KEGG ID: 04060
KEGG Diagram for Cytokine-cytokine receptor interaction
There are 152 IPI Records from this pathway found in Rattus norvegicus.
Location of Cytokine-cytokine receptor interaction proteins on Rat Genome
| IPI Record | Position |
|---|---|
| 1: Acvr1b | 7:139937993-139958724 |
| 2: Amh | 7:10417325-10419673 |
| 3: Amhr2 | 7:141203832-141212653 |
| 4: Bmpr1a | 16:10061939-10105854 |
| 5: Ccl2 | 10:70256263-70258061 |
| 6: Ccl22 | 19:10697324-10704129 |
| 7: Ccl28 | 2:51688294-51712931 |
| 8: Ccl3 | 10:71744559-71746109 |
| 9: Ccl5 | 10:71605827-71610342 |
| 10: Ccr1 | 8:128693658-128699213 |
| 11: Ccr1l1_predicted | 8:128728145-128729215 |
| 12: Ccr2 | 8:128892784-128893905 |
| 13: Ccr3 | 8:128759943-128769337 |
| 14: Ccr4 | 8:118883148-118884230 |
| 15: Ccr5 | 8:128907157-128912287 |
| 16: Ccr6 | 1:47115453-47139825 |
| 17: Ccr7 | 10:87925093-87929259 |
| 18: Ccr8_predicted | 8:125075457-125076518 |
| 19: Ccr9 | 8:128527929-128542009 |
| 20: Cd40lg | X:141925019-141937183 |
| 21: Clcf1 | 1:206802745-206806332 |
| 22: Cntf | 1:215842668-215844691 |
| 23: Cntfr | :- |
| 24: Csf1 | 2:203292765-203307956 |
| 25: Csf1r | 18:57061397-57107295 |
| 26: Csf2 | 10:39665850-39667831 |
| 27: Csf2ra | :- |
| 28: Csf2rb1 | 7:116237279-116271993 |
| 29: Csf3 | 10:87473990-87476365 |
| 30: Csf3r_predicted | 5:145377414-145393604 |
| 31: Ctf1 | 1:187001445-187006655 |
| 32: Cx3cl1 | 19:10666935-10676425 |
| 33: Cx3cr1 | 8:125033630-125047335 |
| 34: Cxcl10 | 14:17265986-17268183 |
| 35: Cxcl11 | 14:17250648-17253423 |
| 36: Cxcl12 | 4:153503576-153516423 |
| 37: Cxcl14 | 17:14286468-14294385 |
| 38: Cxcl16 | 10:57296111-57300721 |
| 39: Cxcl2 | 14:18677129-18679175 |
| 40: Cxcl4 | 14:18812550-18813259 |
| 41: Cxcl7 | 14:18816434-18817238 |
| 42: Cxcr3 | X:89794276-89796927 |
| 43: Cxcr4 | 13:41308286-41312170 |
| 44: Egf | 2:227107576-227194674 |
| 45: Egfr | 14:97617358-97788213 |
| 46: Epo | 12:19552436-19554617 |
| 47: Epor | 8:21061308-21065886 |
| 48: Faslg | 13:77472950-77480210 |
| 49: Flt1 | 12:7858092-8035966 |
| 50: Flt3 | 12:8193201-8268251 |
| 51: Flt4 | 10:35071002-35112006 |
| 52: Ghr | 2:52497358-52658066 |
| 53: Hgf | 4:14864357-14932513 |
| 54: Ifna1 | 5:108011739-108012317 |
| 55: Ifna11_predicted | 5:108150128-108150703 |
| 56: Ifna2_predicted | 5:108085633-108118114 |
| 57: Ifnar1_predicted | 11:31455064-31479849 |
| 58: Ifnb1 | 5:107837628-107838182 |
| 59: Ifng | 7:57621754-57625792 |
| 60: Ifngr1 | 1:14846414-14864896 |
| 61: Ifngr2_predicted | 11:31508768-31526039 |
| 62: Ifnk_predicted | 5:51730055-51804466 |
| 63: Il10 | 13:43953859-43958332 |
| 64: Il10ra | 8:48211040-48224439 |
| 65: Il11 | 1:67786388-67791611 |
| 66: Il11ra1 | 5:59193895-59202275 |
| 67: Il12a | 2:158710261-158717689 |
| 68: Il12b | 10:29558955-29567748 |
| 69: Il12rb1 | 16:19126653-19156365 |
| 70: Il12rb2 | 4:96929755-96995733 |
| 71: Il13 | 10:39093512-39096069 |
| 72: Il13ra1 | 11:73147652-73148932 |
| 73: Il15 | 19:27482376-27499255 |
| 74: Il17b | 18:57665334-57669564 |
| 75: Il17rb_predicted | 16:5336260-5349062 |
| 76: Il17r_predicted | 4:156838210-156862345 |
| 77: Il18 | 8:53936584-53943230 |
| 78: Il18r1_predicted | 9:39633726-39659382 |
| 79: Il1a | 3:116913612-116923352 |
| 80: Il1b | 3:116964427-116970887 |
| 81: Il1r1 | 9:39433337-39473646 |
| 82: Il1r2 | 9:39279397-39319675 |
| 83: Il1rap | 11:76092840-76222495 |
| 84: Il2 | 2:123655005-123659709 |
| 85: Il21_predicted | 2:123774331-123781697 |
| 86: Il23a | 7:1584112-1586226 |
| 87: Il2ra | 17:78051150-78097685 |
| 88: Il2rb | :- |
| 89: Il2rg | X:89339271-89346542 |
| 90: Il3 | 10:39684691-39687041 |
| 91: Il4 | 10:39074582-39080134 |
| 92: Il4ra | 1:184625287-184637860 |
| 93: Il5 | 10:39177783-39180657 |
| 94: Il5ra | 4:142067108-142098051 |
| 95: Il6 | 4:456799-461376 |
| 96: Il6ra | 2:182078051-182128147 |
| 97: Il6st | 2:43806301-43842365 |
| 98: Il7 | 2:96364592-96399206 |
| 99: Il7r_predicted | 2:59105666-59137997 |
| 100: Il8ra | :- |
| 101: Il8rb | 9:73470943-73477315 |
| 102: Il9 | 17:14068757-14071880 |
| 103: Il9r | 10:15678793-15690250 |
| 104: IPI00360197 | 17:77998621-78029657 |
| 105: IPI00373729 | :- |
| 106: IPI00766451 | :- |
| 107: IPI00767429 | :- |
| 108: Kdr | :- |
| 109: Kit | 14:34906043-34984819 |
| 110: Kitl | 7:37714331-37795726 |
| 111: Lep | 4:55934532-55946066 |
| 112: Lepr | 5:122385149-122503365 |
| 113: Lif | 14:84887856-84890630 |
| 114: Lifr | 2:56440206-56477198 |
| 115: LOC498335 | 14:15127072-15131368 |
| 116: LOC500590 | 5:168083864-168099322 |
| 117: Lta | 20:3657842-3659848 |
| 118: Ltbr | 4:161431862-161438265 |
| 119: Met | 4:43134183-43211357 |
| 120: MGC112688 | 4:161351793-161356688 |
| 121: Mpl_predicted | 5:138921476-138931990 |
| 122: Osm | 14:84857232-84860082 |
| 123: Pdgfa | 12:16155455-16172304 |
| 124: Prl | 17:44699101-44709162 |
| 125: Prlr | 2:59660849-59700727 |
| 126: RGD1559655_predicted | 5:154495319-154526724 |
| 127: RGD1559932_predicted | :- |
| 128: RGD1560373_predicted | 11:31380588-31397912 |
| 129: RGD1560810_predicted | 7:120596434-120597836 |
| 130: RGD1561519_predicted | 16:84825684-84855749 |
| 131: RGD1561714_predicted | 20:37114712-37164197 |
| 132: RGD1565911_predicted | :- |
| 133: Tgfbr1 | 5:63976868-64034058 |
| 134: Tgfbr2 | 8:120593595-120680453 |
| 135: Tnf | 20:3661000-3663618 |
| 136: Tnfrsf11a_predicted | 13:11983096-12014371 |
| 137: Tnfrsf11b | 7:90606424-90634431 |
| 138: Tnfrsf12a | 10:12940329-12942347 |
| 139: Tnfrsf19l_predicted | 1:158294776-158302421 |
| 140: Tnfrsf1a | 4:162172542-162185252 |
| 141: Tnfrsf1b | 5:163664139-163697484 |
| 142: Tnfrsf4 | 5:172856351-172859041 |
| 143: Tnfrsf5 | 3:156092602-156107432 |
| 144: Tnfrsf6 | 1:238259337-238274745 |
| 145: Tnfrsf8 | 5:163716462-163762235 |
| 146: Tnfsf13 | 10:56500597-56513053 |
| 147: Tnfsf18_predicted | 13:77136964-77145251 |
| 148: Tnfsf4 | 13:77026337-77050226 |
| 149: Tnfsf9 | :- |
| 150: Tpo | 6:47954848-48025740 |
| 151: Tslpr | :- |
| 152: Xcr1_predicted | 8:128615900-128616868 |
There are 152 IPI Records from this pathway found in Mus musculus.
