Novel clinico-genome network modeling for revolutionizing genotype-phenotype-based personalized cancer care

Expert Review of Molecular Diagnostics

Volumn 10, Issue 1, 2010, Pages 33-48

  Rouko, Dimitrios H ^a  

^a UNIVERSITY OF IOANNINA   (Greece)

Author keywords

Cancer heterogeneity; Genotype phenotype; Interactome; Personalized medicine; Reverse engineering; Signaling pathways network; Systems biology; Transcriptome

Indexed keywords

EPIDERMAL GROWTH FACTOR RECEPTOR; MICRORNA; NOTCH RECEPTOR; SONIC HEDGEHOG PROTEIN; TRANSCRIPTOME; WNT PROTEIN;

ANGIOGENESIS; BREAST CANCER; CANCER GENETICS; CANCER GROWTH; CANCER RESEARCH; CANCER SURVIVAL; CANCER THERAPY; CELL PROLIFERATION; COLORECTAL CANCER; DNA SEQUENCE; GENE EXPRESSION; GENE MUTATION; GENETIC VARIABILITY; GENETICS; GENOME; GENOMICS; GENOTYPE; HUMAN; METASTASIS; NATURAL SELECTION; NEOPLASM; NONHUMAN; PANCREAS CANCER; PATIENT CARE; PHENOTYPE; POINT MUTATION; PROTEIN DNA INTERACTION; REVIEW; RNA INTERFERENCE; SINGLE NUCLEOTIDE POLYMORPHISM; SOMATIC MUTATION; TUMOR GENE;

FEMALE; GENOME, HUMAN; GENOMICS; GENOTYPE; HUMANS; INDIVIDUALIZED MEDICINE; MALE; MODELS, BIOLOGICAL; MUTATION; NEOPLASMS; PHENOTYPE;

EID: 74749106342     PISSN: 14737159     EISSN: 17448352     Source Type: Journal    
DOI: 10.1586/erm.09.69     Document Type: Review

References (122)

