1 orthologs. We propose that the ancestral PAR1 genes share a common epigenetic environment that allows ATRX to control their expression.

Overall design: At P0.5, n = 4 biological replicates of littermate-matched wt/ko pairs (for pair #2 there is one wt and 2 Atrx-null samples (2A & 2B) and we count this as 2 pairs).

Background corr dist: KL-Divergence = 0.0342, L1-Distance = 0.0308, L2-Distance = 0.0011, Normal std = 0.6463

0.648 Kernel fit Pairwise Correlations Normal fit

Density 0.324

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

E13.5 wildE13.5 type wildE13.5 #1 type(0.101522) wildE13.5 #2 type(0.086348) Atrx-nullE13.5 #3 (0.113488) Atrx-null E13.5#1 (0.0901446) Atrx-null P0.5#2 (0.0644031) wild P0.5#3 type (0.0927044) wild #1P0.5 type(0.0695326) wild #2P0.5 type(0.0754124) Atrx-null #3P0.5 (0.0474169) Atrx-null #1P0.5 (0.067113) Atrx-null #2AP0.5 (0.0632789) Atrx-null #2B (0.0727915) #3 (0.0558445) [ min ] [ medium ] [ max ] CEM 1 Rfc5 442.0 668.7 1978.5 P ( S | Z, I ) = 1.00 Rfc4 274.8 452.7 2221.5 Mean Corr = 0.96031 Rfc3 288.0 525.2 1352.9 Pcna 2726.3 4250.6 11117.7 Rfc2 995.7 1117.5 2214.8 Chtf18 4.9 22.5 425.5 Prim1 630.8 1015.3 3059.7 Mcm5 191.8 313.8 3264.5 Rad51 170.4 235.3 1592.0 Mcm7 853.0 1621.8 5991.3 Gins1 178.7 274.8 1316.4 CEM 1 + Lig1 622.9 792.0 3335.5 Top 10 Genes Mcm6 375.8 852.8 4338.3 Mcm2 323.1 516.7 4646.3 Tipin 705.6 999.3 3063.5 Tk1 80.1 110.1 1704.7

Null module GEO Series "GSE21393" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21393 Status: Public on Dec 31 2010 Title: Stroke-brain infiltrating stem cells - mouse Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Genes upregulated in stroke infiltrating stem cells were compared against the parent non-infiltrated mouse stem cell line derived from immortomouseTM.

Abstract

Background and Purpose- Although the therapeutic potential of bone marrow-derived stem cells (SC) has been addressed in different experimental models of ischemic stroke, it is still unclear how SC induce neuroprotection following stroke. In this study, we describe a novel method for recovering SC infiltrating post-stroke brain tissue allowing the determination of genes which become persistently activated / or depressed (compared to their naÃ¯ve counterparts) during SC-mediated neuroprotection.

Methods- Ischemic stroke was induced in C57BL/6 mice by middle cerebral artery occlusion for 1 h, followed by reperfusion. SC were isolated from H-2Kb-tsA58 (immortomouseTM) mice, and were administered (i.v.) 24 h after reperfusion. At the onset of therapeutic improvement (14 days after ischemia), infarcted brain tissue was isolated and infarct-infiltratng SC cultured at 33´C. Microarray analysis and RT-PCR were performed to compare persistent differential gene expression between naÃ¯ve and infiltrating SC populations.

Results- Z-scoring revealed dramatic changes in extracellular genes of analyzed cells. Pair-wise analysis detected 80 extracellular factor genes that were up-regulated ( 2 fold, P<0.05, Benjamini-Hochberg correction) between naÃ¯ve and infiltrated SC. Although several conventional neuroregenerative, nerve guidance and angiogenic factors (bFGF, bone morphogenetic protein, angiopoietins, neural growth factors were among the expressed genes detected we identified Cytokine receptor-like factor 1 (Crlf1), Fgf7, family with sequence similarity 19, member A5 (Fam19a5), Glypican 1 (Gpc1), Dickkopf homolog 2 (Dkk2), Endothelial cell-specific molecule 1, Osteopontin (OPN)35, Tissue factor pathway inhibitor 2, Masp3 mRNA for MBL-associated serine protease-3, Glial cell line derived neurotrophic factor (Gdnf), Bone morphogenetic protein 2 (Bmp2), Olfactomedin 1, Sushi-repeat-containing protein, X-linked 2 (Srpx2).

Conclusions- SC infiltrating the post-i schemic brain assume a persistently altered pattern of expressed extracellular genes compared to naÃ¯ve SC that contributes to neuroprotection, regeneration and angiogenesis in infarcts.

Keywords: Gene activation / suppression study

Overall design: Comparison of persistent stem cell gene expression induced by stroke-infarct infiltration

Background corr dist: KL-Divergence = 0.0364, L1-Distance = 0.0406, L2-Distance = 0.0024, Normal std = 0.6612

0.618 Kernel fit Pairwise Correlations Normal fit

Density 0.309

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Parent Line_1Stroke (0.154763)Infiltrated_2Parent Line_3Stroke (0.169437) (0.216911)Infiltrated_4Parent Line_5Stroke (0.153913) (0.140489)Infiltrated_6 (0.164487)[ min ] [ medium ] [ max ] CEM 1 Rfc5 263.0 1766.3 2154.0 P ( S | Z, I ) = 1.00 Rfc4 353.1 2799.1 3464.5 Mean Corr = 0.95975 Rfc3 108.9 1124.7 1269.6 Pcna 4564.0 14806.9 19165.0 Rfc2 512.0 1152.6 1595.0 Chtf18 3.6 286.7 306.5 Prim1 254.3 3950.7 4951.1 Mcm5 90.1 3012.8 4451.7 Rad51 168.1 1569.1 2587.7 Mcm7 360.8 4174.2 5888.2 Gins1 64.7 542.4 718.3 CEM 1 + Lig1 136.5 1693.0 1924.3 Top 10 Genes Mcm6 1134.6 6279.0 9287.7 Mcm2 178.7 3244.1 7257.0 Tipin 1779.2 5362.3 6961.8 Tk1 89.9 1334.4 2809.3

Null module GEO Series "GSE21379" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 10 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21379 Status: Public on Apr 20 2010 Title: Expression Data from WT and Sh2d1a-/- in vivo follicular helper CD4 T cells (TFH) versus non follicular helper CD4 T cells (non-TFH) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20525889 Summary & Design: Summary: CD4 T cell help is critical for both the generation and maintenance of germinal centers, and T follicular helper (TFH) cells are the CD4 T cell subset required for this process. SAP (SH2D1A) expression in CD4 T cells is essential for germinal center development. However, SAP-deficient mice have only a moderate defect in TFH differentiation as defined by common TFH surface markers. CXCR5+ TFH cells are found within the germinal center as well as along the boundary regions of T/B cell zones. Here we show that germinal center associated T cells (GC TFH) can be identified by their co-expression of CXCR5 and the GL7 epitope, allowing for phenotypic and functional analysis of TFH and GC TFH populations. Here we show GC TFH are a functionally discrete subset of further polarized TFH cells, with enhanced B cell help capacity and a specialized ability to produce IL-4 in a TH2-independent manner. Strikingly, SAP-deficient mice have an absence of the GC TFH subset and SAP- TFH are defective in IL-4 and IL-21 production. We further demonstrate that SLAM (Slamf1, CD150), a surface receptor that utilizes SAP signaling, is specifically required for IL-4 production by GC TFH. GC TFH cells require IL-4 and IL-21 production for optimal help to B cells. These data illustrate complexities of SAP-dependent SLAM family receptor signaling, revealing a prominent role for SLAM receptor ligation in IL-4 production by germinal center CD4 T cells but not in TFH and GC TFH differentiation.

Overall design: Analysis of in vivo antigen-specific (LCMV-specific, SMARTA TCR transgenic) WT and Sh2d1a-/- follicular helper CD4 T cells (CXCR5high),versus non-follicular helper CD4 T cells (CXCR5low), eight days after viral infection.

Background corr dist: KL-Divergence = 0.0691, L1-Distance = 0.0416, L2-Distance = 0.0025, Normal std = 0.5262

0.800 Kernel fit Pairwise Correlations Normal fit

Density 0.400

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

NaÃ¯ve CXCR5_Negative_Rep1(0.135998)CXCR5_Positive_Rep1CXCR5_Negative_Rep2CXCR5_Positive_Rep2 (0.151515)SAPKO (0.0328923)SAPKO_CXCR5_Negative_Rep1 NaÃ¯ve (0.175633)SAPKO_CXCR5_Positive_Rep1 (0.161414)(0.0347442)SAPKO_CXCR5_Negative_Rep2SAPKO_CXCR5_Positive_Rep2 (0.182168) (0.0228447) (0.0614565)[ (0.0413341)min ] [ medium ] [ max ] CEM 1 Rfc5 434.2 832.2 1659.3 P ( S | Z, I ) = 1.00 Rfc4 490.7 948.7 2064.7 Mean Corr = 0.95941 Rfc3 236.0 459.2 1003.8 Pcna 5437.7 7622.6 11432.9 Rfc2 1461.5 1981.3 2652.5 Chtf18 87.7 226.8 534.9 Prim1 790.3 1364.9 3532.6 Mcm5 375.8 966.8 2781.2 Rad51 21.5 296.2 951.8 Mcm7 781.5 956.6 2359.0 Gins1 182.1 625.4 2339.1 CEM 1 + Lig1 297.8 789.6 2005.4 Top 10 Genes Mcm6 1237.2 4067.6 5905.1 Mcm2 656.8 780.5 1821.3 Tipin 805.8 1228.9 2324.4 Tk1 36.5 1412.2 3798.7

Null module GEO Series "GSE12465" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 14 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12465 Status: Public on May 20 2009 Title: Transcriptional signatures of Itk-deficiency using CD3+, CD4+ and CD8+ T-cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19450280 Summary & Design: Summary: The Tec-family kinase Itk plays an important role during T-cell activation and function, and controls also conventional versus innate-like T-cell development. We have characterized the transcriptome of Itk-deficient CD3+ T-cells, including CD4+ and CD8+ subsets, using Affymetrix microarrays. The largest difference between Itk-/- and Wt CD3+ T-cells was found in unstimulated cells, e.g. for killer cell lectin-like receptors. Compared to anti-CD3-stimulation, anti-CD3/CD28 significantly decreased the number of transcripts suggesting that the CD28 co-stimulatory pathway is mainly independent of Itk. The signatures of CD4+ and CD8+ T-cell subsets identified a greater differential expression than in total CD3+ cells. Cyclosporin (CsA)-treatment had a stronger effect on transcriptional regulation than Itk-deficiency, suggesting that only a fraction of TCR-mediated calcineurin/NFAT-activation is dependent on Itk. Bioinformatic analysis of NFAT-sites of the group of transcripts similarly regulated by Itk-deficiency and CsA-treatment, followed by chromatin-immunoprecipitation, revealed NFATc1-binding to the Bub1, IL7R, Ctla2a, Ctla2b, and Schlafen1 genes. Finally, to identify transcripts that are regulated by Tec-family kinases in general, we compared the expression profile of Itk-deficient T-cells with that of Btk-deficient B-cells and a common set of transcripts was found. Taken together, our study provides a general overview about the global transcriptional changes in the absence of Itk.

Overall design: CD3+ CD4+ and CD8+ T-cells from pooled suspensions of spleen and lymph nodes of Wt and Itk knockout mice on C57BL/6 background were isolated after negative depletion. Unstimulated as well as stimulated T-cells were studied. Stimulations were done with anti-CD3 (1 mg/ml) for 24 hrs. For the CD4+ T-cells we collected triplicates from the Itk knockout mice and duplicates from the Wt group. For the CD8+ T-cells, we got duplicates from Itk knockout , while we obtained a single sample from Wt owing to the low cell yield for resting Wt CD8+ T-cells. After CD3-stimulation we got a single sample from the CD8+ subset of both Wt and Itk knockout, while for the CD4+ subsets we collected duplicates.

Background corr dist: KL-Divergence = 0.0403, L1-Distance = 0.0459, L2-Distance = 0.0032, Normal std = 0.6284

0.635 Kernel fit Pairwise Correlations Normal fit

Density 0.317

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Wild typeWild CD4+ typeItk unstimulated CD4+knockoutItk unstimulated knockout CD4+ 1Itk (0.059711) knockout unstimulated CD4+ 2Wild (0.0420172) unstimulated typeCD4+Itk CD8+1knockout unstimulated(0.0413795)Itk unstimulated 2knockout (0.0418571) CD8+Wild 3 unstimulated (0.0465383) typeCD8+ (0.031057)Wild CD4+ unstimulated typeItk CD3-stimulated CD4+1knockout (0.0447417)Itk CD3-stimulated 2knockout (0.0362762) CD4+Wild 1 (0.220841)CD3-stimulated typeCD4+Itk 2 CD8+knockout (0.150731)CD3-stimulated CD3-stimulated 1CD8+ (0.023575) CD3-stimulated 2 (0.0308306) (0.226276)[ min (0.00416827) ] [ medium ] [ max ] CEM 1 Rfc5 491.9 943.5 3128.4 P ( S | Z, I ) = 1.00 Rfc4 408.3 638.9 2576.0 Mean Corr = 0.95900 Rfc3 107.4 179.5 725.6 Pcna 5092.2 8564.0 16043.6 Rfc2 1636.4 2162.0 4132.7 Chtf18 129.8 215.0 674.9 Prim1 491.2 945.4 4370.6 Mcm5 230.2 453.7 2621.3 Rad51 65.6 578.8 4241.1 Mcm7 361.6 825.8 4229.5 Gins1 151.3 288.4 2011.4 CEM 1 + Lig1 611.3 1347.3 6220.1 Top 10 Genes Mcm6 1688.8 3580.5 9564.8 Mcm2 687.6 1088.2 5381.5 Tipin 710.5 1431.9 6243.1 Tk1 314.5 476.7 1492.8

Null module GEO Series "GSE13302" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 30 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13302 Status: Public on May 12 2009 Title: Gene expression profiling in the lung and liver of Perfluorooctane sulfonate (PFOS) exposed mouse fetuses Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19429403 Summary & Design: Summary: Most of the transcriptional changes induced by PFOS in the fetal mouse liver and lung were related to activation of PPARalpha. When compared to the transcript profiles induced by PFOA (Pubmed ID 17681415), few remarkable differences were found other than up-regulation of Cyp3a genes. Because PFOS and PFOA have been shown to differ in their mode of action in the murine neonate, these data suggest that changes related to PFOS-induced neonatal toxicity may not be evident in the fetal transcriptome at term.

