Cancer systems biology: a network modeling perspective
Cancer is now appreciated as not only a highly heterogenous pathology with respect to cell type and tissue origin but also as a disease involving dysregulation of multiple pathways governing fundamental cell processes such as death, proliferation, differentiation and migration. Thus, the activities...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Oxford University Press
2010
|
| Online Access: | http://hdl.handle.net/1721.1/60314 |
| _version_ | 1826216154449838080 |
|---|---|
| author | Lauffenburger, Douglas A. Kreeger, Pamela K. |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Lauffenburger, Douglas A. Kreeger, Pamela K. |
| author_sort | Lauffenburger, Douglas A. |
| collection | MIT |
| description | Cancer is now appreciated as not only a highly heterogenous pathology with respect to cell type and tissue origin but also as a disease involving dysregulation of multiple pathways governing fundamental cell processes such as death, proliferation, differentiation and migration. Thus, the activities of molecular networks that execute metabolic or cytoskeletal processes, or regulate these by signal transduction, are altered in a complex manner by diverse genetic mutations in concert with the environmental context. A major challenge therefore is how to develop actionable understanding of this multivariate dysregulation, with respect both to how it arises from diverse genetic mutations and to how it may be ameliorated by prospective treatments. While high-throughput experimental platform technologies ranging from genomic sequencing to transcriptomic, proteomic and metabolomic profiling are now commonly used for molecular-level characterization of tumor cells and surrounding tissues, the resulting data sets defy straightforward intuitive interpretation with respect to potential therapeutic targets or the effects of perturbation. In this review article, we will discuss how significant advances can be obtained by applying computational modeling approaches to elucidate the pathways most critically involved in tumor formation and progression, impact of particular mutations on pathway operation, consequences of altered cell behavior in tissue environments and effects of molecular therapeutics. |
| first_indexed | 2024-09-23T16:43:08Z |
| format | Article |
| id | mit-1721.1/60314 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T16:43:08Z |
| publishDate | 2010 |
| publisher | Oxford University Press |
| record_format | dspace |
| spelling | mit-1721.1/603142022-10-03T07:46:47Z Cancer systems biology: a network modeling perspective Lauffenburger, Douglas A. Kreeger, Pamela K. Massachusetts Institute of Technology. Department of Biological Engineering Lauffenburger, Douglas A. Lauffenburger, Douglas A. Cancer is now appreciated as not only a highly heterogenous pathology with respect to cell type and tissue origin but also as a disease involving dysregulation of multiple pathways governing fundamental cell processes such as death, proliferation, differentiation and migration. Thus, the activities of molecular networks that execute metabolic or cytoskeletal processes, or regulate these by signal transduction, are altered in a complex manner by diverse genetic mutations in concert with the environmental context. A major challenge therefore is how to develop actionable understanding of this multivariate dysregulation, with respect both to how it arises from diverse genetic mutations and to how it may be ameliorated by prospective treatments. While high-throughput experimental platform technologies ranging from genomic sequencing to transcriptomic, proteomic and metabolomic profiling are now commonly used for molecular-level characterization of tumor cells and surrounding tissues, the resulting data sets defy straightforward intuitive interpretation with respect to potential therapeutic targets or the effects of perturbation. In this review article, we will discuss how significant advances can be obtained by applying computational modeling approaches to elucidate the pathways most critically involved in tumor formation and progression, impact of particular mutations on pathway operation, consequences of altered cell behavior in tissue environments and effects of molecular therapeutics. National Cancer Institute (U.S.). Integrative Cancer Biology Program (U54-CA112967-03 to D.A.L.) American Cancer Society (PF-08-026-01-CCG) 2010-12-17T19:56:42Z 2010-12-17T19:56:42Z 2009-10 2009-10 Article http://purl.org/eprint/type/JournalArticle 0143-3334 1460-2180 http://hdl.handle.net/1721.1/60314 Kreeger, Pamela K., and Douglas A. Lauffenburger. “Cancer systems biology: a network modeling perspective.” Carcinogenesis 31.1 (2010): 2 -8. © The Author 2009. en_US http://dx.doi.org/10.1093/carcin/bgp261 Carcinogenesis Creative Commons Attribution Non-Commercial License http://creativecommons.org/licenses/by-nc/2.5 application/pdf Oxford University Press Prof. Lauffenburger |
| spellingShingle | Lauffenburger, Douglas A. Kreeger, Pamela K. Cancer systems biology: a network modeling perspective |
| title | Cancer systems biology: a network modeling perspective |
| title_full | Cancer systems biology: a network modeling perspective |
| title_fullStr | Cancer systems biology: a network modeling perspective |
| title_full_unstemmed | Cancer systems biology: a network modeling perspective |
| title_short | Cancer systems biology: a network modeling perspective |
| title_sort | cancer systems biology a network modeling perspective |
| url | http://hdl.handle.net/1721.1/60314 |
| work_keys_str_mv | AT lauffenburgerdouglasa cancersystemsbiologyanetworkmodelingperspective AT kreegerpamelak cancersystemsbiologyanetworkmodelingperspective |