期刊论文详细信息
Radiation Oncology
Integrative radiation systems biology
Kristian Unger1 
[1] Research Unit Radiation Cytogenetics, Helmholtz–Zentrum München, German Research Center for Environmental Health, Ingolstädter-Landstr. 1, 85764 Neuherberg, Germany
关键词: Personalised therapy;    Radiation biology;    Multi-level integration;    Systems biology;   
Others  :  815037
DOI  :  10.1186/1748-717X-9-21
 received in 2013-11-22, accepted in 2013-12-31,  发布年份 2014
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【 摘 要 】

Maximisation of the ratio of normal tissue preservation and tumour cell reduction is the main concept of radiotherapy alone or combined with chemo-, immuno- or biologically targeted therapy. The foremost parameter influencing this ratio is radiation sensitivity and its modulation towards a more efficient killing of tumour cells and a better preservation of normal tissue at the same time is the overall aim of modern therapy schemas. Nevertheless, this requires a deep understanding of the molecular mechanisms of radiation sensitivity in order to identify its key players as potential therapeutic targets. Moreover, the success of conventional approaches that tried to statistically associate altered radiation sensitivity with any molecular phenotype such as gene expression proofed to be somewhat limited since the number of clinically used targets is rather sparse. However, currently a paradigm shift is taking place from pure frequentistic association analysis to the rather holistic systems biology approach that seeks to mathematically model the system to be investigated and to allow the prediction of an altered phenotype as the function of one single or a signature of biomarkers. Integrative systems biology also considers the data from different molecular levels such as the genome, transcriptome or proteome in order to partially or fully comprehend the causal chain of molecular mechanisms. An example for the application of this concept currently carried out at the Clinical Cooperation Group “Personalized Radiotherapy in Head and Neck Cancer” of the Helmholtz-Zentrum München and the LMU Munich is described. This review article strives for providing a compact overview on the state of the art of systems biology, its actual challenges, potential applications, chances and limitations in radiation oncology research working towards improved personalised therapy concepts using this relatively new methodology.

【 授权许可】

   
2014 Unger; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D: Global cancer statistics. CA Cancer J Clin 2011, 61(2):69-90. [PMID: 21296855]
  • [2]Orth M, Lauber K, Niyazi M, Friedl AA, Li M, Maihöfer C, Schüttrumpf L, Ernst A, Niemöller OM, Belka C: Current concepts in clinical radiation oncology. Radiat Environ Biophys 2013. [PMID: 24141602]
  • [3]Begg AC: Predicting recurrence after radiotherapy in head and neck cancer. Semin Radiat Onco 2012, 22(2):108-118. [PMID: 22385918]
  • [4]Oksuz DC, Prestwich RJ, Carey B, Wilson S, Senocak MS, Choudhury A, Dyker K, Coyle C, Sen M: Recurrence patterns of locally advanced head and neck squamous cell carcinoma after 3D conformal (chemo)-radiotherapy. Radiat Oncol 2011, 6:54. [http://www.ncbi.nlm.nih.gov/pubmed/21609453 webcite] BioMed Central Full Text
  • [5]Barnett GC, Coles CE, Elliott RM, Baynes C, Luccarini C, Conroy D, Wilkinson JS, Tyrer J, Misra V, Platte R, Gulliford SL, Sydes MR, Hall E, Bentzen SM, Dearnaley DP, Burnet NG, Pharoah PD, Dunning AM, West CM: Independent validation of genes and polymorphisms reported to be associated with radiation toxicity: a prospective analysis study. Lancet Oncol 2012, 13:65-77. [http://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(11)70302-3/fulltext webcite]
