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Induced Changes in Gene Expression in Human CNS Tumors As Determined by U95av2 Chip Oligoarray Analysis

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SUPPLEMENT: Methionine deprivation (MET-stress) induced changes in gene expression in human CNS tumors as determined by U95Av2 chip oligoarray analysis. Tumor cells were grown in culture in a methionine efficient medium (M) or in a medium in which methionine was replaced with homocyctein (H). The expression of selected genes in DAOY, SWB61, SWB40, SWB39, and SWB77 (left) in arbitrary units and ratios of expression in the MET-stressed versus control state (right) are shown. Genes whose expression was significantly (p<0.05) changed my MET-stress are shown in bold. Genes whose expression was significantly downregulated by MET-stress are shaded. U133A* and U95 accession numbers. Gene Expression Level (Arbitary Units) Gene Description (accession #) MET-Stressed/Control (ratios) DAOY(M) DAOY(H) 61(M) 61(H) 40(M) 40(H) 39(M) 39(H) 77(M) 77(H) DESCRIPTION DAOY SWB61 SWB40 SWB39 SWB77 CELL CYCLE RELATED 1705 647 774 191 774 220 199 226 278 115 cyclin A1 (X51688) 0.38 0.25 0.28 1.14 0.41 1494 686 1147 532 1275 451 2262 407 1103 585 cyclin A2 (AW276574) 0.46 0.46 0.35 0.18 0.53 3156 1516 453 64 3265 404 497 184 1373 1715 cyclin B1 (M25753) 0.48 0.14 0.12 0.37 1.25 2415 827 2636 959 3009 568 2547 557 1562 1533 cyclin B2 (AF002822) 0.34 0.36 0.19 0.22 0.98 412 1623 781 1914 710 3867 2915 3599 1950 1333 cyclin D1 (X59791) 3.94 2.45 5.45 1.23 0.68 2984 1657 56 227 14 64 1300 1203 154 359 cyclin D2 (D13693) 0.56 4.06 4.51 0.93 2.34 618 1316 583 1660 1697 1161 1748 1008 2082 856 cyclin D3 (M92287) 2.13 2.85 0.68 0.58 0.41 1284 457 2345 1015 1697 700 1677 736 1144 865 Cell division cycle 2 (CDC2) (BC014563) 0.36 0.43 0.41 0.44 0.76 2318 1645 1964 1139 1386 1389 1916 1254 950 930 CDC2-related protein kinase (M68520) 0.71 0.58 1 0.65 0.98 2335 1857 198 1210 1901 1996 1684 1580 1431 1804 cyclin-dependent kinase 4 (CDK4) (U37022) 0.8 6.12 1.05 0.94 1.26 1078 1112 733 521 1468 896 657 776 458 597 cyclin-dependent kinase 5 (CDK5) (BC005115.1)* 1.03 0.71 0.61 1.18 1.3 23 150 291 390 337 128 310 164 109 24 cyclin-dependent kinase 6 (CDK6) (NM_001259.1)* 6.59 1.34 0.38 0.53 0.22 284 101 139 353 411 100 232 169 766 448 CDK4 inhibitor p18 (p18) (AF041248) 0.35 2.54 0.24 0.73 0.58 775 1238 355 602 1776 1116 1006 438 845 800 cyclin A/CDK2-associated p19 (SKP1) (U33760) 1.6 1.7 0.63 0.44 0.95 33 30 21 26 18 24 31 17 18 24 cyclin A/CDK2-associated p45 (SKP2) (U33761) 0.9 1.25 1.3 0.54 1.3 13 25 59 8 13 15 14 9 10 12 CDK inhibitor p15 (p15) (L36844) 1.87 