Location of Cytokine-cytokine receptor interaction proteins on Mouse Genome
| IPI Record | Position |
|---|---|
| 1: Acvr1 | 2:58204030-58382543 |
| 2: Acvr1b | 15:101002159-101040635 |
| 3: Acvr2a | 2:48636166-48724172 |
| 4: Acvr2b | 9:119251215-119282213 |
| 5: Amh | 10:80208377-80210777 |
| 6: Amhr2 | 15:102273454-102282664 |
| 7: Bmp2 | 2:133244640-133254326 |
| 8: Bmp7 | 2:172512625-172583232 |
| 9: Bmpr1a | 14:33240158-33331638 |
| 10: Bmpr1b | 3:141774523-142106600 |
| 11: Bmpr2 | 1:59709199-59815028 |
| 12: Ccl1 | 11:81992854-81996007 |
| 13: Ccl11 | 11:81874046-81879144 |
| 14: Ccl17 | 8:97699582-97701164 |
| 15: Ccl19 | 4:42033456-42035464 |
| 16: Ccl2 | 11:81851769-81853422 |
| 17: Ccl22 | 8:97634719-97640698 |
| 18: Ccl24 | 5:135855212-135857676 |
| 19: Ccl25 | 8:4349822-4359515 |
| 20: Ccl27 | 4:42677011-42677753 |
| 21: Ccl28 | :- |
| 22: Ccl3 | 11:83464040-83465552 |
| 23: Ccl4 | 11:83478782-83480875 |
| 24: Ccl5 | 11:83341978-83346713 |
| 25: Ccl6 | 11:83404087-83409185 |
| 26: Ccl7 | 11:81861909-81863714 |
| 27: Ccl9 | 11:83389112-83394831 |
| 28: Ccr1 | 9:123810922-123817364 |
| 29: Ccr2 | 9:123954462-123957349 |
| 30: Ccr3 | 9:123870898-123879738 |
| 31: Ccr4 | 9:114339014-114345242 |
| 32: Ccr5 | :- |
| 33: Ccr6 | 17:8074386-8095301 |
| 34: Ccr7 | 11:98960286-98971167 |
| 35: Ccr8 | 9:119940831-119943604 |
| 36: Ccr9 | 9:123527137-123630663 |
| 37: Cd40 | 2:164746841-164762859 |
| 38: Cd40lg | X:53558927-53570826 |
| 39: Cd70 | 17:56831330-56835110 |
| 40: Clcf1 | 19:4214392-4222615 |
| 41: Cntf | 19:12830688-12862352 |
| 42: Cntfr | 4:41846167-41885710 |
| 43: Csf1 | 3:107869116-107888525 |
| 44: Csf1r | 18:61230941-61256506 |
| 45: Csf2 | 11:54090687-54093065 |
| 46: Csf2ra | 19:61279667-61282028 |
| 47: Csf2rb | 15:78153275-78177290 |
| 48: Csf2rb2 | 15:78109765-78132858 |
| 49: Csf3 | 11:98517403-98519719 |
| 50: Csf3r | 4:125529618-125546743 |
| 51: Ctf1 | 7:127503884-127509333 |
| 52: Cx3cl1 | 8:97661333-97671552 |
| 53: Cxcl1 | 5:91966511-91966993 |
| 54: Cxcl12 | 6:117134182-117146986 |
| 55: Cxcl13 | 5:96197241-96201370 |
| 56: Cxcl14 | 13:56298265-56306173 |
| 57: Cxcl15 | 5:91869741-91877100 |
| 58: Cxcl2 | 5:91979145-91979644 |
| 59: Cxcl4 | 5:91847703-91848577 |
| 60: Cxcl5 | 5:91834643-91836824 |
| 61: Cxcl9 | 5:93398190-93403317 |
| 62: Cxcr3 | X:97934255-97936866 |
| 63: Cxcr4 | 1:130415745-130419836 |
| 64: Cxcr6 | 9:123655197-123660458 |
| 65: Eda | X:96178500-96599875 |
| 66: Eda2r | X:93538638-93579891 |
| 67: Edar | 10:57996146-58071053 |
| 68: Egf | 3:129669600-129747338 |
| 69: Egfr | 11:16652206-16813912 |
| 70: Epo | 5:137712873-137714972 |
| 71: Epor | 9:21709306-21713908 |
| 72: Fas | 19:34356663-34393767 |
| 73: Fasl | 1:163617366-163625172 |
| 74: Flt1 | 5:147872545-148036360 |
| 75: Flt3 | 5:147641520-147710644 |
| 76: Flt3l | 7:44999231-45004474 |
| 77: Flt4 | 11:49453150-49495652 |
| 78: Gdf5 | 2:155632468-155636808 |
| 79: Ghr | 15:3267774-3533231 |
| 80: Hgf | 5:16065374-16131263 |
| 81: Ifna1 | 4:88321318-88321887 |
| 82: Ifna11 | 4:88291124-88292606 |
| 83: Ifna13 | 4:88115047-88115616 |
| 84: Ifna2 | 4:88154438-88155010 |
| 85: Ifna4 | 4:88313092-88313652 |
| 86: Ifna5 | 4:88306756-88307325 |
| 87: Ifna6 | :- |
| 88: Ifna7 | 4:88287459-88288031 |
| 89: Ifna9 | 4:88063037-88074607 |
| 90: Ifnab | 4:88161886-88162458 |
| 91: Ifnar1 | 16:91374108-91396296 |
| 92: Ifnar2 | 16:91261758-91294444 |
| 93: Ifnb1 | 4:87993457-87994005 |
| 94: Ifne1 | 4:88350832-88351410 |
| 95: Ifng | 10:117844040-117848885 |
| 96: Ifngr1 | 10:19281386-19299641 |
| 97: Ifngr2 | 16:91435953-91452866 |
| 98: Ifnk | 4:35340942-35342908 |
| 99: Il10 | 1:132847393-132852516 |
| 100: Il10ra | 9:45004833-45020131 |
| 101: Il10rb | 16:91295167-91314688 |
| 102: Il11 | 7:4376654-4379588 |
| 103: Il11ra1 | 4:41952093-41957631 |
| 104: Il11ra2 | :- |
| 105: Il12a | 3:68778573-68786454 |
| 106: Il12b | 11:44243486-44257456 |
| 107: Il12rb1 | 8:73737473-73750411 |
| 108: Il12rb2 | 6:67221596-67305715 |
| 109: Il13 | 11:53474747-53478125 |
| 110: Il13ra1 | X:32543584-32602707 |
| 111: Il15 | 8:85227661-85240228 |
| 112: Il15ra | 2:11623296-11651835 |
| 113: Il17a | 1:20716056-20719647 |
| 114: Il17b | 18:61813304-61817907 |
| 115: Il17ra | 6:120428866-120449348 |
| 116: Il17rb | 14:28825177-28837905 |
| 117: Il18 | 9:50327503-50334067 |
| 118: Il18r1 | 1:40410552-40445379 |
| 119: Il18rap | 1:40459908-40493851 |
| 120: Il19 | 1:132760202-132766787 |
| 121: Il1a | 2:128991051-129001413 |
| 122: Il1b | 2:129056011-129062561 |
| 123: Il1r1 | 1:40169626-40260723 |
| 124: Il1r2 | 1:40029314-40069773 |
| 125: Il1rap | 16:26497062-26640497 |
| 126: Il2 | 3:37312271-37317502 |
| 127: Il20 | 1:132734531-132738997 |
| 128: Il20ra | 10:19402003-19449469 |
| 129: Il21r | 7:125394642-125424418 |
| 130: Il22 | 10:117607935-117613040 |
| 131: Il22ra1 | 4:135000248-135024216 |
| 132: Il22ra2 | 10:19311456-19322568 |
| 133: Il23a | 10:127699089-127701033 |
| 134: Il23r | 6:67352943-67420314 |
| 135: Il24 | 1:132709620-132714885 |
| 136: Il25 | 14:53887188-53890043 |
| 137: Il28ra | 4:134958600-134980257 |
| 138: Il2ra | 2:11560703-11611044 |
| 139: Il2rb | 15:78307808-78322321 |
| 140: Il2rg | X:97467097-97470925 |
| 141: Il3 | 11:54108726-54110700 |
| 142: Il3ra | 14:13139762-13148759 |
| 143: Il4 | 11:53455891-53462067 |
| 144: Il4ra | 7:125356803-125369129 |
| 145: Il5 | 11:53564217-53568526 |
| 146: Il5ra | 6:106678159-106710113 |
| 147: Il6 | 5:30343948-30350755 |
| 148: Il6ra | 3:89955251-89999087 |
| 149: Il6st | 13:113584987-113627719 |
| 150: Il7 | 3:7556913-7587247 |
| 151: Il7r | 15:9450884-9474583 |
| 152: Il8ra | 1:74124995-74127838 |
| 153: Il8rb | 1:74087201-74094453 |
| 154: Il9 | 13:56488899-56491868 |
| 155: Il9r | 11:32088997-32100222 |
| 156: Inhba | 13:15805370-15818147 |
| 157: Inhbb | 1:121243011-121249794 |
| 158: Inhbc | 10:126759269-126773380 |
| 159: Inhbe | 10:126752505-126754721 |
| 160: Kdr | 5:76214954-76260125 |
| 161: Kit | 5:75856705-75938416 |
| 162: Kitl | 10:99445514-99518923 |
| 163: Lep | 6:29010231-29023886 |
