鼻咽癌14-3-3σ蛋白的靶向蛋白质组学研究
|
摘要
鼻咽癌(nasopharyngeal carcinoma, NPC)是我国南方最常见的恶性肿瘤之一,严重威胁我国人民的生命和健康。绝大多数NPC分化差,恶性程度高,易早期发生颈淋巴结和远处转移。NPC转移是一个多基因参与的过程,多个基因之间通过相互作用形成关键性的节点(node),这些节点在NPC转移中具有重要作用。
我们前期实验采用蛋白质组学方法筛选NPC组织差异表达的蛋白质,鉴定了36个NPC组织的差异表达蛋白质,采用免疫组织化学染色检测差异蛋白质14-3-3σ(14-3-3 sigma)在正常鼻咽上皮组织、NPC组织以及颈淋巴结转移NPC组织中的表达情况。结果发现：在NPC组织中存在高频率的14-3-3σ蛋白表达缺失/下调,而且其表达缺失/下调与NPC转移相关,这提示14-3-3σ表达缺失/下调在NPC转移中可能具有重要作用,但14-3-3σ表达缺失/下调促进NPC转移的分子机制尚未阐明。
为了研究14-3-3σ在NPC转移中的作用机制,本研究采用靶向蛋白质组学方法(免疫共沉淀结合质谱分析)分离鉴定NPC细胞中14-3-3σ的相互作用蛋白,采用基因本体论(GO)、功能聚类、信号通路和蛋白—蛋白相互作用(protein-protein interaction, PPI)等生物信息学方法分析14-3-3σ的相互作用蛋白,揭示其生物学意义,并对关键相互作用蛋白(14-3-3σ/EGFR/Keratin 8)进行实验验证和功能研究。
主要结果如下：
1、采用靶向蛋白质组学在NPC细胞中鉴定了111个14-3-30的相互作用蛋白,并对其中4个相互作用蛋白质(Keratin 8、EGFR、RAB7和p53)进行了验证。
2、GO和聚类分析显示：111个14-3-3σ的相互作用蛋白可聚类成13功能相关的簇,这些蛋白的功能主要归类为8个方面：细胞骨架、跨膜转运、分子伴侣、核糖体蛋白、GTPase、蛋白转运、ATPase和RNA结合。
3、KEGG和Biocarta信号通路分析显示：14-3-3σ的相互作用蛋白涉及3条Biocarta信号通路和6条KEGG信号通路,其中16个相互作用蛋白涉及到细胞骨架信号通路,5个相互作用蛋白涉及到囊泡转运信号通路。
4、蛋白相互作用分析显示：14-3-3σ/p53/RAB7相互作用组(Interactome)调控囊泡转运,14-3-3σ/EGFR/CK8相互作用组调控细胞骨架,它们可能与NPC转移相关。
5、实验证实在NPC细胞中存在14-3-3σ/EGFR/Keratin 7相互作用组。6、功能分析显示：14-3-3σ下调能增加NPC细胞EGFR和Keratin 8表达,增强NPC细胞的体外侵袭能力。
研究结果提示,14-3-3σ表达下调可能通过14-3-3σ/EGFR/Keratin8相互作用组而促进NPC侵袭转移。
Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors in southern China, and it poses one of the serious public health problems in this area. Majority of NPC are poorly differentiated and highly malignant, and usually have early cervical lymphnode and distant metastasis. It is well know that the metastasis of NPC is involved in multiple genes interaction, and there were many key nodes formed by the genes interaction. These nodes play an important role in the metastasis of NPC.
In our previous study, we identified 36 differential expression proteins in NPC tissues by proteomic approach. There was a highly frequent downregulaiton of 14-3-3 a in NPC tissues, and its downregulaiton was related to the metastasis of NPC, which indicates that 14-3-3 a downregulaiton may play an important role in the metastasis of NPC. But it is unknown that the mechanism of 14-3-3σdownregulaiton-promoting NPC metastasis.
To study the mechanism of 14-3-3 a downregulaiton-promoting NPC metastasis, targeted proteomics(coimmunoprecipitation coupled with MS) was used to identify 14-3-3 a-interacted proteins. Bioinformatics (Gene Ontology, cluster analysis, signal pathway analysis and protein-protein interaction analysis) was performed to analyzed the data of targeted proteomics to reveal the biological significance. Finally, experimental confirmation and functional studies on the key interactome(14-3-3σ/EGFR/Keratin 8) were performed.
The main results were as following:
1. One hundred and eleven 14-3-3 a-interacted proteins were identified by targeted proteomics, and four 14-3-3 a-interacted proteins (Keratin 8, EGFR, RAB7and p53) were confirmed by coimmunoprecipitation and western blot.
2. Cluster analysis showed that one hundred and eleven 14-3-3 a-interacted proteins were grouped into 13 functional classes, and were further clustered into 8 functional clusters:cytoskeleton, transmembrane transporter, molecular chaperone, ribosome, Ras small GTPase(Rab type), ATPase/ATP binding, protein transport, and RNA binding.
3. KEGG and Biocarta pathway analyses showed that 14-3-3σ-interacted proteins were involved in 3 Biocarta pathways, and 6 KEGG pathways. Among them,16 proteins were involved in cytoskeleton pathway, and 5 proteins were involved in vesicle transport pathway.
4. Protein-protein interaction analysis showed that vesicle transport pathway was regulated by 14-3-3σ/p53/RAB7 interactome, and cytoskeleton pathway was regulated by 14-3-3σ/EGFR/keratin 8 interactome, which may is related to NPC metastasis.
5.14-3-3σ/EGFR/keratin 8 interactome in NPC cells was confirmed by experiments.
6. Functional studies showed that 14-3-3σdownregulation could increase the expression of EGFR and keratin 8, and enhance the in vitro invasive ability in NPC cells.
The data suggest that 14-3-3σdownregulation promotes could the metastasis of NPC possibly through 14-3-3σ/EGFR/keratin 8 interactions.
我们前期实验采用蛋白质组学方法筛选NPC组织差异表达的蛋白质,鉴定了36个NPC组织的差异表达蛋白质,采用免疫组织化学染色检测差异蛋白质14-3-3σ(14-3-3 sigma)在正常鼻咽上皮组织、NPC组织以及颈淋巴结转移NPC组织中的表达情况。结果发现：在NPC组织中存在高频率的14-3-3σ蛋白表达缺失/下调,而且其表达缺失/下调与NPC转移相关,这提示14-3-3σ表达缺失/下调在NPC转移中可能具有重要作用,但14-3-3σ表达缺失/下调促进NPC转移的分子机制尚未阐明。
为了研究14-3-3σ在NPC转移中的作用机制,本研究采用靶向蛋白质组学方法(免疫共沉淀结合质谱分析)分离鉴定NPC细胞中14-3-3σ的相互作用蛋白,采用基因本体论(GO)、功能聚类、信号通路和蛋白—蛋白相互作用(protein-protein interaction, PPI)等生物信息学方法分析14-3-3σ的相互作用蛋白,揭示其生物学意义,并对关键相互作用蛋白(14-3-3σ/EGFR/Keratin 8)进行实验验证和功能研究。
主要结果如下：
1、采用靶向蛋白质组学在NPC细胞中鉴定了111个14-3-30的相互作用蛋白,并对其中4个相互作用蛋白质(Keratin 8、EGFR、RAB7和p53)进行了验证。
2、GO和聚类分析显示：111个14-3-3σ的相互作用蛋白可聚类成13功能相关的簇,这些蛋白的功能主要归类为8个方面：细胞骨架、跨膜转运、分子伴侣、核糖体蛋白、GTPase、蛋白转运、ATPase和RNA结合。
3、KEGG和Biocarta信号通路分析显示：14-3-3σ的相互作用蛋白涉及3条Biocarta信号通路和6条KEGG信号通路,其中16个相互作用蛋白涉及到细胞骨架信号通路,5个相互作用蛋白涉及到囊泡转运信号通路。
4、蛋白相互作用分析显示：14-3-3σ/p53/RAB7相互作用组(Interactome)调控囊泡转运,14-3-3σ/EGFR/CK8相互作用组调控细胞骨架,它们可能与NPC转移相关。
5、实验证实在NPC细胞中存在14-3-3σ/EGFR/Keratin 7相互作用组。6、功能分析显示：14-3-3σ下调能增加NPC细胞EGFR和Keratin 8表达,增强NPC细胞的体外侵袭能力。
研究结果提示,14-3-3σ表达下调可能通过14-3-3σ/EGFR/Keratin8相互作用组而促进NPC侵袭转移。
Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors in southern China, and it poses one of the serious public health problems in this area. Majority of NPC are poorly differentiated and highly malignant, and usually have early cervical lymphnode and distant metastasis. It is well know that the metastasis of NPC is involved in multiple genes interaction, and there were many key nodes formed by the genes interaction. These nodes play an important role in the metastasis of NPC.
In our previous study, we identified 36 differential expression proteins in NPC tissues by proteomic approach. There was a highly frequent downregulaiton of 14-3-3 a in NPC tissues, and its downregulaiton was related to the metastasis of NPC, which indicates that 14-3-3 a downregulaiton may play an important role in the metastasis of NPC. But it is unknown that the mechanism of 14-3-3σdownregulaiton-promoting NPC metastasis.
To study the mechanism of 14-3-3 a downregulaiton-promoting NPC metastasis, targeted proteomics(coimmunoprecipitation coupled with MS) was used to identify 14-3-3 a-interacted proteins. Bioinformatics (Gene Ontology, cluster analysis, signal pathway analysis and protein-protein interaction analysis) was performed to analyzed the data of targeted proteomics to reveal the biological significance. Finally, experimental confirmation and functional studies on the key interactome(14-3-3σ/EGFR/Keratin 8) were performed.
The main results were as following:
1. One hundred and eleven 14-3-3 a-interacted proteins were identified by targeted proteomics, and four 14-3-3 a-interacted proteins (Keratin 8, EGFR, RAB7and p53) were confirmed by coimmunoprecipitation and western blot.
2. Cluster analysis showed that one hundred and eleven 14-3-3 a-interacted proteins were grouped into 13 functional classes, and were further clustered into 8 functional clusters:cytoskeleton, transmembrane transporter, molecular chaperone, ribosome, Ras small GTPase(Rab type), ATPase/ATP binding, protein transport, and RNA binding.
3. KEGG and Biocarta pathway analyses showed that 14-3-3σ-interacted proteins were involved in 3 Biocarta pathways, and 6 KEGG pathways. Among them,16 proteins were involved in cytoskeleton pathway, and 5 proteins were involved in vesicle transport pathway.
4. Protein-protein interaction analysis showed that vesicle transport pathway was regulated by 14-3-3σ/p53/RAB7 interactome, and cytoskeleton pathway was regulated by 14-3-3σ/EGFR/keratin 8 interactome, which may is related to NPC metastasis.
5.14-3-3σ/EGFR/keratin 8 interactome in NPC cells was confirmed by experiments.
6. Functional studies showed that 14-3-3σdownregulation could increase the expression of EGFR and keratin 8, and enhance the in vitro invasive ability in NPC cells.
The data suggest that 14-3-3σdownregulation promotes could the metastasis of NPC possibly through 14-3-3σ/EGFR/keratin 8 interactions.