1. Garcia, M Jemal A, Ward EM et al. Global Cancer Facts and Figures 2007. American Cancer Society, Atlanta GA, USA (2007).
2. Warren JL, Mariotto AB, Meekins A, Topor M, Brown ML. Current and future utilization of services from medical oncologists. J. Clin. Oncol. 26(19), 3242-3247 (2008).
3. American Cancer Society. Cancer Facts and Figures 2008. American Cancer Society, Atlanta, GA, USA (2008).
4. Roukos DH. Mea Culpa with cancertargeted therapy: new thinking and new agents design for novel, causal networksbased, personalized biomedicine. Expert Rev. Mol. Diagn. 9(3), 217-221 (2009).
5. Wood LD, Parsons DW, Jones S. The genomic landscapes of human breast and colorectal cancers. Science 318(5853), 1108-1113 (2007).
6. Jones S, Zhang X, Parsons DW. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 321(5897), 1801-1806 (2008).
7. Snyder M, Weissman S, Gerstein M. Personal phenotypes to go with personal genomes. Mol. Syst. Biol. 5, 273 (2009).
8. Deisboeck TS. Personalizing medicine: a systems biology perspective. Mol. Syst. Biol. 5, 249 (2009).
9. Roukos DH. Personalized cancer diagnostics and therapeutics. Expert Rev. Mol. Diagn. 9(3), 227-229 (2009).
10. Stratton MR, Campbell PJ, Futreal PA. The cancer genome. Nature 458(7239), 719-724 (2009).
11. Shendure J, Ji H. Next-generation DNA sequencing. Nat. Biotechnol. 26(10), 1135-1145 (2008).
12. Garber AM, Tunis SR. Does comparativeeffectiveness research threaten personalized medicine? N. Engl. J. Med. 360(19), 1925-1927 (2009).
13. Nowell PC. The clonal evolution of tumor cell populations. Science 194(4260), 23-28 (1976).
14. Touw IP, Erkeland SJ. Retroviral insertion mutagenesis in mice as a comparative oncogenomics tool to identify disease genes in human leukemia. Mol. Ther. 15(1), 13-19 (2007).
15. Gschwind A, Fischer OM, Ullrich A. The discovery of receptor tyrosine kinases: targets for cancer therapy. Nat. Rev. Cancer 4(5), 361-370 (2004). (Pubitemid 38579482)
16. Burstein HJ. The distinctive nature of HER2-positive breast cancers. N. Engl. J. Med. 353(16), 1652-1654 (2005).
17. Van Cutsem E, Kang Y, Chung H et al. Efficacy results from the ToGA trial: a Phase III study of trastuzumab added to standard chemotherapy (CT) in first-line human epidermal growth factor receptor 2 (HER2)-positive advanced gastric cancer (GC). J. Clin. Oncol. 27(Suppl.), S18, (Abstract LBA4509) (2009).
18. Linardou H, Dahabreh IJ, Kanaloupiti D et al. Assessment of somatic k-RAS mutations as a mechanism associated with resistance to EGFR-targeted agents: a systematic review and meta-analysis of studies in advanced non-small-cell lung cancer and metastatic colorectal cancer. Lancet Oncol. 9(10), 962-972 (2008).
19. Ley TJ, Mardis ER, Ding L. DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome. Nature 456(7218), 66-72 (2008).
20. Mardis ER, Ding L, Dooling DJ. Recurring mutations found by sequencing an acute myeloid leukemia genome. N. Engl. J. Med. 361(11), 1058-1066 (2009).
21. Donnelly P. Progress and challenges in genome-wide association studies in humans. Nature 456(7223), 728-731 (2008).
22. Hunter DJ, Khoury MJ, Drazen JM. Letting the genome out of the bottle - will we get our wish? N. Engl. J. Med. 358(2), 105-107 (2008).
23. Roukos DH. Personal genomics and genome-wide association studies: novel discoveries but limitations for practical personalized medicine. Ann. Surg. Oncol. 16, 772-773 (2009).
24. Lin J, Cook NR, Albert C et al. Vitamins C, E and b-carotene supplementation, and cancer risk: a randomized controlled trial. J. Natl Cancer Inst. 101(1), 14-23 (2009).
25. Qiao YL, Dawsey SM, Kamangar F et al. Total and cancer mortality after supplementation with vitamins and minerals: follow-up of the Linxian General Population Nutrition Intervention Trial. J. Natl Cancer Inst. 101(7), 507-518 (2009).