  • [6]Kaliberov SA, Buchsbaum DJ: Chapter seven–cancer treatment with gene therapy and radiation therapy. Adv Cancer Res 2012, 115:221-263. [PMID: 23021246]
  • [7]Hornberg JJ, Bruggeman FJ, Westerhoff HV, Lankelma J: Cancer: a systems biology disease. Biosystems 2006, 83(2–3):81-90. [PMID: 16426740]
  • [8]Bruggeman FJ, Westerhoff HV: The nature of systems biology. Trends Microbiol 2007, 15:45-50. [http://www.cell.com/trends/microbiology/abstract/S0966-842X(06)00264-2 webcite]
  • [9]Lazebnik Y: Can a biologist fix a radio?—Or, what I learned while studying apoptosis. Cancer Cell 2002, 2(3):179-182. [http://www.cell.com/cancer-cell/fulltext/S1535-6108(02)00133-2 webcite]
  • [10]Bechtel W: Network organization in health and disease: on being a reductionist and a systems biologist too. Pharmacopsychiatry 2013, 46(S 01):S10-S21. [https://www.thieme-connect.com/ejournals/html/10.1055/s-0033-1337922 webcite]
  • [11]Davies JJ, Wilson IM, Lam WL: Array CGH technologies and their applications to cancer genomes. Chromosome Res 2005, 13(3):237-248. [PMID: 15868418]
  • [12]LaFramboise T: Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances. Nucleic Acids Res 2009, 37(13):4181-4193. [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2715261/ webcite]. [PMID: 19570852 PMCID: PMC2715261]
  • [13]Schulze A, Downward J: Navigating gene expression using microarrays–a technology review. Nat Cell Biol 2001, 3(8):E190-195. [PMID: 11483980]
  • [14]Yin JQ, Zhao RC, Morris KV: Profiling microRNA expression with microarrays. Trends Biotechnol 2008, 26(2):70-76. [http://www.cell.com/trends/biotechnology/abstract/S0167-7799(07)00324-1 webcite]
  • [15]Aparicio O, Geisberg JV, Struhl K: Chromatin immunoprecipitation for determining the association of proteins with specific genomic sequences in vivo. Curr Protoc Cell Biol 2004, Chapter 17:Unit 17.7. [PMID: 18228445]
  • [16]Buck MJ, Lieb JD: ChIP-chip: considerations for the design, analysis, and application of genome-wide chromatin immunoprecipitation experiments. Genomics 2004, 83(3):349-360. [PMID: 14986705]
  • [17]Zhang J, Peng F, Li N, Liu Y, Xu Y, Zhou L, Wang J, Zhu J, Huang M, Gong Y: Salvage concurrent radio-chemotherapy for post-operative local recurrence of squamous-cell esophageal cancer. Radiat Oncol 2012, 7:93. [http://www.ncbi.nlm.nih.gov/pubmed/22713587 webcite] BioMed Central Full Text
  • [18]Geenen S, Cojocariu C, Gethings L, Isaac G, Fernandes L, Tonge R, Vissers J, Langrige J, Wilson I, Martin L: Qualitative and Quantitative Characterization of the Metabolome, Lipidome and Proteome of Human Hepatocytes Stably Transfected with Cytochrome P450 2E1 Using Data Independent LC-MS. J Biomol Tech 2013, 24(Suppl):S61—S62. [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3635362/ webcite]. [PMID: null PMCID: PMC3635362].
  • [19]Wieringen WNv, Unger K, Leday GG, Krijgsman O, Menezes RXd, Ylstra B, Wiel MAvd: Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses. BMC Bioinformatics 2012, 13:80. [http://www.biomedcentral.com/1471-2105/13/80/abstract webcite]. [PMID: 22559006] BioMed Central Full Text
  • [20]Leday GGR, van der Vaart AW, van Wieringen WN, van de Wiel MA: Modeling association between DNA copy number and gene expression with constrained piecewise linear regression splines. Ann Appl Stat 2013, 7(2):823-845. [http://projecteuclid.org/euclid.aoas/1372338469 webcite]
  • [21]Hoffman BG, Jones SJM: Genome-wide identification of DNA-protein interactions using chromatin immunoprecipitation coupled with flow cell sequencing. J Endocrinol 2009, 201:1-13. [PMID: 19136617]