0.13 1.16 0.65 1.19 3203 1906 1189 1056 3741 1932 2245 1156 2739 1638 cell division cycle 25 (CDC25) (S78187) 0.6 0.89 0.52 0.51 0.6 423 218 66 241 235 160 500 304 412 95 cell division cycle 25A (CDC25A) (M81933) 0.52 3.66 0.68 0.61 0.23 2041 994 2345 1291 3713 919 2082 1159 1750 1206 cell division cycle 25B (CDC25B) (M81794) 0.49 0.55 0.25 0.56 0.69 273 25 38 58 120 80 36 30 48 55 cell division cycle 25C (CDC25C) (M34065) 0.09 1.52 0.67 0.84 1.14 222 263 219 145 148 166 333 80 565 82 cell division cycle 25C splice variant 3 (AJ304506) 1.18 0.66 1.12 0.24 0.15 1718 1111 120 147 601 486 862 535 335 182 proliferating cell nuclear antigen (PCNA) (J05614) 0.65 1.23 0.81 0.62 0.54 938 432 894 349 1014 420 1455 422 749 640 putative mitotic checkpoint kinase (AF05330) 0.46 0.39 0.41 0.29 0.85 673 335 54 45 480 40 98 31 192 32 mitotic checkpoint kinase Bub1 (BUB1) (AF053305) 0.5 0.83 0.08 0.32 0.17 1755 1356 491 456 1052 583 984 508 905 726 mitotic checkpoint kinase Bub3 (BUB3) (AF047473) 0.77 0.93 0.55 0.52 0.8 694 1858 771 1291 960 1539 198 468 455 131 mitotic arrest deficient (MAD1) (U33822.1) 2.68 1.68 1.6 2.37 0.29 1364 668 1099 716 1121 552 2355 827 499 393 mitotic arrest deficient (MAD2) (BC000356.1)* 0.49 0.65 0.49 0.35 0.79 3582 1782 3911 3869 3635 2433 3399 3131 1395 1205 CDC28 protein kinase 1 (CKS1) (BC001425.1)* 0.5 0.99 0.67 0.92 0.86 2205 1911 5720 5063 11011 5167 4285 2747 1854 1312 CDC28 protein kinase 2 (CKS2) (NM_001827.1)* 0.87 0.89 0.47 0.64 0.71 1716 656 1333 1629 3145 680 2310 1100 1638 895 cell division cycle 20 (CDC20) (BC001088.1)* 0.38 1.22 0.22 0.48 0.55 305 323 234 565 332 353 261 188 460 378 tumor endothelial marker 1 precursor (TEM1) (AF279142.1)* 1.06 2.41 1.06 0.72 0.82 1386 636 140 172 324 164 2078 1507 23 147 neuroepithelial cell transforming gene 1 (NET1) (U02081.8)* 0.46 1.22 0.51 0.73 6.29 7 71 122 85 18 45 122 64 82 43 cell division cycle 14 homolog A (CDC14A) (AF000367.1)* 10.76 0.7 2.51 0.53 0.52 54 70 528 130 85 186 128 158 198 78 cell division cycle 14 homolog B (CDC14B) (NM_003671.1)* 1.3 0.25 2.2 1.24 0.39 35 208 66 19 137 199 120 76 193 50 CDC14A2 phosphatase (AF064102.1)* 5.91 0.29 1.46 0.63 0.26 21 8 274 100 193 63 106 17 78 63 CDC14B3 phosphatase (AF064105.2)* 0.37 0.36 0.33 0.16 0.8 778 1082 768 1028 909 1128 1337 1569 657 780 cell division cycle 5 (CDC5L) (NM_001253.1)* 1.39 1.34 1.24 1.17 1.19 332 226 1005 380 508 438 513 333 226 151 activator of S phase kinase (ASK) (AB028069.1)* 0.68 0.38 0.86 0.65 0.67 p53 Related 2105 2077 300 1405 920 1117 1689 1169 937 1265 p53 (M22898) 0.99 4.69 1.21 0.69 1.35 742 550 308 440 374 529 521 180 687 702 p53 binding protein (U82939) 0.74 1.43 1.41 