26. Taylor PR. Prevention of gastric cancer: a miss. J. Natl Cancer Inst. 99(2), 101-103 (2007).
27. Roukos DH, Murray S, Briasoulis E. Molecular genetic tools shape a roadmap towards a more accurate prognostic prediction and personalized management of cancer. Cancer Biol. Ther. 6, 308-312 (2007).
28. International HapMap Consortium, Frazer KA, Ballinger DG, Cox DR et al. A second-generation human haplotype map of over 3.1 million SNPs. Nature 449(7164), 851-861 (2007).
29. Easton DF, Eeles RA. Genome-wide association studies in cancer. Hum. Mol. Genet. 15, 17(R2), R109-R115 (2008).
30. Stacey SN, Manolescu A, Sulem P et al. Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat. Genet. 39, 865-869 (2007).
31. Easton DF, Pooley KA, Dunning AM et al. Genome-wide association study identifies breast cancer susceptibility loci. Nature 447(7148), 1087-1093 (2007).
32. Stacey SN, Manolescu A, Sulem P et al. Common variants on chromosome 5p12 confer susceptibility to estrogen receptorpositive breast cancer. Nat. Genet. 40(6), 703-706 (2008).
33. Gold B, Kirchhoff T, Stefanov S et al. Genome-wide association study provides evidence for a breast cancer risk locus at 6q22.33. Proc. Natl Acad. Sci. USA 105(11), 4340-4345 (2008).
34. Hunter DJ, Kraft P, Jacobs KB et al. A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat. Genet. 39(7), 870-874 (2007).
35. Gudmundsson J, Sulem P, Rafnar T et al. Common sequence variants on 2p15 and Xp11.22 confer susceptibility to prostate cancer. Nat. Genet. 40(3), 281-283 (2008). (Pubitemid 351311771)
36. Eeles RA, Kote-Jarai J, Giles GG et al. Identification of multiple novel prostate cancer susceptibility loci by a genome-wide association study. Nat. Genet. 40(3), 316-321 (2008).
37. Thomas G, Jacobs KB, Yeager M et al. Multiple loci identified in a genome-wide association study of prostate cancer. Nat. Genet. 40(3), 310-315 (2008).
38. Amundadottir LT, Sulem P, Gudmundsson J et al. A common variant associated with prostate cancer in European and African populations. Nat. Genet. 38(6), 652-658 (2006).
39. Yeager M, Orr N, Hayes RB et al. Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nat. Genet. 39(5), 645-649 (2007).
40. Gudmundsson J, Sulem P, Manolescu A et al. Genome-wide association study identifies a second prostate cancer susceptibility variant at 8q24. Nat. Genet. 39(5), 631-637 (2007).
41. Gudmundsson J, Sulem P, Steinthorsdottir V et al. Two variants on chromosome 17 confer prostate cancer risk, and the one in TCF2 protects against Type 2 diabetes. Nat. Genet. 39(8), 977-983 (2007).
42. Sun J, Zheng SL, Wiklund F et al. Evidence for two independent prostate cancer risk-associated loci in the HNF1B gene at 17q12. Nat. Genet. 40(10), 1153-1155 (2008).
43. Zanke BW, Greenwood CM, Rangrej J et al. Genome-wide association scan identifies a colorectal cancer susceptibility locus on chromosome 8q24. Nat. Genet. 39(8), 989-994 (2007).
44. Broderick P, Carvajal-Carmona L, Pittman AM et al. A genome-wide association study shows that common alleles of SMAD7 influence colorectal cancer risk. Nat. Genet. 39(11), 1315-1317 (2007).
45. Jaeger E, Webb E, Howarth K et al. Common genetic variants at the CRAC1 (HMPS) locus on chromosome 15q13.3 influence colorectal cancer risk. Nat. Genet. 40(1), 26-28 (2008).
46. Tomlinson IP, Webb E, Carvajal-Carmona L et al. A genome-wide association study identifies colorectal cancer susceptibility loci on chromosomes 10p14 and 8q23.3. Nat. Genet. 40(5), 623-630 (2008). (Pubitemid 351601204)
47. Tenesa A, Farrington SM, Prendergast JG et al. Genome-wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nat. Genet. 40(5), 631-637 (2008).