Overall design: Thirty timed-pregnant CD-1 mice were orally dosed from gestation day 1-17 with either 0, 5, or 10 mg/kg/day PFOS in 0.5% Tween 20. At term, fetal lung and liver were collected, total RNA prepared, and samples pooled from three fetuses per litter. Five biological replicates consisting of individual litter samples were then evaluated for each treatment group using Affymetrix mouse 430_2 microarrays.

Background corr dist: KL-Divergence = 0.0214, L1-Distance = 0.0694, L2-Distance = 0.0077, Normal std = 0.8465

0.471 Kernel fit Pairwise Correlations Normal fit

Density 0.236

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

0mg/kg/day0mg/kg/day PFOS,0mg/kg/day lungPFOS,0mg/kg/day rep1 liverPFOS, (0.0389579)0mg/kg/day rep1 lungPFOS, (0.0877436)0mg/kg/day rep2 liverPFOS, (0.0183164)0mg/kg/day rep2 lungPFOS, (0.0677765)0mg/kg/day rep3 liverPFOS, (0.042123)0mg/kg/day rep3 lungPFOS, (0.0180311)0mg/kg/day rep4 liverPFOS, (0.0288711)5mg/kg/day rep4 lungPFOS, (0.0586073)5mg/kg/day rep5 liverPFOS, (0.0381499)5mg/kg/day rep5 lungPFOS, (0.0552698)5mg/kg/day rep1 liverPFOS, (0.0353653)5mg/kg/day rep1 lungPFOS, (0.00686915)5mg/kg/day rep2 liverPFOS, (0.0377341)5mg/kg/day rep2 lungPFOS, (0.0325126)5mg/kg/day rep3 liverPFOS, (0.0432476)5mg/kg/day rep3 lungPFOS, (0.0365008)5mg/kg/day rep4 liverPFOS, (0.0197172)10mg/kg/day rep4 lungPFOS, (0.0284647)10mg/kg/day rep5 liver PFOS, (0.0443098)10mg/kg/day rep5 lungPFOS, (0.0225548)10mg/kg/day rep1 liverPFOS, 10mg/kg/day(0.0299648) rep1 lungPFOS, 10mg/kg/day(0.0216999) rep2 liverPFOS, 10mg/kg/day(0.0157296) rep2 lungPFOS, 10mg/kg/day(0.0401463) rep3 liverPFOS, 10mg/kg/day(0.0212281) rep3 lungPFOS, 10mg/kg/day(0.0152785) rep4 liverPFOS, (0.044341) rep4 lungPFOS, (0.0186064) rep5 liver (0.0172446) rep5 [(0.014638) min ] [ medium ] [ max ] CEM 1 Rfc5 296.0 709.7 957.0 P ( S | Z, I ) = 1.00 Rfc4 380.7 1410.4 2198.1 Mean Corr = 0.95879 Rfc3 209.7 418.7 613.3 Pcna 5092.2 13684.6 20345.3 Rfc2 702.9 953.3 1194.1 Chtf18 47.7 135.3 213.2 Prim1 313.4 1540.5 2117.4 Mcm5 222.1 1454.5 2362.7 Rad51 123.7 670.2 1013.9 Mcm7 658.7 2865.9 4292.1 Gins1 159.9 833.4 1132.2 CEM 1 + Lig1 521.6 1577.4 2231.4 Top 10 Genes Mcm6 1461.6 4942.0 7056.6 Mcm2 333.1 1781.5 2845.0 Tipin 816.2 2397.2 3630.8 Tk1 235.8 1333.6 2217.5

Null module GEO Series "GSE48204" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48204 Status: Public on Jul 26 2013 Title: Gene expression in epithelial, EMT (epithelial-mesenchymal transition) and MET (mesenchymal-epithelial transition) cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23878399 Summary & Design: Summary: NMuMG is an epithelial cell line that can be induced into EMT by TGF-Î² treatment or MET by TGF-Î² withdrawl. During EMT, several marker genes were downregulated/upregulated, which is consistent with its mesenchymal phenotype.

Transcription factors that are regulated during EMT and its reverse process MET are candidate genes for the regulations of the EMT marker genes.

Overall design: NMuMG cells treated with vehicle, TGF-Î² for 11 days, or 11days of TGF-Î² treatment followed by TGF-Î² withdrawl for another 13 days. RNA from these 3 conditions of NMuMG were extracted and subject to microarray analysis

Background corr dist: KL-Divergence = 0.0249, L1-Distance = 0.0454, L2-Distance = 0.0022, Normal std = 0.8085

0.537 Kernel fit Pairwise Correlations Normal fit

Density 0.269

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

ControlControl NMuMGNMuMG NMuMG cells, NMuMGreplicate cells cells, treated NMuMGreplicate cells 1 (0.212367) treatedbyNMuMG cells 211 (0.243274) days treatedby cells 11 with days treatedby 4ng/ml 11 with days by TGF-Î²,4ng/ml 11 with days [ TGF-Î²,4ng/mlfollowed minwith TGF-Î²,4ng/mlfollowed by ] TGF-Î² TGF-Î²,replicate by withdrawlTGF-Î² replicate 1[ (0.0127469) withdrawlmedium for 2 another(0.0120364) for another 13 days,] 13 replicate days, replicate[ 1 max(0.263911) 2 (0.255665) ] CEM 1 Rfc5 625.7 1320.1 2424.2 P ( S | Z, I ) = 1.00 Rfc4 608.5 936.6 1610.9 Mean Corr = 0.95719 Rfc3 491.3 949.9 1067.5 Pcna 9214.4 15516.1 19319.8 Rfc2 890.5 1386.3 1762.3 Chtf18 102.5 233.7 297.2 Prim1 1146.4 2457.4 3816.7 Mcm5 504.5 1398.7 1939.3 Rad51 602.8 1572.0 2462.8 Mcm7 2128.6 3111.8 5337.3 Gins1 463.5 1156.9 1850.5 CEM 1 + Lig1 967.0 1485.9 2291.0 Top 10 Genes Mcm6 1851.8 2987.5 3638.8 Mcm2 943.6 2077.7 2481.9 Tipin 1079.6 2583.8 3962.5 Tk1 1036.5 2860.4 4300.8

Null module GEO Series "GSE17794" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 44 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17794 Status: Public on Jan 11 2010 Title: Expression data from B6C3F1 mice treated with 2-butoxyethanol Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19812364 Summary & Design: Summary: Mice were dosed with 2-BE (900mg/kg) or vehicle by oral gavage and sacrificied either after 4 hours of a single dose or after 7 days of daily dosing.

Overall design: Mice were euthanased by cervical dislocation under ketamine / acepromazine (100 mg/kg / 5 mg/kg, I.P) anesthesia. The bone marrow from the right humerus, a portion of the left lateral liver lobe and half a cross-section of the spleen were harvested and the RNA was isolated from these tissues using standard Qiagen reagents. Standard Affymetrix protocols were used for GeneChip probe preparations. 44 arrays.

Background corr dist: KL-Divergence = 0.0249, L1-Distance = 0.0283, L2-Distance = 0.0013, Normal std = 0.6953

0.574 Kernel fit Pairwise Correlations Normal fit

Density 0.287

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

liver-vehicle-4hours-repliver-vehicle-4hours-repliver-vehicle-4hours-repliver-2BE-4hours-rep 1 (0.0253834)liver-2BE-4hours-rep 2 (0.0262965)liver-2BE-4hours-rep 3 (0.0258033) 1liver-2BE-4hours-rep (0.0264411) 2spleen-vehicle-4hours-rep (0.0277187) 3spleen-vehicle-4hours-rep (0.0282689) 4spleen-vehicle-4hours-rep (0.0276628)spleen-vehicle-4hours-rep 1 (0.00142638)spleen-2BE-4hours-rep 2 (0.00367518)spleen-2BE-4hours-rep 3 (0.00426209)spleen-2BE-4hours-rep 4 (0.00361034)spleen-2BE-4hours-rep 1 (0.000914416)liver-vehicle-7days-rep 2 (0.00520203)liver-vehicle-7days-rep 3 (0.00258408)liver-vehicle-7days-rep 4 (0.00273427)liver-vehicle-7days-rep 1 (0.0247039)liver-2BE-7days-rep 2 (0.0238925)liver-2BE-7days-rep 3 (0.0261167)liver-2BE-7days-rep 4 (0.0241602) 1 (0.0232384)liver-2BE-7days-rep 2 (0.024136)liver-2BE-7days-rep 3 (0.0240099)bone 4marrow-vehicle-7days-rep (0.0248603)bone 5marrow-vehicle-7days-rep (0.0225002)bone marrow-vehicle-7days-repbone marrow-vehicle-7days-repbone 1 (0.0180128) marrow-vehicle-7days-repbone 2 (0.0295345) marrow-2BE-7days-repbone 3 (0.0275606) marrow-2BE-7days-repbone 4 (0.0285829) marrow-2BE-7days-repbone 5 (0.0261353) marrow-2BE-7days-rep 1bone (0.049147) marrow-2BE-7days-rep 2spleen-vehicle-7days-rep (0.0398273) 3spleen-vehicle-7days-rep (0.0499938) 4spleen-vehicle-7days-rep (0.0488237) 5spleen-vehicle-7days-rep (0.043552) 1 (0.00709076)spleen-vehicle-7days-rep 2 (0.00356604)spleen-2BE-7days-rep 3 (0.00483985)spleen-2BE-7days-rep 4 (0.00317089)spleen-2BE-7days-rep 5 (0.00378361) spleen-2BE-7days-rep1 (0.056215) spleen-2BE-7days-rep2 (0.0409299) 3 (0.0190743) 4 (0.0477012) 5 (0.0228567)[ min ] [ medium ] [ max ] CEM 1 Rfc5 279.6 853.2 2224.8 P ( S | Z, I ) = 1.00 Rfc4 81.5 705.5 3375.8 Mean Corr = 0.95557 Rfc3 107.2 403.0 1111.7 Pcna 1799.0 12440.4 32576.0 Rfc2 487.2 1938.0 2928.1 Chtf18 43.4 158.3 577.5 Prim1 165.6 1127.2 3862.0 Mcm5 41.0 1691.9 6555.7 Rad51 33.2 493.5 1929.3 Mcm7 439.6 3085.1 10842.0 Gins1 128.9 336.6 1374.9 CEM 1 + Lig1 178.8 2012.6 6524.3 Top 10 Genes Mcm6 215.6 3736.0 10552.8 Mcm2 84.4 1451.5 5936.9 Tipin 311.5 1864.2 6033.8 Tk1 307.4 1235.5 5118.1

Null module GEO Series "GSE57543" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE57543 Status: Public on May 13 2014 Title: Expression data from B6 mouse miR-142 KO and WT T cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: T cells are critical for modulating immune responses. miRNAs are small, noncoding RNAs and play a significant role in T cell responses. miR-142 is a hematopoietic specific miRNA. To explore the potential role of miR-142 in regulating T cell responses, we generated mutant mice bearing a targeted deletion of the miR-142 gene.

We used microarrays to detail the global programme of gene expression underlying the profile changes between miR-142 KO and WT T cell and identified distinct classes of up-regulated genes during this process.

Overall design: miR-142 KO mice and WT littermates (biological triplicates) matched with age and sex were selected. T cells were purified from spleens by negative selection and processed for RNA isolation and hybridization on Affymetrix microarrays.

Background corr dist: KL-Divergence = 0.0094, L1-Distance = 0.0206, L2-Distance = 0.0006, Normal std = 0.8842

0.451 Kernel fit Pairwise Correlations Normal fit

Density 0.226

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

WT biologicalWT biological repWT 1 biological (0.16943) repKO 2biological (0.14066) repKO 3biological (0.143031) repKO 1 biological (0.0886778) rep 2 (0.364573) rep 3 (0.0936281)[ min ] [ medium ] [ max ] CEM 1 Rfc5 1176.2 2578.1 3371.4 P ( S | Z, I ) = 1.00 Rfc4 1084.3 2691.5 4168.1 Mean Corr = 0.95462 Rfc3 376.7 852.2 1199.2 Pcna 11502.2 15408.4 18458.3 Rfc2 1639.4 2824.9 3154.8 Chtf18 92.9 270.8 370.1 Prim1 1507.3 3615.5 4777.9 Mcm5 803.5 2997.0 4455.2 Rad51 406.6 1415.6 1848.0 Mcm7 1930.7 5702.2 6959.9 Gins1 455.4 2097.7 3065.2 CEM 1 + Lig1 1840.2 4999.9 6175.1 Top 10 Genes Mcm6 5308.8 11048.0 13561.7 Mcm2 787.5 2304.3 3187.3 Tipin 2714.2 5973.8 7926.5 Tk1 521.3 2758.9 4020.4

Null module GEO Series "GSE51628" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 15 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51628 Status: Public on Oct 24 2013 Title: Effects of acute Notch activation on the mammary epithelial compartment in vivo Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Notch signaling is widely implicated in mouse mammary gland development and tumorigenesis. To investigate the effects of acute activation of Notch signaling in the mammary epithelial compartment, we generated bi-transgenic MMTV-rtTA; TetO-NICD1 (MTB/TICNX) mice that conditionally express a constitutively active NOTCH1 intracellular domain (NICD1) construct in the mammary epithelium upon doxycycline administration.