0.35 1.02 1429 4107 2890 7600 1664 4485 1401 2868 810 348 cyclin-dependent kinase inhibitor 1A (p21, Cip1) (U03106) 2.87 2.63 2.7 2.05 0.43 753 757 1730 6282 689 2227 2398 2736 3267 2312 GADD45 (M60974) 1.01 3.63 3.23 1.14 0.71 428 1332 3808 9797 7236 10041 564 1376 955 1354 GADD45 α (Α39617) 3.11 2.57 1.39 2.44 1.42 344 90 1699 760 4029 320 1426 331 241 356 GADD45 β (AF090950.1)* 0.26 0.45 0.08 0.23 1.48 10 516 117 153 108 224 105 644 198 155 GADD45 γ (ΑF079806) 53.79 1.3 2.07 6.13 0.78 786 2707 749 6217 723 2286 1413 3213 1535 1452 GADD34 (U83981) 3.44 8.3 3.16 2.27 0.95 894 1659 846 2768 1086 1705 1385 3273 916 1957 BRCA1 (L78833) 1.86 3.27 1.37 2.36 2.14 281 200 894 885 602 825 476 1420 1008 1001 BRCA2 (U50535) 0.71 0.99 1.37 2.98 0.99 APOPTOSIS 599 2388 184 2800 1838 5225 3287 4450 2128 1901 BCL-1 (M73554) 3.99 15.24 2.84 1.35 0.89 258 162 370 270 166 256 260 198 181 218 BAX alpha (L22473) 0.63 0.73 1.54 0.76 1.2 520 480 851 532 311 610 680 470 473 535 BAX beta (L22474) 0.92 0.63 1.96 0.69 1.13 199 159 162 81 131 263 317 74 157 99 BAX gamma (L22475) 0.8 0.5 2 0.23 0.63 554 420 63 1329 281 594 781 664 453 392 BAX delta (U19599) 0.76 21.16 2.12 0.85 0.87 764 971 730 587 481 583 808 488 376 392 BH3 interacting domain death agonist (BID) (AF042083) 1.27 0.8 1.21 0.6 1.04 174 348 76 117 6 13 33 135 14 23 BCL-2 interacting killer (BIK) (U34584) 2 1.55 2.26 4.1 1.66 653 1040 374 508 465 697 598 563 794 496 BCL2/adenovirus E1B 19kD-interacting protein 2 (BNIP2) (U15173) 1.59 1.36 1.5 0.94 0.62 394 392 723 1935 1474 1821 504 2744 1499 2346 E1B 19K/Bcl-2-binding protein (NIP3) (AF002697) 1 2.68 1.24 5.45 1.56 322 286 547 488 512 382 540 371 337 398 BCL-2 binding component 6 (bbc6) (U66879) 0.89 0.89 0.75 0.69 1.18 600 437 1281 2037 256 767 658 815 620 717 BCL-2 binding component 3 (bbc3) (U82987) 0.73 1.59 3 1.24 1.16 1644 1222 775 3868 3943 6872 2231 9833 4443 7565 BCL2/adenovirus E1B 19kDa-interacting protein 3a (AF079221) 0.74 4.99 1.74 4.41 1.7 449 565 330 239 312 417 566 925 358 276 TNF-induced protein (GG2-1) (NM_014350.1)* 1.06 0.79 1.34 1.35 76 ANTI-APOPTOSIS 203 192 468 94 572 280 73 52 146 244 BCL-2 (M14745) 0.95 0.2 0.49 0.72 1.67 386 358 129 1011 400 530 421 639 444 438 BCL-2, p53 binding protein (BBP/53BP2) (U58334) 0.93 7.85 1.33 1.52 0.99 60 222 110 80 4 61 8 45 26 23 BCL-2 related (BFL-1) (U27467) 3.72 0.73 15.25 5.86 0.86 173 378 874 639 321 425 418 240 516 492 BCL—Xl (Z23115) 2.19 0.73 1.32 0.57 0.95 2010 1683 1452 1757 980 1269 1374 1957 980 961 BCL7B protein (X89985) 0.84 1.21 1.3 1.42 0.98 493 476 156 303 92 205 166 312 148 263 BCL7A protein (X89984) 0.97 1.95 2.23 1.88 1.78 TGF 100 193 299 88 9 10 89 486 305 126 