48. Amos CI, Wu X, Broderick P et al. Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1. Nat. Genet. 40(5), 616-622 (2008).
49. Hung RJ, McKay JD, Gaborieau V et al. A susceptibility locus for lung cancer maps to nicotinic acetylcholine receptor subunit genes on 15q25. Nature 452(7187), 633-637 (2008).
50. Study Group of Millennium Genome Project for Cancer; Sakamoto H, Yoshimura K, Saeki N et al. Genetic variation in PSCA is associated with susceptibility to diffuse-type gastric cancer. Nat. Genet. 40(6), 730-740 (2008).
51. Pharoah PDP, Antoniou AC, Easton DF, Ponder BAJ. Polygenes, risk prediction and targeted prevention of breast cancer. N. Engl. J. Med. 358(26), 2796-2803 (2008).
52. Haiman CA, Patterson N, Freedman ML et al. Multiple regions within 8q24 independently affect risk for prostate cancer. Nat. Genet. 39(5), 638-644 (2007).
53. Antoniou AC, Spurdle AB, Sinilnikova OM et al. Common breast cancer predisposition alleles modify breast cancer risk in BRCA1 and BRCA2 mutation carriers. Am. J. Hum. Genet. 82(4), 937-948 (2008).
54. Stern DL, Orgogozo V. The loci of evolution: how predictable is genetic evolution? Evolution 62(9), 2155-2177 (2008).
55. Roukos DH. Assessing both genetic variation (SNPs/CNVs) and geneenvironment interactions may lead to personalized gastric cancer prevention. Expert Rev. Mol. Diagn. 9(1), 1-6 (2009).
56. Roukos DH. Radiation therapy for breast cancer. N. Engl. J. Med. 360(13), 1362-1363 (2009).
57. Ziogas D, Baltogiannis G, Fatouros M, Roukos DH. Identifying and preventing high-risk gastric cancer individuals with CDH1 mutations. Ann. Surg. 247(4), 714-715 (2008).
58. Roukos DH. Linking contralateral breast cancer with genetics. Radiother. Oncol. 86, 139-141 (2008).
59. Roukos DH. Genetics and genome-wide association studies: surgery-guided algorithm and promise for future breast cancer personalized surgery. Expert Rev. Mol. Diagn. 8(5), 587-597 (2008).
60. Lee C, Morton CC. Structural genomic variation and personalized medicine. N. Engl. J. Med. 358(7), 740-741 (2008).
61. Lupski JR. Structural variation in the human genome. N. Engl. J. Med. 356(11), 1169-1171 (2007).
62. Roukos DH, Ziogas D. Human genetic and structural genomic variation: would genome-wide association studies be the solution for cancer complexity like alexander the great for the "gordian knot"? Ann. Surg. Oncol. 16(3), 774-775; author reply 776-777 (2009).
63. Korbel JO, Urban AE, Affourtit JP et al. Paired-end mapping reveals extensive structural variation in the human genome. Science 318(5849), 420-426 (2007).
64. Hayden EC. Genome sequencing: the third generation. Nature 457(7231), 768-769 (2009).
65. Rockman MV. Reverse engineering the genotype-phenotype map with natural genetic variation. Nature 456(7223), 738-744 (2008).
66. Gunter C. Quantitative genetics. Nature 456(7223), 719 (2008).
67. Borgatti SP, Mehra A, Brass DJ, Labianca G. Network analysis in the social sciences. Science 323(5916), 892-895 (2009).
68. Barabasi AL, Albert R. Emergence of scaling in random networks. Science 286(5439), 509-512 (1999).
69. Durrett R. Random Graph Dynamics. Cambridge University Press, Cambridge, UK (2007).
70. Bohman T. Mathematics. Emergence of connectivity in networks. Science 323(5920), 1438-1439 (2009).
71. Friedman A, Perrimon N. Genetic screening for signal transduction in the era of network biology. Cell 128(2), 225-231 (2007).
72. Joyce JA, Pollard JW. Microenvironmental regulation of metastasis. Nat. Rev. Cancer 9(4), 239-252 (2008)
73. Antoniou AC, Sinilnikova OM, Simard J et al. RAD51 135G-->C modifies breast cancer risk among BRCA2 mutation carriers: results from a combined analysis of 19 studies. Am. J. Hum. Genet. 81(6), 1186-1200 (2007).