| 164: Lepr | 4:101215336-101313489 |
| 165: Lif | 11:4157571-4172517 |
| 166: Lifr | 15:7101575-7138433 |
| 167: Lta | 17:34811218-34813403 |
| 168: Ltb | 17:34802574-34804354 |
| 169: Ltbr | 6:125272195-125279473 |
| 170: Met | 6:17441241-17521823 |
| 171: Mpl | 4:117940347-117955445 |
| 172: Ngfr | 11:95384908-95403788 |
| 173: Osm | 11:4136423-4141029 |
| 174: Osmr | 15:6760805-6821498 |
| 175: Pdgfa | 5:139229656-139248584 |
| 176: Pdgfb | 15:79823129-79842063 |
| 177: Pdgfc | 3:81122343-81299958 |
| 178: Pdgfd | 9:6168612-6377519 |
| 179: Pdgfra | 5:75434033-75479895 |
| 180: Pdgfrb | 18:61170519-61210428 |
| 181: Ppbp | 5:91843718-91845263 |
| 182: Prl | 13:27065042-27072657 |
| 183: Prlr | 15:10121963-10274098 |
| 184: Q80SS5_MOUSE | 4:88063037-88074607 |
| 185: Q810G3_MOUSE | 4:88028904-88043029 |
| 186: Relt | 7:100719935-100737482 |
| 187: Tgfb1 | 7:25395762-25413756 |
| 188: Tgfb2 | 1:188324430-188406777 |
| 189: Tgfb3 | 12:86945904-86968101 |
| 190: Tgfbr1 | 4:47374405-47436024 |
| 191: Tgfbr2 | 9:115932995-116023987 |
| 192: Tnf | 17:34807442-34810048 |
| 193: Tnfrsf10b | 14:68502562-68518625 |
| 194: Tnfrsf11a | 1:107608270-107672751 |
| 195: Tnfrsf11b | 15:54080702-54108567 |
| 196: Tnfrsf12a | 17:23403063-23405066 |
| 197: Tnfrsf13b | 11:60942950-60965567 |
| 198: Tnfrsf13c | 15:82048999-82051615 |
| 199: Tnfrsf14 | 4:153766010-153771877 |
| 200: Tnfrsf17 | 16:11227390-11233650 |
| 201: Tnfrsf18 | 4:154869964-154872695 |
| 202: Tnfrsf19 | 14:59924933-59978922 |
| 203: Tnfrsf1a | 6:125315374-125328103 |
| 204: Tnfrsf1b | 4:144479055-144513557 |
| 205: Tnfrsf21 | 17:42480039-42552546 |
| 206: Tnfrsf25 | 4:150959734-150963919 |
| 207: Tnfrsf4 | 4:154857495-154860412 |
| 208: Tnfrsf8 | 4:144535663-144581834 |
| 209: Tnfrsf9 | 4:149763990-149789893 |
| 210: Tnfsf10 | 3:27508150-27530738 |
| 211: Tnfsf11 | 14:77011609-77042189 |
| 212: Tnfsf12 | :- |
| 213: Tnfsf13 | 11:69498772-69512293 |
| 214: Tnfsf13b | 8:10006815-10035413 |
| 215: Tnfsf14 | 17:56874827-56879512 |
| 216: Tnfsf15 | 4:63213443-63231448 |
| 217: Tnfsf18 | 1:163331332-163343011 |
| 218: Tnfsf4 | 1:163232129-163254883 |
| 219: Tnfsf8 | 4:63319185-63347645 |
| 220: Tnfsf9 | 17:56790776-56792848 |
| 221: Tpo | 12:30640711-30718661 |
| 222: Tpte2 | 5:109795011-109799277 |
| 223: Tslp | 18:32958393-32962802 |
| 224: Vegfa | 17:45480574-45495331 |
| 225: Vegfb | 19:7049516-7054647 |
| 226: Vegfc | 8:55576304-55685794 |
| 227: Xcl1 | 1:166768323-166772189 |
| 228: Xcr1 | 9:123701016-123710826 |
There are 152 IPI Records from this pathway found in Homo sapiens.
Location of Cytokine-cytokine receptor interaction proteins on Human Genome
| IPI Record | Position |
|---|---|
| 1: ACVR1 | 2:158301207-158439869 |
| 2: ACVR1B | 12:50494095-50677124 |
| 3: ACVR2A | 2:148319067-148404863 |
| 4: ACVR2B | 3:38470814-38499869 |
| 5: AMH | 19:2200122-2203071 |
| 6: AMHR2 | 12:52103908-52111579 |
| 7: BMP2 | 20:6696311-6708927 |
| 8: BMP7 | 20:55177211-55275091 |
| 9: BMPR1A | 10:88506387-88674925 |
| 10: BMPR1B | 4:95898151-96295099 |
| 11: BMPR2 | 2:202949916-203140719 |
| 12: CCL1 | 17:29711512-29714365 |
| 13: CCL11 | 17:29636800-29639312 |
| 14: CCL13 | 17:29707584-29709741 |
| 15: CCL14 | 17:31334805-31353125 |
| 16: CCL15 | 17:31334805-31353125 |
| 17: CCL16 | 17:31327651-31332645 |
| 18: CCL17 | 16:56005294-56007475 |
| 19: CCL18 | 17:31415756-31422953 |
| 20: CCL19 | 9:34679564-34681274 |
| 21: CCL2 | 17:29606409-29608329 |
| 22: CCL20 | 2:228386814-228390494 |
| 23: CCL21 | 9:34699002-34700147 |
| 24: CCL22 | 16:55950219-55957600 |
| 25: CCL23 | 17:31364210-31369118 |
| 26: CCL24 | 7:75279050-75280969 |
| 27: CCL25 | 19:8023934-8033109 |
| 28: CCL26 | 7:75236788-75257150 |
| 29: CCL27 | 9:34651893-34656026 |
| 30: CCL28 | 5:43229915-43448250 |
| 31: CCL3 | 17:31439737-31441517 |
| 32: CCL4 | 17:31455333-31457127 |
| 33: CCL5 | 17:31222613-31231490 |
| 34: CCL7 | 17:29621354-29623373 |
| 35: CCL8 | 17:29670168-29672533 |
| 36: CCR1 | 3:46218204-46224836 |
| 37: CCR3 | 3:46227186-46283103 |
| 38: CCR4 | 3:32968070-32972840 |
| 39: CCR5 | 3:46386637-46392695 |
| 40: CCR7 | 17:35963550-35975250 |
| 41: CCR8 | 3:39346219-39351077 |
| 42: CCR9 | 3:45903023-45919671 |
| 43: CD27 | 12:6424327-6431144 |
| 44: CD40 | 20:44180318-44366257 |
| 45: CD40LG | X:135558002-135570215 |
| 46: CD70 | 19:6536867-6542163 |
| 47: CLCF1 | 11:66888219-66897782 |
| 48: CNTF | 11:58146721-58149778 |
| 49: CNTFR | 9:34541430-34579735 |
| 50: CRLF2 | X:1274890-1291527 |
| 51: CSF1 | 1:110254778-110275144 |
| 52: CSF1R | 5:149413051-149473128 |
| 53: CSF2 | 5:131437382-131439758 |
| 54: CSF2RA | X:1347693-1389274 |
| 55: CSF2RB | 22:35648168-35664764 |
| 56: CSF3 | 17:35425214-35427592 |
| 57: CSF3R | 1:36704231-36721466 |
| 58: CTF1 | 16:30815429-30822381 |
| 59: CX3CL1 | 16:55963900-55976455 |
| 60: CX3CR1 | 3:39279989-39298190 |
| 61: CXCL1 | 4:74953973-74968249 |
| 62: CXCL10 | 4:77161297-77163674 |
| 63: CXCL11 | 4:77173975-77176376 |
| 64: CXCL12 | 10:44185619-44200548 |
| 65: CXCL13 | 4:78745998-78752006 |
| 66: CXCL14 | 5:134934274-134942868 |
| 67: CXCL16 | 17:4583577-4589972 |
| 68: CXCL2 | 4:75181657-75183874 |
| 69: CXCL3 | 4:75121178-75123354 |
| 70: CXCL5 | 4:75080224-75083280 |
| 71: CXCL6 | 4:74921277-74923340 |
| 72: CXCL9 | 4:77141523-77147648 |
| 73: CXCR3 | X:70752491-70755092 |
| 74: CXCR4 | 2:136588909-136589979 |
| 75: CXCR6 | 3:45957429-45964833 |
| 76: EDA | X:68752636-69176036 |
| 77: EDA2R | X:65732204-65775608 |
| 78: EDAR | 2:108877366-108972260 |
| 79: EGF | 4:111053499-111152860 |
| 80: EGFR | 7:55054219-55242524 |
| 81: EPO | 7:100156359-100159257 |
| 82: EPOR | 19:11348883-11355883 |
| 83: FAS | 10:90739206-90765521 |
| 84: FASLG | 1:170894777-170902637 |
| 85: FLT1 | 13:27773790-27967232 |
| 86: FLT3 | 13:27475411-27572729 |
| 87: FLT3LG | 19:54669298-54681299 |
| 88: FLT4 | 5:179962143-180009171 |
| 89: GDF5 | 20:33484559-33505982 |
| 90: GH1 | 17:59348294-59349886 |
| 91: GH2 | 17:59311323-59312911 |
| 92: GHR | 5:42459783-42757736 |