TGF-α (X70340) 1.94 0.29 1.11 5.47 0.41 83 128 368 1098 257 107 457 197 445 279 TGF-β -2 (M19154) 1.54 2.98 0.42 0.43 0.63 1075 1075 101 1248 1561 770 1232 1166 833 1405 TGF-β (Μ38449) 1 12.41 0.49 0.95 1.69 167 79 104 325 415 387 124 383 383 337 TGF-β superfamily receptor type I (L17075) 0.48 3.11 0.93 3.09 0.88 1187 4445 2390 31458 810 8892 4251 28156 1886 2674 TGF-β superfamily protein (AB000584) 3.75 13.16 10.98 6.62 1.42 574 421 316 536 707 988 909 642 770 1217 TGF-β activated kinase 1a (AB009356) 0.73 1.7 1.4 0.71 1.58 992 2363 34 1343 950 1275 1400 904 678 219 TGF-β inducible early growth rasp protein alpha (AF050110) 2.38 39.51 1.34 0.65 0.32 3813 4177 1257 1952 3595 3273 3434 1886 3860 2849 TGF-β receptor interacting protein (U36764) 1.1 1.55 0.91 0.55 0.74 254 343 140 632 61 164 381 464 202 328 TGF-β -receptor associated protein-1 (AF022795T) 1.35 4.5 2.68 1.22 1.62 1176 67 2017 722 1096 792 762 391 909 1022 TGF-β activated kinase (TAK1) (AF21807)* 0.06 0.36 0.72 0.51 1.13 591 1882 466 3776 477 3352 1008 2672 889 1662 TGF-β induced early response (TIEG) (U21847.1)* 3.19 8.1 7.03 2.65 1.87 155 196 496 219 746 531 248 152 626 648 TGF-β induced antiapoptotic factor (TIAF1) (D86970.1)* 1.26 0.44 0.71 0.61 1.03 42154 26790 124 833 102 177 27382 15932 16608 18477 TGF-β induced 68kD (TGFBI) (BC000097.1)* 0.64 6.74 1.73 0.58 1.11 112 161 645 495 98 234 363 188 288 215 glioblastoma-derived T-cell suppressor ( TGF-beta2) (Y00083) 1.44 0.77 2.39 0.52 0.74 175 239 158 403 225 457 311 256 319 318 SMAD5 (AF010607) 1.37 2.55 2.03 0.82 1 322 462 112 242 152 152 187 202 151 136 SMAD7 (AF010193) 1.44 2.15 1 1.08 0.9 339 499 37 375 158 342 192 273 215 270 SMAD2 (U78733) 1.47 10.17 2.16 1.42 1.25 505 717 466 223 184 264 323 292 267 286 SMAD3 (AB004922) 1.42 0.48 1.43
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    Table 1 Top 100 phosphorylated substrates and their corresponding kinases in chondrosarcoma cultures as used for IPA analysis. Average Fold Adj intensity in Change p- chondrosarcoma Corresponding MSC value cultures Substrate Protein Psite kinase (log2) MSC 1043.42 RKKKVSSTKRH Cytohesin-1 S394 PKC 1.83 0.001 746.95 RKGYRSQRGHS Vitronectin S381 PKC 1.00 0.056 709.03 RARSTSLNERP Tuberin S939 AKT1 1.64 0.008 559.42 SPPRSSLRRSS Transcription elongation factor A-like1 S37 PKC; GSK3 0.18 0.684 515.29 LRRSLSRSMSQ Telethonin S157 Titin 0.77 0.082 510.00 MQPDNSSDSDY CD5 T434 PKA -0.35 0.671 476.27 GGRGGSRARNL Heterogeneous nuclear ribonucleoprotein K S302 PKCdelta 1.03 0.028 455.97 LKPGSSHRKTK Bruton's tyrosine kinase S180 PKCbeta 1.55 0.001 444.65 RRRMASMQRTG E1A binding protein p300 S1834 AKT; p70S6 kinase; pp90Rsk 0.53 0.195 