Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, to the best of knowledge, there is no satisfactory network-based method for carcinogenesis characterization and diagnosis from the system perspective. In this study, a systems biology approach, which integrated microarray gene expression profiles and protein-protein interaction information, was proposed to develop a network-based biomarker for molecular investigation and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and for non-cancer samples. Based on the network-based biomarker, a total of 40 significant proteins are identified with carcinogenesis relevance values (CRVs) to gain an insight into the network mechanism of lung carcinogenesis. In addition, the network-based biomarker is also acted as the diagnostic tool, demonstrated to be effective to diagnose the smokers with lung cancer. The results show that the network-based biomarker through constructed protein association networks successfully sheds light on the pathways and mechanisms in lung carcinogenic process and, most importantly, provides potential therapeutic targets to combat against cancer.

癌症是一種細胞不正常的增生而造成腫瘤的一種複雜的疾病，而肺癌又是眾多癌症中致死率最高、全世界造成死亡數最多的一種癌症。有許多的論文致力於研究致癌的過程以及尋找可以分類特徵的生物標記，這樣的癌症生物標記通常被用來當作診斷評估的工具或是預後情況的指標。然而，就我們所知，目前並沒有令人滿意的以網路為基礎的方法，從系統的觀點來研究致癌的機制及診斷。因此，在這篇論文中，我們提出了一個結合微陣列基因表現以及蛋白質交互作用資訊的系統生物學方法，用來發展生物網路標記以進行肺癌分子研究及診斷。我們利用這樣的資料，結合一個簡單的線性迴歸模型以及系統鑑別與統計方法來建構蛋白質關聯性網路，而從癌症樣本以及非癌症樣本所建構出來的兩個蛋白質關聯性網路就組成了生物網路標記。根據這個生物網路標記，配合致癌關聯數值的計算，我們總共找出了四十個重要的蛋白質，並藉此來瞭解形成肺癌的網路機制。此外，這個生物網路標記也可以用來當作肺癌診斷的工具，可以有效的診斷出具有肺癌的吸煙者。以上這些結果顯示出這個包含蛋白質關聯性網路的生物網路標記可以讓我們對於形成肺癌的過程以及機制更加瞭解，更重要的是，我們找出的那些重要的蛋白質提供了可能的分子目標來治療癌症。

1. Evan GI, Vousden KH: Proliferation, cell cycle and apoptosis in cancer. Nature 2001, 411:342-348.
2. Parkin DM, Bray F, Ferlay J, Pisani P: Global cancer statistics, 2002. CA Cancer J Clin 2005, 55:74-108.
3. Spira A, Beane JE, Shah V, Steiling K, Liu G, Schembri F, Gilman S, Dumas YM, Calner P, Sebastiani P, et al: Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer. Nat Med 2007, 13:361-366.
4. Brambilla E, Travis WD, Colby TV, Corrin B, Shimosato Y: The new World Health Organization classification of lung tumours. Eur Respir J 2001, 18:1059-1068.
5. Khuder SA: Effect of cigarette smoking on major histological types of lung cancer: a meta-analysis. Lung Cancer 2001, 31:139-148.
6. Spira A, Beane J, Shah V, Liu G, Schembri F, Yang X, Palma J, Brody JS: Effects of cigarette smoke on the human airway epithelial cell transcriptome. Proc Natl Acad Sci U S A 2004, 101:10143-10148.
7. Hecht SS: Tobacco smoke carcinogens and lung cancer. J Natl Cancer Inst 1999, 91:1194-1210.
8. Takahashi H, Ogata H, Nishigaki R, Broide DH, Karin M: Tobacco smoke promotes lung tumorigenesis by triggering IKKbeta- and JNK1-dependent inflammation. Cancer Cell 2010, 17:89-97.
9. Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, et al: Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999, 286:531-537.
10. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, et al: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000, 403:503-511.
11. Hirsch FR, Merrick DT, Franklin WA: Role of biomarkers for early detection of lung cancer and chemoprevention. Eur Respir J 2002, 19:1151-1158.