引文
[1]Yu M C, Yuan J M. Epidemiology of nasopharyngeal carcinoma. Semin Cancer Biol, 2002,12(6):421-429
[2]Wei WI, Sham JS. Nasopharyngeal carcinoma. Lancet,2005,365 (9476):2041-2054
[3]Gargouri B, Lassoued S, Ben Mansour R, Ayadi W, Idriss N, Attia H, El Feki Ael F. High levels of autoantibodies against catalase and superoxide dismutase in nasopharyngeal carcinoma. South Med J,2009,102(12):1222-1226
[4]Chen YB, Hu CM, Pan JJ, Mao Y, Wei W. Optimization of magnetic resonance sequences in lymph node staging of nasopharyngeal carcinoma. Chin Med J (Engl), 2010,123(4):443-446
[5]Dong XR, Zhang T, Fan L, Zhang S, Wu G. Parotid gland metastasis of nasopharyngeal carcinoma:case report and review of the literature. J Int Med Res, 2009,37(6):1994-1999
[6]Han L, Lin SJ, Pan JJ, Chen CB, Zhang Y, Zhang XC, Liao XY, Chen QS. Prognostic factors of 305 nasopharyngeal carcinoma patients treated with intensity-modulated radiotherapy. Chin J Cancer,2010,29(2):145-150
[7]Zhu Q, Wang T, Ren J, Hu K, Liu W, Wu G. FAS-670A/G polymorphism:A biomarker for the metastasis of nasopharyngeal carcinoma in a Chinese population. Clin Chim Acta,2010,411(3-4):179-183
[8]Oluwadara O, Chiappelli F. Biomarkers for early detection of high risk cancers:From gliomas to nasopharyngeal carcinoma. Bioinformation,2009,3(8):332-329
[9]Chua HN, Ning K, Sung WK, Leong HW, Wong L. Using indirect protein-protein interactions for protein complex predication. Comput Syst Bioinformatics Conf,2007, 6:97-109
[10]Wang Z, Zhang J. In search of the biological significance of modular structures in protein networks. PLoS Comput Biol,2007,3(6):e107
[11]Tomazela DM, Patterson BW, Hanson E, Spence KL, Kanion TB, Salinger DH, Vicini P, Barret H, Heins HB, Cole FS, Hamvas A, MacCoss MJ. Measurement of human surfactant protein-B turnover in vivo from tracheal aspirates using targeted proteomics. Anal Chem,2010,82(6):2561-2567
[12]MacLean B, Tomazela DM, Shulman N, Chambers M, Finney GL, Frewen B, Kern R, Tabb DL, Liebler DC, MacCoss MJ. Skyline:an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics.2010, 26(7):966-968
[13]Callipo L, Caruso G, Foglia P, Gubbiotti R, Samperi R, Lagana A. Immunoprecipitation on magnetic beads and liquid chromatography-tandem mass spectrometry for carbonic anhydrase II quantification in human serum. Anal Biochem, 2010,400(2):195-202
[14]Savas JN, Tanese N. A combined immunoprecipitation, mass spectrometric and nucleic acid sequencing approach to determine microRNA-mediated post-transcriptional gene regulatory networks. Brief Funct Genomic Proteomic.2010, 9(1):24-31
[15]Zhan X, Desiderio DM. Mass spectrometric identification of in vivo nitrotyrosine sites in the human pituitary tumor proteome. Methods Mol Biol,2009,566:137-163
[16]Ma M, Sturm RM, Kutz-Naber KK, Fu Q, Li L. Immunoaffinity-based mass spectrometric characterization of the FMRFamide-related peptide family in the pericardial organ of Cancer borealis. Biochem Biophys Res Commun,2009, 390(2):325-330
[17]Cho JY, Lee M, Ahn JM, Park ES, Cho JH, Lee SJ, Kim BG, Heo SH, Park HJ, Zerbini LF, Hwang D, Libermann TA. Proteomic analysis of a PDEF Ets transcription factor-interacting protein complex. J Proteome Res.2009,8(3):1327-1337
[18]Neumann J, Feuerhake F, Kayser G, Wiech T, Aumann K, Passlick B, Fisch P, Werner M, Zur Hausen A. Gene expression profiles of lung adenocarcinoma linked to histopathological grading and survival but not to EGF-R status:a microarray study. BMC Cancer,2010,10(1):77
[19]Ostrovnaya I, Begg CB. Testing clonal relatedness of tumors using array comparative genomic hybridization:a statistical challenge. Clin Cancer Res,2010, 16(5):1358-1367
[20]Wong SC, Chan CM, Ma BB, Lam MY, Choi GC, Au TC, Chan AS, Chan AT. Advanced proteomic technologies for cancer biomarker discovery. Expert Rev Proteomics,2009,6(2):123-134
[21]Kreeger PK, Lauffenburger DA. Cancer systems biology:a network modeling perspective. Carcinogenesis,2010,31(1):2-8
[22]Li H, Liang S. Local network topology in human protein interaction data predicts functional association. PLoS One,2009,4(7):e6410
[23]Yi M, Horton JD, Cohen JC, Hobbs HH, Stephens RM. WholePathwayScope:a comprehensive pathway-based analysis tool for high-throughput data. BMC Bioinformatics,2006,7:30
[24]Buehler A, Urzhumtseva L, Lunin VY, Urzhumtsev A. Cluster analysis for phasing with molecular replacement:a feasibility study. Acta Crystallogr D Biol Crystallogr, 2009,65(Pt 7):644-650
[25]Giglio MG, Collmer CW, Lomax J, Ireland A. Applying the Gene Ontology in microbial annotation. Trends Microbiol,2009,17(7):262-268
[26]Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res,2010,38(Database issue):D355-D360
[27]Huang R, Wallqvist A, Covell DG. Comprehensive analysis of pathway or functionally related gene expression in the National Cancer Institute's anticancer screen. Genomics,2006,87(3):315-328
[28]Zaki N, Lazarova-Molnar S, El-Hajj W, Campbell P. Protein-protein interaction based on pairwise similarity. BMC Bioinformatics,2009,10:150
[29]Stelzl U, Wanker EE. The value of high quality protein-protein interaction networks for systems biology. Curr Opin Chem Biol,2006,10(6):551-558
[30]Li L, Zhang K, Lee J, Cordes S, Davis DP, Tang Z. Discovering cancer genes by integrating network and functional properties. BMC Med Genomics,2009,2:61
[31]Bachman P, Liu Y. Structure discovery in PPI networks using pattern-based network decomposition. Bioinformatics,2009,25(14):1814-1821
[32]Kwoh CK, Ng PY. Network analysis approach for biology. Cell Mol Life Sci,2007, 64(14):1739-1751
[33]Suderman M, Hallett M. Tools for visually exploring biological networks. Bioinformatics,2007,23(20):2651-2659
[34]Hu Z, Mellor J, Wu J, Yamada T, Holloway D, Delisi C. VisANT:data-integrating visual framework for biological networks and modules. Nucleic Acids Res,2005, 33(Web Server issue):W352-W357
[35]Cheng AL, Huang WG, Chen ZC, Peng F, Zhang PF, Li MY, Li F, Li JL, Li C, Yi H, Yi B, Xiao ZQ. Identification of novel nasopharyngeal carcinoma biomarkers by laser capture microdissection and proteomic analysis. Clin Cancer Res,2008, 14(2):435-445
[36]Mhawech P.14-3-3 proteins--an update. Cell Res,2005,15(4):228-236
[37]Hermeking H. The 14-3-3 cancer connection. Nat Rev Cancer,2003,3:931-943
[38]Wang Z, Trope CQ Suo Z, Tr(?)en G, Yang G, Nesland JM, Holm R. The clinicopathological and prognostic impact of 14-3-3 sigma expression on vulvar squamous cell carcinomas. BMC Cancer,2008,8:308
[39]Laronga C, Yang HY, Neal C, Lee MH. Association of the cyclin-dependent kinases and 14-3-3 sigma negatively regulates cell cycle progression. J Biol Chem,2000, 275(30):23106-23112
[40]Wilker EW, van Vugt MA, Artim SA, Huang PH, Petersen CP, Reinhardt HC, Feng Y, Sharp PA, Sonenberg N, White FM, Yaffe MB.14-3-3sigma controls mitotic translation to facilitate cytokinesis. Nature,2007,446(7133):329-332
[41]Dellambra E, Golisano O, Bondanza S, Siviero E, Lacal P, Molinari M, D'Atri S, De Luca M. Downregulation of 14-3-3 sigma prevents clonal evolution and leads to immortalization of primary human Keratinocytes. J Cell Biol,2000, 149(5):1117-1130
[42]Moreira JM, Ohlsson G, Rank FE, Celis JE. Down-regulation of the tumor suppressor protein 14-3-3 sigma is a sporadic event in cancer of the breast. Mol Cell Proteomics,2005,4(4):555-569
[43]Yi B, Tan SX, Tang CE, Huang WG, Cheng AL, Li C, Zhang PF, Li MY, Li JL, Yi H, Peng F, Chen ZC, Xiao ZQ. Inactivation of 14-3-3 sigma by promoter methylation correlates with metastasis in nasopharyngeal carcinoma. J Cell Biochem,2009, 106(5):858-866
[44]Vera J, Schultz J, Ibrahim S, Raatz Y, Wolkenhauer O, Kunz M. Dynamical effects of epigenetic silencing of 14-3-3sigma expression. Mol Biosyst,2010,6(1):254-263
[45]Liang S, Xu Y, Shen G, Zhao X, Zhou J, Li X, Gong F, Ling B, Fang L, Huang C, Wei Y. Gene expression and methylation status of 14-3-3 sigma in human renal carcinoma tissues. IUBMB Life,2008,60(8):534-540
[46]Li DJ, Deng G, Xiao ZQ, Yao HX, Li C, Peng F, Li MY, Zhang PF, Chen YH, Chen ZC. Identificating 14-3-3 sigma as a lymph node metastasis-related protein in human lung squamous carcinoma. Cancer Lett,2009,279(1):65-73
[47]Benzinger A, Muster N, Koch HB, Yates JR 3rd, Hermeking H. Targeted proteomic analysis of 14-3-3 sigma, a p53 effector commonly silenced in cancer. Mol Cell Proteomics,2005,4(6):785-795
[48]Yang H, Zhao R, Lee MH.14-3-3sigma, a p53 regulator, suppresses tumor growth of nasopharyngeal carcinoma. Mol Cancer Ther,2006,5(2):253-260
[49]Neal CL, Yao J, Yang W, Zhou X, Nguyen NT, Lu J, Danes CG, Guo H, Lan KH, Ensor J, Hittelman W, Hung MC, Yu D.14-3-3zeta overexpression defines high risk for breast cancer recurrence and promotes cancer cell survival. Cancer Res,2009, 69(8):3425-3432
[50]Yoon NK, Seligson DB, Chia D, Elshimali Y, Sulur G, Li A, Horvath S, Maresh E, Mah V, Bose S, Bonavida B, Goodglick L. Higher expression levels of 14-3-3sigma in ductal carcinoma in situ of the breast predict poorer outcome. Cancer Biomark, 2009,5(4):215-224
[51]Hu Z, Hung JH, Wang Y, Chang YC, Huang CL, Huyck M, DeLisi C. VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology. Nucleic Acids Res,2009,37(Web Server issue):W115-W121
[52]Hu Z, Snitkin ES, DeLisi C. VisANT:an integrative framework for networks in systems biology. Brief Bioinform,2008,9(4):317-325
[53]Han B, Xie H, Chen Q, Zhang JT. Sensitizing hormone-refractory prostate cancer cells to drug treatment by targeting 14-3-3sigma. Mol Cancer Ther,2006, 5(4):903-912
[54]WARBURG O. On the origin of cancer cells. Science,1956,123(3191):309-314
[55]Gogvadze V, Zhivotovsky B, Orrenius S. The Warburg effect and mitochondrial stability in cancer cells. Mol Aspects Med,2010,31(1):60-74
