KEGG ID: 04630
KEGG Diagram for Jak-STAT signaling pathway
There are 118 IPI Records from this pathway found in Rattus norvegicus.
Location of Jak-STAT signaling pathway proteins on Rat Genome
| IPI Record | Position |
|---|---|
| 1: Akt1 | 6:137640482-137657552 |
| 2: Akt2 | 1:82686233-82726544 |
| 3: Akt3 | 13:92807672-92924984 |
| 4: Bcl2l1 | 3:143129087-143180199 |
| 5: Cblb | 11:49690402-49856762 |
| 6: Cblc | 1:79092830-79108167 |
| 7: Ccnd1 | 1:205360031-205366632 |
| 8: Ccnd2 | 4:163523817-163546501 |
| 9: Ccnd3 | :- |
| 10: Cish | 8:112538514-112545389 |
| 11: Clcf1 | 1:206802745-206806332 |
| 12: Cntf | 1:215842668-215844691 |
| 13: Cntfr | :- |
| 14: Crebbp | 10:11598680-11724122 |
| 15: Csf2 | 10:39665850-39667831 |
| 16: Csf2ra | :- |
| 17: Csf2rb1 | 7:116237279-116271993 |
| 18: Csf3 | 10:87473990-87476365 |
| 19: Csf3r_predicted | 5:145377414-145393604 |
| 20: Ctf1 | 1:187001445-187006655 |
| 21: Epo | 12:19552436-19554617 |
| 22: Epor | 8:21061308-21065886 |
| 23: Ghr | 2:52497358-52658066 |
| 24: Grb2 | 10:105722014-105818649 |
| 25: Ifna1 | 5:108011739-108012317 |
| 26: Ifna11_predicted | 5:108150128-108150703 |
| 27: Ifna2_predicted | 5:108085633-108118114 |
| 28: Ifnar1_predicted | 11:31455064-31479849 |
| 29: Ifnb1 | 5:107837628-107838182 |
| 30: Ifng | 7:57621754-57625792 |
| 31: Ifngr1 | 1:14846414-14864896 |
| 32: Ifngr2_predicted | 11:31508768-31526039 |
| 33: Ifnk_predicted | 5:51730055-51804466 |
| 34: Il10 | 13:43953859-43958332 |
| 35: Il10ra | 8:48211040-48224439 |
| 36: Il11 | 1:67786388-67791611 |
| 37: Il11ra1 | 5:59193895-59202275 |
| 38: Il12a | 2:158710261-158717689 |
| 39: Il12b | 10:29558955-29567748 |
| 40: Il12rb1 | 16:19126653-19156365 |
| 41: Il12rb2 | 4:96929755-96995733 |
| 42: Il13 | 10:39093512-39096069 |
| 43: Il13ra1 | 11:73147652-73148932 |
| 44: Il13ra2 | X:30505846-30533002 |
| 45: Il15 | 19:27482376-27499255 |
| 46: Il2 | 2:123655005-123659709 |
| 47: Il21_predicted | 2:123774331-123781697 |
| 48: Il23a | 7:1584112-1586226 |
| 49: Il24 | 13:43831510-43836908 |
| 50: Il2ra | 17:78051150-78097685 |
| 51: Il2rb | :- |
| 52: Il2rg | X:89339271-89346542 |
| 53: Il3 | 10:39684691-39687041 |
| 54: Il4 | 10:39074582-39080134 |
| 55: Il4ra | 1:184625287-184637860 |
| 56: Il5 | 10:39177783-39180657 |
| 57: Il5ra | 4:142067108-142098051 |
| 58: Il6 | 4:456799-461376 |
| 59: Il6ra | 2:182078051-182128147 |
| 60: Il6st | 2:43806301-43842365 |
| 61: Il7 | 2:96364592-96399206 |
| 62: Il7r_predicted | 2:59105666-59137997 |
| 63: Il9 | 17:14068757-14071880 |
| 64: Il9r | 10:15678793-15690250 |
| 65: IPI00360197 | 17:77998621-78029657 |
| 66: IPI00766451 | :- |
| 67: Isgf3g | 15:33739729-33744981 |
| 68: Jak1 | 5:121805277-121845772 |
| 69: Jak2 | 1:232928515-232974587 |
| 70: Jak3 | 16:18878941-18889441 |
| 71: Lep | 4:55934532-55946066 |
| 72: Lepr | 5:122385149-122503365 |
| 73: Lif | 14:84887856-84890630 |
| 74: Lifr | 2:56440206-56477198 |
| 75: Miz1 | 18:74078683-74129514 |
| 76: Mpl_predicted | 5:138921476-138931990 |
| 77: Myc | 7:98953142-98957835 |
| 78: Osm | 14:84857232-84860082 |
| 79: Pias1_predicted | 8:67024576-67123004 |
| 80: Pias3 | 2:191499055-191507243 |
| 81: Pias4 | 7:10030180-10043646 |
| 82: Pik3ca | 2:118640277-118670170 |
| 83: Pik3cb | 8:103886682-103957112 |
| 84: Pik3cd_predicted | 5:166735338-166750186 |
| 85: Pik3cg_predicted | 6:50444793-50477111 |
| 86: Pik3r1 | 2:32602673-32675350 |
| 87: Pik3r2 | 16:19171101-19179650 |
| 88: Pik3r3 | 5:136497494-136566473 |
| 89: Pim1 | 20:7817154-7821800 |
| 90: Prl | 17:44699101-44709162 |
| 91: Prlr | 2:59660849-59700727 |
| 92: Ptpn11 | 12:36520522-36557116 |
| 93: Ptpn6 | 4:160843701-160856821 |
| 94: RGD1559655_predicted | 5:154495319-154526724 |
| 95: RGD1559932_predicted | :- |
| 96: RGD1560373_predicted | 11:31380588-31397912 |
| 97: RGD1563261_predicted | 10:55182226-55247889 |
| 98: RGD1564499_predicted | 17:88276200-88320716 |
| 99: RGD1564914_predicted | 6:10552015-10582830 |
| 100: RGD1565911_predicted | :- |
| 101: RGD1566151_predicted | 8:105306512-105325963 |
| 102: Socs1 | 10:4819971-4820609 |
| 103: Socs2 | 7:32605717-32608323 |
| 104: Socs3 | 10:107958636-107959313 |
| 105: Socs4_predicted | 15:23229005-23243035 |
| 106: Socs7_predicted | 10:86090333-86134222 |
| 107: Sos1 | 6:3310823-3394313 |
| 108: Sos2 | 6:91610826-91722481 |
| 109: Stam2 | 3:34213153-34236499 |
| 110: Stat1 | 9:46460407-46650076 |
| 111: Stat2 | 7:1564348-1580652 |
| 112: Stat3 | 10:89821078-89872970 |
| 113: Stat4 | 9:46460407-46650076 |
| 114: Stat5a | 10:89795404-89819732 |
| 115: Stat5b | 10:89716624-89743137 |
| 116: Stat6_predicted | 7:67601861-67642616 |
| 117: Tpo | 6:47954848-48025740 |
| 118: Tslpr | :- |
There are 118 IPI Records from this pathway found in Mus musculus.