  • [22]Kielbasa SM, Klein H, Roider HG, Vingron M, Blüthgen N: TransFind—predicting transcriptional regulators for gene sets. Nucleic Acids Res 2010, 38(suppl 2):W275—W280. [http://nar.oxfordjournals.org/content/38/suppl_2/W275 webcite]. [PMID: 20511592]
  • [23]Krumsiek J, Suhre K, Illig T, Adamski J, Theis FJ: Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data. BMC Syst Biol 2011, 5:21. [http://www.biomedcentral.com/1752-0509/5/21/abstract webcite]. [PMID: 21281499] BioMed Central Full Text
  • [24]Gagneur J, Stegle O, Zhu C, Jakob P, Tekkedil MM, Aiyar RS, Schuon A, Pe’er D, Steinmetz LM: Genotype-environment interactions reveal causal pathways that mediate genetic effects on phenotype. PLoS Genet 2013, 9(9):e1003803. [http://dx.doi.org/10.1371/journal.pgen.1003803 webcite]
  • [25]Lasserre J, Chung H, Vingron M: Finding associations among histone modifications using sparse partial correlation networks. PLoS Comput Biol 2013, 9(9):e1003168. [http://dx.doi.org/10.1371/journal.pcbi.1003168 webcite]
  • [26]Krumsiek J, Suhre K, Evans AM, Mitchell MW, Mohney RP, Milburn MV, Wägele B, Römisch-Margl W, Illig T, Adamski J, Gieger C, Theis FJ, Kastenmüller G: Mining the unknown: a systems approach to metabolite identification combining genetic and metabolic information. PLoS Genet 2012, 8(10):e1003005. [http://dx.doi.org/10.1371/journal.pgen.1003005 webcite]
  • [27]Khatri P, Sirota M, Butte AJ: Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput Biol 2012, 8(2):e1002375. [http://dx.doi.org/10.1371/journal.pcbi.1002375 webcite]
  • [28]Kanehisa M, Goto S, Sato Y, Furumichi M, Tanabe M: KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res 2012, 40(Database issue):D109-114. [PMID: 22080510]
  • [29]Matthews L, Gopinath G, Gillespie M, Caudy M, Croft D, de Bono B, Garapati P, Hemish J, Hermjakob H, Jassal B, Kanapin A, Lewis S, Mahajan S, May B, Schmidt E, Vastrik I, Wu G, Birney E, Stein L, D’Eustachio P: Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res 2009, 37(Database issue):D619-622. [PMID: 18981052]
  • [30]Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, Doerks T, Julien P, Roth A, Simonovic M, Bork P, von Mering C: STRING 8–a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 2009, 37(Database issue):D412-416. [PMID: 18940858]
  • [31]Fields S, Sternglanz R: The two-hybrid system: an assay for protein-protein interactions. Trends Genet: TIG 1994, 10(8):286-292. [PMID: 7940758]
  • [32]Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, Christmas R, Avila-Campilo I, Creech M, Gross B, Hanspers K, Isserlin R, Kelley R, Killcoyne S, Lotia S, Maere S, Morris J, Ono K, Pavlovic V, Pico AR, Vailaya A, Wang P, Adler A, Conklin BR, Hood L, Kuiper M, Sander C, Schmulevich I, Schwikowski B, Warner GJ, Ideker T, Bader GD: Integration of biological networks and gene expression data using Cytoscape. Nat Protoc 2007, 2(10):2366-2382. [http://www.nature.com/nprot/journal/v2/n10/full/nprot.2007.324.html webcite]
  • [33]Henriquez Hernandez LA, Lara PC, Pinar B, Bordon E, Gallego CR, Bilbao C, Perez LF, Morales AF: Constitutive gene expression profile segregates toxicity in locally advanced breast cancer patients treated with high-dose hyperfractionated radical radiotherapy. Radiat Oncol (London, England) 2009, 4:17. [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2698866/ webcite]. [PMID: 19497124 PMCID: PMC2698866] BioMed Central Full Text
  • [34]Crick F: Central dogma of molecular biology. Nature 1970, 227(5258):561-563. [PMID: 4913914]
  • [35]Robertson KD: DNA methylation and human disease. Nat Rev Genet 2005, 6(8):597-610. [http://www.nature.com/nrg/journal/v6/n8/full/nrg1655.html webcite]