12. Ein-Dor L, Zuk O, Domany E: Thousands of samples are needed to generate a robust gene list for predicting outcome in cancer. Proc Natl Acad Sci U S A 2006, 103:5923-5928.
13. Hanahan D, Weinberg RA: The hallmarks of cancer. Cell 2000, 100:57-70.
14. Vogelstein B, Kinzler KW: Cancer genes and the pathways they control. Nat Med 2004, 10:789-799.
15. Chuang HY, Lee E, Liu YT, Lee D, Ideker T: Network-based classification of breast cancer metastasis. Mol Syst Biol 2007, 3:140.
16. Taylor IW, Linding R, Warde-Farley D, Liu Y, Pesquita C, Faria D, Bull S, Pawson T, Morris Q, Wrana JL: Dynamic modularity in protein interaction networks predicts breast cancer outcome. Nat Biotechnol 2009, 27:199-204.
17. Luscombe NM, Babu MM, Yu H, Snyder M, Teichmann SA, Gerstein M: Genomic analysis of regulatory network dynamics reveals large topological changes. Nature 2004, 431:308-312.
18. Yang SK, Wang YC, Chao CC, Chuang YJ, Lan CY, Chen BS: Dynamic cross-talk analysis among TNF-R, TLR-4 and IL-1R signalings in TNFalpha-induced inflammatory responses. BMC Med Genomics 2010, 3:19.
19. Stark C, Breitkreutz B-J, Reguly T, Boucher L, Breitkreutz A, Tyers M: BioGRID: a general repository for interaction datasets. Nucl Acids Res 2006, 34:D535-539.
20. Peri S, Navarro JD, Amanchy R, Kristiansen TZ, Jonnalagadda CK, Surendranath V, Niranjan V, Muthusamy B, Gandhi TK, Gronborg M, et al: Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res 2003, 13:2363-2371.
21. Pagano M, Gauvreau K: Principles of biostatistics. 2nd edn. Pacific Grove, CA: Duxbury; 2000.
22. Johansson R: System modeling and identification. Englewood Cliffs, NJ: Prentice Hall; 1993.
23. Chang YH, Wang YC, Chen BS: Identification of transcription factor cooperativity via stochastic system model. Bioinformatics 2006, 22:2276-2282.
24. Akaike H: A new look at the statistical model identification. IEEE Transactions on Automatic Control 1974, 19:716-723.
25. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003, 13:2498-2504.
26. Vicent S, Lopez-Picazo JM, Toledo G, Lozano MD, Torre W, Garcia-Corchon C, Quero C, Soria JC, Martin-Algarra S, Manzano RG, Montuenga LM: ERK1/2 is activated in non-small-cell lung cancer and associated with advanced tumours. Br J Cancer 2004, 90:1047-1052.
27. Hu K, Gan YH, Li SL, Gao Y, Wu DC, Wang CY, Yu GY: Relationship of activated extracellular signal-regulated kinase 1/2 with lung metastasis in salivary adenoid cystic carcinoma. Oncol Rep 2009, 21:137-143.
28. Bierie B, Moses HL: TGF-beta and cancer. Cytokine Growth Factor Rev 2006, 17:29-40.
29. Kishimoto M, Kohno T, Okudela K, Otsuka A, Sasaki H, Tanabe C, Sakiyama T, Hirama C, Kitabayashi I, Minna JD, et al: Mutations and deletions of the CBP gene in human lung cancer. Clin Cancer Res 2005, 11:512-519.
30. Ding L, Getz G, Wheeler DA, Mardis ER, McLellan MD, Cibulskis K, Sougnez C, Greulich H, Muzny DM, Morgan MB, et al: Somatic mutations affect key pathways in lung adenocarcinoma. Nature 2008, 455:1069-1075.
31. Langer CJ: Emerging role of epidermal growth factor receptor inhibition in therapy for advanced malignancy: focus on NSCLC. Int J Radiat Oncol Biol Phys 2004, 58:991-1002.
32. Herbst RS, Heymach JV, Lippman SM: Lung cancer. N Engl J Med 2008, 359:1367-1380.
33. Vander Griend DJ, D'Antonio J, Gurel B, Antony L, Demarzo AM, Isaacs JT: Cell-autonomous intracellular androgen receptor signaling drives the growth of human prostate cancer initiating cells. Prostate 2010, 70:90-99.
