Kegg Pathway: Cytokine-cytokine receptor interaction

KEGG ID: 04060

Reference Diagram

KEGG Diagram for Cytokine-cytokine receptor interaction

Rat

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

Mouse

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

Human

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

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Recent Literature

The effect of propranolol on gene expression during the blood alcohol cycle of rats fed ethanol intragastrically.

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.

Altered profiles of gene expression in curcumin-treated rats with experimentally induced myocardial infarction.

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.

Transcriptional profiling of human cavernosal endothelial cells reveals distinctive cell adhesion phenotype and role for claudin 11 in vascular barrier function.

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.

Whole genome expression analysis within the angiotensin II-apolipoprotein E deficient mouse model of abdominal aortic aneurysm.

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.

A Cytokine-cytokine interaction in the assembly of higher-order structure and activation of the interleukine-3:receptor complex.

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.

Antirheumatic drug response signatures in human chondrocytes: potential molecular targets to stimulate cartilage regeneration.

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).

Differential gene expression profiling of mouse skin after sulfur mustard exposure: Extended time response and inhibitor effect.

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.

Chromosomal aberrations in head and neck squamous cell carcinomas in Norwegian and Sudanese populations by array comparative genomic hybridization.

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.

Rapid response to lipids profile and leukocyte gene expression after rosuvastatin administration in Chinese healthy volunteers.

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.

[Pathway analysis of modulation on geen expression in murine lymphocytes by Lactobacillus peptidoglycan.]

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.

Characterization of the acute temporal changes in excisional murine cutaneous wound inflammation by screening of the wound-edge transcriptome.

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.

Combined oligonucleotide microarray-bioinformatics and constructed membrane arrays to analyze the biological pathways in the carcinogenesis of human lung adenocarcinoma.

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.