Overall design: Two timepoints (48h and 96h) of doxycycline induction in TetO-NICD1 (TICNX; control) and MMTV-rtTA; TetO-NICD1 (MTB/TICNX) mice with 3-4 replicates per timepoint

Background corr dist: KL-Divergence = 0.0788, L1-Distance = 0.0320, L2-Distance = 0.0014, Normal std = 0.4893

0.843 Kernel fit Pairwise Correlations Normal fit

Density 0.422

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

TICNX_48h_rep1TICNX_48h_rep2TICNX_48h_rep3 (0.0736607)TICNX_48h_rep4 (0.0668844)TICNX_96h_rep1 (0.0709787)TICNX_96h_rep2 (0.0485201)TICNX_96h_rep3 (0.0676575)MTB/TICNX_48h_rep1 (0.00768957)MTB/TICNX_48h_rep2 (0.0177001)MTB/TICNX_48h_rep3 MTB/TICNX_48h_rep4(0.00713208) MTB/TICNX_96h_rep1(0.0455494) MTB/TICNX_96h_rep2(0.00539712) MTB/TICNX_96h_rep3(0.0115522) MTB/TICNX_96h_rep4(0.0215686) (0.141348) (0.173568) (0.240793)[ min ] [ medium ] [ max ] CEM 1 Rfc5 243.8 544.8 1323.4 P ( S | Z, I ) = 1.00 Rfc4 192.9 463.9 1156.4 Mean Corr = 0.95377 Rfc3 157.4 241.5 577.0 Pcna 3245.5 5986.0 10820.8 Rfc2 647.7 827.4 1336.4 Chtf18 38.1 60.2 132.8 Prim1 237.9 689.0 2274.0 Mcm5 55.8 355.0 999.5 Rad51 82.2 373.6 1103.5 Mcm7 290.7 824.8 2454.6 Gins1 199.9 330.5 866.4 CEM 1 + Lig1 297.4 928.7 2938.2 Top 10 Genes Mcm6 250.8 1421.2 4211.7 Mcm2 162.3 575.9 1851.7 Tipin 426.6 774.7 1543.0 Tk1 69.2 288.9 837.9

Null module GEO Series "GSE21900" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE21900 Status: Public on May 18 2011 Title: Expression profiling of the Otx2 CKO retina Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21602925 Summary & Design: Summary: In the vertebrate retina, the Otx2 transcription factor plays a crucial role in the cell fate determination of both rod and cone photoreceptors. Otx2 conditional knockout (CKO) mice exhibited a total absence of rods and cones in the retina due to their cell fate conversion to amacrine-like cells. In order to investigate the entire transcriptome regulated by Otx2 in the developing retina, we performed microarray analysis on the Otx2 CKO retina.

Overall design: In order to clarify the molecular role of Otx2 in transcriptional regulation during development, we investigated the expression profile of the Otx2 CKO retina compared with that of the control retina with the genotype Otx2flox/flox;Crx-cre- using microarrays at two time points, P1 and P12.

Background corr dist: KL-Divergence = 0.0680, L1-Distance = 0.0265, L2-Distance = 0.0012, Normal std = 0.5091

0.784 Kernel fit Pairwise Correlations Normal fit

Density 0.392

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

P1-control-ex1P1-control-ex2 P1-control-ex3(0.0929644) P1-Otx2-CKO-ex1(0.103324) P1-Otx2-CKO-ex2(0.0498377)P1-Otx2-CKO-ex3 (0.0479555)P12-control-ex1 (0.141438)P12-control-ex2 (0.0771268)P12-control-ex3 (0.108757)P12-Otx2-CKO-ex1 (0.0676259)P12-Otx2-CKO-ex2 (0.0880566)P12-Otx2-CKO-ex3 (0.0982356) (0.0520789) (0.0726003)[ min ] [ medium ] [ max ] CEM 1 Rfc5 282.9 1548.8 2185.5 P ( S | Z, I ) = 1.00 Rfc4 199.7 2001.7 2475.0 Mean Corr = 0.95343 Rfc3 206.4 1121.8 1342.2 Pcna 3929.3 22053.4 27193.5 Rfc2 868.0 1618.4 2718.2 Chtf18 6.7 241.5 284.1 Prim1 341.5 2586.9 3562.0 Mcm5 66.9 1915.7 3020.9 Rad51 120.3 929.4 1526.8 Mcm7 484.4 5892.7 8500.1 Gins1 17.1 1434.2 2094.5 CEM 1 + Lig1 399.3 2458.0 3180.1 Top 10 Genes Mcm6 144.2 5832.9 7744.4 Mcm2 163.9 2755.4 4195.7 Tipin 529.3 3792.6 6542.0 Tk1 5.4 1243.0 1880.5

Null module GEO Series "GSE28093" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28093 Status: Public on Jun 01 2011 Title: Expression profile of OPC senescence Organism: Mus musculus Experiment type: SNP genotyping by SNP array Platform: GPL1261 Pubmed ID: 20404145 Summary & Design: Summary: To identify factors involved in OPC senescence, we compared gene expressions between OPC-CG4, OPC-FCS and OPC-Rev.

Overall design: We established OPC senescence model system, in which OPC become senescent in the presence of high concentration of FCS. This phenotypes were kept even when the medium was switched to their optimal serum-free medium.

Background corr dist: KL-Divergence = 0.0321, L1-Distance = 0.0147, L2-Distance = 0.0002, Normal std = 0.6545

0.611 Kernel fit Pairwise Correlations Normal fit

Density 0.306

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

OPC-CG4_1OPC-CG4_2 (0.170671)OPC-FCS_1 (0.177274)OPC-FCS_2 (0.217506)OPC-Rev_1 (0.161866)OPC-Rev_2 (0.157534) (0.115149) [ min ] [ medium ] [ max ] CEM 1 Rfc5 264.7 980.6 1110.1 P ( S | Z, I ) = 1.00 Rfc4 136.3 560.0 701.8 Mean Corr = 0.95263 Rfc3 131.0 356.6 462.5 Pcna 4121.6 9177.0 10240.8 Rfc2 534.2 941.6 1062.7 Chtf18 43.8 112.3 134.0 Prim1 402.7 1623.8 1840.7 Mcm5 175.8 1733.8 2134.5 Rad51 183.2 801.5 1099.9 Mcm7 555.6 2979.1 3227.6 Gins1 90.6 494.2 660.5 CEM 1 + Lig1 365.8 1571.1 1739.8 Top 10 Genes Mcm6 713.8 2875.9 3431.4 Mcm2 284.5 1762.7 1951.4 Tipin 588.9 1021.1 1130.6 Tk1 133.8 867.2 1344.9

Null module GEO Series "GSE38257" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 14 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38257 Status: Public on Dec 21 2012 Title: A Novel Tumor suppressor network in squamous malignancies Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23145321 Summary & Design: Summary: The specific ablation of Rb1 gene in stratified epithelia (RbF/F;K14cre) promotes proliferation and altered differentiation but is insufficient to produce spontaneous tumors. The pRb relative, p107, compensates some of the functions of pRb in these tissues, however RbF/F;K14cre;p107-/- mice die postnatally. Acute pRb loss in stratified epithelia, using an inducible mouse model (RbF/F;K14creERTM), shows that p107 exerts specific tumor suppressor functions in its absence. After simultaneous absence of pRb and p107, p53 transcriptional function is impaired and Pten expression is reduced. All mutant mice develop spontaneous squamous tumors carcinomas rapidly. Gene expression analysis of mouse tumors, besides supporting the impaired p53 function and the susceptibility to Akt/mTOR inhibitors, also revealed significant overlap with human squamous carcinomas. Thus, RbF/F;K14creERTM;p107-/- may constitute a new mouse model for these malignancies. Collectively, these data demonstrate the existence of a previously unreported functional connection between pRb, Pten and p53 tumor suppressors, through p107, of a particular relevance in squamous tumor development.

Overall design: Gene expression was compared between normal mouse skin and carcinomas arising in the skin of RbF/F;K14creERTM;p107-/- mouse. All mice were treated with tamoxifen.

Background corr dist: KL-Divergence = 0.0326, L1-Distance = 0.0283, L2-Distance = 0.0009, Normal std = 0.6484

0.639 Kernel fit Pairwise Correlations Normal fit

Density 0.320

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Skin_Normal_1Skin_Normal_2Skin_Normal_3 (0.191273)Skin_Normal_4 (0.152294)Rb_p107_carcinoma_rep1 (0.172035)Rb_p107_carcinoma_rep2 (0.165324)Rb_p107_carcinoma_rep3Rb_p107_carcinoma_rep4 (0.0552141)Rb_p107_carcinoma_rep5 (0.0383501)Rb_p107_carcinoma_rep6 (0.00585131)Rb_p107_carcinoma_rep7 (0.0336527)Rb_p107_carcinoma_rep8 (0.048479)Rb_p107_carcinoma_rep9 (0.0301376)Rb_p107_carcinoma_rep10 (0.0179078) (0.0202196) (0.0425067) (0.0267553)[ min ] [ medium ] [ max ] CEM 1 Rfc5 227.6 1022.0 1328.8 P ( S | Z, I ) = 1.00 Rfc4 288.6 1785.9 2012.0 Mean Corr = 0.95008 Rfc3 160.4 1218.7 1468.4 Pcna 3751.1 24159.5 26267.0 Rfc2 541.5 1237.8 1406.4 Chtf18 39.7 127.7 151.3 Prim1 551.3 7653.9 8232.0 Mcm5 150.9 2959.7 3232.1 Rad51 111.9 1559.3 1817.6 Mcm7 513.3 2902.3 3360.4 Gins1 146.7 1992.9 2251.1 CEM 1 + Lig1 399.0 3322.0 3621.4 Top 10 Genes Mcm6 388.9 4633.5 5149.4 Mcm2 159.4 1677.4 1864.8 Tipin 813.3 3808.4 4233.8 Tk1 145.4 1283.5 1701.3

Null module GEO Series "GSE28457" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28457 Status: Public on May 31 2012 Title: Gene expression profile of E1A infected C2C12 myotubes Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23027903 Summary & Design: Summary: Proliferating C2C12 myoblasts were induced to differentiate into myotubes and then infected with adenovirus expressing E1A (Ad-E1A), which induces cell cycle re-entry and dedifferentiation.

We analyzed the transcriptional profile of E1A infected C2C12-myotubes through the Affymetrix Mouse Genome 430 2.0 Array, searching for genes that were significantly regulated between two independent biological replicates at two different time points (24h and 36h after infection with Ad-E1A). In addition, we took advantage of the E1A mutant known as YH47/dl928 (hereafter referred as YH47), which bears two mutations in the pocket-binding region of E1A (Y48H, C124G) able to disrupt the interaction with Rb and its cognate proteins and to impair cell-cycle re-entry phenotype. YH47 mutant was used to identify the Rb independent transcriptional reprogramming of C2C12.

Overall design: C2C12 cells were differentiated in vitro to myotubes as previously described. Myotubes were, then, infected with an adenovirus carrying the 12S form of E1A (dl520), with the YH47 E1A mutant (dl928) or with a control adenovirus (CTR) expressing a deletion of essentially the entire E1A gene (dl312). Two different time points after infection were considered (24 hours and 36 hours) to evaluate changes in C2C12 cells expression profile. Technical (A or B) and biological replicates (EXP1 or EXP2) were done for each condition.

Background corr dist: KL-Divergence = 0.1997, L1-Distance = 0.0314, L2-Distance = 0.0016, Normal std = 0.3411

1.170 Kernel fit Pairwise Correlations Normal fit

Density 0.585

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

C2C12, C2C12,dl312 infected, C2C12,dl312 infected, C2C12, dl31224h, biological infected, C2C12, dl31224h, biological infected, C2C12, dl520 36h,replicate biological infected, C2C12, dl520 36h,replicate 2, technicalbiological infected, C2C12, dl520 24h,replicate 1, technicalbiological infected, replicateC2C12, dl520 24h,replicate 2, technicalbiological infected, replicateC2C12, dl928 36h,replicate A 1, (0.0297354) technicalbiological infected, replicateC2C12, dl928 36h,replicate A 2, (0.0240242) technicalbiological infected, replicateC2C12, dl928 24h,replicate A 1, (0.0286049) technicalbiological infected, replicateC2C12, dl928 24h,replicate A 2, (0.0198591) technicalbiological infected, replicateC2C12, dl312 36h,replicate A 1, (0.0578909) technicalbiological infected, replicateC2C12, dl312 36h,replicate A 2, (0.00277736) technicalbiological infected, replicateC2C12, dl312 24h,replicate A 1, (0.121699) technicalbiological infected, replicateC2C12, dl312 24h,replicate A 2, (0.157014) technicalbiological infected, replicateC2C12, dl520 36h,replicate A 1, (0.0236471) technicalbiological infected, replicateC2C12, dl520 36h,replicate A 2, (0.0244916) technicalbiological infected, replicateC2C12, dl520 24h,replicate A 1, (0.00918453) technicalbiological infected, replicateC2C12, dl520 24h,replicate A 2, (0.00352292) technicalbiological infected, replicateC2C12, dl928 36h,replicate B 1, (0.0267307) technicalbiological infected, replicateC2C12, dl928 36h,replicate B 2, (0.0226777) technicalbiological infected, replicateC2C12, dl928 24h,replicate B 1, (0.0273498) technicalbiological infected, replicate dl928 24h,replicate B 2, (0.0198336) technicalbiological infected, replicate 36h,replicate B 1, (0.0677591) technicalbiological replicate 36h,replicate B 2, (0.0058506) technicalbiological replicate[ replicate B 1,min (0.130612) technical replicate replicate B 2, (0.130419) ]technical replicate B 1, (0.0297559) technical replicate B[ (0.0251969) medium replicate B (0.00897673) B (0.00238772) ] [ max ] CEM 1 Rfc5 64.0 587.1 4307.9 P ( S | Z, I ) = 1.00 Rfc4 199.9 373.7 2036.4 Mean Corr = 0.94935 Rfc3 220.3 351.4 1514.0 Pcna 3513.5 5730.6 18717.4 Rfc2 655.0 1539.5 3494.8 Chtf18 4.5 60.4 489.0 Prim1 276.1 1014.3 5160.3 Mcm5 79.7 834.3 4274.7 Rad51 45.4 485.6 4675.3 Mcm7 519.0 1410.7 7620.3 Gins1 27.8 194.8 1112.0 CEM 1 + Lig1 211.4 569.9 3244.0 Top 10 Genes Mcm6 258.1 1866.3 7467.4 Mcm2 350.4 1182.4 5147.8 Tipin 392.3 1089.0 3099.9 Tk1 6.1 528.9 3511.0

Null module GEO Series "GSE13225" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13225 Status: Public on Nov 30 2008 Title: (AKR/J x FVB/NJ)F1 versus (DBA/2J x FVB)F1 spleen expression data Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19118016 Summary & Design: Summary: F1 hybrids from (AKR/J x FVB/NJ) and (DBA/2J x FVB/NJ) outcrosses display a 20-fold difference in mammary tumor metastatic capacity, due to differences in inherited polymorphisms. Expression studies were performed to determine whether polymorphism-driven gene expression signatures predictive of outcome could be generated from normal tissues