74. Finak G, Bertos N, Pepin F et al. Stromal gene expression predicts clinical outcome in breast cancer. Nat. Med. 14(5), 518-527 (2008). (Pubitemid 351655218)
75. McAllister SS, Gifford AM, Greiner AL et al. Systemic endocrine instigation of indolent tumor growth requires osteopontin. Cell 133(6), 994-1005 (2008).
76. Friedman N, Linial M, Nachman I, Pe'er D. Using Bayesian networks to analyze expression data. J. Comput. Biol. 7(3-4), 601-620 (2000). (Pubitemid 30944025)
77. Liu B, de la Fuente A, Hoeschele I. Gene network inference via structural equation modeling in genetical genomics experiments. Genetics 178(3), 1763-1776 (2008).
78. Zhu M, Yu M, Zhao S. Understanding quantitative genetics in the systems biology era. Int. J. Biol. Sci. 5(2), 161-170 (2009).
79. Gerke J, Lorenz K, Cohen B. Genetic interactions between transcription factors cause natural variation in yeast. Science 323(5913), 498-501 (2009).
80. Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC. Potent and specific genetic interference by doublestranded RNA in Caenorhabditis elegans. Nature 391(6669), 806-811 (1998). (Pubitemid 28099681)
81. Siomi H, Siomi MC. On the road to reading the RNA-interference code. Nature 457(7228), 396-404 (2009).
82. Markowetz F, Bloch J, Spang R. Nontranscriptional pathway features reconstructed from secondary effects of RNA interference. Bioinformatics 21(21), 4026-4032 (2005)
83. Froehlich H, Fellmann M, Sueltmann H, Poustka A, Beissbarth T. Large scale statistical inference of signaling pathways from RNAi and microarray data. BMC Bioinformatics 8, 386 (2007).
84. Wang K, Alvarez MJ, Bisikirska BC et al. Dissecting the interface between signaling and transcriptional regulation in human B cells. Pac. Symp. Biocomput. 264-275 (2009).
85. Imoto S, Tamada Y, Araki H et al. Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles. Pac. Symp. Biocomput. 559-571 (2006).
86. Nariai N, Kim S, Imoto S, Miyano S. Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks. Pac. Symp. Biocomput. 336-347 (2004).
87. Segal E, Shapira M, Regev A et al. Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet. 34(2), 166-176 (2003).
88. Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A. Reverse engineering of regulatory networks in human B cells. Nat. Genet. 37(4), 382-390 (2005).
89. Niida A, Smith AD, Imoto S et al. Gene set-based module discovery in the breast cancer transcriptome. BMC Bioinformatics 10, 71 (2009).
90. Niida A, Smith AD, Imoto S et al. Integrative bioinformatics analysis of transcriptional regulatory programs in breast cancer cells. BMC Bioinformatics 9, 404 (2008).
91. Basso K. Toward a systems biology approach to investigate cellular networks in normal and malignant B cells. Leukemia 23(7), 1219-1225 (2009).
92. Dalla-Favera R, Pasqualucci L, Bhagat G. Genetic and phenotypic analysis of B-cell post-transplant lymphoproliferative disorders provides insights into disease biology. Hematol Oncol. 26(4), 199-211 (2008).
93. Shakya R, Szabolcs M, McCarthy E et al. The basal-like mammary carcinomas induced by Brca1 or Bard1 inactivation implicate the BRCA1/BARD1 heterodimer in tumor suppression. Proc. Natl Acad. Sci. USA 105(19), 7040-7045 (2008).
94. Hahn WC, Weinberg RA. Modelling the molecular circuitry of cancer. Nat. Rev. Cancer 2(5), 331-341 (2002).
95. Van de Vijver MJ, He YD, Van't Veer LJ et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347(25), 1999-2009 (2002).
96. Paik S, Shak S, Tang G et al. A multigene assay to predict recurrence of tamoxifentreated, node-negative breast cancer. N. Engl J Med. 351(27), 2817-2826 (2004).
97. Bustin SA. Molecular medicine, geneexpression profiling and molecular diagnostics: putting the cart before the horse. Biomark. Med. 2(3), 201-207 (2008).