[56]Chia WJ, Tang BL. Emerging roles for Rab family GTPases in human cancer. Biochim Biophys Acta,2009,1795(2):110-116
[57]Cheng KW, Lahad JP, Gray JW, Mills GB. Emerging role of RAB GTPases in cancer and human disease. Cancer Res,2005,65(7):2516-2519
[58]Schara K, Jansa V, Sustar V, Dolinar D, Pavlic JI, Lokar M, Kralj-Iglic V, Veranic P, Iglic A. Mechanisms for the formation of membranous nanostructures in cell-to-cell communication. Cell Mol Biol Lett,2009,14(4):636-656
[59]Konopleva M, Tabe Y, Zeng Z, Andreeff M. Therapeutic targeting of microenvironmental interactions in leukemia:mechanisms and approaches. Drug Resist Updat,2009,12(4-5):103-113
[60]Warner JR, McIntosh KB. How common are extraribosomal functions of ribosomal proteins? Mol Cell,2009,34(1):3-11
[61]Lindstrom MS. Emerging functions of ribosomal proteins in gene-specific transcription and translation. Biochem Biophys Res Commun.2009,379(2):167-170
[62]Montanaro L, Trere D, Derenzini M. Nucleolus, ribosomes, and cancer. Am J Pathol. 2008,173(2):301-310
[63]Di Cesare S, Nantel A, Marshall JC, Fernandes BF, Antecka E, Orellana ME, Abourbih D, Saornil AM, Burnier MN Jr. Expression profiling of formalin-fixed paraffin embedded primary human uveal melanomas using DASL matrices. J Cancer Res Clin Oncol,2010,136(4):577-586
[64]Wang S, Huang J, He J, Wang A, Xu S, Huang SF, Xiao S. RPL41, a small ribosomal peptide deregulated in tumors, is essential for mitosis and centrosome integrity. Neoplasia,2010,12(3):284-293
[65]Naora H. Involvement of ribosomal proteins in regulating cell growth and apoptosis: translational modulation or recruitment for extraribosomal activity? Immunol Cell Biol,1999,77(3):197-205
[66]Belin S, Beghin A, Solano-Gonzalez E, Bezin L, Brunet-Manquat S, Textoris J, Prats AC, Mertani HC, Dumontet C, Diaz JJ. Dysregulation of ribosome biogenesis and translational capacity is associated with tumor progression of human breast cancer cells. PLoS One,2009,4(9):e7147
[67]Warner JR, McIntosh KB. How common are extraribosomal functions of ribosomal proteins? Mol Cell.2009,34(1):3-11
[68]Hou MM, Chang JW, Pang ST, Chiang YJ, Shen YC, Liao SK, Hsieh JJ, Yeh KY, Chang NJ, Chuang CK. Characterization of the response of dendritic cells and regulatory T cells to tumor antigens in patients with renal cell carcinoma. Chang Gung Med J.2010,33(1):25-35
[69]Breckpot K, Escors D. Dendritic cells for active anti-cancer immunotherapy:targeting activation pathways through genetic modification. Endocr Metab Immune Disord Drug Targets,2009,9(4):328-343
[70]Milani V, Noessner E, Ghose S, Kuppner M, Ahrens B, Scharner A, Gastpar R, Issels RD. Heat shock protein 70:role in antigen presentation and immune stimulation. Int J Hyperthermia,2002,18(6):563-575
[71]Hollander N. Current vaccination strategies for the treatment of B-cell lymphoma and multiple myeloma. Crit Rev Immunol,2009,29(5):399-418
[72]Mycielska ME, Patel A, Rizaner N, Mazurek MP, Keun H, Patel A, Ganapathy V, Djamgoz MB. Citrate transport and metabolism in mammalian cells:prostate epithelial cells and prostate cancer. Bioessays,2009,31(1):10-20
[73]Weinberg F, Chandel NS. Mitochondrial metabolism and cancer. Ann N Y Acad Sci, 2009,1177:66-73
[74]Satoh J, Tabunoki H, Nanri Y, Arima K, Yamamura T. Human astrocytes express 14-3-3 sigma in response to oxidative and DNA-damaging stresses. Neurosci Res, 2006,56(1):61-72
[75]Lee MH, Lozano G. Regulation of the p53-MDM2 pathway by 14-3-3 sigma and other proteins. Semin Cancer Biol,2006,16(3):225-234
[76]Moll R, Franke WW. Intermediate filaments and their interaction with membranes. The desmosome-cytoKeratin filament complex and epithelial differentiation. Pathol Res Pract,1982,175(2-3):146-161
[77]Kreplak L, Bar H, Leterrier JF, Herrmann H, Aebi U. Exploring the mechanical behavior of single intermediate filaments. J Mol Biol,2005,354(3):569-577
[78]Coulombe PA, Omary MB.'Hard' and'soft' principles defining the structure, function and regulation of Keratin intermediate filaments. Curr Opin Cell Biol,2002, 14(1):110-122
[79]Shaevitz JW, Fletcher DA. Load fluctuations drive actin network growth. Proc Natl Acad Sci U S A,2007,104(40):15688-15692
[80]Zeile WL, Zhang F, Dickinson RB, Purich DL. Listeria's right-handed helical rocket-tail trajectories:mechanistic implications for force generation in actin-based motility. Cell Motil Cytoskeleton,2005,60(2):121-128
[81]Hammer JA 3rd, Wu XS. Rabs grab motors:defining the connections between Rab GTPases and motor proteins. Curr Opin Cell Biol,2002,14(1):69-75
[82]Grosshans BL, Ortiz D, Novick P. Rabs and their effectors:achieving specificity in membrane traffic. Proc Natl Acad Sci U S A,2006,103(32):11821-11827
[83]Stenmark H. Rab GTPases as coordinators of vesicle traffic. Nat Rev Mol Cell Biol, 2009,10(8):513-525
[84]Fukuda M. Regulation of secretory vesicle traffic by Rab small GTPases. Cell Mol Life Sci,2008,65(18):2801-2813
[85]Wang JS, Wang FB, Zhang QG, Shen ZZ, Shao ZM. Enhanced expression of Rab27A gene by breast cancer cells promoting invasiveness and the metastasis potential by secretion of insulin-like growth factor-Ⅱ. Mol Cancer Res,2008,6(3):372-382
[86]Palmieri D, Bouadis A, Ronchetti R, Merino MJ, Steeg PS. Rablla differentially modulates epidermal growth factor-induced proliferation and motility in immortal breast cells. Breast Cancer Res Treat,2006,100(2):127-137
[87]Fong T, Morgensztern D, Govindan R. EGFR inhibitors as first-line therapy in advanced non-small cell lung cancer. J Thorac Oncol,2008,3(3):303-310
[88]Cho EY, Han JJ, Choi YL, Kim KM, Oh YL. Comparison of Her-2, EGFR and cyclin D1 in primary breast cancer and paired metastatic lymph nodes:an immunohistochemical and chromogenic in situ hybridization study. J Korean Med Sci,2008,23(6):1053-1061
[89]Kim YJ, Lee GS, Hyun SH, Ka HH, Choi KC, Lee CK, Jeung EB. Uterine expression of epidermal growth factor family during the course of pregnancy in pigs. Reprod Domest Anim.2009,44(5):797-804
[90]Lee J, Ban JY, Won KY, Kim GY, Lim SJ, Lee S, Kim YW, Park YK, Lee SS. Expression of EGFR and follicular dendritic markers in lymphoid follicles from patients with Castleman's disease. Oncol Rep,2008,20(4):851-856
[91]Yang CH. EGFR tyrosine kinase inhibitors for the treatment of NSCLC in East Asia: present and future. Lung Cancer,2008,60 Suppl 2:S23-S30
[92]Uramoto H, Sugio K, Oyama T, Ono K, Sugaya M, Yoshimatsu T, Hanagiri T, Morita M, Yasumoto K. Epidermal growth factor receptor mutations are associated with gefitinib sensitivity in non-small cell lung cancer in Japanese. Lung Cancer,2006, 51(1):71-77
[93]O-charoenrat P, Wongkajornsilp A, Rhys-Evans PH, Eccles SA. Signaling pathways required for matrix metalloproteinase-9 induction by betacellulin in head-and-neck squamous carcinoma cells. Int J Cancer,2004,111(2):174-183
[94]Do NY, Lim SC, Im TS. Expression of c-erbB receptors, MMPs and VEGF in squamous cell carcinoma of the head and neck. Oncol Rep,2004,12(2):229-237
[95]Ceresa BP, Bahr SJ. rab7 activity affects epidermal growth factor:epidermal growth factor receptor degradation by regulating endocytic trafficking from the late endosome. J Biol Chem,2006,281(2):1099-1106
[96]Ceresa BP. Regulation of EGFR endocytic trafficking by rab proteins. Histol Histopathol,2006,21(9):987-993
[97]Fortier AM, Van Themsche C, Asselin E, Cadrin M. Akt isoforms regulate intermediate filament protein levels in epithelial carcinoma cells. FEBS Lett,2010, 584(5):984-988
[98]Zhao Y, Yan Q, Long X, Chen X, Wang Y. Vimentin affects the mobility and invasiveness of prostate cancer cells. Cell Biochem Funct,2008,26(5):571-577
[99]Obermajer N, Doljak B, Kos J. CytoKeratin 8 ectoplasmic domain binds urokinase-type plasminogen activator to breast tumor cells and modulates their adhesion, growth and invasiveness. Mol Cancer,2009,8:88
[100]Kakehashi A, Inoue M, Wei M, Fukushima S, Wanibuchi H. CytoKeratin 8/18 overexpression and complex formation as an indicator of GST-P positive foci transformation into hepatocellular carcinomas. Toxicol Appl Pharmacol,2009, 238(1):71-79
[101]Ishii T, Bandoh S, Fujita J, Ohtsuki Y, Tojo Y, Kanaji N, Fukunaga Y, Ueda Y, Ishida T, Kubo A. Full-length cytoKeratin 8 is released and circulates in patients with non-small cell lung cancer. Tumour Biol,2008,29(1):57-62
[102]Makino T, Yamasaki M, Takeno A, Shirakawa M, Miyata H, Takiguchi S, Nakajima K, Fujiwara Y, Nishida T, Matsuura N, Mori M, Doki Y. CytoKeratins 18 and 8 are poor prognostic markers in patients with squamous cell carcinoma of the oesophagus. Br J Cancer,2009,101(8):1298-1306
[1]Michal, G. Biochemical Pathways (Poster), Boehringer Mannheim,1993
[2]Michal, G. Biochemical Pathways:An Atlas of Biochemistry and Molecular Biology. John Wiley and Sons Ltd.1998
[3]Fields S, Song O. A novel genetic system to detect protein-protein interactions. Nature, 1989,340(6230):245-246
[4]Rigaut G, Shevchenko A, Rutz B, Wilm M, Mann M, Seraphin B. A generic protein purification method for protein complex characterization and proteome exploration. Nat Biotechnol,1999,17(10):1030-1032
[5]Selbach M, Mann M. Protein interaction screening by quantitative
immunoprecipitation combined with knockdown (QUICK). Nat Methods,2006, 3(12):981-983
[6]Echeverri CJ, Perrimon N. High-throughput RNAi screening in cultured cells:a user's guide. Nat Rev Genet,2006,7(5):373-384
[7]Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature,1998, 391(6669):806-811
[8]Lockhart DJ, Dong H, Byrne MC, Follettie MT, Gallo MV, Chee MS, Mittmann M, Wang C, Kobayashi M, Horton H, Brown EL. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol,1996,14(13):1675-1680