Keywords: Basal transcription profiles

Overall design: Spleen from adult F1 animals from (AKR/J x FVB/NJ) and (DBA/2J x FVB/NJ) outcrosses was collected and arrayed on Affymetrics chip to identify basal differences in gene expression between the different genotypes

Background corr dist: KL-Divergence = 0.0222, L1-Distance = 0.0130, L2-Distance = 0.0002, Normal std = 0.7145

0.558 Kernel fit Pairwise Correlations Normal fit

Density 0.279

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

spleen akr1spleen (0.161203) akr2spleen (0.0385006) akr3spleen (0.192739) dba1spleen (0.018246) dba2spleen (0.232964) dba3 (0.356347) [ min ] [ medium ] [ max ] CEM 1 Rfc5 727.6 933.3 1342.5 P ( S | Z, I ) = 1.00 Rfc4 531.8 900.9 1641.7 Mean Corr = 0.94905 Rfc3 316.1 460.2 647.0 Pcna 10268.9 15081.3 25761.0 Rfc2 2507.7 2806.4 3064.3 Chtf18 106.1 167.4 226.8 Prim1 825.3 1107.0 2166.8 Mcm5 1251.8 1976.4 3552.4 Rad51 290.1 420.5 738.1 Mcm7 2613.2 3717.1 7417.4 Gins1 240.8 395.8 741.7 CEM 1 + Lig1 1085.7 1560.7 2926.9 Top 10 Genes Mcm6 1803.6 2622.2 5108.6 Mcm2 1075.8 1599.5 3126.2 Tipin 1439.0 1950.9 3287.3 Tk1 718.8 1335.6 2290.7

Null module GEO Series "GSE48397" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 10 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE48397 Status: Public on Jul 10 2013 Title: Expression data from (mouse) normal lung fibroblasts and carcinoma-associated fibroblasts Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22962265 Summary & Design: Summary: Cancer-associated fibroblasts (CAFs) have been reported to support tumor progression by a variety of mechanisms. However, their role in the progression of non-small cell lung cancer (NSCLC) remains poorly defined. In addition, the extent to which specific proteins secreted by CAFs contribute directly to tumor growth is unclear. To study the role of CAFs in NSCLC, a cross-species functional characterization of mouse and human lung CAFs was performed, including gene expression analysis comparing normal mouse lung fibroblasts (NFs) and mouse lung CAFs to seek for differentially-expressed secreted proteins.

Gene expression microarrays were used to identify transcriptomic changes between NFs and CAFs that may contribute to their different tumor-enhancing capacity.

Overall design: NFs and CAFs were grown in vitro for RNA extraction and hybridization on mouse 430_2 Affymetrix microarrays

Background corr dist: KL-Divergence = 0.0594, L1-Distance = 0.0233, L2-Distance = 0.0009, Normal std = 0.5290

0.754 Kernel fit Pairwise Correlations Normal fit

Density 0.377

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

lung fibroblasts,lung fibroblasts,lung biological fibroblasts,lung biological fibroblasts,replicatelung biological fibroblasts,replicate 1carcinoma-asssociated (0.071121) biological replicate 2carcinoma-asssociated (0.105095) biological replicate 3carcinoma-asssociated (0.385375) replicate 4carcinoma-asssociated (0.228166)fibroblasts, 5carcinoma-asssociated (0.0330466)fibroblasts, biological fibroblasts, biological fibroblasts,replicate biological fibroblasts,replicate 1 (0.0274794) biological[ replicate min2 (0.0142401) biological replicate 3 ](0.0886805) replicate 4 (0.0319725) [5 (0.014825)medium ] [ max ] CEM 1 Rfc5 132.1 555.6 2791.8 P ( S | Z, I ) = 1.00 Rfc4 144.5 342.9 2525.2 Mean Corr = 0.94878 Rfc3 215.8 611.1 1846.3 Pcna 3004.5 8406.9 14532.4 Rfc2 898.7 1279.9 3431.3 Chtf18 70.9 180.9 411.3 Prim1 88.5 600.1 2389.9 Mcm5 87.3 590.4 4008.0 Rad51 62.5 542.4 1576.8 Mcm7 368.3 1290.9 4563.6 Gins1 56.1 177.3 1034.0 CEM 1 + Lig1 319.4 691.4 2805.9 Top 10 Genes Mcm6 175.5 1211.5 3771.9 Mcm2 195.3 737.8 2190.4 Tipin 825.9 1753.5 4232.5 Tk1 87.5 754.7 4058.9

Null module GEO Series "GSE13693" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13693 Status: Public on Feb 06 2009 Title: Gene expression profiling of normal mouse myeloid cell populations Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19200802 Summary & Design: Summary: Normal myeloid lineage cell populations (C57BL/6 mice, aged 4-10 weeks, male or female) with three distinct immunophenotypes were prospectively isolated and characterized. In preparation for FACS sorting, bone marrow cells were separated into c-kit+ and c-kit- fractions using an AutoMACS device. C-kit+ cells were further fractionated based on Gr1 and Mac1 expression, and absence of lineage antigen expression (B220, TER119, CD3, CD4, CD8 and IL7RÎ±), by cell sorting. C-kit+ Gr1+ Mac1lo/- and c-kit+ Gr1+ Mac1+ displayed cytologic features of undifferentiated hematopoietic cells or myeloblasts, whereas c-kit- Gr1+ Mac1+ cells were mature neutrophils.

Overall design: See summary.

Background corr dist: KL-Divergence = 0.0176, L1-Distance = 0.0380, L2-Distance = 0.0018, Normal std = 0.8108

0.500 Kernel fit Pairwise Correlations Normal fit

Density 0.250

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

NORMALNORMAL BM NEUTROPHILS_2NORMAL BM NEUTROPHILS_1NORMAL BM NEUTROPHILS_3NORMAL (0.22157)MYELOBLASTS_CD117POS_GR1+_MAC1-_1NORMAL (0.195523)MYELOBLASTS_CD117POS_GR1+_MAC1-_2NORMAL (0.210592)MYELOBLASTS_CD117POS_GR1+_MAC1-_3NORMAL MYELOBLASTS_CD117POS_GR1+_MAC1+_2NORMAL MYELOBLASTS_CD117POS_GR1+_MAC1+_1 MYELOBLASTS_CD117POS_GR1+_MAC1+_3 (0.125702) (0.0462658)[ min(0.056655) (0.0387617)] (0.032879)[ (0.0720512) medium ] [ max ] CEM 1 Rfc5 182.1 4197.3 4899.1 P ( S | Z, I ) = 1.00 Rfc4 62.6 2140.8 2348.3 Mean Corr = 0.94805 Rfc3 9.7 501.4 916.5 Pcna 1118.3 13535.9 14762.2 Rfc2 3046.4 4744.7 5326.0 Chtf18 3.0 746.1 1030.5 Prim1 115.0 4364.5 5174.5 Mcm5 161.3 5570.7 6370.6 Rad51 3.6 2722.9 3084.5 Mcm7 104.7 6729.1 8532.0 Gins1 62.2 1582.3 2878.6 CEM 1 + Lig1 150.5 6902.7 7500.8 Top 10 Genes Mcm6 459.7 9748.4 11577.5 Mcm2 39.7 5076.8 5865.5 Tipin 79.9 4956.8 5881.4 Tk1 61.4 3707.3 4753.8

Null module GEO Series "GSE16073" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE16073 Status: Public on Oct 22 2009 Title: Expression Data from Pten Null Fibroblasts Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19847259 Summary & Design: Summary: The tumor stroma is believed to contribute to some of the most malignant characteristics of epithelial tumors. However, signaling between stromal and tumor cells is complex and remains poorly understood. Here we show that genetic inactivation of Pten in stromal fibroblasts of mouse mammary glands accelerated the initiation, progression and malignant transformation of mammary epithelial tumors.

Global gene expression profiling in mammary stromal cells identified a Pten-specific signature associated with massive extra-cellular matrix (ECM) remodeling, innate immune cell infiltraion and increased angiogenesis. Execution of this transcriptional program was mediated, in part, by the induction, phosphorylation and recruitment of Ets2 to target promoters. Remarkably, Ets2 inactivation in Pten stroma-deleted tumors was sufficient to decrease tumor growth and progression. These findings identify the Pten-Ets2 axis as a critical stroma-specific signaling pathway that suppresses mammary epithelial tumors.

Overall design: Wild type and Pten null primary mammary fibroblasts isolated from 8 week old female mice were cultured, RNA was extracted and Affymetrix gene expression arrays were performed.

Background corr dist: KL-Divergence = 0.0385, L1-Distance = 0.0292, L2-Distance = 0.0012, Normal std = 0.6328

0.639 Kernel fit Pairwise Correlations Normal fit

Density 0.320

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Pten nullPten fibroblasts, nullPten fibroblasts, null biologicalWild fibroblasts, type biologicalWild rep1fibroblasts, type biological(0.0530724)Wild rep2fibroblasts, type biological(0.0590352) rep3fibroblasts, biological(0.466057) rep1 biological(0.0394986) rep2 (0.199881)[ rep3min (0.182456) ] [ medium ] [ max ] CEM 1 Rfc5 491.1 812.2 1096.5 P ( S | Z, I ) = 1.00 Rfc4 340.7 593.4 789.4 Mean Corr = 0.94801 Rfc3 291.6 381.3 522.6 Pcna 8444.2 11559.4 13764.7 Rfc2 1098.4 1446.6 1799.9 Chtf18 28.6 41.4 50.8 Prim1 438.9 739.7 971.2 Mcm5 249.8 498.0 706.6 Rad51 501.4 682.1 1344.3 Mcm7 668.5 1180.3 1409.3 Gins1 123.1 225.2 260.2 CEM 1 + Lig1 464.9 780.9 1073.9 Top 10 Genes Mcm6 1113.4 2466.0 3157.8 Mcm2 365.4 665.1 924.6 Tipin 1494.8 1777.9 2121.2 Tk1 565.6 1161.6 1901.2

Null module GEO Series "GSE31313" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 22 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31313 Status: Public on Aug 08 2012 Title: Expression data from anti-EpCAM treated and untreated SP cells compared to lung tissue Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: Targeted therapies against cancer stem cells which are enriched in side populations (SP) involves interruption of Wnt-signalling. Furthermore, EpCAM is a SP marker and modulator of Wnt-signalling. Therefore, the effects of an anti-EpCAM treatment on SP-cells and WNT/Î²-catenin signalling was studied.

SP of the murine lung adenocarcinoma cell line A2C12 was obtained by fluorescence activated cell sorting and whole genome scans helped to define their molecular phenotype after anti-EpCAM antibody treatment.

Overall design: Anti-EpCAM treated and untreated A2C12 cells were subjected to Hoechst 33342 dye exclusion assay and sorted to SP fractions by FACS. Gene expression of SP cells was compared to non-transgenic lung tissue.

Background corr dist: KL-Divergence = 0.0208, L1-Distance = 0.0491, L2-Distance = 0.0029, Normal std = 0.7902

0.505 Kernel fit Pairwise Correlations Normal fit

Density 0.252

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

A2C12 SPA2C12 cells SPA2C12 biological cells SPA2C12 biological cells replicate anti-EpCAMA2C12 biological replicate 1 anti-EpCAM(0.062702)A2C12 replicate treated 2 anti-EpCAM(0.0974608)Male treatedSP lung,3 (0.166691)Male cells biological treatedSPlung, biologicalMale cells biological SPlung, biologicalreplicateMale cells replicate biological lung, biologicalreplicateMale 1 replicate (0.0203674) biological1 (0.153391)lung, replicateMale 2 replicate (0.0182484) biological2 (0.020945)lung, replicateMale 3 (0.014333) biological3 (0.248968)lung, replicateMale 4 (0.0144447) biological lung, replicateFemale 5 (0.0159684) biological replicate Female lung,6 (0.013101) biologicalreplicate Female lung,7 (0.0122962) biological Female lung,8 replicate (0.0190754) biological Femalelung, replicate 1 (0.0209524) biological Femalelung, replicate 2 (0.0183123) biological Femalelung, replicate 3 (0.020919) biological Femalelung, replicate 4 (0.0206238) biological lung, replicate 5 (0.00951984) biological replicate 6 (0.00894863) replicate 7 (0.0118067)[ min8 (0.0109245) ] [ medium ] [ max ] CEM 1 Rfc5 133.0 229.9 1839.3 P ( S | Z, I ) = 1.00 Rfc4 121.5 241.2 2933.5 Mean Corr = 0.94795 Rfc3 92.7 168.6 839.7 Pcna 4227.0 5412.7 15875.3 Rfc2 804.7 890.3 1698.5 Chtf18 2.3 33.7 288.8 Prim1 218.5 350.0 3800.5 Mcm5 178.0 252.1 2205.4 Rad51 24.4 63.4 2058.8 Mcm7 478.3 681.3 2772.1 Gins1 47.1 89.0 1365.5 CEM 1 + Lig1 270.0 373.6 2900.8 Top 10 Genes Mcm6 585.9 1020.9 4838.8 Mcm2 254.3 359.9 1622.6 Tipin 462.2 717.9 2939.8 Tk1 57.5 153.7 4861.3

Null module GEO Series "GSE33308" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 10 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE33308 Status: Public on Jan 01 2013 Title: Keratinocyte Growth Factor and Dexamethasone Plus Elevated cAMP Levels Synergistically Support Pluripotent Stem Cell Differentiation into Alveolar Epithelial Type II Cells. Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23176317 Summary & Design: Summary: Alveolar epithelial type II (ATII)-like cells can be generated from murine embryonic stem cells (ESCs), although to date, no robust protocols applying specific differentiation factors are established. We hypothesized that the keratinocyte growth factor (KGF), an important mediator of lung organogenesis and primary ATII cell maturation and proliferation, together with dexamethasone, 8-bromoadenosine-cAMP, and isobutylmethylxanthine (DCI), which induce maturation of primary fetal ATII cells, also support the alveolar differentiation of murine ESCs. Here we demonstrate that the above stimuli synergistically potentiate the alveolar differentiation of ESCs as indicated by increased expression of the surfactant proteins (SP-) C and SP-B. This effect is most profound if KGF is supplied not only in the late stage, but at least also during the intermediate stage of differentiation. Our results indicate that KGF most likely does not enhance the generation of (mes)endodermal or NK2 homeobox 1 (Nkx2.1) expressing progenitor cells but rather, supported by DCI, accelerates further differentiation/maturation of respiratory progeny in the intermediate phase and maturation/proliferation of emerging ATII cells in the late stage of differentiation. Ultrastructural analyses confirmed the presence of ATII-like cells with intracellular composite and lamellar bodies. Finally, induced pluripotent stem cells (iPSCs) were generated from transgenic mice with ATII cell-specific lacZ reporter expression. Again, KGF and DCI synergistically increased SP-C and SP-B expression in iPSC cultures, and lacZ expressing ATII-like cells developed. In conclusion, ATII cell-specific reporter expression enabled the first reliable proof for the generation of murine iPSC-derived ATII cells. In addition, we have shown KGF and DCI to synergistically support the generation of ATII-like cells from ESCs and iPSCs. Combined application of these factors will facilitate more efficient generation of stem cell-derived ATII cells for future basic research and potential therapeutic application.