Location of Jak-STAT signaling pathway proteins on Mouse Genome
| IPI Record | Position |
|---|---|
| 1: Akt1 | :- |
| 2: Akt2 | 7:27300516-27348213 |
| 3: Akt3 | 1:178862039-178967772 |
| 4: Bcl2l1 | 2:152458757-152523123 |
| 5: Cbl | 9:43900257-43985041 |
| 6: Cblb | 16:51952371-52127389 |
| 7: Cblc | 7:18939488-18955304 |
| 8: Ccnd1 | 7:144739321-144749220 |
| 9: Ccnd2 | 6:127091327-127116667 |
| 10: Ccnd3 | 17:46968322-47062874 |
| 11: Cish | 9:107143623-107160885 |
| 12: Clcf1 | 19:4214392-4222615 |
| 13: Cntf | 19:12830688-12862352 |
| 14: Cntfr | 4:41846167-41885710 |
| 15: Crebbp | 16:3999276-4128632 |
| 16: Csf2 | 11:54090687-54093065 |
| 17: Csf2ra | 19:61279667-61282028 |
| 18: Csf2rb | 15:78153275-78177290 |
| 19: Csf2rb2 | 15:78109765-78132858 |
| 20: Csf3 | 11:98517403-98519719 |
| 21: Csf3r | 4:125529618-125546743 |
| 22: Ctf1 | 7:127503884-127509333 |
| 23: Epo | 5:137712873-137714972 |
| 24: Epor | 9:21709306-21713908 |
| 25: Gh | 11:106116361-106117955 |
| 26: Ghr | 15:3267774-3533231 |
| 27: Grb2 | 11:115460216-115524687 |
| 28: Ifna1 | 4:88321318-88321887 |
| 29: Ifna11 | 4:88291124-88292606 |
| 30: Ifna13 | 4:88115047-88115616 |
| 31: Ifna2 | 4:88154438-88155010 |
| 32: Ifna4 | 4:88313092-88313652 |
| 33: Ifna5 | 4:88306756-88307325 |
| 34: Ifna6 | :- |
| 35: Ifna7 | 4:88287459-88288031 |
| 36: Ifna9 | 4:88063037-88074607 |
| 37: Ifnab | 4:88161886-88162458 |
| 38: Ifnar1 | 16:91374108-91396296 |
| 39: Ifnar2 | 16:91261758-91294444 |
| 40: Ifnb1 | 4:87993457-87994005 |
| 41: Ifne1 | 4:88350832-88351410 |
| 42: Ifng | 10:117844040-117848885 |
| 43: Ifngr1 | 10:19281386-19299641 |
| 44: Ifngr2 | 16:91435953-91452866 |
| 45: Ifnk | 4:35340942-35342908 |
| 46: Il10 | 1:132847393-132852516 |
| 47: Il10ra | 9:45004833-45020131 |
| 48: Il10rb | 16:91295167-91314688 |
| 49: Il11 | 7:4376654-4379588 |
| 50: Il11ra1 | 4:41952093-41957631 |
| 51: Il11ra2 | :- |
| 52: Il12a | 3:68778573-68786454 |
| 53: Il12b | 11:44243486-44257456 |
| 54: Il12rb1 | 8:73737473-73750411 |
| 55: Il12rb2 | 6:67221596-67305715 |
| 56: Il13 | 11:53474747-53478125 |
| 57: Il13ra1 | X:32543584-32602707 |
| 58: Il13ra2 | X:142629920-142675560 |
| 59: Il15 | 8:85227661-85240228 |
| 60: Il15ra | 2:11623296-11651835 |
| 61: Il19 | 1:132760202-132766787 |
| 62: Il2 | 3:37312271-37317502 |
| 63: Il20 | 1:132734531-132738997 |
| 64: Il20ra | 10:19402003-19449469 |
| 65: Il20rb | 9:100267073-100295737 |
| 66: Il21r | 7:125394642-125424418 |
| 67: Il22 | 10:117607935-117613040 |
| 68: Il22ra1 | 4:135000248-135024216 |
| 69: Il22ra2 | 10:19311456-19322568 |
| 70: Il23a | 10:127699089-127701033 |
| 71: Il23r | 6:67352943-67420314 |
| 72: Il24 | 1:132709620-132714885 |
| 73: Il28b | 7:28231596-28233082 |
| 74: Il28ra | 4:134958600-134980257 |
| 75: Il2ra | 2:11560703-11611044 |
| 76: Il2rb | 15:78307808-78322321 |
| 77: Il2rg | X:97467097-97470925 |
| 78: Il3 | 11:54108726-54110700 |
| 79: Il3ra | 14:13139762-13148759 |
| 80: Il4 | 11:53455891-53462067 |
| 81: Il4ra | 7:125356803-125369129 |
| 82: Il5 | 11:53564217-53568526 |
| 83: Il5ra | 6:106678159-106710113 |
| 84: Il6 | 5:30343948-30350755 |
| 85: Il6ra | 3:89955251-89999087 |
| 86: Il6st | 13:113584987-113627719 |
| 87: Il7 | 3:7556913-7587247 |
| 88: Il7r | 15:9450884-9474583 |
| 89: Il9 | 13:56488899-56491868 |
| 90: Il9r | 11:32088997-32100222 |
| 91: Irf9 | 14:54558274-54564100 |
| 92: Jak1 | 4:100650299-100763214 |
| 93: Jak2 | 19:29318438-29378334 |
| 94: Jak3 | 8:74605521-74619563 |
| 95: Lep | 6:29010231-29023886 |
| 96: Lepr | 4:101215336-101313489 |
| 97: Lif | 11:4157571-4172517 |
| 98: Lifr | 15:7101575-7138433 |
| 99: Mpl | 4:117940347-117955445 |
| 100: Myc | 15:61815052-61820027 |
| 101: Osm | 11:4136423-4141029 |
| 102: Osmr | 15:6760805-6821498 |
| 103: Pias1 | 9:62679132-62778885 |
| 104: Pias2 | 18:77301699-77357244 |
| 105: Pias3 | 3:96784822-96791367 |
| 106: Pias4 | 10:80557102-80567322 |
| 107: Pik3ca | 3:32627755-32654380 |
| 108: Pik3cb | 9:98847754-98949439 |
| 109: Pik3cd | 4:148492970-148542498 |
| 110: Pik3cg | 12:32758720-32793858 |
| 111: Pik3r1 | 13:102781018-102868441 |
| 112: Pik3r2 | 8:73697168-73705691 |
| 113: Pik3r3 | 4:115719846-115800988 |
| 114: Pik3r5 | 11:68248320-68314041 |
| 115: Pim1 | 17:29217824-29222496 |
| 116: Prl | 13:27065042-27072657 |
| 117: Prlr | 15:10121963-10274098 |
| 118: Ptpn11 | 5:121391158-121451946 |
| 119: Ptpn6 | 6:124686727-124698484 |
| 120: Q80SS5_MOUSE | 4:88063037-88074607 |
| 121: Q810G3_MOUSE | 4:88028904-88043029 |
| 122: Socs1 | 16:10695821-10699114 |
| 123: Socs2 | 10:94815050-94846509 |
| 124: Socs3 | 11:117782179-117785276 |
| 125: Socs4 | 14:46199020-46213468 |
| 126: Socs5 | 17:87016005-87045911 |
| 127: Socs7 | 11:97178641-97214632 |
| 128: Sos1 | 17:80306507-80388261 |
| 129: Sos2 | 12:70502371-70576665 |
| 130: Spred1 | 2:116812891-116870782 |
| 131: Spred2 | 11:19824445-19922600 |
| 132: Spred3 | 7:28867589-28877407 |
| 133: Spry1 | 3:37831507-37836147 |
| 134: Spry2 | 14:104778114-104782418 |
| 135: Spry3 | :- |
| 136: Spry4 | 18:38712235-38727242 |
| 137: Stam | 2:13991854-14066092 |
| 138: Stam2 | 2:52513673-52564209 |
| 139: Stat1 | 1:52064035-52066799 |
| 140: Stat2 | 10:127673525-127695798 |
| 141: Stat3 | 11:100701188-100755630 |
| 142: Stat4 | 1:51952788-52051729 |
| 143: Stat5a | 11:100675493-100701259 |
| 144: Stat5b | 11:100596902-100666816 |
| 145: Stat6 | 10:127046117-127063894 |
| 146: Tpo | 12:30640711-30718661 |
| 147: Tpte2 | 5:109795011-109799277 |
| 148: Tslp | 18:32958393-32962802 |
| 149: Tyk2 | 9:20854476-20881612 |
There are 118 IPI Records from this pathway found in Homo sapiens.