[9]Blat Y, Kleckner N. Cohesins bind to. preferential sites along yeast chromosome III, with differential regulation along arms versus the centric region. Cell,1999, 98(2):249-259
[10]Ren B, Robert F, Wyrick JJ, Aparicio O, Jennings EG, Simon I, Zeitlinger J, Schreiber J, Hannett N, Kanin E, Volkert TL, Wilson CJ, Bell SP, Young RA. Genome-wide location and function of DNA binding proteins. Science,2000,290(5500):2306-2309
[11]Barabasi AL, Oltvai ZN. Network biology:understanding the cell's functional organization. Nat Rev Genet,2004,5(2):101-113
[12]Barabasi AL, Albert R. Emergence of scaling in random networks. Science,1999, 286(5439):509-512
[13]Albert R, Jeong H, Barabasi AL. Error and attack tolerance of complex networks. Nature,2000,406(6794):378-382
[14]Kelley BP, Yuan B, Lewitter F, Sharan R, Stockwell BR, Ideker T. PathBLAST:a tool for alignment of protein interaction networks. Nucleic Acids Res,2004,32(Web Server issue):W83-W88
[15]Saraiya P, Chris N, Karen D. Visualizing biological pathways:requirements analysis, systems evaluation and research agenda. Inf Vis,2005,1-15
[16]Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res, 2010,38 (Database issue):D355-D360
[17]Alfarano C, Andrade CE, Anthony K, Bahroos N, Bajec M, Bantoft K, Betel D, Bobechko B, Boutilier K, Burgess E, Buzadzija K, Cavero R, D'Abreo C, Donaldson I, Dorairajoo D, Dumontier MJ, Dumontier MR, Earles V, Farrall R, Feldman H, Garderman E, Gong Y, Gonzaga R, Grytsan V, Gryz E, Gu V, Haldorsen E, Halupa A,
Haw R, Hrvojic A, Hurrell L, Isserlin R, Jack F, Juma F, Khan A, Kon T, Konopinsky S, Le V, Lee E, Ling S, Magidin M, Moniakis J, Montojo J, Moore S, Muskat B, Ng I, Paraiso JP, Parker B, Pintilie G, Pirone R, Salama JJ, Sgro S, Shan T, Shu Y, Siew J, Skinner D, Snyder K, Stasiuk R, Strumpf D, Tuekam B, Tao S, Wang Z, White M, Willis R, Wolting C, Wong S, Wrong A, Xin C, Yao R, Yates B, Zhang S, Zheng K, Pawson T, Ouellette BF, Hogue CW. The Biomolecular Interaction Network Database and related tools. Nucleic Acids Res,2005,33(Database issue):D418-D424
[18]Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene ontology:tool for the unification of biology. The Gene Ontology Consortium. Nat Genet,2000,25(1):25-29
[19]Xenarios I, Rice DW, Salwinski L, Baron MK, Marcotte EM, Eisenberg D. DIP:the database of interacting proteins. Nucleic Acids Res,2000,28(1):289-291
[20]Killcoyne S, Carter GW, Smith J, Boyle J. Cytoscape:a community-based framework for network modeling. Methods Mol Biol,2009,563:219-239
[21]Breitkreutz BJ, Stark C, Tyers M. Osprey:a network visualization system. Genome Biol,2003,4(3):R22
[22]Han K, Ju BH, Jung H. WebInterViewer:visualizing and analyzing molecular interaction networks. Nucleic Acids Res,2004,32(Web Server issue):W89-W95
[23]Iragne F, Nikolski M, Mathieu B, Auber D, Sherman D. Pro Viz:protein interaction visualization and exploration. Bioinformatics,2005,21(2):272-274
[24]Dogrusoz U, Erson EZ, Giral E, Demir E, Babur O, Cetintas A, Colak R. PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization. Bioinformatics,2006,22(3):374-375
[25]Hu Z, Snitkin ES, DeLisi C. VisANT:an integrative framework for networks in systems biology. Brief Bioinform,2008,9(4):317-325
[26]David, A. Tulip. In Mutzel,P. et al. (eds.) Graph Drawing,9th International Symposium, GD 2001,2265 of Lecture Notes in Computer Science. Springer,2001, pp:435-437. ISBN 3-540-43309-0
[27]Hermjakob H, Montecchi-Palazzi L, Bader G, Wojcik J, Salwinski L, Ceol A, Moore S, Orchard S, Sarkans U, von Mering C, Roechert B, Poux S, Jung E, Mersch H, Kersey P, Lappe M, Li Y, Zeng R, Rana D, Nikolski M, Husi H, Brun C, Shanker K, Grant SG, Sander C, Bork P, Zhu W, Pandey A, Brazma A, Jacq B, Vidal M, Sherman D,
Legrain P, Cesareni G, Xenarios I, Eisenberg D, Steipe B, Hogue C, Apweiler R. The HUPO PSI's molecular interaction format-a community standard for the representation of protein interaction data. Nat Biotechnol,2004,22(2):177-183
[28]Aranda B, Achuthan P, Alam-Faruque Y, Armean I, Bridge A, Derow C, Feuermann M, Ghanbarian AT, Kerrien S, Khadake J, Kerssemakers J, Leroy C, Menden M, Michaut M, Montecchi-Palazzi L, Neuhauser SN, Orchard S, Perreau V, Roechert B, van Eijk K, Hermjakob H. The IntAct molecular interaction database in 2010. Nucleic Acids Res,2010,38(Database issue):D525-D531.
[29]Gene Ontology Consortium. The Gene Ontology project in 2008. Nucleic Acids Res, 2008,36(Database issue):D440-D444
[30]Baitaluk M, Sedova M, Ray A, Gupta A. BiologicalNetworks:visualization and analysis tool for systems biology. Nucleic Acids Res,2006,34(Web Server issue):W466-W471
[31]Baitaluk M, Qian X, Godbole S, Raval A, Ray A, Gupta A. PathSys:integrating molecular interaction graphs for systems biology. BMC Bioinformatics,2006,7:55
[32]Sugiyama K, Shojiro T, Mitsuhiko T. Methods for visual understanding of hierarchical system structures. IEEE Trans, Systems, Man and Cybernetics 11(2):109-125
[33]Nikitin A, Egorov S, Daraselia N, Mazo I. Pathway studio-the analysis and navigation of molecular networks. Bioinformatics,2003,19(16):2155-2157
[34]Schreiber F. High quality visualization of biochemical pathways in BioPath. In Silico Biol,2002,2(2):59-73
[35]Paek E, Park J, Lee KJ. Multi-layered representation for cell signaling pathways. Mol Cell Proteomics,2004,3(10):1009-1022
[36]Kitano H. A graphical notation for biological networks. BioSilico,2003,1(5):169-176
[37]Eades P. A heuristic for graph drawing. Congressus Numerantium,1984,42:142-160
[38]Fruchterman TMJ, Reingold EM. Graph drawing by force-directed placement. Soft Pract Exper,1991,21(11):1129-1164
[39]Kamada T, Kawai S. An algorithm for drawing general undirected graphs. Inf Process Lett,1989,31(1):7-15
[40]Rzhetsky A, Iossifov I, Koike T, Krauthammer M, Kra P, Morris M, Yu H, Duboue PA, Weng W, Wilbur WJ, Hatzivassiloglou V, Friedman C. Gene Ways:a system for extracting, analyzing, visualizing, and integrating molecular pathway data. J Biomed Inform,2004,37(1):43-53
[41]Li W, Kurata H. A grid layout algorithm for automatic drawing of biochemical networks. Bioinformatics,2005,21(9):2036-2042
[42]Nagasaki M, Doi A, Matsuno H, Miyano S. Genomic Object Net:Ⅰ. A platform for modelling and simulating biopathways. Appl Bioinformatics,2003,2(3):181-184
[43]Barsky A, Gardy JL, Hancock RE, Munzner T. Cerebral:a Cytoscape plugin for layout of and interaction with biological networks using subcellular localization annotation. Bioinformatics,2007,23(8):1040-1042
[44]Schwikowski B, Uetz P, Fields S. A network of protein-protein interactions in yeast. Nat Biotechnol,2000,18(12):1257-1261
[45]Andreeva A, Howorth D, Chandonia JM, Brenner SE, Hubbard TJ, Chothia C, Murzin AG. Data growth and its impact on the SCOP database:new developments. Nucleic Acids Res,2008,36(Database issue):D419-D425
[46]Lappe M, Park J, Niggemann O, Holm L. Generating protein interaction maps from incomplete data:application to fold assignment. Bioinformatics,2001,17(Suppl 1):S149-S156
[47]Vlasblom J, Wu S, Pu S, Superina M, Liu G, Orsi C, Wodak SJ. GenePro:a Cytoscape plug-in for advanced visualization and analysis of interaction networks. Bioinformatics, 2006,22(17):2178-2179
[48]Longabaugh WJ, Davidson EH, Bolouri H. Computational representation of developmental genetic regulatory networks. Dev Biol,2005,283(1):1-16
[49]Ceol A, Chatr Aryamontri A, Licata L, Peluso D, Briganti L, Perfetto L, Castagnoli L, Cesareni G. MINT, the molecular interaction database:2009 update. Nucleic Acids Res,2010,38(Database issue):D532-D539
[50]Chatr-aryamontri A, Ceol A, Palazzi LM, Nardelli G, Schneider MV, Castagnoli L, Cesareni G. MINT:the Molecular INTeraction database. Nucleic Acids Res,2007, 35(Database issue):D572-D574
[51]Henry N, Fekete JD. Matrixexplorer:a dual-representation system to explore social networks. IEEE Trans Vis Comput Graph,2006,12(5):677-684
[52]Klipp E, Liebermeister W, Helbig A, Kowald A, Schaber J. Systems biology standards-the community speaks. Nat Biotechnol,2007,25(4):390-391
[53]Cook DL, Farley JF, Tapscott SJ. A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems. Genome Biol,2001,2(4):research0012.1-0012.10
[54]Kitano H. A graphical notation for biological networks. BioSilico,2003,1(5):169-176
[55]Kohn KW, Aladjem MI, Weinstein JN, Pommier Y. Molecular interaction maps of
bioregulatory networks:a general rubric for systems biology. Mol Biol Cell,2006, 17(1):1-13
[56]Kohn KW, Aladjem MI, Kim S, Weinstein JN, Pommier Y. Depicting combinatorial complexity with the molecular interaction map notation. Mol Syst Biol,2006,2:51
[57]Kohn KW. Molecular interaction maps as information organizers and simulation guides. Chaos,2001,11(1):84-97
[58]Kurata H, Matoba N, Shimizu N. CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle. Nucleic Acids Res,2003,31(14):4071-4084
[59]Pirson I, Fortemaison N, Jacobs C, Dremier S, Dumont JE, Maenhaut C. The visual display of regulatory information and networks. Trends Cell Biol,2000, 10(10):404-408
[60]Funahashi A, Jouraku A, Matsuoka Y, Kitano H. Integration of CellDesigner and SABIO-RK. In Silico Biol,2007,7(2 Suppl):S81-S90
[61]Funahashi A, Tanimura N, Morohashi M, Kitano H. CellDesigner:a process diagram editor for gene-regulatory and biochemical networks. BIOSILICO,2003,1:159-162,
[62]Funahashi A, Matsuoka Y, Jouraku A, Morohashi M, Kikuchi N, Kitano H. CellDesigner 3.5:A Versatile Modeling Tool for Biochemical Networks Proceedings of the IEEE,2008,96(8):1254-1265
[63]Dwyer T, Rolletschek H, Schreiber F. Representing experimental biological data in metabolic networks. In Chen,Y.-P.P.APBC, volume 29 of CRPIT. Australian Computer Society,2004, pp.13-20 ISBN 1-920682-11-2.