Overall design: mESCs at d24 of differentiation with KGF and DCI treatment

Background corr dist: KL-Divergence = 0.0344, L1-Distance = 0.0193, L2-Distance = 0.0005, Normal std = 0.6401

0.623 Kernel fit Pairwise Correlations Normal fit

Density 0.312

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

mESCs mESCsat d8 of mESCsat differentiation d8 of mESCsat differentiation d17 of mESCs at(Control) differentiation d17 of mESCs atwith differentiation (0.247993)d17 KGF of mESCsat (Control)differentiation d17treatment of mESCsat withdifferentiation d24 (0.00888945) (0.36449) KGFof mESCsat withdifferentiation d24 treatment DCIof mESCsat withdifferentiation d24 treatment KGF(0.0093611)of at (Control)differentiation d24 and (0.000685457) of DCI withdifferentiation (0.0689641) treatment KGF with treatment DCI[ (0.00510092) withmin treatment KGF(0.0780542) and] (0.0954212) DCI treatment[ medium (0.121041) ] [ max ] CEM 1 Rfc5 438.0 894.1 1636.5 P ( S | Z, I ) = 1.00 Rfc4 560.6 1012.0 1943.2 Mean Corr = 0.94705 Rfc3 300.8 610.4 1162.7 Pcna 4726.0 9162.2 13198.2 Rfc2 765.1 1246.4 1893.6 Chtf18 53.5 120.2 347.1 Prim1 311.4 1266.2 2354.2 Mcm5 104.8 629.3 1318.3 Rad51 188.5 658.6 1465.0 Mcm7 583.9 1389.2 2534.5 Gins1 130.6 452.5 1139.3 CEM 1 + Lig1 496.7 1375.0 3220.1 Top 10 Genes Mcm6 512.6 1990.3 3699.5 Mcm2 371.8 1134.2 2758.8 Tipin 1514.2 2415.6 4384.5 Tk1 278.8 891.8 951.6

Null module GEO Series "GSE51243" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 7 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51243 Status: Public on Sep 28 2013 Title: Comparison of the transcriptome of TEL-JAK2- versus activated NOTCH1 (ICN1)-induced T cell acute lymphoblastic leukemias (mouse) Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24268771 Summary & Design: Summary: The TEL-JAK2 fusion oncogene and the ICN1 activated allele of NOTCH1 are the result of specific chromosomal translocations in T cell acute lymphoblastic leukemia (T-ALL). Mouse models of these diseases (TEL-JAK2 transgenic mice; Carron C. et al. Blood (2000); a bone marrow transplantation model for ICN1-induced T-ALL) were used to compare the transcriptional program specific to each oncoprotein in mouse models of these leukemias. Tumor load was >50% leukemic cells in all selected organs.

Overall design: Leukemic cells were collected from the thymus of terminally-ill TEL-JAK2 leukemic mice and bone marrow of terminally-ill ICN1 leukemic mice. RNA was extracted from each sample and processed for hybridization to Affymetrix arrays.

Background corr dist: KL-Divergence = 0.0331, L1-Distance = 0.0151, L2-Distance = 0.0003, Normal std = 0.6426

0.621 Kernel fit Pairwise Correlations Normal fit

Density 0.310

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

ICN1_1701ICN1_1840 leukemiaICN1_24306 leukemia (0.321293)TJ2_1192 leukemia (0.165473)TJ2_1209 leukemia (0.0851986)TJ2_1210 leukemia (0.0680557)TJ2_1261 leukemia (0.0781397) leukemia (0.241469) (0.0403708)[ min ] [ medium ] [ max ] CEM 1 Rfc5 1027.3 1457.2 2781.7 P ( S | Z, I ) = 1.00 Rfc4 796.8 1694.9 4258.0 Mean Corr = 0.94653 Rfc3 351.6 596.6 1505.3 Pcna 16298.9 21989.4 32830.3 Rfc2 1440.7 1916.4 2766.7 Chtf18 105.7 182.7 364.7 Prim1 1077.7 2282.9 6045.4 Mcm5 1113.1 2098.5 5396.8 Rad51 388.8 1052.6 2681.8 Mcm7 4483.4 5880.9 12362.0 Gins1 413.8 741.4 2116.1 CEM 1 + Lig1 1039.2 1997.7 4177.0 Top 10 Genes Mcm6 5550.2 8957.6 13510.3 Mcm2 1672.9 2501.0 5190.3 Tipin 1702.0 3178.1 7263.0 Tk1 420.2 951.5 4890.7

Null module GEO Series "GSE51075" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE51075 Status: Public on Sep 22 2013 Title: Transcriptional responses of murine macrophages to the adenylate cyclase toxin of Bordetella pertussis Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 17890046 Summary & Design: Summary: Three different recombinant forms of CyaA were used to investigate transcriptional responses of murine bone marrow-derived macrophages (BMDMs) using Affymetrix Mouse Genome Genechips. These forms were enzymically active, invasive CyaA, nonenzymically active, invasive CyaA (CyaA*) and non-enzymically active, non-invasive CyaA (proCyaA*). BMMs, treated with 20 ng/ml of CyaA for 24 h, showed over 1000 significant changes in gene transcription compared with control cells. CyaA caused an increase in transcription of many inflammatory genes and genes associated with various signalling cascades such as those involved in cyclic AMP-dependent protein kinase A signalling. Most strikingly, CyaA caused down-regulation of numerous genes involved in cell proliferation. CyaA* at 20 ng/ml significantly up-regulated the transcription of only twelve genes after 24 h whereas proCyaA* at this concentration significantly increased the transcription of only two genes.

Overall design: The effect of administration of three different recombinant forms of pertussis toxin to mouse bone marrow derived macrophages are compared with a vehicle only contol 24 hours after treatment in technical triplicate measurements

Background corr dist: KL-Divergence = 0.0967, L1-Distance = 0.0706, L2-Distance = 0.0078, Normal std = 0.5189

0.873 Kernel fit Pairwise Correlations Normal fit

Density 0.437

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

BMDM_CyaA*_24h_rep1BMDM_CyaA*_24h_rep2BMDM_CyaA*_24h_rep3BMDM_CyaA_24h_rep1 (0.0287775)BMDM_CyaA_24h_rep2 (0.0290901)BMDM_CyaA_24h_rep3 (0.0263801)BMDM_ProCyaA*_24h_rep1 (0.250844)BMDM_ProCyaA*_24h_rep2 (0.244772)BMDM_ProCyaA*_24h_rep3 (0.224574)BMDM_Urea_24h_rep1 (0.0461819)BMDM_Urea_24h_rep2 (0.032203)BMDM_Urea_24h_rep3 (0.0232791) (0.0364986) (0.0231761) (0.0342244)[ min ] [ medium ] [ max ] CEM 1 Rfc5 150.2 1684.7 1876.3 P ( S | Z, I ) = 1.00 Rfc4 114.7 1246.9 1324.2 Mean Corr = 0.94543 Rfc3 334.3 850.6 1000.5 Pcna 7485.1 32559.3 33856.6 Rfc2 1113.6 3272.3 3621.0 Chtf18 113.0 374.5 447.4 Prim1 111.0 1891.5 1996.0 Mcm5 154.3 3395.2 3681.8 Rad51 71.6 1459.1 1565.7 Mcm7 196.4 4514.0 4660.4 Gins1 76.5 1301.5 1415.9 CEM 1 + Lig1 415.2 2313.5 2447.4 Top 10 Genes Mcm6 379.0 10022.2 10268.8 Mcm2 197.3 3105.8 3482.2 Tipin 489.3 3884.1 4184.9 Tk1 110.3 2755.6 2972.6

Null module GEO Series "GSE23833" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE23833 Status: Public on Sep 01 2010 Title: The Forkhead factor FoxQ1 influences epithelial differentiation Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20717954 Summary & Design: Summary: The Forkhead family of transcription factors comprises numerous members and is implicated in various cellular functions, including cell growth, apoptosis, migration and differentiation.In this study we identified the Forkhead factor FoxQ1 as increased in expression during TGF-beta1 induced changes in epithelial differentiation, suggesting functional roles of FoxQ1 for epithelial plasticity.The repression of FoxQ1 in mammary epithelial cells led to a change in cell morphology characterized by an increase in cell size, pronounced cell-cell contacts and an increased expression of several junction proteins (e.g. E-cadherin). In addition, FoxQ1 knock-down cells revealed rearrangements in the actin-cytoskeleton and slowed down cell cycle G1-phase progression.Furthermore, repression of FoxQ1 enhanced the migratory capacity of coherent mammary epithelial cells.Gene expression profiling of NM18 cells indicated that FoxQ1 is a relevant downstream mediator of TGF-beta1 induced gene expression changes. This included the differential expression of transcription factors involved in epithelial plasticity, e.g. Ets-1, Zeb1 and Zeb2.In summary, this study has elucidated the functional impact of FoxQ1 on epithelial differentiation

Overall design:

Background corr dist: KL-Divergence = 0.0453, L1-Distance = 0.0772, L2-Distance = 0.0080, Normal std = 0.6930

0.668 Kernel fit Pairwise Correlations Normal fit

Density 0.334

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

2h_co._enriched12h_co._enriched22h_co._enriched3 (0.0951124)2h_co._total1 (0.0648681)2h_co._total2 (0.0484571) (0.0829113)2h_co._total3 (0.0845426)2h_TGFbeta_enriched1 (0.125304)2h_TGFbeta_enriched22h_TGFbeta_enriched32h_TGFbeta_total1 (0.103659)2h_TGFbeta_total2 (0.0923737)2h_TGFbeta_total3 (0.0920945) (0.0707302) (0.0721889) (0.0677578)[ min ] [ medium ] [ max ] CEM 1 Rfc5 520.7 1358.7 1510.6 P ( S | Z, I ) = 1.00 Rfc4 420.9 1098.8 1413.3 Mean Corr = 0.94533 Rfc3 188.0 397.2 494.7 Pcna 4453.2 12219.0 17158.8 Rfc2 624.1 2001.2 2066.2 Chtf18 113.3 332.8 430.8 Prim1 1141.4 3015.3 3242.4 Mcm5 453.8 1124.7 1574.1 Rad51 572.0 1568.9 1632.0 Mcm7 631.8 3250.6 4275.5 Gins1 1296.4 1801.8 1983.6 CEM 1 + Lig1 1070.9 3800.0 4545.9 Top 10 Genes Mcm6 1943.1 7473.0 8548.0 Mcm2 802.6 3018.2 3368.0 Tipin 1472.3 1832.4 2569.4 Tk1 1049.6 2353.0 3852.9

Null module GEO Series "GSE32386" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 13 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE32386 Status: Public on Apr 01 2012 Title: Expression profiling of murine neuroblastoma in transgenic mice Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 22764207 Summary & Design: Summary: Neuroblastoma is an embryonal tumor arising from the neural crest. It can be mimicked in mice by neural crest-specific overepxression of oncogenes such as MYCN or mutated ALK.

Overall design: Expression profiling of murine neuroblastoma driven by MYCN were compared to those driven by mutated ALK or both oncogenes. Mouse normal adrenal tissue served as a control.

Background corr dist: KL-Divergence = 0.0643, L1-Distance = 0.0382, L2-Distance = 0.0025, Normal std = 0.5410

0.775 Kernel fit Pairwise Correlations Normal fit

Density 0.387

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

66389_lo66977_ro (0.0579624)66977_ru (0.0460981)70660_lu (0.00866166)74128_wlr (0.0756246)74128_wr (0.165655)74129_wl (0.135113)C57Bl6_1 (0.0981236)C57Bl6_2 (0.109526)C57Bl6_3 (0.150628)86823-2x (0.114528)82743-lo (0.0166877)77204-10 (0.00941862) (0.0119743) [ min ] [ medium ] [ max ] CEM 1 Rfc5 241.4 1437.1 2709.4 P ( S | Z, I ) = 1.00 Rfc4 245.0 1841.7 3886.1 Mean Corr = 0.94153 Rfc3 160.4 731.0 1552.6 Pcna 2668.9 12779.1 16271.9 Rfc2 924.6 2023.4 2417.2 Chtf18 55.5 176.7 408.6 Prim1 244.7 3202.3 5150.7 Mcm5 85.2 1483.6 2496.2 Rad51 73.8 1925.0 2616.3 Mcm7 305.8 3259.1 6556.4 Gins1 155.3 1732.0 2492.9 CEM 1 + Lig1 492.6 3749.7 5116.2 Top 10 Genes Mcm6 644.6 4361.9 5183.5 Mcm2 346.6 2357.2 3926.7 Tipin 529.3 2985.8 5689.9 Tk1 109.5 751.5 884.4

Null module GEO Series "GSE46797" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 6 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE46797 Status: Public on May 10 2013 Title: Expression data from c-Myc+ Notch1 T-ALL initiating cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23791182 Summary & Design: Summary: Missense FBXW7 mutations are prevalent in various tumors, including T-cell acute lymphoblastic leukemia (T-ALL). To study the effects of such lesions, we generated animals carrying regulatable Fbxw7 mutant alleles. We show here that these mutations specifically bolster cancer-initiating cell activity in collaboration with Notch1 oncogenes, but spare normal hematopoietic stem cell function. We were also able to show that FBXW7 mutations specifically affect the ubiquitylation and half-life of c-Myc protein, a key T-ALL oncogene. Using animals carrying c-Myc fusion alleles, we connected Fbxw7 function to c-Myc abundance and correlated c-Myc expression to leukemia-initiating activity.