Guanine nucleotide binding protein, alpha Z 440.26 HLRSESQRQRR polypeptide S27 PKC 0.88 0.199 6-phosphofructo-2-kinase/fructose-2,6- 424.12 RPRNYSVGSRP biphosphatase 2 S483 AKT 1.32 0.003 419.61 KKKIATRKPRF Metabotropic glutamate receptor 1 T695 PKC 1.75 0.001 391.21 DNSSDSDYDLH CD5 T453 Lck; Fyn -2.09 0.001 377.39 LRQLRSPRRAQ Ras associated protein Rab4 S204 CDC2 0.63 0.091 376.28 SSQRVSSYRRT Desmin S12 Aurora kinase B 0.56 0.255 369.05 ARIGGSRRERS EP4 receptor S354 PKC 0.29 0.543 RPS6 kinase alpha 3; PKA; 367.99 EPKRRSARLSA HMG14 S7 PKC -0.01 0.996 Peptidylglycine alpha amidating 349.08 SRKGYSRKGFD monooxygenase S930 PKC 0.21 0.678 347.92 RRRLSSLRAST Ribosomal protein S6 S236 PAK2 0.02 0.985 346.84 RSNPPSRKGSG Connexin
  • Short-Hairpin RNA Library: Identification of Therapeutic Partners for Gefitinib-Resistant Non-Small Cell Lung Cancer

    Short-Hairpin RNA Library: Identification of Therapeutic Partners for Gefitinib-Resistant Non-Small Cell Lung Cancer

    www.impactjournals.com/oncotarget/ Oncotarget, Vol. 6, No.2 Short-hairpin RNA library: identification of therapeutic partners for gefitinib-resistant non-small cell lung cancer Makoto Sudo1, Seiichi Mori2, Vikas Madan1, Henry Yang1, Geraldine Leong1 and H. Phillip Koeffler1,3,4 1 Cancer Science Institute of Singapore, NUS, Singapore 2 Division of Cancer Genomics, The Cancer Institute of Japanese Foundation for Cancer Research, Tokyo, Japan 3 Department of Hematology and Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, USA 4 National University Cancer Institute, National University Hospital, Singapore Correspondence to: Makoto Sudo, email: [email protected] Keywords: combination chemotherapy, dasatinib, gefitinib, PRKCSH, short-hairpin RNA library screening, thioridazine Received: August 19, 2014 Accepted: November 24, 2014 Published: November 25, 2014 This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Somatic mutations of the epidermal growth factor receptor often cause resistance to therapy with tyrosine kinase inhibitor in non-small cell lung cancer (NSCLC). In this study, we aimed to identify partner drugs and pathways that can induce cell death in combination with gefitinib in NSCLC cells. We undertook a genome-wide RNAi screen to identify synthetic lethality with gefitinib in tyrosine kinase inhibitor resistant cells. The screening data were utilized in different approaches. Firstly, we identifiedPRKCSH as a candidate gene, silencing of which induces apoptosis of NSCLC cells treated with gefitinib. Next, in an in silico gene signature pathway analysis of shRNA library data, a strong correlation of genes involved in the CD27 signaling cascade was observed.
