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Safikhani Z, Smirnov P, Freeman M, El-Hachem N, She A, Rene Q, Goldenberg A, Birkbak NJ, Hatzis C, Shi L, Beck AH, Aerts HJ, Quackenbush J, Haibe-Kains B. Revisiting inconsistency in large pharmacogenomic studies. F1000Res 2016; 5:2333. [PMID: 28928933 PMCID: PMC5580432 DOI: 10.12688/f1000research.9611.3] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/11/2017] [Indexed: 01/30/2023] Open
Abstract
In 2013, we published a comparative analysis of mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE). While we found good concordance in gene expression profiles, there was substantial inconsistency in the drug responses reported by the GDSC and CCLE projects. We received extensive feedback on the comparisons that we performed. This feedback, along with the release of new data, prompted us to revisit our initial analysis. We present a new analysis using these expanded data, where we address the most significant suggestions for improvements on our published analysis - that targeted therapies and broad cytotoxic drugs should have been treated differently in assessing consistency, that consistency of both molecular profiles and drug sensitivity measurements should be compared across cell lines, and that the software analysis tools provided should have been easier to run, particularly as the GDSC and CCLE released additional data. Our re-analysis supports our previous finding that gene expression data are significantly more consistent than drug sensitivity measurements. Using new statistics to assess data consistency allowed identification of two broad effect drugs and three targeted drugs with moderate to good consistency in drug sensitivity data between GDSC and CCLE. For three other targeted drugs, there were not enough sensitive cell lines to assess the consistency of the pharmacological profiles. We found evidence of inconsistencies in pharmacological phenotypes for the remaining eight drugs. Overall, our findings suggest that the drug sensitivity data in GDSC and CCLE continue to present challenges for robust biomarker discovery. This re-analysis provides additional support for the argument that experimental standardization and validation of pharmacogenomic response will be necessary to advance the broad use of large pharmacogenomic screens.
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Affiliation(s)
- Zhaleh Safikhani
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Petr Smirnov
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Mark Freeman
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Nehme El-Hachem
- Institut de Recherches Cliniques de Montréal, Montréal, H2W 1R7, Canada
| | - Adrian She
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Quevedo Rene
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Anna Goldenberg
- Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada
- Hospital for Sick Children, Toronto, M5G 1X8, Canada
| | | | - Christos Hatzis
- Yale Cancer Center, Yale University, New Haven, CT, 06510, USA
- Section of Medical Oncology, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Leming Shi
- University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA
- Fudan University, Shanghai City, 200135, China
| | - Andrew H. Beck
- Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, 02215, USA
| | - Hugo J.W.L. Aerts
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Boston, MA, 02215, USA
- Department of Radiation Oncology and Radiology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA
| | - John Quackenbush
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Boston, MA, 02215, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Benjamin Haibe-Kains
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
- Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada
- Ontario Institute of Cancer Research, Toronto, M5G 1L7, Canada
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Safikhani Z, Smirnov P, Freeman M, El-Hachem N, She A, Rene Q, Goldenberg A, Birkbak NJ, Hatzis C, Shi L, Beck AH, Aerts HJ, Quackenbush J, Haibe-Kains B. Revisiting inconsistency in large pharmacogenomic studies. F1000Res 2016; 5:2333. [PMID: 28928933 PMCID: PMC5580432 DOI: 10.12688/f1000research.9611.2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/21/2017] [Indexed: 11/13/2023] Open
Abstract
In 2013, we published a comparative analysis of mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE). While we found good concordance in gene expression profiles, there was substantial inconsistency in the drug responses reported by the GDSC and CCLE projects. We received extensive feedback on the comparisons that we performed. This feedback, along with the release of new data, prompted us to revisit our initial analysis. We present a new analysis using these expanded data, where we address the most significant suggestions for improvements on our published analysis - that targeted therapies and broad cytotoxic drugs should have been treated differently in assessing consistency, that consistency of both molecular profiles and drug sensitivity measurements should be compared across cell lines, and that the software analysis tools provided should have been easier to run, particularly as the GDSC and CCLE released additional data. Our re-analysis supports our previous finding that gene expression data are significantly more consistent than drug sensitivity measurements. Using new statistics to assess data consistency allowed identification of two broad effect drugs and three targeted drugs with moderate to good consistency in drug sensitivity data between GDSC and CCLE. For three other targeted drugs, there were not enough sensitive cell lines to assess the consistency of the pharmacological profiles. We found evidence of inconsistencies in pharmacological phenotypes for the remaining eight drugs. Overall, our findings suggest that the drug sensitivity data in GDSC and CCLE continue to present challenges for robust biomarker discovery. This re-analysis provides additional support for the argument that experimental standardization and validation of pharmacogenomic response will be necessary to advance the broad use of large pharmacogenomic screens.