Overall design: Three independent Notch1 T-ALL were derived on c-Myc-GFP background and sorted from the spleen of leukemic mice on the basis of GFP expression for RNA extraction and hybridization on Affymetrix microarrays

Background corr dist: KL-Divergence = 0.0376, L1-Distance = 0.0289, L2-Distance = 0.0011, Normal std = 0.6371

0.637 Kernel fit Pairwise Correlations Normal fit

Density 0.318

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Notch1 Notch1T-ALL MycGFP Notch1T-ALL MycGFP Notch1T-ALL negative MycGFP Notch1T-ALL negative replicate MycGFP Notch1T-ALL negative replicate 1 (0.0581046) MycGFP T-ALL positive replicate 2 (0.212341) MycGFP positive replicate 3 (0.223673) positive replicate 1 (0.333026)[ replicatemin 2 (0.116285) 3] (0.0565697) [ medium ] [ max ] CEM 1 Rfc5 227.9 691.6 1065.8 P ( S | Z, I ) = 1.00 Rfc4 338.2 2692.1 3810.0 Mean Corr = 0.94116 Rfc3 74.3 529.8 721.0 Pcna 3937.2 12127.7 13740.8 Rfc2 427.6 1049.6 1501.5 Chtf18 86.5 439.0 747.1 Prim1 305.0 2378.7 3010.9 Mcm5 208.6 1568.7 2220.7 Rad51 124.5 841.4 1404.2 Mcm7 373.2 1616.4 1971.8 Gins1 162.7 2147.7 2608.1 CEM 1 + Lig1 273.0 2738.4 2911.3 Top 10 Genes Mcm6 558.2 4688.8 4862.6 Mcm2 316.2 1377.4 1599.9 Tipin 686.7 3385.1 6045.6 Tk1 640.7 4551.2 5320.3

Null module GEO Series "GSE54490" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 12 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE54490 Status: Public on Feb 16 2014 Title: FoxA1 directs the lineage and immunosuppressive properties of FoxA1+ regulatory T cells in EAE and MS Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24531377 Summary & Design: Summary: Affymetrix gene expression analysis was carried out to investigate the differences in gene profile of MBP89-101-reactive encephalitogenic T cells before and after co-culture with cerebellar granular neurons (CGNs). Co-culture of MBP89-101-reactive encephalitogenic T cells with CGNs leads to generation of T cells with regulatory T cells phenotype (CD4+CD25+membrane bound TGF-b+ T cells) or a new regulatory phenotype (CD4highPD-L1high T cells). CGN-induced CD4+CD25+membrane bound TGF-b+ T regulatory cells, CD4highPD-L1high T cells were purified by FACSAria. IFN-beta induced T lymphocytes (CD4highPD-L1high T cells) were also FACSAria purified. All these populations were compared to MBP89-101-reactive encephalitogenic T cells. Samples were prepared from biological triplicates for each FACSAria sorted population.

Overall design: There are four different cell types, as determined by cell surface markers, in triplicate in the experiment.

Background corr dist: KL-Divergence = 0.0239, L1-Distance = 0.0546, L2-Distance = 0.0040, Normal std = 0.7910

0.572 Kernel fit Pairwise Correlations Normal fit

Density 0.286

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

EncephalitogenicEncephalitogenicEncephalitogenic Tcellsneuron rep1 Tcells (0.0377149)neuroninduced rep2 Tcells (0.00767781)neuroninduced FoxA1Treg rep3 (0.0100399)Treginduced FoxA1Treg rep1rep1Treg FoxA1Treg (0.0287013)(0.055291) rep2rep2Treg (0.0557137)(0.06712) rep3rep3IFN-beta (0.0632909)(0.0974022)IFN-beta inducedIFN-beta induced FoxA1Treg induced FoxA1Treg rep1 FoxA1Treg (0.201469) rep2 (0.175252) rep3[ min (0.200327) ] [ medium ] [ max ] CEM 1 Rfc5 1576.1 3086.6 3629.6 P ( S | Z, I ) = 1.00 Rfc4 1071.7 2340.0 2910.4 Mean Corr = 0.94063 Rfc3 566.7 1329.2 1536.1 Pcna 10873.9 27006.0 31155.4 Rfc2 2339.4 3117.0 3335.1 Chtf18 51.3 426.2 506.3 Prim1 1345.3 4326.9 4804.5 Mcm5 1027.5 6366.7 7011.2 Rad51 558.5 3959.1 4403.7 Mcm7 1767.5 7413.3 8452.3 Gins1 580.4 1529.3 1682.9 CEM 1 + Lig1 1071.1 6981.0 8173.3 Top 10 Genes Mcm6 4267.1 14012.5 15731.5 Mcm2 1349.3 3221.5 3560.8 Tipin 2025.3 6016.6 6683.6 Tk1 571.1 3257.4 3776.1

Null module GEO Series "GSE19004" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19004 Status: Public on Jul 01 2010 Title: Mouse HCC model Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: A mouse model of HCC has been developed based on the reported inactivation of the RB pathway in the majority of human HCC. This mouse model harbors floxed alleles of Rb and p130 genes, as well as germline mutation of the p107 gene. Various strategies to activate the activity of a Cre recombinase leads to the efficient deletion of the three genes in the liver of adult mice (TKO mice). Disruption of the RB pathway induces the rapid development of HCC. These HCCs share many similar features of human HCC.

Overall design: The goal of this array is to assess genome wide expression of TKO HCCs. Gene expression of control livers (n=4) or TKO HCCs (n=5) was measured using the Affymetrix GeneChip Mouse Genome 430-2.0 arrays

Background corr dist: KL-Divergence = 0.0372, L1-Distance = 0.0331, L2-Distance = 0.0020, Normal std = 0.6133

0.650 Kernel fit Pairwise Correlations Normal fit

Density 0.325

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

triple knockouttriple knockouttriple hepatocellular knockouttriple hepatocellular knockouttriple carcinomahepatocellular knockoutnormal carcinomahepatocellular - 1 normal(0.106056)liver carcinomahepatocellular - -1 2 normal(0.0870109)(0.136547)liver carcinoma - - 3 2 normal(0.0598598) liver(0.127029)carcinoma - - 4 3 (0.114481) liver(0.135325) - - 5 4 (0.105792) (0.1279) [ min ] [ medium ] [ max ] CEM 1 Rfc5 424.4 2838.5 3326.8 P ( S | Z, I ) = 1.00 Rfc4 228.4 3979.4 7211.5 Mean Corr = 0.93947 Rfc3 269.5 1932.9 2281.9 Pcna 3358.5 18429.0 25903.4 Rfc2 784.1 2378.5 2955.7 Chtf18 49.4 281.5 489.8 Prim1 364.1 5348.4 9480.8 Mcm5 68.9 3396.6 5381.0 Rad51 36.4 1982.3 3010.7 Mcm7 405.8 7735.0 9735.6 Gins1 271.0 2348.9 3544.5 CEM 1 + Lig1 156.6 2062.5 2906.9 Top 10 Genes Mcm6 186.1 9741.3 16652.9 Mcm2 58.0 2413.7 3033.7 Tipin 640.8 1842.3 2334.3 Tk1 1082.0 3462.0 6557.2

Null module GEO Series "GSE24628" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 16 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE24628 Status: Public on Nov 01 2010 Title: Subtypes of medulloblastoma have distinct developmental origins Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 21150899 Summary & Design: Summary: Medulloblastoma encompasses a collection of clinically and molecularly diverse tumor subtypes that together comprise the most common malignant childhood brain tumor. These tumors are thought to arise within the cerebellum, with approximately 25% originating from granule neuron precursor cells (GNPCs) following aberrant activation of the Sonic Hedgehog pathway (hereafter, SHH-subtype). The pathological processes that drive heterogeneity among the other medulloblastoma subtypes are not known, hindering the development of much needed new therapies. Here, we provide evidence that a discrete subtype of medulloblastoma that contains activating mutations in the WNT pathway effector CTNNB1 (hereafter, WNT-subtype), arises outside the cerebellum from cells of the dorsal brainstem. We found that genes marking human WNT-subtype medulloblastomas are more frequently expressed in the lower rhombic lip (LRL) and embryonic dorsal brainstem than in the upper rhombic lip (URL) and developing cerebellum. Magnetic resonance imaging (MRI) and intra-operative reports showed that human WNT-subtype tumors infiltrate the dorsal brainstem, while SHH-subtype tumors are located within the cerebellar hemispheres. Activating mutations in Ctnnb1 had little impact on progenitor cell populations in the cerebellum, but caused the abnormal accumulation of cells on the embryonic dorsal brainstem that included aberrantly proliferating Zic1+ precursor cells. These lesions persisted in all mutant adult mice and in 15% of cases in which Tp53 was concurrently deleted, progressed to form medulloblastomas that recapitulated the anatomy and gene expression profiles of human WNT-subtype medulloblastoma. We provide the first evidence that subtypes of medulloblastoma have distinct cellular origins. Our data provide an explanation for the marked molecular and clinical differences between SHH and WNT-subtype medulloblastomas and have profound implications for future research and treatment of this important childhood cancer.

Overall design: A total of 16 samples are analyzed, repsresenting 4 experimental groups: Ctnnb1 medulloblastoma (3 samples); Ptch1 medulloblastoma (6 samples); embryonic dorsal brainstem (4 samples); and postnatal granule neuron precursor cells (3 samples). Every sample was prepared from a different mouse.

Background corr dist: KL-Divergence = 0.1173, L1-Distance = 0.0431, L2-Distance = 0.0036, Normal std = 0.4305

0.963 Kernel fit Pairwise Correlations Normal fit

Density 0.482

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

pgr003 pgr006(0.00508494) pgr010(0.083713) pgr011(0.030523) pgr012(0.0680629) pgr013(0.0904054) pgr014(0.191777) pgr016(0.114408) pgr029(0.0185358) pgr033(0.014982) pgr035(0.00924664) pgr049(0.016197) pgr051(0.0707489) pgr053(0.0995409) pgr055(0.0747709) pgr066(0.0833417) (0.0286619) [ min ] [ medium ] [ max ] CEM 1 Rfc5 221.2 694.4 2159.1 P ( S | Z, I ) = 1.00 Rfc4 289.7 1328.6 3956.6 Mean Corr = 0.93931 Rfc3 224.7 540.9 990.2 Pcna 1619.1 10000.0 18361.4 Rfc2 829.0 1223.6 2368.6 Chtf18 3.4 110.4 342.2 Prim1 888.8 2551.3 7323.9 Mcm5 85.1 864.7 2053.0 Rad51 133.0 638.8 1690.8 Mcm7 439.8 2762.8 7867.1 Gins1 130.2 939.8 2168.0 CEM 1 + Lig1 715.0 1462.4 2866.4 Top 10 Genes Mcm6 530.0 3039.4 10886.8 Mcm2 114.0 1168.1 4527.3 Tipin 595.0 2106.5 6391.4 Tk1 33.7 804.2 2192.0

Null module GEO Series "GSE17796" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 39 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17796 Status: Public on Jan 11 2010 Title: Expression data from B6C3F1 mice treated with reduced oxygen Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19812364 Summary & Design: Summary: Mice received decreasing oxygen concentrations from 21% to 6% O2 for ~ 30 minutes. Then, the mice remained an additional 120 minutes at 6% O2, control mice were placed insimilarchambers but recieved normal (21%) oxygen.

Background corr dist: KL-Divergence = 0.0270, L1-Distance = 0.0739, L2-Distance = 0.0083, Normal std = 0.7950

0.502 Kernel fit Pairwise Correlations Normal fit

Density 0.251

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

liver-vehicle-2hours-repliver-vehicle-2hours-repliver-vehicle-2hours-repliver-vehicle-2hours-rep 1 (0.0243946)liver-hypoxia-2hours-rep 2 (0.0278952)liver-hypoxia-2hours-rep 3 (0.0276342)liver-hypoxia-2hours-rep 4 (0.0275027)liver-hypoxia-2hours-rep 1 (0.0288652)liver-hypoxia-2hours-rep 2 (0.0256299)liver-hypoxia-2hours-rep 3 (0.0226385)liver-hypoxia-2hours-rep 4 (0.0302985)liver-hypoxia-2hours-rep 5 (0.0242242)liver-vehicle-2hours-rep 6 (0.0280498)liver-vehicle-2hours-rep 7 (0.0283882)liver-vehicle-2hours-rep 8 (0.0249528)liver-vehicle-2hours-rep 5 (0.0264435)bone 6 (0.0297223) marrow-vehicle-2hours-repbone 7 (0.032655) marrow-vehicle-2hours-repbone 8 (0.0279618) marrow-vehicle-2hours-repbone marrow-hypoxia-2hours-repbone 1 (0.0419817)marrow-hypoxia-2hours-repbone 2 (0.0550364)marrow-hypoxia-2hours-repbone 3 (0.0580386)marrow-hypoxia-2hours-repspleen-vehicle-2hours-rep 1 (0.0527593)spleen-vehicle-2hours-rep 2 (0.0438509)spleen-vehicle-2hours-rep 3 (0.0609832)spleen-vehicle-2hours-rep 41 (0.0501341)(0.00782162)spleen-hypoxia-2hours-rep 2 (0.0328958)spleen-hypoxia-2hours-rep 3 (0.0159985)spleen-hypoxia-2hours-rep 4 (0.00444793)spleen-hypoxia-2hours-rep 1 (0.0018362)spleen-vehicle-2hours-rep 2 (0.00237179)spleen-hypoxia-2hours-rep 3 (0.00452355)spleen-hypoxia-2hours-rep 4 (0.0806213)spleen-vehicle-2hours-rep 5 (0.00321597)spleen-vehicle-2hours-rep 7 (0.00754486)spleen-vehicle-2hours-rep 8 (0.00698576)spleen-hypoxia-2hours-rep 6 (0.00310457)spleen-hypoxia-2hours-rep 7 (0.00715502) 8 (0.00333742) 5 (0.00315436) 6 (0.0149446)[ min ] [ medium ] [ max ] CEM 1 Rfc5 339.7 831.8 1974.9 P ( S | Z, I ) = 1.00 Rfc4 126.0 893.5 2541.2 Mean Corr = 0.93907 Rfc3 195.0 492.0 980.0 Pcna 1695.3 14550.1 29637.7 Rfc2 465.6 2119.6 2924.9 Chtf18 41.4 162.3 406.5 Prim1 206.1 1186.5 3155.0 Mcm5 62.7 2117.1 5740.3 Rad51 28.1 462.2 1236.0 Mcm7 537.9 3689.6 9435.8 Gins1 160.2 373.2 1176.7 CEM 1 + Lig1 111.0 1925.0 5678.7 Top 10 Genes Mcm6 326.7 4176.7 10329.6 Mcm2 105.0 1684.6 5009.0 Tipin 373.1 2382.7 5863.5 Tk1 261.5 1288.4 3375.3