98. Roukos DH. Twenty-one-gene assay: challenges and promises in translating personal genomics and whole-genome scans into personalized treatment of breast cancer. J. Clin. Oncol. 27(8), 1337-1338 (2009).
99. Huang CC, Bredel M. Use of gene signatures to improve risk estimation in cancer. JAMA 299(13), 1605-1606 (2008).
100. Zhu J, Zhang B, Smith EN et al. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nat. Genet. 40(7), 854-861 (2008).
101. Chuang HY, Lee E, Liu YT, Lee D, Ideker T. Network-based classification of breast cancer metastasis. Mol. Syst. Biol. 3, 140 (2007).
102. Taylor IW, Linding R, Warde-Farley D. Dynamic modularity in protein interaction networks predicts breast cancer outcome. Nat. Biotechnol. 27(2), 199-204 (2009).
103. Sakakibara D. Protein structure determination in living cells by in-cell NMR spectroscopy. Nature 458(7234), 102-105 (2009).
104. Inomata K, Ohno A, Tochio H et al. High-resolution multi-dimensional NMR spectroscopy of proteins in human cells. Nature 458(7234), 106-109 (2009).
105. Burz DS, Shekhtman A. Structural biology: inside the living cell. Nature 458(7234), 37-38 (2009).
106. Roukos DH. Genome-wide association studies: how predictable is a person's cancer risk? Expert Rev. Anticancer Ther. 9(4), 389-392 (2009).
107. Roukos DH. Breast-cancer stromal cells with TP53 mutations. N. Engl. J. Med. 358(15), 1636; author reply 1636 (2008).
108. Pàez-Ribes M, Allen E, Hudock J et al. Antiangiogenic therapy elicits malignant progression of tumors to increased local invasion and distant metastasis. Cancer Cell 15(3), 220-231 (2009).
109. Ebos JM, Lee CR, Cruz-Munoz W, Bjarnason GA, Christensen JG, Kerbel RS. Accelerated metastasis after short-term treatment with a potent inhibitor of tumor angiogenesis. Cancer Cell 15(3), 232-239 (2009).
110. Ellis LM, Reardon DA. Cancer: the nuances of therapy. Nature 458(7236), 290-292 (2009).
111. Roukos DH. Tzakos A, Zografos G. Current concerns and challenge s towards tailored anti-angiogenic therapy in cancer. Expert Rev. Anticancer Ther. 9(10), 1413-1416 (2009).
112. Smith EN, Kruglyak L. Gene-environment interaction in yeast gene expression. PLoS Biol. 6(4), E83 (2008).
113. Zhang J, Yang PL, Gray NS. Targeting cancer with small molecule kinase inhibitors. Nat. Rev. Cancer 9(1), 28-39 (2009).
114. Lewis J. From signals to patterns: space, time, and mathematics in developmental biology. Science 322(5900), 399-403 (2008).
115. Bennett CN, Green JE. Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models. Breast Cancer Res. 10(5), 213 (2008).
116. Yuan TL, Cantley LC. PI3K pathway alterations in cancer: variations on a theme. Oncogene 27(41), 5497-5510 (2008).
117. Deisboeck TS, Zhang L, Yoon J, Costa J. In silico cancer modeling: is it ready for prime time? Nat. Clin. Pract. Oncol. 6(1), 34-42 (2008).
118. Roukos DH. Isolated tumor cells in breast cancer. N. Engl. J. Med. 361, 1994-1995 (2009).
119. Roukos DH. Breast cancer outcomes: the crucial role of the breast surgeon in the era of personal genetics and systems biology. Ann. Surg. 249(6), 1067-1068 (2009).
120. Ziogas D, Roukos DH. Genetics and personal genomics for personalized breast cancer surgery: progress and challenges in research and clinical practice. Ann. Surg. Oncol. 16(7), 1771-1782 (2009).
121. Roukos DH. Targeting gastric cancer with trastuzumab: new clinical practice and innovative developments to overcome resistance. Ann. Surg. Oncol. (2009) DOI: 10.1245/s10434-009-0766-0 (Epub ahead of print).
122. Ziogas D, Roukos DH. CDH1 testing: can it predict the prophylactic or therapeutic nature of total gastrectomy in hereditary diffuse gastric cancer? Ann. Surg. Oncol. 16(10), 2678-2681 (2009).