| 93: HGF | 7:81166258-81237388 |
| 94: IFNA10 | 9:21196180-21197142 |
| 95: IFNA13 | 9:21430440-21431315 |
| 96: IFNA14 | 9:21191234-21229990 |
| 97: IFNA16 | 9:21206372-21207310 |
| 98: IFNA17 | 9:21217242-21218221 |
| 99: IFNA2 | 9:21374253-21375387 |
| 100: IFNA21 | 9:21155636-21156659 |
| 101: IFNA4 | 9:21176693-21177670 |
| 102: IFNA5 | 9:21294325-21295311 |
| 103: IFNA6 | 9:21339834-21341377 |
| 104: IFNA7 | 9:21191234-21229990 |
| 105: IFNA8 | 9:21399146-21400184 |
| 106: IFNAR1 | 21:33619079-33654038 |
| 107: IFNAR2 | 21:33524076-33559839 |
| 108: IFNB1 | 9:21067104-21067962 |
| 109: IFNE1 | 9:21471067-21471693 |
| 110: IFNG | 12:66834816-66839790 |
| 111: IFNGR1 | 6:137560314-137582279 |
| 112: IFNGR2 | 21:33697072-33731698 |
| 113: IFNK | 9:27514302-27516491 |
| 114: IFNW1 | 9:21130213-21132144 |
| 115: IL10 | 1:205007570-205012462 |
| 116: IL10RA | 11:117362319-117377404 |
| 117: IL10RB | 21:33560533-33591409 |
| 118: IL11 | 19:60567569-60573626 |
| 119: IL11RA | 9:34636635-34651884 |
| 120: IL12A | 3:161189323-161196499 |
| 121: IL12B | 5:158674369-158690059 |
| 122: IL12RB1 | 19:18031701-18058702 |
| 123: IL12RB2 | 1:67545635-67635171 |
| 124: IL13 | 5:132021764-132024701 |
| 125: IL13RA1 | X:117745563-117812530 |
| 126: IL15 | 4:142777204-142874061 |
| 127: IL15RA | 10:6034340-6060156 |
| 128: IL17A | 6:52159144-52163395 |
| 129: IL17B | 5:148734025-148739031 |
| 130: IL17RA | 22:15945858-15971387 |
| 131: IL17RB | 3:53855612-53874866 |
| 132: IL18 | 11:111519186-111540050 |
| 133: IL18R1 | 2:102345529-102381650 |
| 134: IL18RAP | 2:102401686-102435457 |
| 135: IL19 | 1:205038838-205082949 |
| 136: IL1A | 2:113247966-113259442 |
| 137: IL1B | 2:113303808-113310827 |
| 138: IL1R1 | 2:102125678-102159788 |
| 139: IL1R2 | 2:101974738-102011312 |
| 140: IL1RAP | 3:191714585-191858537 |
| 141: IL2 | 4:123592080-123597339 |
| 142: IL20 | 1:205105322-205109191 |
| 143: IL20RA | 6:137362801-137407991 |
| 144: IL21 | 4:123753221-123761662 |
| 145: IL21R | 16:27321224-27369616 |
| 146: IL22 | 12:66928292-66933651 |
| 147: IL22RA1 | 1:24318848-24342198 |
| 148: IL22RA2 | 6:137506651-137536478 |
| 149: IL23A | 12:55018926-55020460 |
| 150: IL23R | 1:67404671-67498250 |
| 151: IL24 | 1:205137411-205144107 |
| 152: IL25 | 14:22911858-22915445 |
| 153: IL26 | 12:66881892-66905803 |
| 154: IL28A | 19:44451149-44452493 |
| 155: IL28B | 19:44426033-44427609 |
| 156: IL28RA | 1:24353234-24387036 |
| 157: IL29 | 19:44478805-44481152 |
| 158: IL2RA | 10:6092658-6144294 |
| 159: IL2RB | 22:35851824-35875908 |
| 160: IL2RG | X:70243979-70248188 |
| 161: IL3 | 5:131424121-131426796 |
| 162: IL3RA | X:1415509-1461581 |
| 163: IL4 | 5:132037272-132046267 |
| 164: IL4R | 16:27259005-27283599 |
| 165: IL5 | 5:131905035-131907113 |
| 166: IL5RA | 3:3086421-3127031 |
| 167: IL6 | 7:22732028-22738091 |
| 168: IL6R | 1:152644293-152708550 |
| 169: IL6ST | 5:55266680-55326529 |
| 170: IL7 | 8:79807564-79880313 |
| 171: IL7R | 5:35892748-35915462 |
| 172: IL8 | 4:74825139-74828295 |
| 173: IL8RA | 2:218735815-218739961 |
| 174: IL8RB | 2:218698991-218710220 |
| 175: IL9 | 5:135255834-135259415 |
| 176: IL9R | X:154880440-154893676 |
| 177: INHBA | 7:41695126-41709231 |
| 178: INHBB | 2:120819469-120825444 |
| 179: INHBC | 12:56114810-56130876 |
| 180: INHBE | 12:56135363-56138056 |
| 181: KDR | 4:55639401-55686519 |
| 182: KIT | 4:55218842-55301638 |
| 183: KITLG | 12:87410697-87498369 |
| 184: LEP | 7:127668567-127684917 |
| 185: LEPR | 1:65658858-65879830 |
| 186: LIF | 22:28966441-28972748 |
| 187: LIFR | 5:38510823-38631253 |
| 188: LOC728045 | :- |
| 189: LOC729230 | 3:46370644-46377423 |
| 190: LTA | 6:31648042-31650080 |
| 191: LTB | 6:31656314-31658183 |
| 192: LTBR | 12:6363595-6370994 |
| 193: MET | 7:116099695-116223632 |
| 194: MPL | 1:43576065-43591030 |
| 195: NGFR | 17:44927654-44947356 |
| 196: OSM | 22:28988821-28992840 |
| 197: OSMR | 5:38881893-38971500 |
| 198: PDGFB | 22:37949310-37971006 |
| 199: PDGFC | 4:157902214-158111996 |
| 200: PDGFRA | 4:54790204-54859171 |
| 201: PDGFRB | 5:149473598-149515615 |
| 202: PF4 | 4:75065660-75066541 |
| 203: PF4V1 | 4:74937877-74939065 |
| 204: PLEKHQ1 | 15:62921167-62947252 |
| 205: PPBP | 4:75071622-75072764 |
| 206: PRL | 6:22395459-22405709 |
| 207: PRLR | 5:35084621-35266334 |
| 208: RELT | 11:72765053-72786166 |
| 209: TGFB1 | 19:46528254-46551628 |
| 210: TGFB2 | 1:216586200-216684584 |
| 211: TGFB3 | 14:75494195-75517242 |
| 212: TGFBR1 | 9:100907233-100956406 |
| 213: TGFBR2 | 3:30622998-30710635 |
| 214: TNF | 6:31678016-31680778 |
| 215: TNFRSF10A | 8:23104009-23138584 |
| 216: TNFRSF10B | 8:22933598-22982637 |
| 217: TNFRSF10C | 8:23016377-23030895 |
| 218: TNFRSF10D | 8:23049046-23077488 |
| 219: TNFRSF11A | 18:58143500-58205872 |
| 220: TNFRSF11B | 8:120004978-120033492 |
| 221: TNFRSF12A | 16:3010343-3012382 |
| 222: TNFRSF13B | 17:16783124-16816127 |
| 223: TNFRSF13C | 22:40650991-40652728 |
| 224: TNFRSF14 | 1:2479150-2486613 |
| 225: TNFRSF17 | 16:11966465-11969426 |
| 226: TNFRSF18 | 1:1128752-1131952 |
| 227: TNFRSF19 | 13:23042723-23148232 |
| 228: TNFRSF1A | 12:6308185-6321522 |
| 229: TNFRSF1B | 1:12149647-12191872 |
| 230: TNFRSF21 | 6:47307228-47385639 |
| 231: TNFRSF25 | 1:6443798-6502708 |
| 232: TNFRSF4 | 1:1136569-1139375 |
| 233: TNFRSF6B | 20:61759607-61800495 |
| 234: TNFRSF8 | 1:12046021-12126851 |
| 235: TNFRSF9 | 1:7902494-7923513 |
| 236: TNFSF10 | 3:173706159-173723963 |
| 237: TNFSF11 | 13:42034872-42079308 |
| 238: TNFSF12 | 17:7392932-7405649 |
| 239: TNFSF13 | 17:7392932-7405649 |
| 240: TNFSF13B | 13:107720067-107758826 |
| 241: TNFSF14 | 19:6615568-6621599 |
| 242: TNFSF15 | 9:116591421-116608227 |
| 243: TNFSF18 | 1:171275723-171286679 |
| 244: TNFSF4 | 1:171419494-171443094 |
| 245: TNFSF8 | 9:116704945-116732591 |
| 246: TNFSF9 | 19:6482037-6486933 |
| 247: TPO | 2:1396240-1525506 |
| 248: TSLP | 5:110433677-110441622 |
| 249: VEGFA | 6:43845924-43862202 |
| 250: VEGFB | 11:63758646-63762834 |
| 251: VEGFC | 4:177841685-177950889 |
| 252: XCL1 | 1:166812335-166817939 |