Null module GEO Series "GSE44260" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 10 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE44260 Status: Public on Mar 06 2013 Title: Murine germinal center and naive B cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 23514741 Summary & Design: Summary: Gene expressions of murine germinal center and naive B cells on Affymetrix platform

Overall design: The experiment include 3 d14 GC B1-8, 3 d14 GC V23 and 4 NaÃ¯ve samples

Background corr dist: KL-Divergence = 0.0522, L1-Distance = 0.0558, L2-Distance = 0.0041, Normal std = 0.6145

0.712 Kernel fit Pairwise Correlations Normal fit

Density 0.356

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

Navie_rep1Navie_rep2 (0.160481)Navie_rep3 (0.109481)Navie_rep4 (0.1428)d14 GC(0.140757) d14B1-8_rep1 GC d14B1-8_rep2 (0.059104)GC d14B1-8_rep3 (0.0521368)GC d14V23_rep1 (0.025799)GC d14V23_rep2 (0.0643299) GC V23_rep3 (0.150606) (0.0945051) [ min ] [ medium ] [ max ] CEM 1 Rfc5 854.7 3263.9 4197.9 P ( S | Z, I ) = 1.00 Rfc4 636.4 2259.9 3243.4 Mean Corr = 0.93776 Rfc3 327.4 1658.5 2074.5 Pcna 6099.2 15246.1 17716.7 Rfc2 2700.3 4873.6 5358.4 Chtf18 116.7 268.9 446.3 Prim1 1253.1 4047.1 5225.7 Mcm5 988.6 7292.4 8278.1 Rad51 352.1 2136.3 2718.1 Mcm7 1298.3 6288.5 7274.7 Gins1 181.4 1184.1 1488.3 CEM 1 + Lig1 876.6 6220.3 7284.9 Top 10 Genes Mcm6 1466.7 6973.5 7781.1 Mcm2 805.0 4912.5 6590.6 Tipin 859.9 4987.5 5851.8 Tk1 1040.9 2541.6 2886.2

Null module GEO Series "GSE14004" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 9 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14004 Status: Public on Jan 14 2009 Title: Re-expression of GATA2 Cooperates with PPAR gamma Depletion to Revert the Adipocyte Phenotype Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19136559 Summary & Design: Summary: The nuclear receptor PPAR gamma is required for adipocyte differentiation, but its role in mature adipocytes is less clear. Here we report that knockdown of PPAR gamma expression in 3T3-L1 adipocytes returned the expression of most adipocyte genes towards preadipocyte levels. Consistently, down regulated but not up regulated genes showed strong enrichment of PPAR gamma binding. Surprisingly, not all adipocyte genes were reversed and the adipocyte morphology was maintained for an extended period after PPAR gamma depletion. To explain this, we focused on transcriptional regulators whose adipogenic regulation was not reversed upon PPAR gamma depletion. We identified GATA2, a transcription factor whose down-regulation early in adipogenesis is required for preadipocyte differentiation, remaining low after PPAR gamma knockdown. Forced expression of GATA2 in mature adipocytes complemented PPAR gamma depletion and impaired adipocyte functionality with a more preadipocyte- like gene expression profile. Ectopic expression of GATA2 in adipose tissue in vivo had similar effect on adipogenic gene expression. These results suggest that PPAR gamma-independent down regulation of GATA2 prevents reversion of mature adipocytes after PPAR gamma depletion.

Keywords: cell type comparison, Gata2, PPAR gamma, adipocyte, preadipocytes, differentiation

Overall design: Technical replicates: PPAR gamma siRNA 1, PPAR gamma siRNA 2, PPAR gamma siRNA 3

Background corr dist: KL-Divergence = 0.0294, L1-Distance = 0.0232, L2-Distance = 0.0006, Normal std = 0.6966

0.586 Kernel fit Pairwise Correlations Normal fit

Density 0.293

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

preadipocytepreadipocyte rep1preadipocyte (0.303055) rep2control (0.165553) rep3 controlsiRNA (0.123633) rep1controlsiRNA (0.120647) rep2PPARsiRNA (0.160611) gamma rep3PPAR (0.0878159) gammasiRNAPPAR rep1gammasiRNA (0.00956074) rep2siRNA (0.0204584) rep3 (0.00866505)[ min ] [ medium ] [ max ] CEM 1 Rfc5 257.8 398.3 770.2 P ( S | Z, I ) = 1.00 Rfc4 457.6 566.2 791.2 Mean Corr = 0.93759 Rfc3 311.1 467.5 869.9 Pcna 4920.0 6520.6 10858.0 Rfc2 1218.4 1580.4 1961.1 Chtf18 47.8 93.9 182.8 Prim1 184.9 562.7 926.6 Mcm5 84.2 146.8 861.0 Rad51 50.0 256.4 694.5 Mcm7 723.0 1038.9 2394.3 Gins1 149.1 202.1 252.8 CEM 1 + Lig1 201.9 501.4 1220.8 Top 10 Genes Mcm6 350.7 1028.3 2769.1 Mcm2 395.3 777.2 3072.2 Tipin 1175.5 1333.0 1601.5 Tk1 94.2 161.1 767.1

Null module GEO Series "GSE13873" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 27 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13873 Status: Public on Mar 05 2009 Title: Expression data from murine gastric epithelium Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19454706 Summary & Design: Summary: Chronic infection with the bacterial pathogen Helicobacter pylori is a risk factor for the development of gastric cancer, yet remains asymptomatic in a majority of individuals. We report here that the C57Bl6 mouse model of experimental infection with the closely related H. felis recapitulates this wide range in host susceptibility. A majority of infected mice develop premalignant lesions such as gastric atrophy, compensatory epithelial hyperplasia and intestinal metaplasia, whereas a minority is completely protected from preneoplasia. Protection is associated with the failure to mount an IFN-gamma response to the infection and an associated high Helicobacter burden. We demonstrate that IFN-gamma is essential for clearance of Helicobacter, but also mediates the formation of preneoplastic lesions. We further provide evidence that IFN-gamma triggers a specific transcriptional program in murine gastric epithelial cells in vitro and in vivo, and induces their preferential transformation to the hyperplastic phenotype. In summary, our data suggest a dual role for IFN-gamma in Helicobacter pathogenesis that could provide an explanation for the differential susceptibility to H. pylori-induced gastric pathology in the human population.

Keywords: response to in vitro stimulus / comparison of histopathological states

Overall design: We chose mice for gene expression profiling that following Helicobacter infection had (a) symptoms of gastritis, but no epithelial changes, (b) atrophic gastritis accompanied by corpus gland hyperplasia or (c) atrophic gastritis accompanied by intestinal metaplasia. An uninfected control group was also included in the analysis, as were two groups of mice that lacked mature T- and B-cells due to a deletion mutation in the rag1 gene (Rag-1-/-) and that were either experimentally infected or served as Rag-1-/- uninfected controls. To see the effects of IFNg on murine gastric epithelial cells we analysed an immortalized murine primary gastric epithelial cell line treated with three different concentrations of IFNg in comparison to an untreated control.

Background corr dist: KL-Divergence = 0.0517, L1-Distance = 0.0400, L2-Distance = 0.0031, Normal std = 0.5764

0.692 Kernel fit Pairwise Correlations Normal fit

Density 0.346

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

IMPGE untreatedIMPGE IFNGIMPGE (0.20262) 1 (0.204373)IFNGIMPGE 2 (0.207586)IFNGstomach 3 (0.157222)stomach uninfectedstomach uninfected 1 (0.00518541)stomach infected 2 (0.00865257)stomach infected gastritisstomach infected gastritis 1 (0.00840625)stomach infected gastritis 2 (0.00694014)stomach infected gastritis 3 (0.00947631)stomach infected metaplasia 4 (0.00466172)stomach infected hyperplasia 1stomach (0.00361978)infected hyperplasia stomach1 infected(0.00851415) hyperplasia stomach2 infected(0.00182037) hyperplasia stomach3 infected(0.00112185) hyperplasia stomach4 infected(0.00220477) metaplasia stomach5 infected(0.00146459) metaplasia 2stomach (0.00963103)infected metaplasia 3stomach (0.00989769)uninfected metaplasia 4stomach (0.00599844)uninfected Rg 5stomach (0.0175928) infected1 (0.0156572) Rgstomach infected2 Rg (0.00711514) 1stomach (0.018252)infected Rg 2stomach (0.0299258)infected Rg 3 (0.0177521)infected Rg 4 (0.0175102) Rg 5 (0.0167986)[ min ] [ medium ] [ max ] CEM 1 Rfc5 382.9 670.9 1905.5 P ( S | Z, I ) = 1.00 Rfc4 183.8 471.5 2883.6 Mean Corr = 0.93751 Rfc3 146.1 262.8 1322.3 Pcna 5107.7 6902.0 24288.7 Rfc2 748.7 1154.9 1913.2 Chtf18 48.6 83.5 383.6 Prim1 404.5 968.1 3976.5 Mcm5 224.9 580.2 2473.2 Rad51 220.2 511.3 2808.7 Mcm7 555.1 1226.7 4228.3 Gins1 197.1 396.4 1033.8 CEM 1 + Lig1 760.6 1391.1 2125.9 Top 10 Genes Mcm6 1092.2 2568.4 7831.0 Mcm2 461.1 941.6 4246.5 Tipin 389.8 620.9 4629.2 Tk1 348.6 737.0 3124.6

Null module GEO Series "GSE50813" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 24 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50813 Status: Public on Dec 31 2013 Title: Prevention of mammary tumor progression by silencing HoxA1 via intraductal injection of nanoparticle-formulated siRNA Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 24382894 Summary & Design: Summary: Silencing HoxA1 in vivo by intraductal delivery of nanoparticle-formulated siRNA reduced mammary tumor incidence by 75% , reduced cell proliferation, and prevented loss of ER and PR expression.

Overall design: 8 week wild type FVB mouse whole mammary gland and 8week to 20 week transgenic FVB C3(1)-SV40Tag mouse whole mammary gland

Background corr dist: KL-Divergence = 0.1026, L1-Distance = 0.0245, L2-Distance = 0.0008, Normal std = 0.4380

0.911 Kernel fit Pairwise Correlations Normal fit

Density 0.455

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

8 weeks8 wildweeks type8 wildweeks Mammary33 type8 wildweeks Mammary34 type8 wild(0.0190737)weeks Mammary35 type8 wild(0.0167693)weeks Mammary36 type8 tumor(0.0426718)weeks Mammary37 8Mammary1 tumor(0.0328688)weeks 8Mammary2 tumor(0.0276341)weeks (0.0108464) 8Mammary3 tumorweeks (0.00117644) 12Mammary4 tumor weeks (0.0162408) 12Mammary5 tumorweeks (0.0310552)12 Mammary6 tumorweeks (0.0306443)12 Mammary7 tumorweeks (0.0117315)12 Mammary8 tumorweeks (0.00157092)16 Mammary9 tumorweeks (0.0064266)16 Mammary10 tumorweeks (0.00104749)16 Mammary11 tumorweeks (0.00179004)16 Mammary13 tumorweeks (0.00567411)16 Mammary14 tumorweeks (0.00143521)20 Mammary15 tumorweeks (0.00704009)20 Mammary32 tumorweeks (0.00251658)20 Mammary22 tumorweeks (0.00271148)20 Mammary23 tumorweeks (0.173758) Mammary24 tumor (0.149078) Mammary31 (0.219485) (0.186754)[ min ] [ medium ] [ max ] CEM 1 Rfc5 266.7 974.6 3986.2 P ( S | Z, I ) = 1.00 Rfc4 281.2 1103.6 3519.9 Mean Corr = 0.93623 Rfc3 172.8 520.7 2581.0 Pcna 4342.7 11349.2 36956.5 Rfc2 638.5 901.7 1915.4 Chtf18 34.7 105.7 392.6 Prim1 333.7 1470.7 5188.3 Mcm5 103.4 678.4 2463.5 Rad51 84.0 633.1 2377.1 Mcm7 411.4 1561.9 5514.5 Gins1 167.3 530.5 1504.8 CEM 1 + Lig1 326.9 1398.8 4008.8 Top 10 Genes Mcm6 269.4 2816.1 9185.1 Mcm2 138.0 1154.2 4335.3 Tipin 586.3 1531.5 4402.3 Tk1 98.3 551.5 2449.6

Null module GEO Series "GSE17266" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 59 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17266 Status: Public on Jan 12 2010 Title: Expression data from B6C3F1 mice treated with baclofen Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 19812364 Summary & Design: Summary: Mice were treated with either 100mg/kg baclofen or 0.5% methylcellulose alone by oral gavage for 1 or 5 days.

Overall design: Mice were sacrificed by cervical dislocation after either a single dose (1day) or 5 daily doses (5 days) of either baclofen or 0.5% methylcellulose two hours after the last dose. The bone marrow from the right humerus, a portion of the left lateral liver lobe and half a cross-section of the spleen were harvested and the RNA was isolated from these tissues using standard Qiagen reagents. Standard Affymetrix protocols were used for GeneChip probe preparations. 59 arrays.