Location of Jak-STAT signaling pathway proteins on Human Genome
| IPI Record | Position |
|---|---|
| 1: AKT1 | 14:104306734-104333125 |
| 2: AKT2 | 19:45430084-45483036 |
| 3: AKT3 | 1:241718158-242080053 |
| 4: BCL2L1 | 20:29715916-29774366 |
| 5: CBL | 11:118582200-118684066 |
| 6: CBLB | 3:106859799-107070577 |
| 7: CBLC | 19:49972966-49995736 |
| 8: CCND1 | 11:69165054-69178422 |
| 9: CCND2 | 12:4253199-4284777 |
| 10: CCND3 | 6:42010649-42124404 |
| 11: CISH | 3:50618925-50624207 |
| 12: CLCF1 | 11:66888219-66897782 |
| 13: CNTF | 11:58146721-58149778 |
| 14: CNTFR | 9:34541430-34579735 |
| 15: CREBBP | 16:3716572-3870723 |
| 16: CRLF2 | X:1274890-1291527 |
| 17: CSF2 | 5:131437382-131439758 |
| 18: CSF2RA | X:1347693-1389274 |
| 19: CSF2RB | 22:35648168-35664764 |
| 20: CSF3 | 17:35425214-35427592 |
| 21: CSF3R | 1:36704231-36721466 |
| 22: CTF1 | 16:30815429-30822381 |
| 23: EP300 | 22:39817736-39905472 |
| 24: EPO | 7:100156359-100159257 |
| 25: EPOR | 19:11348883-11355883 |
| 26: GH1 | 17:59348294-59349886 |
| 27: GH2 | 17:59311323-59312911 |
| 28: GHR | 5:42459783-42757736 |
| 29: GRB2 | 17:70825753-70913384 |
| 30: IFNA10 | 9:21196180-21197142 |
| 31: IFNA13 | 9:21430440-21431315 |
| 32: IFNA14 | 9:21191234-21229990 |
| 33: IFNA16 | 9:21206372-21207310 |
| 34: IFNA17 | 9:21217242-21218221 |
| 35: IFNA2 | 9:21374253-21375387 |
| 36: IFNA21 | 9:21155636-21156659 |
| 37: IFNA4 | 9:21176693-21177670 |
| 38: IFNA5 | 9:21294325-21295311 |
| 39: IFNA6 | 9:21339834-21341377 |
| 40: IFNA7 | 9:21191234-21229990 |
| 41: IFNA8 | 9:21399146-21400184 |
| 42: IFNAR1 | 21:33619079-33654038 |
| 43: IFNAR2 | 21:33524076-33559839 |
| 44: IFNB1 | 9:21067104-21067962 |
| 45: IFNE1 | 9:21471067-21471693 |
| 46: IFNG | 12:66834816-66839790 |
| 47: IFNGR1 | 6:137560314-137582279 |
| 48: IFNGR2 | 21:33697072-33731698 |
| 49: IFNK | 9:27514302-27516491 |
| 50: IFNW1 | 9:21130213-21132144 |
| 51: IL10 | 1:205007570-205012462 |
| 52: IL10RA | 11:117362319-117377404 |
| 53: IL10RB | 21:33560533-33591409 |
| 54: IL11 | 19:60567569-60573626 |
| 55: IL11RA | 9:34636635-34651884 |
| 56: IL12A | 3:161189323-161196499 |
| 57: IL12B | 5:158674369-158690059 |
| 58: IL12RB1 | 19:18031701-18058702 |
| 59: IL12RB2 | 1:67545635-67635171 |
| 60: IL13 | 5:132021764-132024701 |
| 61: IL13RA1 | X:117745563-117812530 |
| 62: IL13RA2 | X:114144794-114159792 |
| 63: IL15 | 4:142777204-142874061 |
| 64: IL15RA | 10:6034340-6060156 |
| 65: IL19 | 1:205038838-205082949 |
| 66: IL2 | 4:123592080-123597339 |
| 67: IL20 | 1:205105322-205109191 |
| 68: IL20RA | 6:137362801-137407991 |
| 69: IL21 | 4:123753221-123761662 |
| 70: IL21R | 16:27321224-27369616 |
| 71: IL22 | 12:66928292-66933651 |
| 72: IL22RA1 | 1:24318848-24342198 |
| 73: IL22RA2 | 6:137506651-137536478 |
| 74: IL23A | 12:55018926-55020460 |
| 75: IL23R | 1:67404671-67498250 |
| 76: IL24 | 1:205137411-205144107 |
| 77: IL26 | 12:66881892-66905803 |
| 78: IL28A | 19:44451149-44452493 |
| 79: IL28B | 19:44426033-44427609 |
| 80: IL28RA | 1:24353234-24387036 |
| 81: IL29 | 19:44478805-44481152 |
| 82: IL2RA | 10:6092658-6144294 |
| 83: IL2RB | 22:35851824-35875908 |
| 84: IL2RG | X:70243979-70248188 |
| 85: IL3 | 5:131424121-131426796 |
| 86: IL3RA | X:1415509-1461581 |
| 87: IL4 | 5:132037272-132046267 |
| 88: IL4R | 16:27259005-27283599 |
| 89: IL5 | 5:131905035-131907113 |
| 90: IL5RA | 3:3086421-3127031 |
| 91: IL6 | 7:22732028-22738091 |
| 92: IL6R | 1:152644293-152708550 |
| 93: IL6ST | 5:55266680-55326529 |
| 94: IL7 | 8:79807564-79880313 |
| 95: IL7R | 5:35892748-35915462 |
| 96: IL9 | 5:135255834-135259415 |
| 97: IL9R | X:154880440-154893676 |
| 98: IRF9 | 14:23685936-23706451 |
| 99: JAK1 | 1:65071500-65204775 |
| 100: JAK2 | 9:4975245-5118183 |
| 101: JAK3 | 19:17788324-17819800 |
| 102: LEP | 7:127668567-127684917 |
| 103: LEPR | 1:65658858-65879830 |
| 104: LIF | 22:28966441-28972748 |
| 105: LIFR | 5:38510823-38631253 |
| 106: MPL | 1:43576065-43591030 |
| 107: MYC | 8:128817498-128822853 |
| 108: OSM | 22:28988821-28992840 |
| 109: OSMR | 5:38881893-38971500 |
| 110: PIAS1 | 15:66165695-66267392 |
| 111: PIAS2 | 18:42646058-42751464 |
| 112: PIAS3 | 1:144287346-144297903 |
| 113: PIAS4 | 19:3958748-3990383 |
| 114: PIK3CA | 3:180349005-180435189 |
| 115: PIK3CB | 3:139856921-139960875 |
| 116: PIK3CD | 1:9634390-9711564 |
| 117: PIK3CG | 7:106292977-106334801 |
| 118: PIK3R1 | 5:67547360-67633403 |
| 119: PIK3R2 | 19:18125016-18142343 |
| 120: PIK3R3 | 1:46278399-46371054 |
| 121: PIK3R5 | 17:8722953-8756559 |
| 122: PIM1 | 6:37245957-37251180 |
| 123: PRL | 6:22395459-22405709 |
| 124: PRLR | 5:35084621-35266334 |
| 125: PTPN11 | 12:111340919-111432099 |
| 126: PTPN6 | 12:6930763-6940740 |
| 127: SOCS1 | 16:11255775-11257540 |
| 128: SOCS2 | 12:92487729-92494109 |