| 253: XCL2 | 1:166776626-166779859 |
| 254: XCR1 | 3:46037295-46043983 |
Exp Mol Pathol. 2009 Nov 16;
Jun L, Bardag-Gorce F, Oliva J, French BA, Dedes J, French SW
Propranolol, a beta adrenergic blocker prevents the blood alcohol (BAL) cycle in rats fed ethanol intragastrically at a constant rate by preventing the cyclic changes in the metabolic rate caused by fluctuating levels of norepinephrine released into the blood. The change in the rate of metabolism changes the rate of alcohol elimination in the blood which causes the BAL to cycle. Microarray analysis of the livers from the rats fed ethanol and propranolol showed similar changes in clusters of functionally related gene expressions. The controls and the trough of the cycle differed dramatically from the cluster pattern seen in the rats at the peaks of the blood alcohol cycle. The changes in gene expression induced by ethanol were similar when propranolol was fed without ethanol especially with the changes in the kinases and phosphatases, Toll-like receptor signaling and Cytokine-cytokine receptor interaction were also changed. The changes in gene expression caused by ethanol and propranolol feeding are alike probably because both drugs induce beta adrenergic receptor desensitization.
Pharmacol Res. 2009 Sep 9;
Hong D, Zeng X, Xu W, Ma J, Tong Y, Chen Y
Curcumin has extensive cardioprotective effects against diabetic cardiovascular complications, cardiac hypertrophy and myocardial infarction (MI), but the molecular mechanism behind such cardioprotective effects remains still unclear. To explore the mechanism of MI, a rat model of coronary artery ligation was used to assess the cardioprotective effects of curcumin. Microarray technology was employed to detect the gene expression in the heart of MI rats treated with curcumin. Semiquantitative RT-PCR was then performed to verify the microarray result. Our results showed that curcumin could improve heart function, diminish infarct size and reverse the abnormal changes in the activities of serum lactate dehydrogenase and creatine kinase MB in rats after MI. A total of 179 genes were found to be significantly differentially expressed between sham-operated rats and coronary artery-ligated rats. Cytokine-cytokine receptor interaction, ECM-receptor interaction, focal adhesions and colorectal cancer pathway may be involved in the cardioprotective effects of curcumin.
Physiol Genomics. 2009 Oct 7; 39(2): 100-8
Wessells H, Sullivan CJ, Tsubota Y, Engel KL, Kim B, Olson NE, Thorner D, Chitaley K
To determine specific molecular features of endothelial cells (ECs) relevant to the physiological process of penile erection we compared gene expression of human EC derived from corpus cavernosum of men with and without erectile dysfunction (HCCEC) to coronary artery (HCAEC) and umbilical vein (HUVEC) using Affymetrix GeneChip microarrays and GeneSifter software. Genes differentially expressed across samples were partitioned around medoids to identify genes with highest expression in HCCEC. A total of 190 genes/transcripts were highly expressed only in HCCEC. Gene Ontology classification indicated cavernosal enrichment in genes related to cell adhesion, extracellular matrix, pattern specification and organogenesis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed high expression of genes relating to ECM-receptor interaction, focal adhesions, and Cytokine-cytokine receptor interaction. Real-time PCR confirmed expression differences in cadherins 2 and 11, claudin 11 (CLDN11), desmoplakin, and versican. CLDN11, a component of tight junctions not previously described in ECs, was highly expressed only in HCCEC and its knockdown by siRNA significantly reduced transendothelial electrical resistance in HCCEC. Overall, cavernosal ECs exhibited a transcriptional profile encoding matrix and adhesion proteins that regulate structural and functional characteristics of blood vessels. Contribution of the tight junction protein CLDN11 to barrier function in endothelial cells is novel and may reflect hemodynamic requirements of the corpus cavernosum.
BMC Genomics. 2009; 10: 298
Rush C, Nyara M, Moxon JV, Trollope A, Cullen B, Golledge J
BACKGROUND: An animal model commonly used to investigate pathways and potential therapeutic interventions relevant to abdominal aortic aneurysm (AAA) involves subcutaneous infusion of angiotensin II within the apolipoprotein E deficient mouse. The aim of this study was to investigate genes differentially expressed in aneurysms forming within this mouse model in order to assess the relevance of this model to human AAA. RESULTS: Using microarrays we identified genes relevant to aneurysm formation within apolipoprotein E deficient mice. Firstly we investigated genes differentially expressed in the aneurysm prone segment of the suprarenal aorta in these mice. Secondly we investigated genes that were differentially expressed in the aortas of mice developing aneurysms relative to those that did not develop aneurysms in response to angiotensin II infusion. Our findings suggest that a host of inflammation and extracellular matrix remodelling pathways are upregulated within the aorta in mice developing aneurysms. Kyoto Encyclopedia of Genes and Genome categories enriched in the aortas of mice with aneurysms included Cytokine-cytokine receptor interaction, leukocyte transendothelial migration, natural killer cell mediated cytotoxicity and hematopoietic cell lineage. Genes associated with extracellular matrix remodelling, such as a range of matrix metalloproteinases were also differentially expressed in relation to aneurysm formation. CONCLUSION: This study is the first report describing whole genome expression arrays in the apolipoprotein E deficient mice in relation to aneurysm formation. The findings suggest that the pathways believed to be critical in human AAA are also relevant to aneurysm formation in this mouse model. The findings therefore support the value of this model to investigate interventions and mechanisms of human AAA.