Background corr dist: KL-Divergence = 0.0198, L1-Distance = 0.0483, L2-Distance = 0.0033, Normal std = 0.7864

0.507 Kernel fit Pairwise Correlations Normal fit

Density 0.254

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

liver-vehicle-1day-repliver-baclofen-1day-repliver-baclofen-1day-rep 1liver-vehicle-1day-rep (0.0223688)liver-baclofen-1day-rep 1 (0.0208793)liver-vehicle-1day-rep 2 (0.0225863) 2liver-baclofen-1day-rep (0.0230548)liver-vehicle-5day-rep 3 (0.0229734) 3liver-baclofen-5day-rep (0.0208125)liver-vehicle-5day-rep 4 (0.0227615) 1liver-baclofen-5day-rep (0.0227374)liver-vehicle-5day-rep 1 (0.0231344) 2liver-baclofen-5day-rep (0.0224917)liver-vehicle-5day-rep 2 (0.02295) 3liver-baclofen-5day-rep (0.0217454)liver-baclofen-5day-rep 3 (0.0230833) 4liver-baclofen-5day-rep (0.0221913)liver-baclofen-5day-rep 4 (0.0222064)liver-baclofen-5day-rep 5 (0.0229466)bone 6 (0.023264) marrow-vehicle-1day-repbone 7 (0.0234314) marrow-baclofen-1day-repbone 8 (0.0220644) marrow-vehicle-1day-repbone marrow-baclofen-1day-repbone 1 (0.0172054) marrow-vehicle-1day-repbone 1 (0.0373969) marrow-baclofen-1day-repbone 2 (0.0204651) marrow-vehicle-1day-repbone 2 (0.0207005) marrow-baclofen-1day-repbone 3 (0.0180022) marrow-vehicle-5day-repbone 3 (0.0213901) marrow-baclofen-5day-repbone 4 (0.0179918) marrow-vehicle-5day-repbone 4 (0.0361365) marrow-baclofen-5day-repbone 1 (0.0142917) marrow-vehicle-5day-repbone 1 (0.0342299) marrow-baclofen-5day-repbone 2 (0.0231586) marrow-vehicle-5day-repbone 2 (0.035082) marrow-baclofen-5day-repbone 3 (0.0221612) marrow-baclofen-5day-repbone 3 (0.0263429) marrow-baclofen-5day-repbone 4 (0.0164204) marrow-baclofen-5day-repbone 4 (0.0182905) marrow-baclofen-5day-repspleen-vehicle-1day-rep 5 (0.032698)spleen-baclofen-1day-rep 6 (0.0358456)spleen-vehicle-1day-rep 7 (0.0323018)spleen-baclofen-1day-rep 1 8 (0.0140495) (0.01293)spleen-vehicle-1day-rep 1 (0.00335323)spleen-baclofen-1day-rep 2 (0.00240933)spleen-vehicle-1day-rep 2 (0.00158701)spleen-baclofen-1day-rep 3 (0.00473436)spleen-vehicle-5day-rep 3 (0.00195846)spleen-baclofen-5day-rep 4 (0.00219685)spleen-vehicle-5day-rep 4 (0.00247458)spleen-baclofen-5day-rep 1 (0.00145769)spleen-vehicle-5day-rep 1 (0.00447256)spleen-baclofen-5day-rep 2 (0.00477726)spleen-vehicle-5day-rep 2 (0.00444906)spleen-baclofen-5day-rep 3 (0.00209437)spleen-baclofen-5day-rep 3 (0.00247674)spleen-baclofen-5day-rep 4 (0.0018393)spleen-baclofen-5day-rep 4 (0.00214619)spleen-baclofen-5day-rep 5 (0.00391783) 6 (0.00820792) 7 (0.00311764) 8 (0.0075558)[ min ] [ medium ] [ max ] CEM 1 Rfc5 272.9 840.6 2192.4 P ( S | Z, I ) = 1.00 Rfc4 94.5 797.0 2900.7 Mean Corr = 0.93613 Rfc3 211.2 398.2 1054.8 Pcna 2129.5 12842.3 25324.9 Rfc2 437.7 2227.7 2889.5 Chtf18 38.7 179.2 438.5 Prim1 183.0 1115.1 3265.6 Mcm5 39.3 1817.0 6535.5 Rad51 27.2 479.9 1552.6 Mcm7 484.7 3298.2 9866.1 Gins1 144.8 379.8 1142.1 CEM 1 + Lig1 178.7 2421.3 6128.3 Top 10 Genes Mcm6 308.9 4515.7 10523.0 Mcm2 53.9 2060.0 4898.1 Tipin 241.8 2102.6 5435.7 Tk1 407.9 1288.5 3959.4

Null module GEO Series "GSE31359" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 8 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31359 Status: Public on Aug 13 2011 Title: Expression data from mouse EMT-induced and non-induced cells Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: Summary & Design: Summary: The conversion of an epithelial cell to a mesenchymal cell is critical to vertebrate embryogenesis and a defining structural feature of organ development, such as forming fibroblasts in injured tissues, or in initiating metastases in epithelial cancer. From a general perspective, EMT is about disaggregating epithelial units and reshaping epithelia for movement. This phenotypic conversion requires the molecular reprogramming of epithelia with new biochemical instructions. It is known that commonly used molecular markers for EMT include increased expression of N-cadherin and vimentin, nuclear localization of beta-catenin, and increased production of the transcription factors such as Snail, Twist, and SIP1/ZEB2. Much of this conversion, however, has been studied during experiments that expose new transduction and signaling pathways in epithelia, and more recently in fibrogenic tissues. It is not yet clear whether the fibroblast transition of EMT is an expected middle phase of transdifferentiating epithelia, or whether EMT producing fibroblasts is an arrested form of transdifferentiation. EMT is easily engaged by a combination of cytokines associated with proteolytic digestion of basement membranes upon which epithelia reside. We analyzed PCA and hierarchical clustering method of the gene expression pattern of the renal tubular cells and mammary gland cells. We then identified the genes which discriminate between the renal tubular and the mammary gland epithelial cells (PC1), or EMT-induced and non-induced cells (PC3). Undergoing EMT identifies the genes that discriminate between the renal tubular and the mammary gland epithelial cells(PC1), or EMT-induced and non-induced cells (PC3).

Overall design: Affymetrix GeneChip Mouse Genome 430 2.0 Array was used to transcriptionally profile to compare mouse EMT-induced cells and non-induced cells.

Background corr dist: KL-Divergence = 0.0562, L1-Distance = 0.0330, L2-Distance = 0.0017, Normal std = 0.5554

0.725 Kernel fit Pairwise Correlations Normal fit

Density 0.362

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

NC-EpH4EMT-EpH4 (0.0432377)NC-mProx (0.0649329)EMT-mProx (0.141557)NC-MCT (0.0873904)EMT-MCT (0.126042)NC-NMuMG (0.141672)EMT-NMuMG (0.194675) (0.200494) [ min ] [ medium ] [ max ] CEM 1 Rfc5 278.2 4141.9 5382.5 P ( S | Z, I ) = 1.00 Rfc4 311.2 2354.4 2915.4 Mean Corr = 0.93602 Rfc3 316.3 1773.3 2631.5 Pcna 5380.6 13191.0 17760.6 Rfc2 774.8 2478.6 2729.8 Chtf18 49.4 471.9 714.1 Prim1 319.8 4892.3 6030.8 Mcm5 130.2 2903.7 4235.9 Rad51 218.3 1601.2 2712.5 Mcm7 1080.1 6832.9 8293.6 Gins1 131.9 1050.6 1507.0 CEM 1 + Lig1 566.8 2444.5 3556.4 Top 10 Genes Mcm6 912.1 5456.6 6606.2 Mcm2 688.2 5428.6 7349.1 Tipin 444.1 4078.7 5209.3 Tk1 87.8 3196.3 4081.8

Null module GEO Series "GSE22180" Expression Profiles Scale of expression profile Z-scores Num of samples in this series: 60 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

GEO Link: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22180 Status: Public on Oct 02 2010 Title: In vitro carcinogenicity testing with Balb/c 3T3 Cells treated with various chemical carcinogens Organism: Mus musculus Experiment type: Expression profiling by array Platform: GPL1261 Pubmed ID: 20713471 Summary & Design: Summary: Background: Information on the carcinogenic potential of chemicals is only availably for High Production Volume products. There is however, a pressing need for alternative methods allowing for the chronic toxicity of substances, including carcinogenicity, to be detected earlier and more reliably. Here we applied advanced genomics to a cellular transformation assay to identify gene signatures useful for the prediction of risk for carcinogenicity. Methods: Genome wide gene expression analysis and qRT-PCR were applied to untransformed and transformed Balb/c 3T3 cells that exposed to 2, 4-diaminotoluene (DAT), benzo(a)pyrene (BaP), 2-Acetylaminoflourene (AAF) and 3-methycholanthrene (MCA) for 24h and 120h, at different concentrations, respectively. Furthermore, various bioinformatics tools were used to identify gene signatures predicting for the carcinogenic risk. Results: Bioinformatics analysis revealed distinct datasets for the individual chemicals tested while the number of significantly regulated genes increased with ascending treatment concentration of the cell cultures. Filtering of the data revealed a common gene signature that comprised of 13 genes whose regulation in cancer tissue has already been established. Strikingly, this gene signature was already identified prior to cell transformation therefore confirming the predictive power of this gene signature in identifying carcinogenic risks of chemicals. Comparison of fold changes determined by microarray analysis and qRT-PCR were in good agreement. Conclusion: Our data describes selective and commonly regulated carcinogenic pathways observed in an easy to use in vitro carcinogenicity assay. Here we defined a set of genes which can serve as a simply assay to predict the risk for carcinogenicity by use of an alternative in vitro testing strategy.

Overall design: Balb/c 3T3 cells were seeded at 200 cells in each 60 x 15 mm culture dish with 4 ml M10F, using six culture dishes for every treatment. When cells reached a confluence of 60-65%, the culture medium was removed and replaced with fresh medium containing all tested chemicals at a specific concentration and two time points (24 and 120h). First we treated the cells both 24h and 120h with concentrations reported in the literature (0.5´M BaP, 50´M DAT, 25´M AAF and 2´M MCA). In a second approach IC20 concentrations were investigated for each chemical at both time points. The concentrations determined for IC20 ranged from 1.5 ´M BaP to 700 ´M DAT for 24h of treatment, and from 0.1 ´M BaP or MCA to 10´M AAF for 120h of treatment. Balb/c 3T3 cells treated with 0.75% DMSO alone were kept as controls. Each experiment was run in triplicate.

Background corr dist: KL-Divergence = 0.0902, L1-Distance = 0.0536, L2-Distance = 0.0063, Normal std = 0.4799

0.897 Kernel fit Pairwise Correlations Normal fit

Density 0.449

0.000 CEM 1

Z-score -5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 Correlation -1.00 -1.00 -1.00 -0.96 -0.76 0.00 0.76 0.96 1.00 1.00 1.00

Pre-normalization Quantiles

AAF_25´M_24h_Replicate1AAF_25´M_24h_Replicate2AAF_25´M_24h_Replicate3AAF_25´M_120h_Replicate1 (0.00230296)AAF_25´M_120h_Replicate2 (0.0027843)AAF_25´M_120h_Replicate3 (0.00243126)BaP_0.5´M_24h_Replicate1 (0.0231618)BaP_0.5´M_24h_Replicate2 (0.0212016)BaP_0.5´M_24h_Replicate3 (0.0178418)BaP_0.5´M_120h_Replicate1 (0.0139617)BaP_0.5´M_120h_Replicate2 (0.0094011)BaP_0.5´M_120h_Replicate3 (0.012827)Control_DMSO_24h_Replicate1 (0.0184001)Control_DMSO_24h_Replicate2 (0.0144001)Control_DMSO_24h_Replicate3 (0.0163705)Control_DMSO_120h_Replicate1Control_DMSO_120h_Replicate2 (0.00351921)Control_DMSO_120h_Replicate3 (0.00210009)DAT_50´M_24h_Replicate1 (0.0049633)DAT_50´M_24h_Replicate2 (0.0243851)DAT_50´M_24h_Replicate3 (0.0234911)DAT_50´M_120h_Replicate1 (0.023606) (0.0124563)DAT_50´M_120h_Replicate2 (0.0097501)DAT_50´M_120h_Replicate3 (0.010615)MCA_2´M_24h_Replicate1 (0.00996738)MCA_2´M_24h_Replicate2 (0.0125203)MCA_2´M_24h_Replicate3 (0.0112123)MCA_2´M_120h_Replicate1 (0.009981)MCA_2´M_120h_Replicate2 (0.00831957)MCA_2´M_120h_Replicate3 (0.00339794)AAF_10´M_24h_Replicate1 (0.00588746)AAF_10´M_24h_Replicate2 (0.00569125)AAF_10´M_24h_Replicate3 (0.00575289)AAF_10´M_120h_Replicate1 (0.0152729)AAF_10´M_120h_Replicate2 (0.0111929)AAF_10´M_120h_Replicate3 (0.0277874)BaP_1.5´M_24h_Replicate1 (0.0218759)BaP_1.5´M_24h_Replicate2 (0.0177848)BaP_1.5´M_24h_Replicate3 (0.0125592)BaP_0.1´M_120h_Replicate1 (0.0398553)BaP_0.1´M_120h_Replicate2 (0.0221937)BaP_0.1´M_120h_Replicate3 (0.0441012)Control_DMSO_24h_E2_Replicate1 (0.0170909)Control_DMSO_24h_E2_Replicate2 (0.0160765)Control_DMSO_24h_E2_Replicate3 (0.011326)Control_DMSO_120h_E2_Replicate1Control_DMSO_120h_E2_Replicate2 (0.0205386)Control_DMSO_120h_E2_Replicate3 (0.0162704)DAT_700´M_24h_Replicate1 (0.0340963)DAT_700´M_24h_Replicate2 (0.0144669)DAT_700´M_24h_Replicate3 (0.0151884)DAT_0.2´M_120h_Replicate1 (0.0395307)(0.00687817)DAT_0.2´M_120h_Replicate2 (0.0280121)DAT_0.2´M_120h_Replicate3 (0.0567893)MCA_20´M_24h_Replicate1 (0.0128369)MCA_20´M_24h_Replicate2 (0.0139364)MCA_20´M_24h_Replicate3 (0.00963038)MCA_0.1´M_120h_Replicate1 (0.0294803)MCA_0.1´M_120h_Replicate2 (0.0197545)MCA_0.1´M_120h_Replicate3 (0.038257) (0.0178856) (0.015954) [(0.0106769) min ] [ medium ] [ max ] CEM 1 Rfc5 674.5 2436.3 3984.0 P ( S | Z, I ) = 1.00 Rfc4 415.9 1801.7 2816.9 Mean Corr = 0.93576 Rfc3 329.4 1242.0 3554.9 Pcna 4776.6 13198.5 20730.5 Rfc2 950.6 2000.3 4066.7 Chtf18 83.7 504.3 1186.3 Prim1 1166.7 2811.6 5045.7 Mcm5 574.4 3744.8 6357.5 Rad51 268.4 1511.6 4221.2 Mcm7 1176.9 3889.3 9255.7 Gins1 143.3 636.1 1203.9 CEM 1 + Lig1 743.0 2808.5 5621.9 Top 10 Genes Mcm6 2205.0 6433.1 10517.8 Mcm2 1060.0 3777.5 9775.1 Tipin 885.8 2267.6 5213.7 Tk1 296.6 2341.5 4384.0

Null module