| 129: SOCS3 | 17:73864459-73867753 |
| 130: SOCS4 | 14:54563594-54585957 |
| 131: SOCS5 | 2:46779595-46843424 |
| 132: SOCS7 | 17:33761531-33809541 |
| 133: SOS1 | 2:39066469-39201067 |
| 134: SOS2 | 14:49654812-49767751 |
| 135: SPRED1 | 15:36331808-36433526 |
| 136: SPRED2 | 2:65391492-65512815 |
| 137: SPRY1 | 4:124537406-124544357 |
| 138: SPRY2 | 13:79808112-79813918 |
| 139: SPRY3 | X:154650645-154665315 |
| 140: SPRY4 | 5:141670189-141684750 |
| 141: STAM | 10:17726130-17797919 |
| 142: STAM2 | 2:152683353-152740752 |
| 143: STAT1 | 2:191542121-191587181 |
| 144: STAT2 | 12:55021651-55040176 |
| 145: STAT3 | 17:37718869-37794039 |
| 146: STAT4 | 2:191602553-191724539 |
| 147: STAT5A | 17:37693091-37717484 |
| 148: STAT5B | 17:37604722-37681950 |
| 149: STAT6 | 12:55775462-55791428 |
| 150: TPO | 2:1396240-1525506 |
| 151: TSLP | 5:110433677-110441622 |
| 152: TYK2 | 19:10322205-10350114 |
Haematologica. 2010 Feb 4;
Wozniak MB, Villuendas R, Bischoff JR, Blanco-Aparicio C, Martínez Leal JF, de La Cueva P, Rodriguez ME, Herreros B, Martin-Perez D, Longo MI, Herrera M, Piris MA, Ortiz-Romero PL
Background Vorinostat [Suberoylanilide hydroxamic acid (SAHA)], an inhibitor of class I and II histone deacetylases (HDAC), has been approved for the treatment of cutaneous T-cell lymphoma (CTCL). In spite of emerging information on vorinostat effect on many cancer types, there is still little knowledge on mechanism of action, essential for the proper use in combination therapy. Herein, we investigate the alterations in gene expression profile (GEP) in CTCL cells treated with vorinostat over time. Subsequently, we have evaluated inhibitors of PI3K, PIM and HSP90 as potential combination agents in the treatment of CTCL. DESIGN AND METHODS: The genes significantly up- or down-regulated by vorinostat over different time periods (2-fold change, FDR corrected P-value<0.05) were selected using short-time series expression miner (STEM). Cell viability was examined in vitro in CTCL cells through measuring intracellular ATP content. Drug interactions were analysed by the combination index method with Calcusyn software. RESULTS: The functional analysis suggests that vorinostat modifies signaling of T cell receptor, MAPK, and Jak-STAT pathways. The phosphorylation studies of ZAP70 (Tyr319, Tyr493) and its downstream target AKT (Ser473) revealed that vorinostat inhibits phosphorylation of these kinases. Combination of vorinostat with PI3K inhibitors resulted in synergy while cytotoxic antagonism was observed when combining vorinostat with HSP90 inhibitor in CTCL. Conclusions These results demonstrate the potential targets of SAHA, underlining the importance of TCR signaling inhibition following vorinostat treatment. Additionaly, we show that combination therapies involving HDACi and inhibitors of PI3K can be potentially efficacious for the treatment of CTCL.
Evidence for microRNA Involvement in Exercise-Associated Neutrophil Gene Expression Changes.
J Appl Physiol. 2010 Jan 28;
Radom-Aizik S, Zaldivar FP, Oliver SR, Galassetti PR, Cooper DM
Exercise leads to a rapid change in the profile of gene expression in circulating neutrophils. MicroRNAs (miRNAs) have been discovered to play important roles in immune function and often act to attenuate or silence gene translation. We hypothesized that miRNA expression in circulating neutrophils would be affected by brief exercise. Eleven healthy men (19-30 yr old) performed ten 2-min bouts of cycle ergometer exercise interspersed with 1-min rest at a constant work equivalent to about 76% of VO2max. We used the Agilent Human miRNA V2 Microarray. A conservative statistical approach was used to determine that exercise significantly altered 38 miRNAs (20 had lower expression). Using RT-PCR, we verified the expression level changes from before to after exercise of 7 miRNAs. In silico analysis showed that collectively 36 miRNAs potentially targeted 4,724 genes (2 of the miRNAs had no apparent gene targets). Moreover, when we compared the gene expression changes (n=458) in neutrophils that have been altered by exercise, as previously reported, with the miRNAs altered by exercise, we identified three pathways, Ubiquitin-mediated proteolysis, Jak-STAT signaling pathway, and Hedgehog signaling pathway, in which an interaction of miRNA and gene expression was plausible. Each of these pathways is known to play a role in key mechanisms of inflammation. Brief exercise alters miRNA profile in circulating neutrophils in humans. These data support the hypothesis that exercise associated changes in neutrophil miRNA expression play a role in neutrophil gene expression in response to physical activity. Key words: leukocytes, granulocyte, epigenetic, immune system.
