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When Mathematics Outsmarts Cancer

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Bioinformatics and Biomedical Engineering (IWBBIO 2019)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 11465))

Abstract

Mathematics has become essential in cancer biology. Recent developments in high-throughput molecular profiling techniques enable assessing molecular states of tumors in great detail. Cancer genome data are collected at a large scale in numerous clinical studies and in international consortia, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. Developing mathematical models that are consistent with and predictive of the true underlying biological mechanisms is a central goal of cancer biology. In this work, we used percolations and power-law models to study protein-protein interactions in cancer fusions. We used site-directed knockouts to understand the modular components of fusion protein-protein interaction networks, thereby providing models for target-based drug predictions.

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References

  1. Nowell, P.C.: The clonal evolution of tumor cell populations. Science 194, 23–28 (1976)

    Article  Google Scholar 

  2. Armitage, P., et al.: The age distribution of cancer and multistage theory of carcino-genesis. Br. J. Cancer 1, 1–2 (1954)

    Article  Google Scholar 

  3. Jones, S., et al.: Comparative lesion sequencing provides insights into tumor evolution. Proc. Natl. Acad. Sci. U.S.A. 105, 4283–4288 (2008)

    Article  Google Scholar 

  4. Werner, B., et al.: A deterministic model for the occurrence and dynamics of multiple mutations in hierarchically organized tissues. J. R. Soc. Interface 10, 20130349 (2013)

    Article  Google Scholar 

  5. Haeno, H., et al.: A progenitor cell origin of myeloid malignancies. Proc. Natl. Acad. Sci. USA 106, 16616–16621 (2009)

    Article  Google Scholar 

  6. Desper, R., et al.: Inferring tree models for oncogenesis from comparative genome hybridization data. J. Comput. Biol. 6, 37–51 (1999)

    Article  Google Scholar 

  7. Desper, R., et al.: Distance-based reconstruction of tree models for oncogenesis. J. Comput. Biol. 7, 789–803 (2000)

    Article  Google Scholar 

  8. Hoglund, M., et al.: Statistical behavior of complex cancer karyotypes. Genes Chromosomes Cancer 42, 327–341 (2005)

    Article  Google Scholar 

  9. Huang, Z., et al.: Construction of tree models for pathogenesis of nasopharyngeal carcinoma. Genes Chromosomes Cancer 40, 307–315 (2004)

    Article  Google Scholar 

  10. Pathare, S., et al.: Construction of oncogenetic tree models reveals multiple pathways of oral cancer progression. Int. J. Cancer 124, 2864–2871 (2009)

    Article  Google Scholar 

  11. Hjelm, M., et al.: New probabilistic network models and algorithms for oncogenesis. J. Comput. Biol. 13, 853–865 (2006)

    Article  MathSciNet  Google Scholar 

  12. Mitelman, F., et al.: The impact of translocations and gene fusions on cancer causation. Nat. Rev. Cancer 7, 233–245 (2007)

    Article  Google Scholar 

  13. Gorohovski, A., et al.: ChiTaRS-3.1-the enhanced chimeric transcripts and RNA- seq database matched with protein-protein interactions. Nucleic Acids Res. 45(D1), D790–D795 (2017)

    Article  Google Scholar 

  14. Frenkel-Morgenstern, M., et al.: Chimeras taking shape: potential functions of proteins encoded by chimeric RNA transcripts. Genome Res. 22(7), 1231–1242 (2012)

    Article  Google Scholar 

  15. Bentz, M., et al.: Detection of chimeric BCR-ABL genes on bone marrow samples and blood smears in chronic myeloid and acute lymphoblastic leukemia by in situ hybridization. Blood 83, 1922–1928 (1994)

    Google Scholar 

  16. Bärlund, M., et al.: Cloning of BCAS3 (17q23) and BCAS4 (20q13) genes that undergo amplification, overexpression, and fusion in breast cancer. Genes Chromosomes Cancer 35(4), 311–317 (2002)

    Article  Google Scholar 

  17. Ishida, S., et al.: The genomic breakpoint and chimeric transcripts in the EWSR1- ETV4/E1AF gene fusion in Ewing sarcoma. Cytogenet Cell Genet. 82(3–4), 278–283 (1998)

    Article  Google Scholar 

  18. Barabási, A.L.: Scale-free networks: a decade and beyond. Science 325(5939), 412–413 (2009)

    Article  MathSciNet  Google Scholar 

  19. Frenkel-Morgenstern, M., et al.: ChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer. Nucleic Acids Res. 45(12), 7094–7105 (2017)

    Article  Google Scholar 

  20. Frenkel-Morgenstern, M., et al.: ChiTaRS: a database of human, mouse and fruit fly chimeric transcripts and RNA-sequencing data. Nucleic Acids Res. 41(Database issue), D142–D151 (2013)

    Google Scholar 

  21. Frenkel-Morgenstern, M., et al.: ChiTaRS 2.1–an improved database of the chimeric transcripts and RNA-seq data with novel sense-antisense chimeric RNA transcripts. Nucleic Acids Res. 43(Database issue), D68–D75 (2015)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Systems Biology, Columbia University Medical Center, Herbert Irving Cancer Research Center, 1130 Street Nicholas Avenue, New York, NY, 10032, USA

    Somnath Tagore

  2. The Azrieli Faculty of Medicine, Bar-Ilan University, 8 Henrietta Szold Street, 13195, Safed, Israel

    Milana Frenkel-Morgenstern

Authors
  1. Somnath Tagore
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  2. Milana Frenkel-Morgenstern
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Corresponding author

Correspondence to Milana Frenkel-Morgenstern .

Editor information

Editors and Affiliations

  1. Department of Computer Architecture and Computer Technology Higher Technical School of Information Technology and Telecommunications Engineering, CITIC-UGR, Granada, Spain

    Ignacio Rojas

  2. ETSIIT, University of Granada, Granada, Spain

    Olga Valenzuela

  3. CITIC-UGR, University of Granada, Granada, Spain

    Fernando Rojas

  4. Fundacion Progreso y Salud, Granada, Spain

    Francisco Ortuño

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Tagore, S., Frenkel-Morgenstern, M. (2019). When Mathematics Outsmarts Cancer. In: Rojas, I., Valenzuela, O., Rojas, F., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2019. Lecture Notes in Computer Science(), vol 11465. Springer, Cham. https://doi.org/10.1007/978-3-030-17938-0_42

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  • DOI: https://doi.org/10.1007/978-3-030-17938-0_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17937-3

  • Online ISBN: 978-3-030-17938-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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