[64]Schreiber F, Schwobbermeyer H. MAVisto:a tool for the exploration of network motifs. Bioinformatics.2005,21(17):3572-3574
[65]Adar E. Guess:a language and interface for graph exploration. In CHI'06: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM Press, New York, USA,2006, pp:791-800 ISBN 1-59593-372-7.
[66]UniProt Consortium. The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res,2010,38(Database issue):D142-D148
[67]Yip YL, Famiglietti M, Gos A, Duek PD, David FP, Gateau A, Bairoch A. Annotating single amino acid polymorphisms in the UniProt/Swiss-Prot knowledgebase. Hum Mutat,2008,29(3):361-366
[68]Swainston N, Mendes P. libAnnotationSBML:a library for exploiting SBML annotations. Bioinformatics,2009,25(17):2292-2293
[69]Odriguez N, Donizelli M, Le Novere N. SBMLeditor:effective creation of models in the Systems Biology Markup language (SBML). BMC Bioinformatics,2007,8:79
[70]Finney A, Hucka M. Systems biology markup language:Level 2 and beyond. Biochem Soc Trans,2003,31(Pt 6):1472-1473
[71]Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, Arkin AP, Bornstein BJ, Bray D, Cornish-Bowden A, Cuellar AA, Dronov S, Gilles ED, Ginkel M, Gor V, Goryanin II, Hedley WJ, Hodgman TC, Hofmeyr JH, Hunter PJ, Juty NS, Kasberger JL, Kremling A, Kummer U, Le Novere N, Loew LM, Lucio D, Mendes P, Minch E, Mjolsness ED, Nakayama Y, Nelson MR, Nielsen PF, Sakurada T, Schaff JC, Shapiro BE, Shimizu TS, Spence HD, Stelling J, Takahashi K, Tomita M, Wagner J, Wang J; SBML Forum. The systems biology markup language (SBML):a medium for representation and exchange of biochemical network models. Bioinformatics,2003, 19(4):524-531
[72]Kerrien S, Orchard S, Montecchi-Palazzi L, Aranda B, Quinn AF, Vinod N, Bader GD, Xenarios I, Wojcik J, Sherman D, Tyers M, Salama JJ, Moore S, Ceol A, Chatr-Aryamontri A, Oesterheld M, Stumpflen V, Salwinski L, Nerothin J, Cerami E, Cusick ME, Vidal M, Gilson M, Armstrong J, Woollard P, Hogue C, Eisenberg D, Cesareni G, Apweiler R, Hermjakob H. Broadening the horizon-level 2.5 of the HUPO-PSI format for molecular interactions. BMC Biol,2007,5:44
[73]Stromback L, Lambrix P. Representations of molecular pathways:an evaluation of SBML, PSI MI and BioPAX. Bioinformatics,2005,21(24):4401-4407
[74]Scott MS, Perkins T, Bunnell S, Pepin F, Thomas DY, Hallett M. Identifying regulatory subnetworks for a set of genes. Mol Cell Proteomics.2005,4(5):683-692
[75]Schreiber F, Schwobbermeyer H. MAVisto:a tool for the exploration of network motifs. Bioinformatics.2005,21(17):3572-3574
[76]Ho Y, Gruhler A, Heilbut A, Bader GD, Moore L, Adams SL, Millar A, Taylor P, Bennett K, Boutilier K, Yang L, Wolting C, Donaldson I, Schandorff S, Shewnarane J, Vo M, Taggart J, Goudreault M, Muskat B, Alfarano C, Dewar D, Lin Z, Michalickova K, Willems AR, Sassi H, Nielsen PA, Rasmussen KJ, Andersen JR, Johansen LE, Hansen LH, Jespersen H, Podtelejnikov A, Nielsen E, Crawford J, Poulsen V, S(?)rensen BD, Matthiesen J, Hendrickson RC, Gleeson F, Pawson T, Moran MF, Durocher D, Mann M, Hogue CW, Figeys D, Tyers M. Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature,2002, 415(6868):180-183
[77]Ludemann A, Weicht D, Selbig J, Kopka J. PaVESy:Pathway Visualization and Editing System. Bioinformatics,2004,20(16):2841-2844
[78]Tong AH, Evangelista M, Parsons AB, Xu H, Bader GD, Page N, Robinson M, Raghibizadeh S, Hogue CW, Bussey H, Andrews B, Tyers M, Boone C. Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science,2001, 294(5550):2364-2368
[79]Jin R, McCallen S., Liu CC, Xiang Y, Almaas E, Zhou XJ. Identifying dynamic network modules with temporal and spatial constraints. Pac Symp Biocomput, 2009:203-214
[80]Jung SH, Jang WH, Hur HY, Hyun B, Han DS. Protein complex prediction based on mutually exclusive interactions in protein interaction network. Genome Inform,2008, 21:77-88
[81]Miyamoto-Sato E, Fujimori S, Ishizaka M, Hirai N, Masuoka K, Saito R, Ozawa Y, Hino K, Washio T, Tomita M, Yamashita T, Oshikubo T, Akasaka H, Sugiyama J, Matsumoto Y, Yanagawa H. A comprehensive resource of interacting protein regions for refining human transcription factor networks. PLoS One,2010,5(2):e9289
[82]Huang Y, Li S. Detection of characteristic sub pathway network for angiogenesis based on the comprehensive pathway network. BMC Bioinformatics,2010,11(Suppl 1):S32
[83]Ng KL, Ciou JS, Huang CH. Prediction of protein functions based on function-function correlation relations. Comput Biol Med,2010,40(3):300-305
[84]Jung SH, Hyun B, Jang WH, Hur HY, Han DS. Protein complex prediction based on simultaneous protein interaction network. Bioinformatics,2010,26(3):385-391
[85]Kushwaha SK, Shakya M. PINAT1.0:Protein interaction network analysis tool. Bioinformation,2009,3(10):419-421
[2]Wei WI, Sham JS. Nasopharyngeal carcinoma. Lancet,2005,365 (9476):2041-2054
[3]Gargouri B, Lassoued S, Ben Mansour R, Ayadi W, Idriss N, Attia H, El Feki Ael F. High levels of autoantibodies against catalase and superoxide dismutase in nasopharyngeal carcinoma. South Med J,2009,102(12):1222-1226
[4]Chen YB, Hu CM, Pan JJ, Mao Y, Wei W. Optimization of magnetic resonance sequences in lymph node staging of nasopharyngeal carcinoma. Chin Med J (Engl), 2010,123(4):443-446
[5]Dong XR, Zhang T, Fan L, Zhang S, Wu G. Parotid gland metastasis of nasopharyngeal carcinoma:case report and review of the literature. J Int Med Res, 2009,37(6):1994-1999
[6]Han L, Lin SJ, Pan JJ, Chen CB, Zhang Y, Zhang XC, Liao XY, Chen QS. Prognostic factors of 305 nasopharyngeal carcinoma patients treated with intensity-modulated radiotherapy. Chin J Cancer,2010,29(2):145-150
[7]Zhu Q, Wang T, Ren J, Hu K, Liu W, Wu G. FAS-670A/G polymorphism:A biomarker for the metastasis of nasopharyngeal carcinoma in a Chinese population. Clin Chim Acta,2010,411(3-4):179-183
[8]Oluwadara O, Chiappelli F. Biomarkers for early detection of high risk cancers:From gliomas to nasopharyngeal carcinoma. Bioinformation,2009,3(8):332-329
[9]Chua HN, Ning K, Sung WK, Leong HW, Wong L. Using indirect protein-protein interactions for protein complex predication. Comput Syst Bioinformatics Conf,2007, 6:97-109
[10]Wang Z, Zhang J. In search of the biological significance of modular structures in protein networks. PLoS Comput Biol,2007,3(6):e107
[11]Tomazela DM, Patterson BW, Hanson E, Spence KL, Kanion TB, Salinger DH, Vicini P, Barret H, Heins HB, Cole FS, Hamvas A, MacCoss MJ. Measurement of human surfactant protein-B turnover in vivo from tracheal aspirates using targeted proteomics. Anal Chem,2010,82(6):2561-2567
[12]MacLean B, Tomazela DM, Shulman N, Chambers M, Finney GL, Frewen B, Kern R, Tabb DL, Liebler DC, MacCoss MJ. Skyline:an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics.2010, 26(7):966-968
[13]Callipo L, Caruso G, Foglia P, Gubbiotti R, Samperi R, Lagana A. Immunoprecipitation on magnetic beads and liquid chromatography-tandem mass spectrometry for carbonic anhydrase II quantification in human serum. Anal Biochem, 2010,400(2):195-202
[14]Savas JN, Tanese N. A combined immunoprecipitation, mass spectrometric and nucleic acid sequencing approach to determine microRNA-mediated post-transcriptional gene regulatory networks. Brief Funct Genomic Proteomic.2010, 9(1):24-31
[15]Zhan X, Desiderio DM. Mass spectrometric identification of in vivo nitrotyrosine sites in the human pituitary tumor proteome. Methods Mol Biol,2009,566:137-163
[16]Ma M, Sturm RM, Kutz-Naber KK, Fu Q, Li L. Immunoaffinity-based mass spectrometric characterization of the FMRFamide-related peptide family in the pericardial organ of Cancer borealis. Biochem Biophys Res Commun,2009, 390(2):325-330
[17]Cho JY, Lee M, Ahn JM, Park ES, Cho JH, Lee SJ, Kim BG, Heo SH, Park HJ, Zerbini LF, Hwang D, Libermann TA. Proteomic analysis of a PDEF Ets transcription factor-interacting protein complex. J Proteome Res.2009,8(3):1327-1337
[18]Neumann J, Feuerhake F, Kayser G, Wiech T, Aumann K, Passlick B, Fisch P, Werner M, Zur Hausen A. Gene expression profiles of lung adenocarcinoma linked to histopathological grading and survival but not to EGF-R status:a microarray study. BMC Cancer,2010,10(1):77
[19]Ostrovnaya I, Begg CB. Testing clonal relatedness of tumors using array comparative genomic hybridization:a statistical challenge. Clin Cancer Res,2010, 16(5):1358-1367
[20]Wong SC, Chan CM, Ma BB, Lam MY, Choi GC, Au TC, Chan AS, Chan AT. Advanced proteomic technologies for cancer biomarker discovery. Expert Rev Proteomics,2009,6(2):123-134
[21]Kreeger PK, Lauffenburger DA. Cancer systems biology:a network modeling perspective. Carcinogenesis,2010,31(1):2-8
[22]Li H, Liang S. Local network topology in human protein interaction data predicts functional association. PLoS One,2009,4(7):e6410
[23]Yi M, Horton JD, Cohen JC, Hobbs HH, Stephens RM. WholePathwayScope:a comprehensive pathway-based analysis tool for high-throughput data. BMC Bioinformatics,2006,7:30
[24]Buehler A, Urzhumtseva L, Lunin VY, Urzhumtsev A. Cluster analysis for phasing with molecular replacement:a feasibility study. Acta Crystallogr D Biol Crystallogr, 2009,65(Pt 7):644-650
[25]Giglio MG, Collmer CW, Lomax J, Ireland A. Applying the Gene Ontology in microbial annotation. Trends Microbiol,2009,17(7):262-268
[26]Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res,2010,38(Database issue):D355-D360
[27]Huang R, Wallqvist A, Covell DG. Comprehensive analysis of pathway or functionally related gene expression in the National Cancer Institute's anticancer screen. Genomics,2006,87(3):315-328