J Virol. 2010 Jan 27;
Laurent-Rolle M, Boer EF, Lubick KJ, Wolfinbarger JB, Carmody AB, Rockx B, Liu W, Ashour J, Shupert WL, Holbrook MR, Barrett AD, Mason PW, Bloom ME, Garcia-Sastre A, Khromykh AA, Best SM
Flaviviruses transmitted by arthropods represent a tremendous disease burden for humans, causing millions of infections annually. All vector-borne flaviviruses studied to date suppress host innate responses to infection by inhibiting interferon alpha/beta (IFN)-mediated Jak-STAT signal transduction. The viral nonstructural protein NS5 of some flaviviruses functions as the major IFN antagonist, associated with inhibition of IFN-dependent STAT1 phosphorylation (pY-STAT1) or with STAT2 degradation. West Nile virus (WNV) infection prevents pY-STAT1, although a role for WNV NS5 in IFN antagonism has not been fully explored. Here, we report that NS5 from the virulent NY99 strain of WNV prevented pY-STAT1 accumulation, suppressed IFN-dependent gene expression and rescued the growth of a highly IFN-sensitive virus (Newcastle disease virus) in the presence of IFN, suggesting that this protein can function as an efficient IFN antagonist. In contrast, NS5 from Kunjin virus (KUN), a naturally attenuated subtype of WNV, was a poor suppressor of pY-STAT1. Mutation of a single residue in KUN NS5 to the analogous residue in WNV-NY99 NS5 (S653F) rendered KUN NS5 an efficient inhibitor of pY-STAT1. Incorporation of this mutation into recombinant KUN resulted in 30-fold greater inhibition of Jak-STAT signaling compared to the wild-type virus and enhanced KUN replication in the presence of IFN. Thus, a naturally occurring mutation is associated with the function of NS5 in IFN antagonism and may influence virulence of WNV field isolates.
Interleukin-29 Binds to Melanoma Cells Inducing Jak-STAT Signal Transduction and Apoptosis.
Mol Cancer Ther. 2010 Jan 26;
Guenterberg KD, Grignol VP, Raig ET, Zimmerer JM, Chan AN, Blaskovits FM, Young GS, Nuovo GJ, Mundy BL, Lesinski GB, Carson WE
Interleukin-29 (IL-29) is a member of the type III IFN family that has been shown to have antiviral activity and to inhibit cell growth. Melanoma cell lines were tested for expression of the IL-29 receptor (IL-29R) and their response to IL-29. Expression of IL-28R1 and IL-10R2, components of IL-29R, was evaluated using reverse transcription-PCR. A combination of immunoblot analysis and flow cytometry was used to evaluate IL-29-induced signal transduction. U133 Plus 2.0 Arrays and real-time PCR were used to evaluate gene expression. Apoptosis was measured using Annexin V/propridium iodide staining. In situ PCR for IL-29R was done on paraffin-embedded melanoma tumors. Both IL-28R1 and IL-10R2 were expressed on the A375, 1106 MEL, Hs294T, 18105 MEL, MEL 39, SK MEL 5, and F01 cell lines. Incubation of melanoma cell lines with IL-29 (10-1,000 ng/mL) led to phosphorylation of signal transducer and activator of transcription 1 (STAT1) and STAT2. Microarray analysis and quantitative reverse transcription-PCR showed a marked increase in transcripts of IFN-regulated genes after treatment with IL-29. In the F01 cell line, bortezomib-induced and temozolomide-induced apoptosis was synergistically enhanced following the addition of IL-29. In situ PCR revealed that IL-10R2 and IL-28R1 were present in six of eight primary human melanoma tumors but not in benign nevi specimens. In conclusion, IL-29 receptors are expressed on the surface of human melanoma cell lines and patient samples, and treatment of these cell lines with IL-29 leads to signaling via the Jak-STAT pathway, the transcription of a unique set of genes, and apoptosis. Mol Cancer Ther; 9(2); OF1-11.
[The present state of research in direct antiviral mechanism of interferon on hepatitis B virus]
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2009 Dec; 26(6): 1358-62, 1371
Liu F, Tang H
In addition to immune regulation, interferon could suppress hepatitis B virus (HBV) replication through direct antiviral effect. After binding with the receptors on cell membrane, interferon directly inhibits HBV at different steps in HBV replication cycle by activating cell signaling cascades such as Jak-STAT pathway, interferon regulatory factor (IRFs) signaling pathway, and so on, followed by inducing a series of cytokines which are involved in regulation of the function of HBV enhancer I / X promoter (Ehn I / Xp). Also, interferon could induce the host cells to produce anti-viral proteins. This review describes the direct antiviral mechanism of interferon on HBV.
Glia. 2010 Jan 20;
Kirsch M, Trautmann N, Ernst M, Hofmann HD
Ciliary neurotrophic factor (CNTF) and the related cytokine leukemia inhibitory factor (LIF) have been implicated in regulating astrogliosis following CNS lesions. Application of the factors activates astrocytes in vivo and in vitro, and their expression as well as their receptors is upregulated after brain injury. Here, we investigated their function by studying Müller cell activation induced by optic nerve crush in CNTF- and LIF-deficient mice, and in animals with deficiencies in cytokine signaling pathways. In the retina of CNTF(-/-) mice, basal GFAP expression was reduced, but unexpectedly, injury-induced upregulation in activated Müller cells was increased during the first 3 days after lesion as compared to wild-type animals and this corresponded with higher phosphorylation level of STAT3, an indicator of cytokine signaling. The observation that LIF expression was strongly upregulated in CNTF(-/-) mice but not in wild-type animals following optic nerve lesion provided a possible explanation. In fact, additional ablation of the LIF gene in CNTF/LIF double knockout mice almost completely abolished early lesion-induced GFAP upregulation in Müller cells and STAT3 phosphorylation. Early Müller cell activation was also eliminated in LIF(-/-) mice, despite normal CNTF levels, as well as in mutants deficient in gp130/JAK/STAT signaling and in conditional STAT3 knockout mice. Our results demonstrate that LIF signaling via the gp130/JAK/STAT3 pathway is required for the initiation of the astrogliosis-like reaction of retinal Müller cells after optic nerve injury. A potential role of CNTF was possibly masked by a compensatory increase in LIF signaling in the absence of CNTF. (c) 2010 Wiley-Liss, Inc.
SMAD7 controls iron metabolism as a potent inhibitor of hepcidin expression.
Blood. 2009 Dec 29;
Mleczko-Sanecka K, Casanovas G, Ragab A, Breitkopf K, Muller A, Boutros M, Dooley S, Hentze MW, Muckenthaler MU
Hepcidin is the master regulatory hormone of systemic iron metabolism. Hepcidin deficiency causes common iron overload syndromes while its overexpression is responsible for microcytic anemias. Hepcidin transcription is activated by the bone morphogenetic protein (BMP) and the inflammatory Jak-STAT pathways, while comparatively little is known about how hepcidin expression is inhibited. Using high-throughput siRNA screening we identify SMAD7 as a potent hepcidin suppressor. SMAD7 is an inhibitory SMAD protein that mediates a negative feedback loop to both TGF-beta and BMP signaling and that recently was shown to be co-regulated with hepcidin via SMAD4 in response to altered iron availability in vivo. We show that SMAD7 is co-regulated with hepcidin by BMPs in primary murine hepatocytes and that SMAD7 overexpression completely abolishes hepcidin activation by BMPs and TGF-beta. We identify a distinct SMAD regulatory motif (GTCAAGAC) within the hepcidin promoter involved in SMAD7-dependent hepcidin suppression, demonstrating that SMAD7 does not simply antagonize the previously reported hemojuvelin/BMP-responsive elements. This work identifies a potent inhibitory factor for hepcidin expression and uncovers a negative feedback pathway for hepcidin regulation, providing insight into a mechanism how hepcidin expression may be limited to avoid iron deficiency.