Differential gene expression in umbilical cord blood and maternal peripheral blood.
Eur J Haematol. 2009 Sep; 83(3): 183-90
Merkerova M, Vasikova A, Bruchova H, Libalova H, Topinka J, Balascak I, Sram RJ, Brdicka R
OBJECTIVES: Umbilical cord blood (UCB) has become a useful alternative source of hematopoietic stem cells for clinical and research applications. UCB represents neonatal blood and differs from adult blood in many aspects, displaying different cell composition and various features of cellular immaturity. To understand molecular basis of phenotypic differences between neonatal and adult blood, we studied variations in transcriptome of UCB and maternal peripheral blood (PB). METHODS: Using Illumina microarrays, we determined gene expression profiles of UCB and PB samples obtained from 30 mothers giving birth to living baby. RESULTS: Out of 20,589 tested genes, 424 genes were down-regulated and 417 genes were up-regulated in UCB compared with PB. Reduced expression of many immunity-related pathways (e.g. TLR pathway, Jak-STAT pathway, Cytokine-cytokine receptor interaction) in neonatal blood cells may contribute to the poor response to antigens, increasing susceptibility to infections at the time of disappearance of protective maternal antibodies. On the other hand, overexpression of erythropoiesis-related genes (glycophorins, fetal hemoglobins, enzymes catalysing heme synthesis and erythrocyte differentiation) in UCB probably enforces red cell production in newborns. CONCLUSIONS: Our study demonstrates that neonatal and maternal bloods show specific gene expression profiles, likely reflecting differences in phenotypes of immunologically immature and fully evolved hematopoietic cells.
Gene expression profiling to define host response to baculoviral transduction in the brain.
J Neurochem. 2009 Jun; 109(5): 1203-14
Boulaire J, Zhao Y, Wang S
Recombinant baculoviral vectors efficiently transduce several types of cells in the brain. To characterize host responses to virus challenge, thus verifying the suitability of using baculovirus for the development of gene therapy strategies in the central nervous system, we used cDNA microarray technology to examine in vitro and in vivo global cellular gene expression profiles in the rat brain, cultured human astrocytes and human neuronal cells after viral transduction. We demonstrated that the transduction induced host antiviral responses as a major reaction in all three types of samples profiled. The related genes were mainly those associated with innate immunity, including several of the genes involved in Toll-like receptor signaling pathway and Cytokine-cytokine receptor interaction. These findings should be useful in understanding the molecular basis for neural cell response to baculoviral transduction and in guiding rational therapeutic applications of baculoviral vectors in the central nervous systems.
PLoS One. 2009; 4(4): e5188
Dey R, Ji K, Liu Z, Chen L
Interleukine-3 (IL-3) binds its receptor and initiates a cascade of signaling processes that regulate the proliferation and differentiation of hematopoietic cells. To understand the detailed mechanisms of IL-3 induced receptor activation, we generated a homology model of the IL-3:receptor complex based on the closely related crystal structure of the GM-CSF:receptor complex. Model-predicted interactions between IL-3 and its receptor are in excellent agreement with mutagenesis data, which validate the model and establish a detailed view of IL-3:receptor interaction. The homology structure reveals an IL-3:IL-3 interaction interface in a higher-order complex modeled after the dodecamer of the GM-CSF:receptor complex wherein an analogous GM-CSF:GM-CSF interface is also identified. This interface is mediated by a proline-rich hydrophobic motif (PPLPLL) of the AA' loop that is highly exposed in the structure of isolated IL-3. Various experimental data suggest that this motif is required for IL-3 function through receptor-binding independent mechanisms. These observations are consistent with structure-function studies of the GM-CSF:receptor complex showing that formation of the higher-order cytokine:receptor complex is required for signaling. However, a key question not answered from previous studies is how cytokine binding facilitates the assembly of the higher-order complex. Our studies here reveal a potential Cytokine-cytokine interaction that participates in the assembly of the dodecamer complex, thus linking cytokine binding to receptor activation.
Gene expression profiling of human mesenchymal stem cells chemotactically induced with CXCL12.
Cell Tissue Res. 2009 May; 336(2): 225-36
Stich S, Haag M, Häupl T, Sezer O, Notter M, Kaps C, Sittinger M, Ringe J
In situ tissue engineering is a promising approach in regenerative medicine, with the possibility that adult stem or progenitor cells will be guided chemotactically to a tissue defect and subsequently differentiate into the surrounding tissue type. Mesenchymal stem cells (MSC) represent attractive candidate cells. Chemokines such as CXCL12 (SDF-1alpha) chemoattract MSC, but little is known about the molecular processes involved in the chemotaxis and migration of MSC. In this study, MSC recruitment by CXCL12 was investigated by genome-wide microarray analysis. The dose-dependent migration potential of bone-marrow-derived MSC toward CXCL12 was measured in an in vitro assay, with a maximum being recorded at a concentration of 1,000 nM CXCL12. Microarray analysis of MSC stimulated with CXCL12 and non-stimulated controls showed 30 differentially expressed genes (24 induced and six repressed). Pathway analysis revealed 11 differentially expressed genes involved in cellular movement and Cytokine-cytokine receptor interaction, including those for migratory inducers such as the chemokines CXCL8 and CCL26, the leukocyte inhibitory factor, secretogranin II, and prostaglandin endoperoxide synthase 2. These results were confirmed by real-time polymerase chain reaction for selected genes. The obtained data provide further insights into the molecular mechanisms involved in chemotactic processes in cell migration and designate CXCL12 as a promising candidate for in situ recruitment in regenerative therapies.
Amphotericin B up-regulates angiogenic genes in hepatocellular carcinoma cell lines.
Eur J Clin Invest. 2009 Mar; 39(3): 239-45
Lin ZY, Chuang WL, Chuang YH
BACKGROUND: Amphotericin B (AmB) has a discordant influence on epirubicin (4'-epidoxorubicin) cytotoxicity in hepatocellular carcinoma (HCC). This indicates that the cellular function of HCC may be significantly influenced by AmB. Whether the influence of AmB on HCC has any possibility to influence cancer growth has not been studied. This study was to try and clarify this issue. MATERIALS AND METHODS: Two HCC cell lines including one without augmentation of the epirubicin cytotoxicity by AmB (cell line A; HCC24/KMUH) and one with this effect (cell line B; HCC38/KMUH) were studied by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and whole human genome microarray (experimental group: 2.5 microg mL(-1) AmB). RESULTS: Differential expressions of genes induced by AmB in two cell lines had no influence on cell proliferation as determined by MTT assay. Only cell line B showed up-regulation of genes related to oxidative stress, acute phase reaction, Cytokine-cytokine receptor interaction and complement and coagulation cascades. Among the chemokine genes up-regulated by AmB, five genes (CCL2, CXCL1, CXCL5, CXCL6, IL8) were angiogenic. Cell line B also showed up-regulation of one angiogenic C10orf10 gene and down-regulation of one angiostatic chemokine gene (CXCL10). Up- or down-regulation of other genes in cell line A and B did not show any evidence to promote angiogenesis. CONCLUSION: AmB has the capacity to concomitantly up-regulate angiogenic genes in HCC cells susceptible to AmB-induced oxidative stress.
Detection of Deregulated Pathways to Lymphatic Metastasis in Oral Squamous Cell Carcinoma.
Pathol Oncol Res. 2009 Feb 12;
Zhao E, Xu J, Yin X, Sun Y, Shi J, Li X
Oral squamous cell carcinoma (OSCC) is a common malignancy, in which lymph node metastasis is a major determinant of outcome. The pathway deregulation resulting from a large number of somatic genetic alterations in the development of the tumor, plays an important role in lymphatic metastasis process. To detect the deregulated pathways to lymphatic metastasis in OSCC, we performed pathway-oriented analysis using gene expression profile from 16 samples without lymphatic metastasis and 27 samples with lymphatic metastasis. We identified seven significantly (p < 0.05) deregulated pathways: the erythropoietin signaling pathway, signaling pathway from G-protein families, Cytokine-cytokine receptor interaction, the Janus kinase-signal transducer and activator of transcription signaling pathway, ribosome, colorectal cancer, B cell receptor signaling pathway. The biological relevance of these pathways to OSCC is the focus of ongoing studies, as well as complex interactions and crosstalk between them. These pathways might provide additional clues about factors that regulate the course for OSCC patients and might offer new opportunities for therapeutic intervention.