[28]Zaki N, Lazarova-Molnar S, El-Hajj W, Campbell P. Protein-protein interaction based on pairwise similarity. BMC Bioinformatics,2009,10:150
[29]Stelzl U, Wanker EE. The value of high quality protein-protein interaction networks for systems biology. Curr Opin Chem Biol,2006,10(6):551-558
[30]Li L, Zhang K, Lee J, Cordes S, Davis DP, Tang Z. Discovering cancer genes by integrating network and functional properties. BMC Med Genomics,2009,2:61
[31]Bachman P, Liu Y. Structure discovery in PPI networks using pattern-based network decomposition. Bioinformatics,2009,25(14):1814-1821
[32]Kwoh CK, Ng PY. Network analysis approach for biology. Cell Mol Life Sci,2007, 64(14):1739-1751
[33]Suderman M, Hallett M. Tools for visually exploring biological networks. Bioinformatics,2007,23(20):2651-2659
[34]Hu Z, Mellor J, Wu J, Yamada T, Holloway D, Delisi C. VisANT:data-integrating visual framework for biological networks and modules. Nucleic Acids Res,2005, 33(Web Server issue):W352-W357
[35]Cheng AL, Huang WG, Chen ZC, Peng F, Zhang PF, Li MY, Li F, Li JL, Li C, Yi H, Yi B, Xiao ZQ. Identification of novel nasopharyngeal carcinoma biomarkers by laser capture microdissection and proteomic analysis. Clin Cancer Res,2008, 14(2):435-445
[36]Mhawech P.14-3-3 proteins--an update. Cell Res,2005,15(4):228-236
[37]Hermeking H. The 14-3-3 cancer connection. Nat Rev Cancer,2003,3:931-943
[38]Wang Z, Trope CQ Suo Z, Tr(?)en G, Yang G, Nesland JM, Holm R. The clinicopathological and prognostic impact of 14-3-3 sigma expression on vulvar squamous cell carcinomas. BMC Cancer,2008,8:308
[39]Laronga C, Yang HY, Neal C, Lee MH. Association of the cyclin-dependent kinases and 14-3-3 sigma negatively regulates cell cycle progression. J Biol Chem,2000, 275(30):23106-23112
[40]Wilker EW, van Vugt MA, Artim SA, Huang PH, Petersen CP, Reinhardt HC, Feng Y, Sharp PA, Sonenberg N, White FM, Yaffe MB.14-3-3sigma controls mitotic translation to facilitate cytokinesis. Nature,2007,446(7133):329-332
[41]Dellambra E, Golisano O, Bondanza S, Siviero E, Lacal P, Molinari M, D'Atri S, De Luca M. Downregulation of 14-3-3 sigma prevents clonal evolution and leads to immortalization of primary human Keratinocytes. J Cell Biol,2000, 149(5):1117-1130
[42]Moreira JM, Ohlsson G, Rank FE, Celis JE. Down-regulation of the tumor suppressor protein 14-3-3 sigma is a sporadic event in cancer of the breast. Mol Cell Proteomics,2005,4(4):555-569
[43]Yi B, Tan SX, Tang CE, Huang WG, Cheng AL, Li C, Zhang PF, Li MY, Li JL, Yi H, Peng F, Chen ZC, Xiao ZQ. Inactivation of 14-3-3 sigma by promoter methylation correlates with metastasis in nasopharyngeal carcinoma. J Cell Biochem,2009, 106(5):858-866
[44]Vera J, Schultz J, Ibrahim S, Raatz Y, Wolkenhauer O, Kunz M. Dynamical effects of epigenetic silencing of 14-3-3sigma expression. Mol Biosyst,2010,6(1):254-263
[45]Liang S, Xu Y, Shen G, Zhao X, Zhou J, Li X, Gong F, Ling B, Fang L, Huang C, Wei Y. Gene expression and methylation status of 14-3-3 sigma in human renal carcinoma tissues. IUBMB Life,2008,60(8):534-540
[46]Li DJ, Deng G, Xiao ZQ, Yao HX, Li C, Peng F, Li MY, Zhang PF, Chen YH, Chen ZC. Identificating 14-3-3 sigma as a lymph node metastasis-related protein in human lung squamous carcinoma. Cancer Lett,2009,279(1):65-73
[47]Benzinger A, Muster N, Koch HB, Yates JR 3rd, Hermeking H. Targeted proteomic analysis of 14-3-3 sigma, a p53 effector commonly silenced in cancer. Mol Cell Proteomics,2005,4(6):785-795
[48]Yang H, Zhao R, Lee MH.14-3-3sigma, a p53 regulator, suppresses tumor growth of nasopharyngeal carcinoma. Mol Cancer Ther,2006,5(2):253-260
[49]Neal CL, Yao J, Yang W, Zhou X, Nguyen NT, Lu J, Danes CG, Guo H, Lan KH, Ensor J, Hittelman W, Hung MC, Yu D.14-3-3zeta overexpression defines high risk for breast cancer recurrence and promotes cancer cell survival. Cancer Res,2009, 69(8):3425-3432
[50]Yoon NK, Seligson DB, Chia D, Elshimali Y, Sulur G, Li A, Horvath S, Maresh E, Mah V, Bose S, Bonavida B, Goodglick L. Higher expression levels of 14-3-3sigma in ductal carcinoma in situ of the breast predict poorer outcome. Cancer Biomark, 2009,5(4):215-224
[51]Hu Z, Hung JH, Wang Y, Chang YC, Huang CL, Huyck M, DeLisi C. VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology. Nucleic Acids Res,2009,37(Web Server issue):W115-W121
[52]Hu Z, Snitkin ES, DeLisi C. VisANT:an integrative framework for networks in systems biology. Brief Bioinform,2008,9(4):317-325
[53]Han B, Xie H, Chen Q, Zhang JT. Sensitizing hormone-refractory prostate cancer cells to drug treatment by targeting 14-3-3sigma. Mol Cancer Ther,2006, 5(4):903-912
[54]WARBURG O. On the origin of cancer cells. Science,1956,123(3191):309-314
[55]Gogvadze V, Zhivotovsky B, Orrenius S. The Warburg effect and mitochondrial stability in cancer cells. Mol Aspects Med,2010,31(1):60-74
[56]Chia WJ, Tang BL. Emerging roles for Rab family GTPases in human cancer. Biochim Biophys Acta,2009,1795(2):110-116
[57]Cheng KW, Lahad JP, Gray JW, Mills GB. Emerging role of RAB GTPases in cancer and human disease. Cancer Res,2005,65(7):2516-2519
[58]Schara K, Jansa V, Sustar V, Dolinar D, Pavlic JI, Lokar M, Kralj-Iglic V, Veranic P, Iglic A. Mechanisms for the formation of membranous nanostructures in cell-to-cell communication. Cell Mol Biol Lett,2009,14(4):636-656
[59]Konopleva M, Tabe Y, Zeng Z, Andreeff M. Therapeutic targeting of microenvironmental interactions in leukemia:mechanisms and approaches. Drug Resist Updat,2009,12(4-5):103-113
[60]Warner JR, McIntosh KB. How common are extraribosomal functions of ribosomal proteins? Mol Cell,2009,34(1):3-11
[61]Lindstrom MS. Emerging functions of ribosomal proteins in gene-specific transcription and translation. Biochem Biophys Res Commun.2009,379(2):167-170
[62]Montanaro L, Trere D, Derenzini M. Nucleolus, ribosomes, and cancer. Am J Pathol. 2008,173(2):301-310
[63]Di Cesare S, Nantel A, Marshall JC, Fernandes BF, Antecka E, Orellana ME, Abourbih D, Saornil AM, Burnier MN Jr. Expression profiling of formalin-fixed paraffin embedded primary human uveal melanomas using DASL matrices. J Cancer Res Clin Oncol,2010,136(4):577-586
[64]Wang S, Huang J, He J, Wang A, Xu S, Huang SF, Xiao S. RPL41, a small ribosomal peptide deregulated in tumors, is essential for mitosis and centrosome integrity. Neoplasia,2010,12(3):284-293
[65]Naora H. Involvement of ribosomal proteins in regulating cell growth and apoptosis: translational modulation or recruitment for extraribosomal activity? Immunol Cell Biol,1999,77(3):197-205
[66]Belin S, Beghin A, Solano-Gonzalez E, Bezin L, Brunet-Manquat S, Textoris J, Prats AC, Mertani HC, Dumontet C, Diaz JJ. Dysregulation of ribosome biogenesis and translational capacity is associated with tumor progression of human breast cancer cells. PLoS One,2009,4(9):e7147
[67]Warner JR, McIntosh KB. How common are extraribosomal functions of ribosomal proteins? Mol Cell.2009,34(1):3-11
[68]Hou MM, Chang JW, Pang ST, Chiang YJ, Shen YC, Liao SK, Hsieh JJ, Yeh KY, Chang NJ, Chuang CK. Characterization of the response of dendritic cells and regulatory T cells to tumor antigens in patients with renal cell carcinoma. Chang Gung Med J.2010,33(1):25-35
[69]Breckpot K, Escors D. Dendritic cells for active anti-cancer immunotherapy:targeting activation pathways through genetic modification. Endocr Metab Immune Disord Drug Targets,2009,9(4):328-343
[70]Milani V, Noessner E, Ghose S, Kuppner M, Ahrens B, Scharner A, Gastpar R, Issels RD. Heat shock protein 70:role in antigen presentation and immune stimulation. Int J Hyperthermia,2002,18(6):563-575
[71]Hollander N. Current vaccination strategies for the treatment of B-cell lymphoma and multiple myeloma. Crit Rev Immunol,2009,29(5):399-418
[72]Mycielska ME, Patel A, Rizaner N, Mazurek MP, Keun H, Patel A, Ganapathy V, Djamgoz MB. Citrate transport and metabolism in mammalian cells:prostate epithelial cells and prostate cancer. Bioessays,2009,31(1):10-20
[73]Weinberg F, Chandel NS. Mitochondrial metabolism and cancer. Ann N Y Acad Sci, 2009,1177:66-73
[74]Satoh J, Tabunoki H, Nanri Y, Arima K, Yamamura T. Human astrocytes express 14-3-3 sigma in response to oxidative and DNA-damaging stresses. Neurosci Res, 2006,56(1):61-72
[75]Lee MH, Lozano G. Regulation of the p53-MDM2 pathway by 14-3-3 sigma and other proteins. Semin Cancer Biol,2006,16(3):225-234
[76]Moll R, Franke WW. Intermediate filaments and their interaction with membranes. The desmosome-cytoKeratin filament complex and epithelial differentiation. Pathol Res Pract,1982,175(2-3):146-161
[77]Kreplak L, Bar H, Leterrier JF, Herrmann H, Aebi U. Exploring the mechanical behavior of single intermediate filaments. J Mol Biol,2005,354(3):569-577
[78]Coulombe PA, Omary MB.'Hard' and'soft' principles defining the structure, function and regulation of Keratin intermediate filaments. Curr Opin Cell Biol,2002, 14(1):110-122
[79]Shaevitz JW, Fletcher DA. Load fluctuations drive actin network growth. Proc Natl Acad Sci U S A,2007,104(40):15688-15692
[80]Zeile WL, Zhang F, Dickinson RB, Purich DL. Listeria's right-handed helical rocket-tail trajectories:mechanistic implications for force generation in actin-based motility. Cell Motil Cytoskeleton,2005,60(2):121-128
[81]Hammer JA 3rd, Wu XS. Rabs grab motors:defining the connections between Rab GTPases and motor proteins. Curr Opin Cell Biol,2002,14(1):69-75