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Affiliation(s)
- Zhaleh Safikhani
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Petr Smirnov
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Mark Freeman
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Nehme El-Hachem
- Institut de Recherches Cliniques de Montréal, Montréal, H2W 1R7, Canada
| | - Adrian She
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Quevedo Rene
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Anna Goldenberg
- Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada
- Hospital for Sick Children, Toronto, M5G 1X8, Canada
| | | | - Christos Hatzis
- Yale Cancer Center, Yale University, New Haven, CT, 06510, USA
- Section of Medical Oncology, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Leming Shi
- University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA
- Fudan University, Shanghai City, 200135, China
| | - Andrew H. Beck
- Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, 02215, USA
| | - Hugo J.W.L. Aerts
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Boston, MA, 02215, USA
- Department of Radiation Oncology and Radiology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA
| | - John Quackenbush
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Boston, MA, 02215, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Benjamin Haibe-Kains
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
- Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada
- Ontario Institute of Cancer Research, Toronto, M5G 1L7, Canada
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Safikhani Z, Smirnov P, Freeman M, El-Hachem N, She A, Rene Q, Goldenberg A, Birkbak NJ, Hatzis C, Shi L, Beck AH, Aerts HJ, Quackenbush J, Haibe-Kains B. Revisiting inconsistency in large pharmacogenomic studies. F1000Res 2016; 5:2333. [PMID: 28928933 PMCID: PMC5580432 DOI: 10.12688/f1000research.9611.1] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/15/2016] [Indexed: 01/22/2023] Open
Abstract
In 2013, we published a comparative analysis mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE). While we found good concordance in gene expression profiles, there was substantial inconsistency in the drug responses reported by the GDSC and CCLE projects. We received extensive feedback on the comparisons that we performed. This feedback, along with the release of new data, prompted us to revisit our initial analysis. Here we present a new analysis using these expanded data in which we address the most significant suggestions for improvements on our published analysis - that targeted therapies and broad cytotoxic drugs should have been treated differently in assessing consistency, that consistency of both molecular profiles and drug sensitivity measurements should both be compared across cell lines, and that the software analysis tools we provided should have been easier to run, particularly as the GDSC and CCLE released additional data. Our re-analysis supports our previous finding that gene expression data are significantly more consistent than drug sensitivity measurements. The use of new statistics to assess data consistency allowed us to identify two broad effect drugs and three targeted drugs with moderate to good consistency in drug sensitivity data between GDSC and CCLE. For three other targeted drugs, there were not enough sensitive cell lines to assess the consistency of the pharmacological profiles. We found evidence of inconsistencies in pharmacological phenotypes for the remaining eight drugs. Overall, our findings suggest that the drug sensitivity data in GDSC and CCLE continue to present challenges for robust biomarker discovery. This re-analysis provides additional support for the argument that experimental standardization and validation of pharmacogenomic response will be necessary to advance the broad use of large pharmacogenomic screens.
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Affiliation(s)
- Zhaleh Safikhani
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Petr Smirnov
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Mark Freeman
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Nehme El-Hachem
- Institut de Recherches Cliniques de Montréal, Montréal, H2W 1R7, Canada
| | - Adrian She
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Quevedo Rene
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
| | - Anna Goldenberg
- Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada
- Hospital for Sick Children, Toronto, M5G 1X8, Canada
| | | | - Christos Hatzis
- Yale Cancer Center, Yale University, New Haven, CT, 06510, USA
- Section of Medical Oncology, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - Leming Shi
- University of Arkansas for Medical Sciences, Little Rock, AR, 72205, USA
- Fudan University, Shanghai City, 200135, China
| | - Andrew H. Beck
- Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, 02215, USA
| | - Hugo J.W.L. Aerts
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Boston, MA, 02215, USA
- Department of Radiation Oncology and Radiology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA
| | - John Quackenbush
- Department of Biostatistics and Computational Biology and Center for Cancer Computational Biology, Boston, MA, 02215, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
| | - Benjamin Haibe-Kains
- Department of Medical Biophysics, University of Toronto, Toronto, M5G 1L7, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, M5G 1L7, Canada
- Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada
- Ontario Institute of Cancer Research, Toronto, M5G 1L7, Canada
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