In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer
Abstract Background Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2017-06-01
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| Series: | Molecular Cancer |
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| Online Access: | http://link.springer.com/article/10.1186/s12943-017-0673-0 |
| _version_ | 1828526895411494912 |
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| author | Basel Abu-Jamous Francesca M. Buffa Adrian L. Harris Asoke K. Nandi |
| author_facet | Basel Abu-Jamous Francesca M. Buffa Adrian L. Harris Asoke K. Nandi |
| author_sort | Basel Abu-Jamous |
| collection | DOAJ |
| description | Abstract Background Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified. However, it was observed that cell line data do not always concur with clinical data, and therefore conclusions from cell line analysis should be considered with caution. As many transcriptomic cell-line datasets from hypoxia related contexts are available, integrative approaches which investigate these datasets collectively, while not ignoring clinical data, are required. Results We analyse sixteen heterogeneous breast cancer cell-line transcriptomic datasets in hypoxia-related conditions collectively by employing the unique capabilities of the method, UNCLES, which integrates clustering results from multiple datasets and can address questions that cannot be answered by existing methods. This has been demonstrated by comparison with the state-of-the-art iCluster method. From this collection of genome-wide datasets include 15,588 genes, UNCLES identified a relatively high number of genes (>1000 overall) which are consistently co-regulated over all of the datasets, and some of which are still poorly understood and represent new potential HIF targets, such as RSBN1 and KIAA0195. Two main, anti-correlated, clusters were identified; the first is enriched with MYC targets participating in growth and proliferation, while the other is enriched with HIF targets directly participating in the hypoxia response. Surprisingly, in six clinical datasets, some sub-clusters of growth genes are found consistently positively correlated with hypoxia response genes, unlike the observation in cell lines. Moreover, the ability to predict bad prognosis by a combined signature of one sub-cluster of growth genes and one sub-cluster of hypoxia-induced genes appears to be comparable and perhaps greater than that of known hypoxia signatures. Conclusions We present a clustering approach suitable to integrate data from diverse experimental set-ups. Its application to breast cancer cell line datasets reveals new hypoxia-regulated signatures of genes which behave differently when in vitro (cell-line) data is compared with in vivo (clinical) data, and are of a prognostic value comparable or exceeding the state-of-the-art hypoxia signatures. |
| first_indexed | 2024-12-11T21:30:22Z |
| format | Article |
| id | doaj.art-607aeb687fcf4adb860c943f3cb51b92 |
| institution | Directory Open Access Journal |
| issn | 1476-4598 |
| language | English |
| last_indexed | 2024-12-11T21:30:22Z |
| publishDate | 2017-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Molecular Cancer |
| spelling | doaj.art-607aeb687fcf4adb860c943f3cb51b922022-12-22T00:50:11ZengBMCMolecular Cancer1476-45982017-06-0116111910.1186/s12943-017-0673-0In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancerBasel Abu-Jamous0Francesca M. Buffa1Adrian L. Harris2Asoke K. Nandi3Department of Electronic and Computer Engineering, Brunel University LondonCancer Research UK, Department of Oncology, Weatherall Institute of Molecular MedicineCancer Research UK, Department of Oncology, Weatherall Institute of Molecular MedicineDepartment of Electronic and Computer Engineering, Brunel University LondonAbstract Background Hypoxia is a characteristic of breast tumours indicating poor prognosis. Based on the assumption that those genes which are up-regulated under hypoxia in cell-lines are expected to be predictors of poor prognosis in clinical data, many signatures of poor prognosis were identified. However, it was observed that cell line data do not always concur with clinical data, and therefore conclusions from cell line analysis should be considered with caution. As many transcriptomic cell-line datasets from hypoxia related contexts are available, integrative approaches which investigate these datasets collectively, while not ignoring clinical data, are required. Results We analyse sixteen heterogeneous breast cancer cell-line transcriptomic datasets in hypoxia-related conditions collectively by employing the unique capabilities of the method, UNCLES, which integrates clustering results from multiple datasets and can address questions that cannot be answered by existing methods. This has been demonstrated by comparison with the state-of-the-art iCluster method. From this collection of genome-wide datasets include 15,588 genes, UNCLES identified a relatively high number of genes (>1000 overall) which are consistently co-regulated over all of the datasets, and some of which are still poorly understood and represent new potential HIF targets, such as RSBN1 and KIAA0195. Two main, anti-correlated, clusters were identified; the first is enriched with MYC targets participating in growth and proliferation, while the other is enriched with HIF targets directly participating in the hypoxia response. Surprisingly, in six clinical datasets, some sub-clusters of growth genes are found consistently positively correlated with hypoxia response genes, unlike the observation in cell lines. Moreover, the ability to predict bad prognosis by a combined signature of one sub-cluster of growth genes and one sub-cluster of hypoxia-induced genes appears to be comparable and perhaps greater than that of known hypoxia signatures. Conclusions We present a clustering approach suitable to integrate data from diverse experimental set-ups. Its application to breast cancer cell line datasets reveals new hypoxia-regulated signatures of genes which behave differently when in vitro (cell-line) data is compared with in vivo (clinical) data, and are of a prognostic value comparable or exceeding the state-of-the-art hypoxia signatures.http://link.springer.com/article/10.1186/s12943-017-0673-0Breast cancerCell linesHypoxiaCo-expressionCo-regulationGenome-wide analysis |
| spellingShingle | Basel Abu-Jamous Francesca M. Buffa Adrian L. Harris Asoke K. Nandi In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer Molecular Cancer Breast cancer Cell lines Hypoxia Co-expression Co-regulation Genome-wide analysis |
| title | In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer |
| title_full | In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer |
| title_fullStr | In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer |
| title_full_unstemmed | In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer |
| title_short | In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer |
| title_sort | in vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer |
| topic | Breast cancer Cell lines Hypoxia Co-expression Co-regulation Genome-wide analysis |
| url | http://link.springer.com/article/10.1186/s12943-017-0673-0 |
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