Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types.
Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable inform...
| Main Authors: | , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2008
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| _version_ | 1826263903539036160 |
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| author | Starmans, M Krishnapuram, B Steck, H Horlings, H Nuyten, D van de Vijver, M Seigneuric, R Buffa, F Harris, A Wouters, BG Lambin, P |
| author_facet | Starmans, M Krishnapuram, B Steck, H Horlings, H Nuyten, D van de Vijver, M Seigneuric, R Buffa, F Harris, A Wouters, BG Lambin, P |
| author_sort | Starmans, M |
| collection | OXFORD |
| description | Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable information on tumour status, prognosis and prediction. This will help individualizing treatment and should result in better tumour control, and more rapid and cost-effective research and development. From in vitro published microarray studies, two proliferation signatures were compiled. The prognostic value of these signatures was tested in five large clinical microarray data sets. More than 1000 patients with breast, renal or lung cancer were included. One of the signatures (110 genes) had significant prognostic value in all data sets. Stratifying patients in groups resulted in a clear difference in survival (P-values <0.05). Multivariate Cox-regression analyses showed that this signature added substantial value to the clinical factors used for prognosis. Further patient stratification was compared to patient stratification with several well-known published signatures. Contingency tables and Cramer's V statistics indicated that these primarily identify the same patients as the proliferation signature does. The proliferation signature is a strong prognostic factor, with the potential to be converted into a predictive test. Furthermore, evidence is provided that supports the idea that many published signatures track the same biological processes and that proliferation is one of them. |
| first_indexed | 2024-03-06T19:59:17Z |
| format | Journal article |
| id | oxford-uuid:26b72c10-f5f4-46c1-8613-6fb3444a80bd |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:59:17Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | oxford-uuid:26b72c10-f5f4-46c1-8613-6fb3444a80bd2022-03-26T12:02:41ZRobust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:26b72c10-f5f4-46c1-8613-6fb3444a80bdEnglishSymplectic Elements at Oxford2008Starmans, MKrishnapuram, BSteck, HHorlings, HNuyten, Dvan de Vijver, MSeigneuric, RBuffa, FHarris, AWouters, BGLambin, PTumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable information on tumour status, prognosis and prediction. This will help individualizing treatment and should result in better tumour control, and more rapid and cost-effective research and development. From in vitro published microarray studies, two proliferation signatures were compiled. The prognostic value of these signatures was tested in five large clinical microarray data sets. More than 1000 patients with breast, renal or lung cancer were included. One of the signatures (110 genes) had significant prognostic value in all data sets. Stratifying patients in groups resulted in a clear difference in survival (P-values <0.05). Multivariate Cox-regression analyses showed that this signature added substantial value to the clinical factors used for prognosis. Further patient stratification was compared to patient stratification with several well-known published signatures. Contingency tables and Cramer's V statistics indicated that these primarily identify the same patients as the proliferation signature does. The proliferation signature is a strong prognostic factor, with the potential to be converted into a predictive test. Furthermore, evidence is provided that supports the idea that many published signatures track the same biological processes and that proliferation is one of them. |
| spellingShingle | Starmans, M Krishnapuram, B Steck, H Horlings, H Nuyten, D van de Vijver, M Seigneuric, R Buffa, F Harris, A Wouters, BG Lambin, P Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types. |
| title | Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types. |
| title_full | Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types. |
| title_fullStr | Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types. |
| title_full_unstemmed | Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types. |
| title_short | Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types. |
| title_sort | robust prognostic value of a knowledge based proliferation signature across large patient microarray studies spanning different cancer types |
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