Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models
Resistance to chemotherapy often results from dysfunctional apoptosis, however multiple proteins with overlapping functions regulate this pathway. We sought to determine whether an extensively validated, deterministic apoptosis systems model, ‘DR_MOMP’, could be used as a stratification tool for the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/12/10/2978 |
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| author | Alice C. O’Farrell Monika A. Jarzabek Andreas U. Lindner Steven Carberry Emer Conroy Ian S. Miller Kate Connor Liam Shiels Eugenia R. Zanella Federico Lucantoni Adam Lafferty Kieron White Mariangela Meyer Villamandos Patrick Dicker William M. Gallagher Simon A. Keek Sebastian Sanduleanu Philippe Lambin Henry C. Woodruff Andrea Bertotti Livio Trusolino Annette T. Byrne Jochen H. M. Prehn |
| author_facet | Alice C. O’Farrell Monika A. Jarzabek Andreas U. Lindner Steven Carberry Emer Conroy Ian S. Miller Kate Connor Liam Shiels Eugenia R. Zanella Federico Lucantoni Adam Lafferty Kieron White Mariangela Meyer Villamandos Patrick Dicker William M. Gallagher Simon A. Keek Sebastian Sanduleanu Philippe Lambin Henry C. Woodruff Andrea Bertotti Livio Trusolino Annette T. Byrne Jochen H. M. Prehn |
| author_sort | Alice C. O’Farrell |
| collection | DOAJ |
| description | Resistance to chemotherapy often results from dysfunctional apoptosis, however multiple proteins with overlapping functions regulate this pathway. We sought to determine whether an extensively validated, deterministic apoptosis systems model, ‘DR_MOMP’, could be used as a stratification tool for the apoptosis sensitiser and BCL-2 antagonist, ABT-199 in patient-derived xenograft (PDX) models of colorectal cancer (CRC). Through quantitative profiling of BCL-2 family proteins, we identified two PDX models which were predicted by DR_MOMP to be sufficiently sensitive to 5-fluorouracil (5-FU)-based chemotherapy (CRC0344), or less responsive to chemotherapy but sensitised by ABT-199 (CRC0076). Treatment with ABT-199 significantly improved responses of CRC0076 PDXs to 5-FU-based chemotherapy, but showed no sensitisation in CRC0344 PDXs, as predicted from systems modelling. <sup>18</sup>F-Fluorodeoxyglucose positron emission tomography/computed tomography (<sup>18</sup>F-FDG-PET/CT) scans were performed to investigate possible early biomarkers of response. In CRC0076, a significant post-treatment decrease in mean standard uptake value was indeed evident only in the combination treatment group. Radiomic CT feature analysis of pre-treatment images in CRC0076 and CRC0344 PDXs identified features which could phenotypically discriminate between models, but were not predictive of treatment responses. Collectively our data indicate that systems modelling may identify metastatic (m)CRC patients benefitting from ABT-199, and that <sup>18</sup>F-FDG-PET could independently support such predictions. |
| first_indexed | 2024-03-10T15:37:59Z |
| format | Article |
| id | doaj.art-ea5a96ef8f444a88b82dbd3caf5d5111 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T15:37:59Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-ea5a96ef8f444a88b82dbd3caf5d51112023-11-20T17:05:45ZengMDPI AGCancers2072-66942020-10-011210297810.3390/cancers12102978Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft ModelsAlice C. O’Farrell0Monika A. Jarzabek1Andreas U. Lindner2Steven Carberry3Emer Conroy4Ian S. Miller5Kate Connor6Liam Shiels7Eugenia R. Zanella8Federico Lucantoni9Adam Lafferty10Kieron White11Mariangela Meyer Villamandos12Patrick Dicker13William M. Gallagher14Simon A. Keek15Sebastian Sanduleanu16Philippe Lambin17Henry C. Woodruff18Andrea Bertotti19Livio Trusolino20Annette T. Byrne21Jochen H. M. Prehn22Precision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandPrecision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandDepartment of Physiology and Medical Physics, Centre for Systems Medicine, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandDepartment of Physiology and Medical Physics, Centre for Systems Medicine, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandUCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Belfield, D04 V1W8 