Arthritis Res Ther. 2009; 11(1): R15
Andreas K, Häupl T, Lübke C, Ringe J, Morawietz L, Wachtel A, Sittinger M, Kaps C
INTRODUCTION: Rheumatoid arthritis (RA) leads to progressive destruction of articular cartilage. This study aimed to disclose major mechanisms of antirheumatic drug action on human chondrocytes and to reveal marker and pharmacological target genes that are involved in cartilage dysfunction and regeneration. METHODS: An interactive in vitro cultivation system composed of human chondrocyte alginate cultures and conditioned supernatant of SV40 T-antigen immortalised human synovial fibroblasts was used. Chondrocyte alginate cultures were stimulated with supernatant of RA synovial fibroblasts, of healthy donor synovial fibroblasts, and of RA synovial fibroblasts that have been antirheumatically treated with disease-modifying antirheumatic drugs (DMARDs) (azathioprine, gold sodium thiomalate, chloroquine phosphate, and methotrexate), nonsteroidal anti-inflammatory drugs (NSAIDs) (piroxicam and diclofenac), or steroidal anti-inflammatory drugs (SAIDs) (methylprednisolone and prednisolone). Chondrocyte gene expression profile was analysed using microarrays. Real-time reverse transcription-polymerase chain reaction and enzyme-linked immunosorbent assay were performed for validation of microarray data. RESULTS: Genome-wide expression analysis revealed 110 RA-related genes in human chondrocytes: expression of catabolic mediators (inflammation, cytokines/chemokines, and matrix degradation) was induced, and expression of anabolic mediators (matrix synthesis and proliferation/differentiation) was repressed. Potential marker genes to define and influence cartilage/chondrocyte integrity and regeneration were determined and include already established genes (COX-2, CXCR-4, IL-1RN, IL-6/8, MMP-10/12, and TLR-2) and novel genes (ADORA2A, BCL2-A1, CTGF, CXCR-7, CYR-61, HSD11B-1, IL-23A, MARCKS, MXRA-5, NDUFA4L2, NR4A3, SMS, STS, TNFAIP-2, and TXNIP). Antirheumatic treatment with SAIDs showed complete and strong reversion of RA-related gene expression in human chondrocytes, whereas treatment with NSAIDs and the DMARD chloroquine phosphate had only moderate to minor effects. Treatment with the DMARDs azathioprine, gold sodium thiomalate, and methotrexate efficiently reverted chondrocyte RA-related gene expression toward the 'healthy' level. Pathways of Cytokine-cytokine receptor interaction, transforming growth factor-beta/Toll-like receptor/Jak-STAT (signal transducer and activator of transcription) signalling and extracellular matrix receptor interaction were targeted by antirheumatics. CONCLUSIONS: Our findings indicate that RA-relevant stimuli result in the molecular activation of catabolic and inflammatory processes in human chondrocytes that are reverted by antirheumatic treatment. Candidate genes that evolved in this study for new therapeutic approaches include suppression of specific immune responses (COX-2, IL-23A, and IL-6) and activation of cartilage regeneration (CTGF and CYR-61).
Toxicol Appl Pharmacol. 2009 Jan 15; 234(2): 156-65
Gerecke DR, Chen M, Isukapalli SS, Gordon MK, Chang YC, Tong W, Androulakis IP, Georgopoulos PG
Sulfur mustard (HD, SM), is a chemical warfare agent that within hours causes extensive blistering at the dermal-epidermal junction of skin. To better understand the progression of SM-induced blistering, gene expression profiling for mouse skin was performed after a single high dose of SM exposure. Punch biopsies of mouse ears were collected at both early and late time periods following SM exposure (previous studies only considered early time periods). The biopsies were examined for pathological disturbances and the samples further assayed for gene expression profiling using the Affymetrix microarray analysis system. Principal component analysis and hierarchical cluster analysis of the differently expressed genes, performed with ArrayTrack showed clear separation of the various groups. Pathway analysis employing the KEGG library and Ingenuity Pathway Analysis (IPA) indicated that Cytokine-cytokine receptor interaction, cell adhesion molecules (CAMs), and hematopoietic cell lineage are common pathways affected at different time points. Gene ontology analysis identified the most significantly altered biological processes as the immune response, inflammatory response, and chemotaxis; these findings are consistent with other reported results for shorter time periods. Selected genes were chosen for RT-PCR verification and showed correlations in the general trends for the microarrays. Interleukin 1 beta was checked for biological analysis to confirm the presence of protein correlated to the corresponding microarray data. The impact of a matrix metalloproteinase inhibitor, MMP-2/MMP-9 inhibitor I, against SM exposure was assessed. These results can help in understanding the molecular mechanism of SM-induced blistering, as well as to test the efficacy of different inhibitors.
Oncol Rep. 2008 Oct; 20(4): 825-43
Roman E, Meza-Zepeda LA, Kresse SH, Myklebost O, Vasstrand EN, Ibrahim SO
We used microarray-based comparative genomic hybridization to explore genome-wide profiles of chromosomal aberrations in 26 samples of head and neck cancers compared to their pair-wise normal controls. The samples were obtained from Sudanese (n=11) and Norwegian (n=15) patients. The findings were correlated with clinicopathological variables. We identified the amplification of 41 common chromosomal regions (harboring 149 candidate genes) and the deletion of 22 (28 candidate genes). Predominant chromosomal alterations that were observed included high-level amplification at 1q21 (harboring the S100A gene family) and 11q22 (including several MMP family members). Regions of copy number increase was also identified at 6p21 (p21), 7p12 (EGFR), 17p13 (p53) and 19p13.2 (p19INK4d), while regions showing deletion included among others 3p25.2 (RAF1) and 9p21 (p15, p16). We found genes from four common biological pathways (MAPK signaling, Cytokine-cytokine receptor interaction, ECM-receptor interaction and Jak-STAT signaling) to be predominantly over-represented in areas of gain and loss. The current study provides valuable information on chromosomal aberrations likely to be involved in the pathogenesis of head and neck cancers. An increased copy number of the S100A and MMP gene family members, known to be involved in invasion and metastasis, may play an important role in the development of the tumors. Hierarchical clustering of the chromosomal alterations with clinicopathological parameters showed little correlation, suggesting an occurrence of gains/losses regardless of ethnic differences and clinicopathological status between the patients from the two countries. Our findings indicate the existence of common gene-specific amplifications/deletions in these tumors, regardless of the source of the samples or attributed carcinogenic risk factors.
Detection of deregulated pathways to lymphatic metastasis in oral squamous cell carcinoma.
Pathol Oncol Res. 2009 Jun; 15(2): 217-23
Zhao E, Xu J, Yin X, Sun Y, Shi J, Li X
Oral squamous cell carcinoma (OSCC) is a common malignancy, in which lymph node metastasis is a major determinant of outcome. The pathway deregulation resulting from a large number of somatic genetic alterations in the development of the tumor, plays an important role in lymphatic metastasis process. To detect the deregulated pathways to lymphatic metastasis in OSCC, we performed pathway-oriented analysis using gene expression profile from 16 samples without lymphatic metastasis and 27 samples with lymphatic metastasis. We identified seven significantly (p < 0.05) deregulated pathways: the erythropoietin (EPO) Signaling Pathway, Signaling Pathway from G-Protein Families, Cytokine-cytokine receptor interaction, the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling pathway, Ribosome, Colorectal cancer, B cell receptor signaling pathway. The biological relevance of these pathways to OSCC is the focus of ongoing studies, as well as complex interactions and crosstalk between them. These pathways might provide additional clues about factors that regulate the course for OSCC patients and might offer new opportunities for therapeutic intervention.
Chin Med J (Engl). 2008 Jul 5; 121(13): 1215-9
Hua CX, Li YS, Liu YQ, Liu H, Li N, Wu Y, Xu L, Huang YL
BACKGROUND: Statins are potent lipid-lowering agents widely used in medical practice. There has been growing evidence suggesting the pleiotropic effects of statins in addition to the lipid-lowering effect. However, it is still unclear how rapidly the beneficial effects of statins occur. The transcriptome of peripheral blood cells can be used as a sensor to drug therapy. The purpose of the study was to investigate the acute effects of rosuvastatin both on lipids profile and gene expression of peripheral leukocytes following therapy with a single dose of rosuvastatin. METHODS: Thirty healthy Chinese male volunteers were enrolled. The serum lipids, high-sensitivity C-reactive protein, and plasma fibrinogen were determined before and 72 hours after administration of 20 mg of rosuvastatin. The differentially expressed genes of peripheral leukocytes after administration of rosuvastatin were screened using human oligonucleotide microarray gene expression chips. Then four of the differentially expressed genes including ATM, CASP8, IL8RB and S100B were verified by real-time polymerase chain reaction (PCR). RESULTS: Rosuvastatin decreased both serum total cholesterol and low-density lipoprotein cholesterol significantly 72 hours after administration of a single dose of 20 mg rosuvastatin. However, no significant changes occurred in blood high-density lipoprotein cholesterol, triglycerides, C-reactive protein and fibrinogen after the treatment. A total of 24 genes were differentially expressed after the treatment. They were involved in important cell biological processes such as Cytokine-cytokine receptor interaction, apoptosis signaling, etc. CONCLUSIONS: Rosuvastatin rapidly modulates the serum lipids and affects the gene expression of peripheral leukocytes in healthy volunteers. This finding provides some new clues for further studies on its potential pleiotropic effects.