  • [36]Kim HJ, Kim JH, Chie EK, Young PD, Kim IA, Kim IH: DNMT (DNA methyltransferase) inhibitors radiosensitize human cancer cells by suppressing DNA repair activity. Radiat Oncol (London, England) 2012, 7:39. [PMID: 22429326] BioMed Central Full Text
  • [37]He L, Hannon GJ: MicroRNAs: small RNAs with a big role in gene regulation. Nat Rev Genet 2004, 5(7):522-531. [http://www.nature.com/nrg/journal/v5/n7/full/nrg1379.html webcite]
  • [38]Niyazi M, Zehentmayr F, Niemoller OM, Eigenbrod S, Kretzschmar H, Schulze-Osthoff K, Tonn JC, Atkinson M, Mortl S, Belka C: MiRNA expression patterns predict survival in glioblastoma. Radiat Oncol 2011, 6:153. [http://www.ncbi.nlm.nih.gov/pubmed/22074483 webcite] BioMed Central Full Text
  • [39]Spitz F, Furlong EEM: Transcription factors: from enhancer binding to developmental control. Nat Rev Genet 2012, 13(9):613-626. [http://www.nature.com/nrg/journal/v13/n9/abs/nrg3207.html webcite]
  • [40]Lindel K, Rieken S, Daffinger S, Weber KJ, de Villiers E, Debus J: The transcriptional regulator gene E2 of the Human Papillomavirus (HPV) 16 influences the radiosensitivity of cervical keratinocytes. Radiat Oncol (London, England) 2012, 7:187. [PMID: 23134732] BioMed Central Full Text
  • [41]Thomaz CE, Gillies D, Feitosa R: A new covariance estimate for Bayesian classifiers in biometric recognition. IEEE Trans Circuits Syst Video Technol 2004, 14(2):214-223.
  • [42]Marbach D, Costello JC, Küffner R, Vega NM, Prill RJ, Camacho DM, Allison KR, Consortium TD, Kellis M, Collins JJ, Stolovitzky G: Wisdom of crowds for robust gene network inference. Nat Methods 2012, 9(8):796-804. [http://www.nature.com/nmeth/journal/v9/n8/full/nmeth.2016.html webcite]
  • [43]Karlebach G, Shamir R: Modelling and analysis of gene regulatory networks. Nat Rev Mol Cell Biol 2008, 9(10):770-780. [http://www.nature.com/nrm/journal/v9/n10/full/nrm2503.html webcite]
  • [44]Mitrea C, Taghavi Z, Bokanizad B, Hanoudi S, Tagett R, Donato M, Voichita C, Draghici S: Methods and approaches in the topology-based analysis of biological pathways. Front Physiol 2013., 4[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3794382/ webcite]. [PMID: 24133454 PMCID: PMC3794382]
  • [45]Telesford QK, Simpson SL, Burdette JH, Hayasaka S, Laurienti PJ: The brain as a complex system: using network science as a tool for understanding the brain. Brain Connectivity 2011, 1(4):295-308. [PMID: 22432419]
  • [46]Klipp E, Liebermeister W: Mathematical modeling of intracellular signaling pathways. BMC Neuroscience 2006, 7(Suppl 1):S10. [http://www.biomedcentral.com/1471-2202/7/S1/S10 webcite]. [PMID: 17118154] BioMed Central Full Text
  • [47]de Jong H: Modeling and simulation of genetic regulatory systems: a literature review. J Comput Biol 2002, 9:67-103. [PMID: 11911796]
  • [48]Hill AV: The combinations of haemoglobin with oxygen and with carbon monoxide. I. Biochem J 1913, 7(5):471-480. [PMID: 16742267]
  • [49]Klinger B, Sieber A, Fritsche-Guenther R, Witzel F, Berry L, Schumacher D, Yan Y, Durek P, Merchant M, Schäfer R, Sers C, Blüthgen N: Network quantification of EGFR signaling unveils potential for targeted combination therapy. Mol Syst Biol 2013,. 9. [http://msb.embopress.org/content/9/1/673 webcite]
  • [50]Prahallad A, Sun C, Huang S, Di Nicolantonio F, Salazar R, Zecchin D, Beijersbergen RL, Bardelli A, Bernards R: Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR. Nature 2012, 483(7387):100-103. [PMID: 22281684]
  • [51]Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V, Djoumbou Y, Eisner R, Guo AC, Wishart DS: DrugBank 3.0: a comprehensive resource for ’omics’ research on drugs. Nucleic Acids Res 2011, 39(Database issue):D1035-1041. [PMID: 21059682]
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