J Cell Physiol. 2010 Apr; 223(1): 123-33
Mikami Y, Asano M, Honda MJ, Takagi M
Alkaline phosphatase (ALP) is generally believed to be a faithful marker of osteoblast differentiation, and its expression is induced by bone morphogenetic protein-2 (BMP-2) and dexamethasone (Dex). However, the effects of combined administration of BMP-2 and Dex on ALP transcription have not been extensively examined. In this study, we found that BMP-2 and Dex synergistically increase ALP levels in mouse C3H10T1/2 pluripotent stem cells. However, switching from one inducer to the other, by adding BMP-2 or Dex to cell cultures at different times, was no more effective than continuous treatment with either inducer alone. A significant induction of ALP mRNA expression was observed only in cells continuously treated with both inducers. This result suggests that both BMP-2 and Dex may act in the same pathway or at the same stage of differentiation. A luciferase assay using ALP promoter deletion constructs showed that a region of the promoter containing a putative signal transducer and activator of transcription 3 (STAT3) response element (SRE) responds to treatment with a combination of BMP-2 and Dex. Furthermore, a ChIP assay indicated that STAT3 bound to the SRE. In addition, a STAT3 siRNA suppressed the synergistic effect of BMP-2 and Dex on ALP levels. These results indicate that STAT3 may play an important role in regulating ALP expression. To our knowledge, this is the first time that STAT3 has been implicated in the regulation of ALP expression by BMP-2 and Dex. These findings raise the possibility of developing new strategies for the enhancement of bone formation using a combination of BMPs and Dex.
Activation of Jak-STAT and nitric oxide signaling as a mechanism for donor heart dysfunction.
J Heart Lung Transplant. 2009 Dec 16;
Bulcao CF, D'Souza KM, Malhotra R, Staron M, Duffy JY, Pandalai PK, Jeevanandam V, Akhter SA
BACKGROUND: Donor heart dysfunction (DHD) precluding procurement for transplantation occurs in up to 25% of brain-dead (BD) donors. The molecular mechanisms of DHD remain unclear. We investigated the potential role of myocardial interleukin (IL)-6 signaling through the JAK2-STAT3 pathway, which can lead to the generation of nitric oxide (NO) and decreased cardiac myocyte contractility. METHODS: Hearts were procured using standard technique with University of Wisconsin (UW) solution from 14 donors with a left ventricular (LV) ejection fraction of <35% (DHD). Ten hearts with normal function (NF) after BD served as controls. LV IL-6 was quantitated by enzyme-linked immunoassay (ELISA) and JAK2-STAT3 signaling was assessed by expression of phosphorylated STAT3. Inducible NO synthase (iNOS) and caspase-3 were measured by activity assays. RESULTS: Myocardial IL-6 expression was 8-fold greater in the DHD group vs NF controls. Phosphorylated STAT3 expression was 5-fold higher in DHD than in NF, indicating increased JAK2-STAT3 signaling. LV activity of iNOS was 2.5-fold greater in DHD than in NF. LV expression of the pro-apoptotic gene Bnip3 and caspase-3 activity were 3-fold greater in the DHD group than in the NF group. CONCLUSIONS: Myocardial IL-6 expression is significantly higher in the setting of DHD compared with hearts procured with normal function. This may lead to increased JAK2-STAT3 signaling and upregulation of iNOS, which has been shown to decrease cardiac myocyte contractility. Increased NO production may also lead to increased apoptosis through upregulation of Bnip3 gene expression. Increased iNOS signaling may be an important mechanism of DHD and represents a novel therapeutic target to improve cardiac function after BD.
Virology. 2009 Dec 13;
Chen Z, Lawson S, Sun Z, Zhou X, Guan X, Christopher-Hennings J, Nelson EA, Fang Y
The porcine reproductive and respiratory syndrome virus nsp1 is predicted to be auto-cleaved from the replicase polyprotein into nsp1alpha and nsp1beta subunits. In infected cells, we detected the actual existence of nsp1alpha and nsp1beta. Cleavage sites between nsp1alpha/nsp1beta and nsp1beta/nsp2 were identified by protein microsequencing analysis. Time course study showed that nsp1alpha and nsp1beta mainly localize into the cell nucleus after 10 h post infection. Further analysis revealed that both proteins dramatically inhibited IFN-beta expression. The nsp1beta was observed to significantly inhibit expression from an interferon-stimulated response element promoter after Sendai virus infection or interferon treatment. It was further determined to inhibit nuclear translocation of STAT1 in the Jak-STAT signaling pathway. These results demonstrated that nsp1beta has ability to inhibit both interferon synthesis and signaling, while nsp1alpha alone strongly inhibits interferon synthesis. These findings provide important insights into mechanisms of nsp1 in PRRSV pathogenesis and its impact in vaccine development.
Exp Neurol. 2010 Feb; 221(2): 353-66
Xiao Q, Du Y, Wu W, Yip HK
Bone morphogenetic proteins (BMPs) play a critical role in regulating cell fate determination during central nervous system (CNS) development. In light of recent findings that BMP-2/4/7 expressions are upregulated after spinal cord injury, we hypothesized that the BMP signaling pathway is important in regulating cellular composition in the injured spinal cord. We found that BMP expressions were upregulated in neural stem cells (NSCs), neurons, oligodendrocytes and microglia/macrophages. Increased expression levels of pSmad1/5/8 (downstream molecules of BMP) were detected in neurons, NSCs, astrocytes, oligodendrocytes and oligodendroglial progenitor cells (OPCs). Active astrocytes which form the astroglial scar were probably derived from NSCs, OPCs and resident astrocytes. Since quiescent NSCs in the normal adult spinal cord will proliferate and differentiate actively into neural cells after traumatic injury, we proposed that BMPs can regulate cellular components by controlling NSC differentiation. Neurosphere culture from adult mouse spinal cord showed that BMP-4 promoted astrocyte differentiation from NSCs while suppressing production of neurons and oligodendrocytes. Conversely, inhibition of BMP-4 by Noggin notably decreased the ratio of astrocyte to neuron numbers. However, intrathecal administration of Noggin in the injured spinal cord failed to attenuate glial fibrillar acidic protein (GFAP) expression even though it effectively reduced pSmad expression. Noggin treatment did not block phosphorylation of Stat3 and the induction of GFAP in the injured spinal cord, suggesting that in addition to the BMP/Smad pathway, the JAK/STAT pathway may also be involved in the regulation of GFAP expression after spinal cord injury.
