A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes
We describe a thermodynamic-motivated, information theoretic analysis of proteomic data collected from a series of 8 glioblastoma multiforme (GBM) tumors. GBMs are considered here as prototypes of heterogeneous cancers. That heterogeneity is viewed here as manifesting in different unbalanced biologi...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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American Chemical Society (ACS)
2017
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| Online Access: | http://hdl.handle.net/1721.1/110914 https://orcid.org/0000-0002-1545-1651 |
| _version_ | 1826209326948155392 |
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| author | Kravchenko-Balasha, Nataly Johnson, Hannah Heath, James R. Levine, R. D. White, Forest M |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Kravchenko-Balasha, Nataly Johnson, Hannah Heath, James R. Levine, R. D. White, Forest M |
| author_sort | Kravchenko-Balasha, Nataly |
| collection | MIT |
| description | We describe a thermodynamic-motivated, information theoretic analysis of proteomic data collected from a series of 8 glioblastoma multiforme (GBM) tumors. GBMs are considered here as prototypes of heterogeneous cancers. That heterogeneity is viewed here as manifesting in different unbalanced biological processes that are associated with thermodynamic-like constraints. The analysis yields a molecular description of a stable steady state that is common across all tumors. It also resolves molecular descriptions of unbalanced processes that are shared by several tumors, such as hyperactivated phosphoprotein signaling networks. Further, it resolves unbalanced processes that provide unique classifiers of tumor subgroups. The results of the theoretical interpretation are compared against those of statistical multivariate methods and are shown to provide a superior level of resolution for identifying unbalanced processes in GBM tumors. The identification of specific constraints for each GBM tumor suggests tumor-specific combination therapies that may reverse this imbalance. |
| first_indexed | 2024-09-23T14:20:46Z |
| format | Article |
| id | mit-1721.1/110914 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T14:20:46Z |
| publishDate | 2017 |
| publisher | American Chemical Society (ACS) |
| record_format | dspace |
| spelling | mit-1721.1/1109142022-09-29T08:51:38Z A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes Kravchenko-Balasha, Nataly Johnson, Hannah Heath, James R. Levine, R. D. White, Forest M Massachusetts Institute of Technology. Department of Biological Engineering White, Forest M We describe a thermodynamic-motivated, information theoretic analysis of proteomic data collected from a series of 8 glioblastoma multiforme (GBM) tumors. GBMs are considered here as prototypes of heterogeneous cancers. That heterogeneity is viewed here as manifesting in different unbalanced biological processes that are associated with thermodynamic-like constraints. The analysis yields a molecular description of a stable steady state that is common across all tumors. It also resolves molecular descriptions of unbalanced processes that are shared by several tumors, such as hyperactivated phosphoprotein signaling networks. Further, it resolves unbalanced processes that provide unique classifiers of tumor subgroups. The results of the theoretical interpretation are compared against those of statistical multivariate methods and are shown to provide a superior level of resolution for identifying unbalanced processes in GBM tumors. The identification of specific constraints for each GBM tumor suggests tumor-specific combination therapies that may reverse this imbalance. 2017-08-03T13:52:39Z 2017-08-03T13:52:39Z 2016-07 2016-02 Article http://purl.org/eprint/type/JournalArticle 1520-6106 1520-5207 http://hdl.handle.net/1721.1/110914 Kravchenko-Balasha, Nataly; Johnson, Hannah and White, Forest M. “A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes.” The Journal of Physical Chemistry B 120, 26 (July 2016): 5990–5997 © 2016 American Chemical Society https://orcid.org/0000-0002-1545-1651 en_US http://dx.doi.org/10.1021/acs.jpcb.6b01692 Journal of Physical Chemistry B Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf American Chemical Society (ACS) PMC |
| spellingShingle | Kravchenko-Balasha, Nataly Johnson, Hannah Heath, James R. Levine, R. D. White, Forest M A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes |
| title | A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes |
| title_full | A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes |
| title_fullStr | A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes |
| title_full_unstemmed | A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes |
| title_short | A Thermodynamic-Based Interpretation of Protein Expression Heterogeneity in Different Glioblastoma Multiforme Tumors Identifies Tumor-Specific Unbalanced Processes |
| title_sort | thermodynamic based interpretation of protein expression heterogeneity in different glioblastoma multiforme tumors identifies tumor specific unbalanced processes |
| url | http://hdl.handle.net/1721.1/110914 https://orcid.org/0000-0002-1545-1651 |
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