Xi Bao Yu Fen Zi Mian Yi Xue Za Zhi. 2008 Jun; 24(6): 553-6
Sun J, Chang GF, LE GW, Shi YH
AIM: To investigate the mechanism that Lactobacillus peptidoglycan modulates mice immune response. METHODS: BALB/c mice were administrated (i.p.) with Lactobacillus peptidoglcyan once or three times. Peritoneal macrophages and spleen lymphocytes were isolated for gene expression analysis using genearray. PathwayExplorer and GeneMAPP were used to explore significant pathway in database. RESULTS: The analysis resulted in five significant pathways: Cytokine-cytokine receptor interaction, T helper cell surface molecules, ribosomal proteins, inflammatory response pathway and mm heme biosynthesis. CONCLUSION: Lactobacillus peptidoglycan induced expression of considerable genes, which related to protective immune response and activation of Th cells. The induced immune response might be Th1 type.
Physiol Genomics. 2008 Jul 15; 34(2): 162-84
Roy S, Khanna S, Rink C, Biswas S, Sen CK
This work represents a maiden effort to systematically screen the transcriptome of the healing wound-edge tissue temporally using high-density GeneChips. Changes during the acute inflammatory phase of murine excisional wounds were characterized histologically. Sets of genes that significantly changed in expression during healing could be segregated into the following five sets: up-early (6-24 h; Cytokine-cytokine receptor interaction pathway), up-intermediary (12-96 h; leukocyte-endothelial interaction pathway), up-late (48-96 h; cell-cycle pathway), down-early (6-12 h; purine metabolism) and down-intermediary (12-96 h; oxidative phosphorylation pathway). Results from microarray and real-time PCR analyses were consistent. Results listing all genes that were significantly changed at any specific time point were further mined for cell-type (neutrophils, macrophages, endothelial, fibroblasts, and pluripotent stem cells) specificity. Candidate genes were also clustered on the basis of their functional annotation, linking them to inflammation, angiogenesis, reactive oxygen species (ROS), or extracellular matrix (ECM) categories. Rapid induction of genes encoding NADPH oxidase subunits and downregulation of catalase in response to wounding is consistent with the fact that low levels of endogenous H2O2 is required for wound healing. Angiogenic genes, previously not connected to cutaneous wound healing, that were induced in the healing wound-edge included adiponectin, epiregulin, angiomotin, Nogo, and VEGF-B. This study provides a digested database that may serve as a valuable reference tool to develop novel hypotheses aiming to elucidate the biology of cutaneous wound healing comprehensively.
Gene expression profile in obesity and type 2 diabetes mellitus.
Lipids Health Dis. 2007; 6: 35
Das UN, Rao AA
Obesity is an important component of metabolic syndrome X and predisposes to the development of type 2 diabetes mellitus. The incidence of obesity, type 2 diabetes mellitus and metabolic syndrome X is increasing, and the cause(s) for this increasing incidence is not clear. Although genetics could play an important role in the higher prevalence of these diseases, it is not clear how genetic factors interact with environmental and dietary factors to increase their incidence. We performed gene expression profile in subjects with obesity and type 2 diabetes mellitus with and without family history of these diseases. It was noted that genes involved in carbohydrate, lipid and amino acid metabolism pathways, glycan of biosynthesis, metabolism of cofactors and vitamin pathways, ubiquitin mediated proteolysis, signal transduction pathways, neuroactive ligand-receptor interaction, nervous system pathways, neurodegenerative disorders pathways are upregulated in obesity compared to healthy subjects. In contrast genes involved in cell adhesion molecules, Cytokine-cytokine receptor interaction, insulin signaling and immune system pathways are downregulated in obese. Genes involved in signal transduction, regulation of actin cytoskeleton, antigen processing and presentation, complement and coagulation cascades, axon guidance and neurodegenerative disorders pathways are upregulated in subjects with type 2 diabetes with family history of diabetes compared to those who are diabetic but with no family history. Genes involved in oxidative phosphorylation, immune, nervous system, and metabolic disorders pathways are upregulated in those with diabetes with family history of diabetes compared to those with diabetes but with no family history. In contrast, genes involved in lipid and amino acid pathways, ubiquitin mediated proteolysis, signal transduction, insulin signaling and PPAR signaling pathways are downregulated in subjects with diabetes with family history of diabetes. It was noted that genes involved in inflammatory pathway are differentially expressed both in obesity and type 2 diabetes. These results suggest that genes concerned with carbohydrate, lipid and amino acid metabolic pathways, neuronal function and inflammation play a significant role in the pathobiology of obesity and type 2 diabetes.
[Differential gene expression profile in seasonal allergic rhinitis with and without asthma]
Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi. 2007 Sep; 42(9): 654-9
Xue JM, Zhao CQ, Zhao HL, Liang AH, Xie J
OBJECTIVE: To screen the differential expression gene profile in nasal mucosa of seasonal allergic rhinitis (SAR) and SAR with asthma, oligonucleotide microarray (Affymetrix HG-U133-plus2) was employed to analyze the changes of gene expressions with GeneSpring software. METHODS: Inferior turbinate mucosa was obtained from five SAR patients and four SAR with asthma patients. Total RNA was extracted from the nasal mucosal biopsies and pooled into one SAR control pool and one SAR with asthma patient pool, and biotin-labeled cRNA probes were hybridized with Affymetrix HG-U133-plus2 array. The hybridization results were confirmed by RT-PCR analysis. The analysis of differential expression profiles were performed by GeneSpring software 7.3. RESULTS: Out of 47,000 analysed transcripts, 1,900 genes were differentially expressed at least 2-fold in which 849 genes were up-regulated and 1,051 genes were down-regulated in nasal mucosa of SAR with asthma patients compared with that in SAR patients. These genes were involved in cell metabolism, gene transcription, cell proliferation, signal transduction, immune response, enzyme activity, transmembrane receptor activity, cytoskeletal protein binding, and many other aspects. Pathway analysis displayed 161 groups, of which including more than 20 genes were as follow: Cytokine-cytokine receptor interaction, focal adhesion, cell adhesion molecules (CAMs), regulation of actin cytoskeleton, cell communication, gap junction, MAPK signaling pathway, calcium signaling pathway, leukocyte transendothelial migration, and purine metabolism. CONCLUSIONS: The data suggested that multigenetic expression and regulation changes were involved in the development of SAR and SAR complicated with asthma, whose molecular mechanisms might be elucidated by identification of these differential genes.
Oncol Rep. 2007 Sep; 18(3): 569-79
Chang MY, Yu YP, Tsai JR, Sheu CC, Chong IW, Lin SR
The present study systematically explores the biological pathways and altered expression of genes speculatively participating in lung carcinogenesis by using oligonucleotide microarray-bioinformatic analysis methods. The results revealed that 1,396 genes were up-regulated and 1,965 were down-regulated in lung adenocarcinoma carcinogenesis. Gene ontology and relevant bioinformatics tools indicated that the functional category to which the most frequently differentially expressed genes were classified, was to the Cytokine-cytokine receptor interaction pathway, focal adhesion pathway and the mitogen-activated protein kinase signaling pathway. Furthermore, we constructed a membrane array, consisting of 51 up-regulated genes in lung adenocarcinoma, in order to verify the biological pathways involved in the carcinogenesis of lung cancer. The analysis of 45 lung adenocarcinoma tissue specimens demonstrated that the genes involved in these three biological pathways had high rates of overexpression. Out of the 51 genes, 17 genes were demonstrated to be overexpressed in all 45 lung adenocarcinoma tissues compared to the paired normal lung tissues. These findings could have implications in understanding the process of lung adenocarcinoma carcinogenesis. Moreover, our developed membrane arrays could be a potentially feasible and promising tool in clinical practice for analyzing the molecular mechanisms of lung adenocarcinoma carcinogenesis.