STAT1/2 is involved in the inhibition of cell growth induced by U0126 in HeLa cells.
Cell Mol Biol (Noisy-le-grand). 2009; 55 Suppl: OL1168-74
Zhao LY, Huang C, Li ZF, Liu L, Ni L, Song TS
The mitogen-activated protein kinase (MAPK) signaling cascade plays an important role in cell life. Herein we show that small interfering RNAs targeting MAPK1 can inhibit HeLa cell growth and induce apoptosis along with up-regulation of signal transducers and activator 1 and 2 (STAT1/2). However, across-talk between the ras-raf-ERK1/2 signalling cascade and the Jak-STAT pathway remain largely unknown. Using MEK inhibitor U0126 and JAK-2 inhibitor AG490, we analyzed the relationship between ERK1/2 and STAT1/2 in HeLa cells. U0126 inhibited HeLa cell growth, arrested the cell cycle at G1/G0, and induced cell apoptosis, and AG490 partially reversed the effects of U0126. U0126 induced up-regulation of ERK1/2 and down-regulation of phosphorylated ERK1/2, increased STAT1 and STAT2 expression in a dose-dependent manner, and activated STAT1/2 via their phosphorylation. AG490 markedly inhibited the phosphorylation of STAT1 and STAT2 and slightly increased that of ERK1/2 inhibited by U0126. We suggest that STAT1/2 is involved in the inhibition of cell growth induced by U0126 in HeLa cells.
Molecular targets and regulators of cardiac hypertrophy.
Pharmacol Res. 2009 Dec 5;
Rohini A, Agrawal N, Koyani CN, Singh R
Cardiac hypertrophy is one of the main ways in which cardiomyocytes respond to mechanical and neurohormonal stimuli. It enables myocytes to increase their work output, which improves cardiac pump function. Although cardiac hypertrophy may initially represent an adaptive response of the myocardium, ultimately, it often progresses to ventricular dilatation and heart failure which is one of the leading causes of mortality in the western world. A number of signaling modulators that influence gene expression, apoptosis, cytokine release and growth factor signaling, etc. are known to regulate heart. By using genetic and cellular models of cardiac hypertrophy it has been proved that pathological hypertrophy can be prevented or reversed. This finding has promoted an enormous drive to identify novel and specific regulators of hypertrophy. In this review, we have discussed the various molecular signal transduction pathways and the regulators of hypertrophic response which includes calcineurin, cGMP, NFAT, natriuretic peptides, histone deacetylase, IL-6 cytokine family, Gq/G11 signaling, PI3K, MAPK pathways, Na/H exchanger, RAS, polypeptide growth factors, ANP, NO, TNF-alpha, PPAR and JAK/STAT pathway, microRNA, Cardiac angiogenesis and gene mutations in adult heart. Augmented knowledge of these signaling pathways and their interactions may potentially be translated into pharmacological therapies for the treatment of various cardiac diseases that are adversely affected by hypertrophy. The purpose of this review is to provide the current knowledge about the molecular pathogenesis of cardiac hypertrophy, with special emphasis on novel researches and investigations.
Exp Cell Res. 2010 Feb 15; 316(4): 603-14
Blank VC, Peña C, Roguin LP
In the search of mimetic peptides of the interferon-alpha2b molecule (IFN-alpha2b), we have previously designed and synthesized a chimeric cyclic peptide of the IFN-alpha2b that inhibits WISH cell proliferation by inducing an apoptotic response. Here, we first studied the ability of this peptide to activate intracellular signaling pathways and then evaluated the participation of some signals in the induction of apoptosis. Stimulation of WISH cells with the cyclic peptide showed tyrosine phosphorylation of Jak1 and Tyk2 kinases, tyrosine and serine phosphorylation of STAT1 and STAT3 transcription factors and activation of p38 MAPK pathway, although phosphorylation levels or kinetics were in some conditions different to those obtained under IFN-alpha2b stimulus. JNK and p44/42 pathways were not activated by the peptide in WISH cells. We also showed that STAT1 and STAT3 downregulation by RNA interference decreased the antiproliferative activity and the amount of apoptotic cells induced by the peptide. Pharmacological inhibition of p38 MAPK also reduced the peptide growth inhibitory activity and the apoptotic effect. Thus, we demonstrated that the cyclic peptide regulates WISH cell proliferation through the activation of Jak/STAT signaling pathway. In addition, our results indicate that p38 MAPK may also be involved in cell growth regulation. This study suggests that STAT1, STAT3 and p38 MAPK would be mediating the antitumor and apoptotic response triggered by the cyclic peptide in WISH cells.
J Virol. 2010 Feb; 84(4): 2027-37
Goodman AG, Zeng H, Proll SC, Peng X, Cillóniz C, Carter VS, Korth MJ, Tumpey TM, Katze MG
The innate immune response provides the first line of defense against foreign pathogens by responding to molecules that are a signature of a pathogenic infection. Certain RNA viruses, such as influenza virus, produce double-stranded RNA as an intermediate during the replication life cycle, which activates pathogen recognition receptors capable of inducing interferon production. By engaging interferon receptors, interferon activates the Jak-STAT pathway and results in the positive feedback of interferon production, amplifying the response to viral infection. To examine how deficiencies in interferon signaling affect the cellular response to infection, we performed influenza virus infections of mouse embryonic fibroblasts lacking the alpha/beta interferon receptor, the gamma interferon receptor, or both. In the absence of the alpha/beta interferon receptor, we observed increased viral replication but decreased activation of PKR, Stat1, and NF-kappaB; the presence or absence of the gamma interferon receptor did not exhibit discernible differences in these readouts. Analysis of gene expression profiles showed that while cells lacking the alpha/beta interferon receptor exhibited decreased levels of transcription of antiviral genes, genes related to inflammatory and apoptotic responses were transcribed to levels similar to those of cells containing the receptor. These results indicate that while the alpha/beta interferon receptor is needed to curb viral replication, it is dispensable for the induction of certain inflammatory and apoptotic genes. We have identified potential pathways, via interferon regulatory factor 3 (IRF3) activation or Hoxa13, Polr2a, Nr4a1, or Ing1 induction, that contribute to this redundancy. This study illustrates another way in which the host has evolved to establish several overlapping mechanisms to respond to viral infections.
Functional cooperation between Stat-1 and ets-1 to optimize icam-1 gene transcription.