[82]Grosshans BL, Ortiz D, Novick P. Rabs and their effectors:achieving specificity in membrane traffic. Proc Natl Acad Sci U S A,2006,103(32):11821-11827
[83]Stenmark H. Rab GTPases as coordinators of vesicle traffic. Nat Rev Mol Cell Biol, 2009,10(8):513-525
[84]Fukuda M. Regulation of secretory vesicle traffic by Rab small GTPases. Cell Mol Life Sci,2008,65(18):2801-2813
[85]Wang JS, Wang FB, Zhang QG, Shen ZZ, Shao ZM. Enhanced expression of Rab27A gene by breast cancer cells promoting invasiveness and the metastasis potential by secretion of insulin-like growth factor-Ⅱ. Mol Cancer Res,2008,6(3):372-382
[86]Palmieri D, Bouadis A, Ronchetti R, Merino MJ, Steeg PS. Rablla differentially modulates epidermal growth factor-induced proliferation and motility in immortal breast cells. Breast Cancer Res Treat,2006,100(2):127-137
[87]Fong T, Morgensztern D, Govindan R. EGFR inhibitors as first-line therapy in advanced non-small cell lung cancer. J Thorac Oncol,2008,3(3):303-310
[88]Cho EY, Han JJ, Choi YL, Kim KM, Oh YL. Comparison of Her-2, EGFR and cyclin D1 in primary breast cancer and paired metastatic lymph nodes:an immunohistochemical and chromogenic in situ hybridization study. J Korean Med Sci,2008,23(6):1053-1061
[89]Kim YJ, Lee GS, Hyun SH, Ka HH, Choi KC, Lee CK, Jeung EB. Uterine expression of epidermal growth factor family during the course of pregnancy in pigs. Reprod Domest Anim.2009,44(5):797-804
[90]Lee J, Ban JY, Won KY, Kim GY, Lim SJ, Lee S, Kim YW, Park YK, Lee SS. Expression of EGFR and follicular dendritic markers in lymphoid follicles from patients with Castleman's disease. Oncol Rep,2008,20(4):851-856
[91]Yang CH. EGFR tyrosine kinase inhibitors for the treatment of NSCLC in East Asia: present and future. Lung Cancer,2008,60 Suppl 2:S23-S30
[92]Uramoto H, Sugio K, Oyama T, Ono K, Sugaya M, Yoshimatsu T, Hanagiri T, Morita M, Yasumoto K. Epidermal growth factor receptor mutations are associated with gefitinib sensitivity in non-small cell lung cancer in Japanese. Lung Cancer,2006, 51(1):71-77
[93]O-charoenrat P, Wongkajornsilp A, Rhys-Evans PH, Eccles SA. Signaling pathways required for matrix metalloproteinase-9 induction by betacellulin in head-and-neck squamous carcinoma cells. Int J Cancer,2004,111(2):174-183
[94]Do NY, Lim SC, Im TS. Expression of c-erbB receptors, MMPs and VEGF in squamous cell carcinoma of the head and neck. Oncol Rep,2004,12(2):229-237
[95]Ceresa BP, Bahr SJ. rab7 activity affects epidermal growth factor:epidermal growth factor receptor degradation by regulating endocytic trafficking from the late endosome. J Biol Chem,2006,281(2):1099-1106
[96]Ceresa BP. Regulation of EGFR endocytic trafficking by rab proteins. Histol Histopathol,2006,21(9):987-993
[97]Fortier AM, Van Themsche C, Asselin E, Cadrin M. Akt isoforms regulate intermediate filament protein levels in epithelial carcinoma cells. FEBS Lett,2010, 584(5):984-988
[98]Zhao Y, Yan Q, Long X, Chen X, Wang Y. Vimentin affects the mobility and invasiveness of prostate cancer cells. Cell Biochem Funct,2008,26(5):571-577
[99]Obermajer N, Doljak B, Kos J. CytoKeratin 8 ectoplasmic domain binds urokinase-type plasminogen activator to breast tumor cells and modulates their adhesion, growth and invasiveness. Mol Cancer,2009,8:88
[100]Kakehashi A, Inoue M, Wei M, Fukushima S, Wanibuchi H. CytoKeratin 8/18 overexpression and complex formation as an indicator of GST-P positive foci transformation into hepatocellular carcinomas. Toxicol Appl Pharmacol,2009, 238(1):71-79
[101]Ishii T, Bandoh S, Fujita J, Ohtsuki Y, Tojo Y, Kanaji N, Fukunaga Y, Ueda Y, Ishida T, Kubo A. Full-length cytoKeratin 8 is released and circulates in patients with non-small cell lung cancer. Tumour Biol,2008,29(1):57-62
[102]Makino T, Yamasaki M, Takeno A, Shirakawa M, Miyata H, Takiguchi S, Nakajima K, Fujiwara Y, Nishida T, Matsuura N, Mori M, Doki Y. CytoKeratins 18 and 8 are poor prognostic markers in patients with squamous cell carcinoma of the oesophagus. Br J Cancer,2009,101(8):1298-1306
[1]Michal, G. Biochemical Pathways (Poster), Boehringer Mannheim,1993
[2]Michal, G. Biochemical Pathways:An Atlas of Biochemistry and Molecular Biology. John Wiley and Sons Ltd.1998
[3]Fields S, Song O. A novel genetic system to detect protein-protein interactions. Nature, 1989,340(6230):245-246
[4]Rigaut G, Shevchenko A, Rutz B, Wilm M, Mann M, Seraphin B. A generic protein purification method for protein complex characterization and proteome exploration. Nat Biotechnol,1999,17(10):1030-1032
[5]Selbach M, Mann M. Protein interaction screening by quantitative
immunoprecipitation combined with knockdown (QUICK). Nat Methods,2006, 3(12):981-983
[6]Echeverri CJ, Perrimon N. High-throughput RNAi screening in cultured cells:a user's guide. Nat Rev Genet,2006,7(5):373-384
[7]Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature,1998, 391(6669):806-811
[8]Lockhart DJ, Dong H, Byrne MC, Follettie MT, Gallo MV, Chee MS, Mittmann M, Wang C, Kobayashi M, Horton H, Brown EL. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat Biotechnol,1996,14(13):1675-1680
[9]Blat Y, Kleckner N. Cohesins bind to. preferential sites along yeast chromosome III, with differential regulation along arms versus the centric region. Cell,1999, 98(2):249-259
[10]Ren B, Robert F, Wyrick JJ, Aparicio O, Jennings EG, Simon I, Zeitlinger J, Schreiber J, Hannett N, Kanin E, Volkert TL, Wilson CJ, Bell SP, Young RA. Genome-wide location and function of DNA binding proteins. Science,2000,290(5500):2306-2309
[11]Barabasi AL, Oltvai ZN. Network biology:understanding the cell's functional organization. Nat Rev Genet,2004,5(2):101-113
[12]Barabasi AL, Albert R. Emergence of scaling in random networks. Science,1999, 286(5439):509-512
[13]Albert R, Jeong H, Barabasi AL. Error and attack tolerance of complex networks. Nature,2000,406(6794):378-382
[14]Kelley BP, Yuan B, Lewitter F, Sharan R, Stockwell BR, Ideker T. PathBLAST:a tool for alignment of protein interaction networks. Nucleic Acids Res,2004,32(Web Server issue):W83-W88
[15]Saraiya P, Chris N, Karen D. Visualizing biological pathways:requirements analysis, systems evaluation and research agenda. Inf Vis,2005,1-15
[16]Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res, 2010,38 (Database issue):D355-D360
[17]Alfarano C, Andrade CE, Anthony K, Bahroos N, Bajec M, Bantoft K, Betel D, Bobechko B, Boutilier K, Burgess E, Buzadzija K, Cavero R, D'Abreo C, Donaldson I, Dorairajoo D, Dumontier MJ, Dumontier MR, Earles V, Farrall R, Feldman H, Garderman E, Gong Y, Gonzaga R, Grytsan V, Gryz E, Gu V, Haldorsen E, Halupa A,
Haw R, Hrvojic A, Hurrell L, Isserlin R, Jack F, Juma F, Khan A, Kon T, Konopinsky S, Le V, Lee E, Ling S, Magidin M, Moniakis J, Montojo J, Moore S, Muskat B, Ng I, Paraiso JP, Parker B, Pintilie G, Pirone R, Salama JJ, Sgro S, Shan T, Shu Y, Siew J, Skinner D, Snyder K, Stasiuk R, Strumpf D, Tuekam B, Tao S, Wang Z, White M, Willis R, Wolting C, Wong S, Wrong A, Xin C, Yao R, Yates B, Zhang S, Zheng K, Pawson T, Ouellette BF, Hogue CW. The Biomolecular Interaction Network Database and related tools. Nucleic Acids Res,2005,33(Database issue):D418-D424
[18]Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene ontology:tool for the unification of biology. The Gene Ontology Consortium. Nat Genet,2000,25(1):25-29
[19]Xenarios I, Rice DW, Salwinski L, Baron MK, Marcotte EM, Eisenberg D. DIP:the database of interacting proteins. Nucleic Acids Res,2000,28(1):289-291
[20]Killcoyne S, Carter GW, Smith J, Boyle J. Cytoscape:a community-based framework for network modeling. Methods Mol Biol,2009,563:219-239
[21]Breitkreutz BJ, Stark C, Tyers M. Osprey:a network visualization system. Genome Biol,2003,4(3):R22
[22]Han K, Ju BH, Jung H. WebInterViewer:visualizing and analyzing molecular interaction networks. Nucleic Acids Res,2004,32(Web Server issue):W89-W95
[23]Iragne F, Nikolski M, Mathieu B, Auber D, Sherman D. Pro Viz:protein interaction visualization and exploration. Bioinformatics,2005,21(2):272-274
[24]Dogrusoz U, Erson EZ, Giral E, Demir E, Babur O, Cetintas A, Colak R. PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization. Bioinformatics,2006,22(3):374-375
[25]Hu Z, Snitkin ES, DeLisi C. VisANT:an integrative framework for networks in systems biology. Brief Bioinform,2008,9(4):317-325
[26]David, A. Tulip. In Mutzel,P. et al. (eds.) Graph Drawing,9th International Symposium, GD 2001,2265 of Lecture Notes in Computer Science. Springer,2001, pp:435-437. ISBN 3-540-43309-0
[27]Hermjakob H, Montecchi-Palazzi L, Bader G, Wojcik J, Salwinski L, Ceol A, Moore S, Orchard S, Sarkans U, von Mering C, Roechert B, Poux S, Jung E, Mersch H, Kersey P, Lappe M, Li Y, Zeng R, Rana D, Nikolski M, Husi H, Brun C, Shanker K, Grant SG, Sander C, Bork P, Zhu W, Pandey A, Brazma A, Jacq B, Vidal M, Sherman D,
Legrain P, Cesareni G, Xenarios I, Eisenberg D, Steipe B, Hogue C, Apweiler R. The HUPO PSI's molecular interaction format-a community standard for the representation of protein interaction data. Nat Biotechnol,2004,22(2):177-183
[28]Aranda B, Achuthan P, Alam-Faruque Y, Armean I, Bridge A, Derow C, Feuermann M, Ghanbarian AT, Kerrien S, Khadake J, Kerssemakers J, Leroy C, Menden M, Michaut M, Montecchi-Palazzi L, Neuhauser SN, Orchard S, Perreau V, Roechert B, van Eijk K, Hermjakob H. The IntAct molecular interaction database in 2010. Nucleic Acids Res,2010,38(Database issue):D525-D531.