34. Mitra SK, Schlaepfer DD: Integrin-regulated FAK-Src signaling in normal and cancer cells. Curr Opin Cell Biol 2006, 18:516-523.
35. Byers LA, Sen B, Saigal B, Diao L, Wang J, Nanjundan M, Cascone T, Mills GB, Heymach JV, Johnson FM: Reciprocal regulation of c-Src and STAT3 in non-small cell lung cancer. Clin Cancer Res 2009, 15:6852-6861.
36. Behrens C, Lin HY, Lee JJ, Raso MG, Hong WK, Wistuba, II, Lotan R: Immunohistochemical expression of basic fibroblast growth factor and fibroblast growth factor receptors 1 and 2 in the pathogenesis of lung cancer. Clin Cancer Res 2008, 14:6014-6022.
37. Welcsh PL, Owens KN, King MC: Insights into the functions of BRCA1 and BRCA2. Trends Genet 2000, 16:69-74.
38. Henderson BE, Feigelson HS: Hormonal carcinogenesis. Carcinogenesis 2000, 21:427-433.
39. Cox ME, Gleave ME, Zakikhani M, Bell RH, Piura E, Vickers E, Cunningham M, Larsson O, Fazli L, Pollak M: Insulin receptor expression by human prostate cancers. Prostate 2009, 69:33-40.
40. McLean GW, Carragher NO, Avizienyte E, Evans J, Brunton VG, Frame MC: The role of focal-adhesion kinase in cancer - a new therapeutic opportunity. Nat Rev Cancer 2005, 5:505-515.
41. Gallegos Ruiz MI, Floor K, Roepman P, Rodriguez JA, Meijer GA, Mooi WJ, Jassem E, Niklinski J, Muley T, van Zandwijk N, et al: Integration of gene dosage and gene expression in non-small cell lung cancer, identification of HSP90 as potential target. PLoS One 2008, 3:e0001722.
42. Wang H, Davis A, Yu S, Ahmed K: Response of cancer cells to molecular interruption of the CK2 signal. Mol Cell Biochem 2001, 227:167-174.
43. Barker N, Clevers H: Mining the Wnt pathway for cancer therapeutics. Nat Rev Drug Discov 2006, 5:997-1014.
44. Deniaud E, Baguet J, Mathieu AL, Pages G, Marvel J, Leverrier Y: Overexpression of Sp1 transcription factor induces apoptosis. Oncogene 2006, 25:7096-7105.
45. Imai MA, Oda Y, Oda M, Nakanishi I, Kawahara E: Overexpression of E2F1 associated with LOH at RB locus and hyperphosphorylation of RB in non-small cell lung carcinoma. J Cancer Res Clin Oncol 2004, 130:320-326.
46. Li Z, Zhao J, Du Y, Park HR, Sun SY, Bernal-Mizrachi L, Aitken A, Khuri FR, Fu H: Down-regulation of 14-3-3zeta suppresses anchorage-independent growth of lung cancer cells through anoikis activation. Proc Natl Acad Sci U S A 2008, 105:162-167.
47. West KA, Linnoila IR, Belinsky SA, Harris CC, Dennis PA: Tobacco carcinogen-induced cellular transformation increases activation of the phosphatidylinositol 3'-kinase/Akt pathway in vitro and in vivo. Cancer Res 2004, 64:446-451.
48. Sala G, Dituri F, Raimondi C, Previdi S, Maffucci T, Mazzoletti M, Rossi C, Iezzi M, Lattanzio R, Piantelli M, et al: Phospholipase Cgamma1 is required for metastasis development and progression. Cancer Res 2008, 68:10187-10196.
49. Zajac-Kaye M: Myc oncogene: a key component in cell cycle regulation and its implication for lung cancer. Lung Cancer 2001, 34 Suppl 2:S43-46.
50. Chen ZY, Cai L, Bie P, Wang SG, Jiang Y, Dong JH, Li XW: Roles of Fyn in pancreatic cancer metastasis. J Gastroenterol Hepatol 2010, 25:293-301.