Biochem Cell Biol. 2009 Dec; 87(6): 905-18
Yockell-Lelièvre J, Spriet C, Cantin P, Malenfant P, Heliot L, de Launoit Y, Audette M
Intercellular adhesion molecule-1 (ICAM-1) plays an important role in the immune system, enabling the interactions between effector cells and target cells. It is also known to be involved in tumor growth and metastasis. Its expression is transcriptionally regulated by several proinflammatory cytokines including IFN-gamma, which induces ICAM-1 transcription via the Jak-STAT signaling pathway in a Stat1-dependent fashion. The ICAM-1 promoter contains several cis-active regulatory elements including 2 Ets binding sites (EBSs) located at positions -158 and -138 relatively to the AUG, which were previously shown to play a role in the constitutive activity of the ICAM-1 promoter. In the present study, we have determined whether the EBSs are also involved in the regulation of ICAM-1 gene transcription by pro-inflammatory cytokines. Transient transfection assays were performed with reporter genes containing ICAM-1 promoter constructions cloned upstream from the firefly luciferase gene. Site-specific mutations of the EBS diminished the promoter activity stimulated by IFN-gamma, although the IFN-gamma responsive element (pIgammaRE), which binds Stat1, was intact. Stimulation of the transcriptional activity following IFN-gamma treatment was significantly reduced when both EBSs were inactivated. Co-immunoprecipitation experiments provided evidence of a physical interaction involving Ets1 and Stat1. In COS-1 and HEK 293 cells cotransfected with CFP-Stat1 and YFP-Ets fusion protein, fluorescence resonance energy transfer experiments confirmed the close proximity of these 2 proteins in living cells following treatment with IFN-gamma.
Heparin and suramin alter plitidepsin uptake via inhibition of GPCR coupled signaling.
J Chemother. 2009 Nov; 21(5): 550-7
Longo-Sorbello GS, Gao H, Mishra PJ, Kamen B, Soto A, Jimeno J, Aracil M, Paz de Paz MF, Bertino JR, Banerjee D
Plitidepsin (Aplidin) is a novel antitumor agent, derived from the mediterranean tunicate Aplidium albicans, and is currently in phase ii clinical trials with evidence of activity in heavily pretreated multiple myeloma, renal cell carcinoma, melanoma and neuroblastoma patients. As compared to its parental compound didemnin B, plitidepsin has shown a better therapeutic index with less bone marrow toxicity, cardiotoxicity and neurotoxicity in patients and a more potent cytotoxic effect in several tumor cell lines. As sensitivity to the drug varies between cell lines and fresh leukemia samples, we performed studies on transport of plitidepsin in leukemia and lymphoma cell lines to determine the mechanism of uptake. The drug is taken up by an active transport process, i.e. the process is temperature and energy dependent, and has a high-affinity binding site with Kt =212 nM and Vmax = 15 pmoles/min. Importantly, once inside the cell, efflux of plitidepsin is minimum, suggesting that the drug is bound to intracellular macromolecules. Further work showed that plitidepsin binds to G-Protein Coupled Receptors (GPCRs), since GPCR and GRK (GPCR kinases) inhibitors suramin and heparin respectively, markedly reduce the drug uptake and its cytotoxic activity. signaling via Jak/Stat pathway is inhibited by pharmacological concentrations of plitidepsin, further confirming the relationship between plitidepsin and GPCRs.
[Epigenetic mechanisms regulating neural cell fate determination]
No To Hattatsu. 2009 Nov; 41(6): 411-4
Nakashima K, Kohyama J, Namihira M, Gage FH, Okano H, Sawamoto K
Neural stem/progenitor cells (NSCs/NPCs) give rise to neurons, astrocytes, and oligodendrocytes. It has become apparent that intracellular epigenetic modification including DNA methylation, in concert with extracellular cues such as cytokine signaling, is deeply involved in specifiying the fate of NSCs/NPCs by defining cell-type specific gene expression. However, it is still unclear how differentiated neural cells retain their specific attributes by repressing cellular properties characteristic of other lineages. In previous work, we have shown that methyl-CpG binding protein transcriptional repressors (MBDs), which were expressed predominantly in neurons in the central nervous system, inhibited astrocyte-specific gene expression by binding to highly methylated regions of their target genes. Here we report that oligodendrocytes, which do not express MBDs, can transdifferentiate into astrocytes both in vitro (cytokine stimulation) and in vive (ischemic injury) through the activation of the JAK/STAT signaling pathway. These findings suggest that differentiation plasticity in neural cells is regulated by cell-intrinsic epigenetic mechanisms in collaboration with ambient cell-extrinsic cues.
J Dairy Sci. 2009 Dec; 92(12): 6186-91
Khatib H, Huang W, Mikheil D, Schutzkus V, Monson RL
Infertility is a major cause of dairy cow culling and economic loss. Signal transducer and activator of transcription (STAT) proteins are transcription factors that play an important role in fertility and early embryonic development, among many other functions. Previous studies have reported the association of several genes from the JAK/STAT signaling pathway with fertility traits in cattle. The STAT1 and STAT3 genes are members of this pathway and are known to interact with each other by forming a heterodimer complex that enters the nucleus and controls expression of specific genes. Thus, the objective of this study was to investigate the effects of the interactions between polymorphisms in these genes on fertilization and early embryonic survival rates using an in vitro fertilization system. A total of 7,519 oocytes, collected from 445 ovaries, were exposed to sperm and a total of 5,075 embryos were produced. Fertilization rate was calculated as the number of cleaved embryos at 48 h post-fertilization out of the total number of oocytes exposed to sperm. Early embryonic survival rate of embryos was calculated as the number of blastocysts on d 7 of development out of the total number of embryos cultured. Effects of ovary genotypes on fertilization and early embryonic survival rates were evaluated. Single-SNP analysis revealed a statistically significant association between SNP25402 in STAT3 and fertilization rate. Oocytes produced from ovaries with AA genotype showed a 0.701 fertilization rate versus 0.666 and 0.663 for oocytes produced from AC and CC ovaries, respectively. The interaction between STAT3 SNP (SNP19069/SNP25402) was highly significant for survival rate but not for fertilization rate. Also, the interaction between STAT1 SNP and SNP19069 was highly significant for survival rate. Genotype combinations found to promote fertilization and embryonic survival could be incorporated into breeding programs aimed at improving fertility performance in dairy cattle.
Oncostatin M and leukemia inhibitory factor increase hepcidin expression in hepatoma cell lines.
Int J Hematol. 2009 Dec; 90(5): 545-52
Kanda J, Uchiyama T, Tomosugi N, Higuchi M, Uchiyama T, Kawabata H
Overproduction of hepcidin by interleukin-6 (IL-6) is considered to be the main factor responsible for the development of anemia in inflammatory conditions. Since oncostatin M (OSM), a member of the IL-6 family, plays an important role in immune and inflammatory responses, we assessed the effect of OSM on hepcidin expression, as well as that of leukemia inhibitory factor (LIF), another member of the IL-6 family. We found that hepcidin expression was markedly induced by OSM and LIF in a time- and dose-dependent manner in hepatoma cell lines, and this expression was induced independent of IL-6/IL-6 receptor signaling. Luciferase assay revealed that OSM and LIF stimulated a -1.3-kb hepcidin promoter. This effect was markedly reduced when the signal transducer and activator of transcription (STAT) site of the promoter was mutated, and was almost completely abolished in the presence of AG-490, a Janus kinase (JAK) inhibitor. Hence, the JAK/STAT pathway plays a major role in OSM- and LIF-induced activation of the hepcidin promoter. In conclusion, we demonstrated that OSM and LIF can induce hepcidin expression mainly through the JAK/STAT pathways. Further studies are warranted to evaluate the clinical significance of OSM and LIF in the development of anemia in various inflammatory diseases.