[29]Gene Ontology Consortium. The Gene Ontology project in 2008. Nucleic Acids Res, 2008,36(Database issue):D440-D444
[30]Baitaluk M, Sedova M, Ray A, Gupta A. BiologicalNetworks:visualization and analysis tool for systems biology. Nucleic Acids Res,2006,34(Web Server issue):W466-W471
[31]Baitaluk M, Qian X, Godbole S, Raval A, Ray A, Gupta A. PathSys:integrating molecular interaction graphs for systems biology. BMC Bioinformatics,2006,7:55
[32]Sugiyama K, Shojiro T, Mitsuhiko T. Methods for visual understanding of hierarchical system structures. IEEE Trans, Systems, Man and Cybernetics 11(2):109-125
[33]Nikitin A, Egorov S, Daraselia N, Mazo I. Pathway studio-the analysis and navigation of molecular networks. Bioinformatics,2003,19(16):2155-2157
[34]Schreiber F. High quality visualization of biochemical pathways in BioPath. In Silico Biol,2002,2(2):59-73
[35]Paek E, Park J, Lee KJ. Multi-layered representation for cell signaling pathways. Mol Cell Proteomics,2004,3(10):1009-1022
[36]Kitano H. A graphical notation for biological networks. BioSilico,2003,1(5):169-176
[37]Eades P. A heuristic for graph drawing. Congressus Numerantium,1984,42:142-160
[38]Fruchterman TMJ, Reingold EM. Graph drawing by force-directed placement. Soft Pract Exper,1991,21(11):1129-1164
[39]Kamada T, Kawai S. An algorithm for drawing general undirected graphs. Inf Process Lett,1989,31(1):7-15
[40]Rzhetsky A, Iossifov I, Koike T, Krauthammer M, Kra P, Morris M, Yu H, Duboue PA, Weng W, Wilbur WJ, Hatzivassiloglou V, Friedman C. Gene Ways:a system for extracting, analyzing, visualizing, and integrating molecular pathway data. J Biomed Inform,2004,37(1):43-53
[41]Li W, Kurata H. A grid layout algorithm for automatic drawing of biochemical networks. Bioinformatics,2005,21(9):2036-2042
[42]Nagasaki M, Doi A, Matsuno H, Miyano S. Genomic Object Net:Ⅰ. A platform for modelling and simulating biopathways. Appl Bioinformatics,2003,2(3):181-184
[43]Barsky A, Gardy JL, Hancock RE, Munzner T. Cerebral:a Cytoscape plugin for layout of and interaction with biological networks using subcellular localization annotation. Bioinformatics,2007,23(8):1040-1042
[44]Schwikowski B, Uetz P, Fields S. A network of protein-protein interactions in yeast. Nat Biotechnol,2000,18(12):1257-1261
[45]Andreeva A, Howorth D, Chandonia JM, Brenner SE, Hubbard TJ, Chothia C, Murzin AG. Data growth and its impact on the SCOP database:new developments. Nucleic Acids Res,2008,36(Database issue):D419-D425
[46]Lappe M, Park J, Niggemann O, Holm L. Generating protein interaction maps from incomplete data:application to fold assignment. Bioinformatics,2001,17(Suppl 1):S149-S156
[47]Vlasblom J, Wu S, Pu S, Superina M, Liu G, Orsi C, Wodak SJ. GenePro:a Cytoscape plug-in for advanced visualization and analysis of interaction networks. Bioinformatics, 2006,22(17):2178-2179
[48]Longabaugh WJ, Davidson EH, Bolouri H. Computational representation of developmental genetic regulatory networks. Dev Biol,2005,283(1):1-16
[49]Ceol A, Chatr Aryamontri A, Licata L, Peluso D, Briganti L, Perfetto L, Castagnoli L, Cesareni G. MINT, the molecular interaction database:2009 update. Nucleic Acids Res,2010,38(Database issue):D532-D539
[50]Chatr-aryamontri A, Ceol A, Palazzi LM, Nardelli G, Schneider MV, Castagnoli L, Cesareni G. MINT:the Molecular INTeraction database. Nucleic Acids Res,2007, 35(Database issue):D572-D574
[51]Henry N, Fekete JD. Matrixexplorer:a dual-representation system to explore social networks. IEEE Trans Vis Comput Graph,2006,12(5):677-684
[52]Klipp E, Liebermeister W, Helbig A, Kowald A, Schaber J. Systems biology standards-the community speaks. Nat Biotechnol,2007,25(4):390-391
[53]Cook DL, Farley JF, Tapscott SJ. A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems. Genome Biol,2001,2(4):research0012.1-0012.10
[54]Kitano H. A graphical notation for biological networks. BioSilico,2003,1(5):169-176
[55]Kohn KW, Aladjem MI, Weinstein JN, Pommier Y. Molecular interaction maps of
bioregulatory networks:a general rubric for systems biology. Mol Biol Cell,2006, 17(1):1-13
[56]Kohn KW, Aladjem MI, Kim S, Weinstein JN, Pommier Y. Depicting combinatorial complexity with the molecular interaction map notation. Mol Syst Biol,2006,2:51
[57]Kohn KW. Molecular interaction maps as information organizers and simulation guides. Chaos,2001,11(1):84-97
[58]Kurata H, Matoba N, Shimizu N. CADLIVE for constructing a large-scale biochemical network based on a simulation-directed notation and its application to yeast cell cycle. Nucleic Acids Res,2003,31(14):4071-4084
[59]Pirson I, Fortemaison N, Jacobs C, Dremier S, Dumont JE, Maenhaut C. The visual display of regulatory information and networks. Trends Cell Biol,2000, 10(10):404-408
[60]Funahashi A, Jouraku A, Matsuoka Y, Kitano H. Integration of CellDesigner and SABIO-RK. In Silico Biol,2007,7(2 Suppl):S81-S90
[61]Funahashi A, Tanimura N, Morohashi M, Kitano H. CellDesigner:a process diagram editor for gene-regulatory and biochemical networks. BIOSILICO,2003,1:159-162,
[62]Funahashi A, Matsuoka Y, Jouraku A, Morohashi M, Kikuchi N, Kitano H. CellDesigner 3.5:A Versatile Modeling Tool for Biochemical Networks Proceedings of the IEEE,2008,96(8):1254-1265
[63]Dwyer T, Rolletschek H, Schreiber F. Representing experimental biological data in metabolic networks. In Chen,Y.-P.P.APBC, volume 29 of CRPIT. Australian Computer Society,2004, pp.13-20 ISBN 1-920682-11-2.
[64]Schreiber F, Schwobbermeyer H. MAVisto:a tool for the exploration of network motifs. Bioinformatics.2005,21(17):3572-3574
[65]Adar E. Guess:a language and interface for graph exploration. In CHI'06: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM Press, New York, USA,2006, pp:791-800 ISBN 1-59593-372-7.
[66]UniProt Consortium. The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res,2010,38(Database issue):D142-D148
[67]Yip YL, Famiglietti M, Gos A, Duek PD, David FP, Gateau A, Bairoch A. Annotating single amino acid polymorphisms in the UniProt/Swiss-Prot knowledgebase. Hum Mutat,2008,29(3):361-366
[68]Swainston N, Mendes P. libAnnotationSBML:a library for exploiting SBML annotations. Bioinformatics,2009,25(17):2292-2293
[69]Odriguez N, Donizelli M, Le Novere N. SBMLeditor:effective creation of models in the Systems Biology Markup language (SBML). BMC Bioinformatics,2007,8:79
[70]Finney A, Hucka M. Systems biology markup language:Level 2 and beyond. Biochem Soc Trans,2003,31(Pt 6):1472-1473
[71]Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, Arkin AP, Bornstein BJ, Bray D, Cornish-Bowden A, Cuellar AA, Dronov S, Gilles ED, Ginkel M, Gor V, Goryanin II, Hedley WJ, Hodgman TC, Hofmeyr JH, Hunter PJ, Juty NS, Kasberger JL, Kremling A, Kummer U, Le Novere N, Loew LM, Lucio D, Mendes P, Minch E, Mjolsness ED, Nakayama Y, Nelson MR, Nielsen PF, Sakurada T, Schaff JC, Shapiro BE, Shimizu TS, Spence HD, Stelling J, Takahashi K, Tomita M, Wagner J, Wang J; SBML Forum. The systems biology markup language (SBML):a medium for representation and exchange of biochemical network models. Bioinformatics,2003, 19(4):524-531
[72]Kerrien S, Orchard S, Montecchi-Palazzi L, Aranda B, Quinn AF, Vinod N, Bader GD, Xenarios I, Wojcik J, Sherman D, Tyers M, Salama JJ, Moore S, Ceol A, Chatr-Aryamontri A, Oesterheld M, Stumpflen V, Salwinski L, Nerothin J, Cerami E, Cusick ME, Vidal M, Gilson M, Armstrong J, Woollard P, Hogue C, Eisenberg D, Cesareni G, Apweiler R, Hermjakob H. Broadening the horizon-level 2.5 of the HUPO-PSI format for molecular interactions. BMC Biol,2007,5:44
[73]Stromback L, Lambrix P. Representations of molecular pathways:an evaluation of SBML, PSI MI and BioPAX. Bioinformatics,2005,21(24):4401-4407
[74]Scott MS, Perkins T, Bunnell S, Pepin F, Thomas DY, Hallett M. Identifying regulatory subnetworks for a set of genes. Mol Cell Proteomics.2005,4(5):683-692
[75]Schreiber F, Schwobbermeyer H. MAVisto:a tool for the exploration of network motifs. Bioinformatics.2005,21(17):3572-3574
[76]Ho Y, Gruhler A, Heilbut A, Bader GD, Moore L, Adams SL, Millar A, Taylor P, Bennett K, Boutilier K, Yang L, Wolting C, Donaldson I, Schandorff S, Shewnarane J, Vo M, Taggart J, Goudreault M, Muskat B, Alfarano C, Dewar D, Lin Z, Michalickova K, Willems AR, Sassi H, Nielsen PA, Rasmussen KJ, Andersen JR, Johansen LE, Hansen LH, Jespersen H, Podtelejnikov A, Nielsen E, Crawford J, Poulsen V, S(?)rensen BD, Matthiesen J, Hendrickson RC, Gleeson F, Pawson T, Moran MF, Durocher D, Mann M, Hogue CW, Figeys D, Tyers M. Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature,2002, 415(6868):180-183
[77]Ludemann A, Weicht D, Selbig J, Kopka J. PaVESy:Pathway Visualization and Editing System. Bioinformatics,2004,20(16):2841-2844
[78]Tong AH, Evangelista M, Parsons AB, Xu H, Bader GD, Page N, Robinson M, Raghibizadeh S, Hogue CW, Bussey H, Andrews B, Tyers M, Boone C. Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science,2001, 294(5550):2364-2368
[79]Jin R, McCallen S., Liu CC, Xiang Y, Almaas E, Zhou XJ. Identifying dynamic network modules with temporal and spatial constraints. Pac Symp Biocomput, 2009:203-214
[80]Jung SH, Jang WH, Hur HY, Hyun B, Han DS. Protein complex prediction based on mutually exclusive interactions in protein interaction network. Genome Inform,2008, 21:77-88
[81]Miyamoto-Sato E, Fujimori S, Ishizaka M, Hirai N, Masuoka K, Saito R, Ozawa Y, Hino K, Washio T, Tomita M, Yamashita T, Oshikubo T, Akasaka H, Sugiyama J, Matsumoto Y, Yanagawa H. A comprehensive resource of interacting protein regions for refining human transcription factor networks. PLoS One,2010,5(2):e9289
[82]Huang Y, Li S. Detection of characteristic sub pathway network for angiogenesis based on the comprehensive pathway network. BMC Bioinformatics,2010,11(Suppl 1):S32
[83]Ng KL, Ciou JS, Huang CH. Prediction of protein functions based on function-function correlation relations. Comput Biol Med,2010,40(3):300-305
[84]Jung SH, Hyun B, Jang WH, Hur HY, Han DS. Protein complex prediction based on simultaneous protein interaction network. Bioinformatics,2010,26(3):385-391
[85]Kushwaha SK, Shakya M. PINAT1.0:Protein interaction network analysis tool. Bioinformation,2009,3(10):419-421