Identification of key processes underlying cancer phenotypes using biologic pathway analysis.
Cancer is recognized to be a family of gene-based diseases whose causes are to be found in disruptions of basic biologic processes. An increasingly deep catalogue of canonical networks details the specific molecular interaction of genes and their products. However, mapping of disease phenotypes to a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2007-05-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC1855990?pdf=render |
| _version_ | 1818120172052938752 |
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| author | Sol Efroni Carl F Schaefer Kenneth H Buetow |
| author_facet | Sol Efroni Carl F Schaefer Kenneth H Buetow |
| author_sort | Sol Efroni |
| collection | DOAJ |
| description | Cancer is recognized to be a family of gene-based diseases whose causes are to be found in disruptions of basic biologic processes. An increasingly deep catalogue of canonical networks details the specific molecular interaction of genes and their products. However, mapping of disease phenotypes to alterations of these networks of interactions is accomplished indirectly and non-systematically. Here we objectively identify pathways associated with malignancy, staging, and outcome in cancer through application of an analytic approach that systematically evaluates differences in the activity and consistency of interactions within canonical biologic processes. Using large collections of publicly accessible genome-wide gene expression, we identify small, common sets of pathways - Trka Receptor, Apoptosis response to DNA Damage, Ceramide, Telomerase, CD40L and Calcineurin - whose differences robustly distinguish diverse tumor types from corresponding normal samples, predict tumor grade, and distinguish phenotypes such as estrogen receptor status and p53 mutation state. Pathways identified through this analysis perform as well or better than phenotypes used in the original studies in predicting cancer outcome. This approach provides a means to use genome-wide characterizations to map key biological processes to important clinical features in disease. |
| first_indexed | 2024-12-11T05:21:52Z |
| format | Article |
| id | doaj.art-e343364ba8f04e29ab7ec2c629070c46 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-11T05:21:52Z |
| publishDate | 2007-05-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-e343364ba8f04e29ab7ec2c629070c462022-12-22T01:19:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032007-05-0125e42510.1371/journal.pone.0000425Identification of key processes underlying cancer phenotypes using biologic pathway analysis.Sol EfroniCarl F SchaeferKenneth H BuetowCancer is recognized to be a family of gene-based diseases whose causes are to be found in disruptions of basic biologic processes. An increasingly deep catalogue of canonical networks details the specific molecular interaction of genes and their products. However, mapping of disease phenotypes to alterations of these networks of interactions is accomplished indirectly and non-systematically. Here we objectively identify pathways associated with malignancy, staging, and outcome in cancer through application of an analytic approach that systematically evaluates differences in the activity and consistency of interactions within canonical biologic processes. Using large collections of publicly accessible genome-wide gene expression, we identify small, common sets of pathways - Trka Receptor, Apoptosis response to DNA Damage, Ceramide, Telomerase, CD40L and Calcineurin - whose differences robustly distinguish diverse tumor types from corresponding normal samples, predict tumor grade, and distinguish phenotypes such as estrogen receptor status and p53 mutation state. Pathways identified through this analysis perform as well or better than phenotypes used in the original studies in predicting cancer outcome. This approach provides a means to use genome-wide characterizations to map key biological processes to important clinical features in disease.http://europepmc.org/articles/PMC1855990?pdf=render |
| spellingShingle | Sol Efroni Carl F Schaefer Kenneth H Buetow Identification of key processes underlying cancer phenotypes using biologic pathway analysis. PLoS ONE |
| title | Identification of key processes underlying cancer phenotypes using biologic pathway analysis. |
| title_full | Identification of key processes underlying cancer phenotypes using biologic pathway analysis. |
| title_fullStr | Identification of key processes underlying cancer phenotypes using biologic pathway analysis. |
| title_full_unstemmed | Identification of key processes underlying cancer phenotypes using biologic pathway analysis. |
| title_short | Identification of key processes underlying cancer phenotypes using biologic pathway analysis. |
| title_sort | identification of key processes underlying cancer phenotypes using biologic pathway analysis |
| url | http://europepmc.org/articles/PMC1855990?pdf=render |
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