  • Knockdown of Mitogen-Activated Protein Kinase Kinase 3 Negatively Regulates Hepatitis a Virus Replication

    Knockdown of Mitogen-Activated Protein Kinase Kinase 3 Negatively Regulates Hepatitis a Virus Replication

    International Journal of Molecular Sciences Article Knockdown of Mitogen-Activated Protein Kinase Kinase 3 Negatively Regulates Hepatitis A Virus Replication Tatsuo Kanda 1,* , Reina Sasaki-Tanaka 1, Ryota Masuzaki 1 , Naoki Matsumoto 1, Hiroaki Okamoto 2 and Mitsuhiko Moriyama 1 1 Division of Gastroenterology and Hepatology, Department of Medicine, Nihon University School of Medicine, 30-1 Oyaguchi-kamicho, Itabashi-ku, Tokyo 173-8610, Japan; [email protected] (R.S.-T.); [email protected] (R.M.); [email protected] (N.M.); [email protected] (M.M.) 2 Division of Virology, Department of Infection and Immunity, Jichi Medical University School of Medicine, Shimotsuke, Tochigi 329-0498, Japan; [email protected] * Correspondence: [email protected]; Tel.: +81-3-3972-8111 Abstract: Zinc chloride is known to be effective in combatting hepatitis A virus (HAV) infection, and zinc ions seem to be especially involved in Toll-like receptor (TLR) signaling pathways. In the present study, we examined this involvement in human hepatoma cell lines using a human TLR signaling target RT-PCR array. We also observed that zinc chloride inhibited mitogen-activated protein kinase kinase 3 (MAP2K3) expression, which could downregulate HAV replication in human hepatocytes. It is possible that zinc chloride may inhibit HAV replication in association with its inhibition of MAP2K3. In that regard, this study set out to determine whether MAP2K3 could be considered a modulating factor in the development of the HAV pathogen-associated molecular pattern (PAMP) Citation: Kanda, T.; Sasaki-Tanaka, and its triggering of interferon-β production.
  • A Novel Glycogen Synthase Kinase-3 Inhibitor Optimized for Acute

    A Novel Glycogen Synthase Kinase-3 Inhibitor Optimized for Acute

    Published OnlineFirst May 9, 2016; DOI: 10.1158/1535-7163.MCT-15-0566 Small Molecule Therapeutics Molecular Cancer Therapeutics A Novel Glycogen Synthase Kinase-3 Inhibitor Optimized for Acute Myeloid Leukemia Differentiation Activity Sophia Hu1, Masumi Ueda2, Lindsay Stetson1, James Ignatz-Hoover1, Stephen Moreton1, Amit Chakrabarti3, Zhiqiang Xia3, Goutam Karan3, Marcos de Lima2, Mukesh K. Agrawal3,4, and David N. Wald1,3,5 Abstract Standard therapies used for the treatment of acute myeloid describe the discovery of a novel GSK3 inhibitor, GS87. GS87 leukemia (AML) are cytotoxic agents that target rapidly prolifer- was discovered in efforts to optimize GSK3 inhibition for AML ating cells. Unfortunately, this therapeutic approach has differentiation activity. Despite GS87's dramatic ability to induce limited efficacy and significant toxicity and the majority of AML AML differentiation, kinase profiling reveals its high specificity patients still die of their disease. In contrast to the poor prognosis in targeting GSK3 as compared with other kinases. GS87 demon- of most AML patients, most individuals with a rare subtype of strates high efficacy in a mouse AML model system and unlike AML, acute promyelocytic leukemia, can be cured by differenti- current AML therapeutics, exhibits little effect on normal bone ation therapy using regimens containing all-trans retinoic acid. marrow cells. GS87 induces potent differentiation by more GSK3 has been previously identified as a therapeutic target in effectively activating GSK3-dependent signaling components AML where its inhibition can lead to the differentiation and including MAPK signaling as compared with other GSK3 growth arrest of leukemic cells. Unfortunately, existing GSK3 inhibitors. GS87 is a novel GSK3 inhibitor with therapeutic inhibitors lead to suboptimal differentiation activity making potential as a differentiation agent for non-promyelocytic AML.