51. Wang B, Liu K, Lin HY, Bellam N, Ling S, Lin WC: 14-3-3Tau regulates ubiquitin-independent proteasomal degradation of p21, a novel mechanism of p21 downregulation in breast cancer. Mol Cell Biol 2010, 30:1508-1527.
52. Inoue J, Gohda J, Akiyama T, Semba K: NF-kappaB activation in development and progression of cancer. Cancer Sci 2007, 98:268-274.
53. Langenfeld EM, Kong Y, Langenfeld J: Bone morphogenetic protein 2 stimulation of tumor growth involves the activation of Smad-1/5. Oncogene 2006, 25:685-692.
54. Ventura JJ, Tenbaum S, Perdiguero E, Huth M, Guerra C, Barbacid M, Pasparakis M, Nebreda AR: p38alpha MAP kinase is essential in lung stem and progenitor cell proliferation and differentiation. Nat Genet 2007, 39:750-758.
55. Hollstein M, Sidransky D, Vogelstein B, Harris CC: p53 mutations in human cancers. Science 1991, 253:49-53.
56. Deng X, Tannehill-Gregg SH, Nadella MV, He G, Levine A, Cao Y, Rosol TJ: Parathyroid hormone-related protein and ezrin are up-regulated in human lung cancer bone metastases. Clin Exp Metastasis 2007, 24:107-119.
57. Liu H, Radisky DC, Nelson CM, Zhang H, Fata JE, Roth RA, Bissell MJ: Mechanism of Akt1 inhibition of breast cancer cell invasion reveals a protumorigenic role for TSC2. Proc Natl Acad Sci U S A 2006, 103:4134-4139.
58. Kyriakis JM, Avruch J: Mammalian mitogen-activated protein kinase signal transduction pathways activated by stress and inflammation. Physiol Rev 2001, 81:807-869.
59. Shi Y, Massague J: Mechanisms of TGF-beta signaling from cell membrane to the nucleus. Cell 2003, 113:685-700.
60. Zwick E, Bange J, Ullrich A: Receptor tyrosine kinase signalling as a target for cancer intervention strategies. Endocr Relat Cancer 2001, 8:161-173.
61. Potter CJ, Pedraza LG, Xu T: Akt regulates growth by directly phosphorylating Tsc2. Nat Cell Biol 2002, 4:658-665.
62. Coussens LM, Werb Z: Inflammation and cancer. Nature 2002, 420:860-867.
63. Wang YC, Chen BS: Integrated cellular network of transcription regulations and protein-protein interactions. BMC Syst Biol 2010, 4:20.
64. Mathivanan S, Periaswamy B, Gandhi TK, Kandasamy K, Suresh S, Mohmood R, Ramachandra YL, Pandey A: An evaluation of human protein-protein interaction data in the public domain. BMC Bioinformatics 2006, 7 Suppl 5:S19.
65. Petrelli A, Giordano S: From single- to multi-target drugs in cancer therapy: when aspecificity becomes an advantage. Curr Med Chem 2008, 15:422-432.
66. Kris MG, Natale RB, Herbst RS, Lynch TJ, Jr., Prager D, Belani CP, Schiller JH, Kelly K, Spiridonidis H, Sandler A, et al: Efficacy of gefitinib, an inhibitor of the epidermal growth factor receptor tyrosine kinase, in symptomatic patients with non-small cell lung cancer: a randomized trial. JAMA 2003, 290:2149-2158.
67. Erler JT, Linding R: Network-based drugs and biomarkers. J Pathol 2010, 220:290-296.
68. Zimmermann GR, Lehar J, Keith CT: Multi-target therapeutics: when the whole is greater than the sum of the parts. Drug Discov Today 2007, 12:34-42.
69. Hocking RR: A Biometrics invited paper. The analysis and selection of variables in linear regression. Biometrics 1976, 32:1-49.
70. Seber GAF, Lee AJ: Linear regression analysis. 2nd edn. Hoboken, N.J.: Wiley-Interscience; 2003.