Dublin, IrelandPrecision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandPrecision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandPrecision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandCandiolo Cancer Institute—FPO IRCCS, Candiolo, 10060 Torino, ItalyDepartment of Physiology and Medical Physics, Centre for Systems Medicine, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandPrecision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandPrecision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandDepartment of Physiology and Medical Physics, Centre for Systems Medicine, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandDepartment of Epidemiology and Public Health Medicine, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandUCD School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Belfield, D04 V1W8 Dublin, IrelandThe D-Lab, Department of Precision Medicine, GROW—School for Oncology, Maastricht University, 6229 ER Maastricht, The NetherlandsThe D-Lab, Department of Precision Medicine, GROW—School for Oncology, Maastricht University, 6229 ER Maastricht, The NetherlandsThe D-Lab, Department of Precision Medicine, GROW—School for Oncology, Maastricht University, 6229 ER Maastricht, The NetherlandsThe D-Lab, Department of Precision Medicine, GROW—School for Oncology, Maastricht University, 6229 ER Maastricht, The NetherlandsCandiolo Cancer Institute—FPO IRCCS, Candiolo, 10060 Torino, ItalyCandiolo Cancer Institute—FPO IRCCS, Candiolo, 10060 Torino, ItalyPrecision Cancer Medicine Group, Department of Physiology and Medical Physics, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandDepartment of Physiology and Medical Physics, Centre for Systems Medicine, Royal College of Surgeons in Ireland, D02 YN77 Dublin, IrelandResistance to chemotherapy often results from dysfunctional apoptosis, however multiple proteins with overlapping functions regulate this pathway. We sought to determine whether an extensively validated, deterministic apoptosis systems model, ‘DR_MOMP’, could be used as a stratification tool for the apoptosis sensitiser and BCL-2 antagonist, ABT-199 in patient-derived xenograft (PDX) models of colorectal cancer (CRC). Through quantitative profiling of BCL-2 family proteins, we identified two PDX models which were predicted by DR_MOMP to be sufficiently sensitive to 5-fluorouracil (5-FU)-based chemotherapy (CRC0344), or less responsive to chemotherapy but sensitised by ABT-199 (CRC0076). Treatment with ABT-199 significantly improved responses of CRC0076 PDXs to 5-FU-based chemotherapy, but showed no sensitisation in CRC0344 PDXs, as predicted from systems modelling. <sup>18</sup>F-Fluorodeoxyglucose positron emission tomography/computed tomography (<sup>18</sup>F-FDG-PET/CT) scans were performed to investigate possible early biomarkers of response. In CRC0076, a significant post-treatment decrease in mean standard uptake value was indeed evident only in the combination treatment group. Radiomic CT feature analysis of pre-treatment images in CRC0076 and CRC0344 PDXs identified features which could phenotypically discriminate between models, but were not predictive of treatment responses. Collectively our data indicate that systems modelling may identify metastatic (m)CRC patients benefitting from ABT-199, and that <sup>18</sup>F-FDG-PET could independently support such predictions.https://www.mdpi.com/2072-6694/12/10/2978ABT-199Venetoclaxcolorectal cancerBCL-2FOLFOXPDX |
| spellingShingle | Alice C. O’Farrell Monika A. Jarzabek Andreas U. Lindner Steven Carberry Emer Conroy Ian S. Miller Kate Connor Liam Shiels Eugenia R. Zanella Federico Lucantoni Adam Lafferty Kieron White Mariangela Meyer Villamandos Patrick Dicker William M. Gallagher Simon A. Keek Sebastian Sanduleanu Philippe Lambin Henry C. Woodruff Andrea Bertotti Livio Trusolino Annette T. Byrne Jochen H. M. Prehn Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models Cancers ABT-199 Venetoclax colorectal cancer BCL-2 FOLFOX PDX |
| title | Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models |
| title_full | Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models |
| title_fullStr | Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models |
| title_full_unstemmed | Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models |
| title_short | Implementing Systems Modelling and Molecular Imaging to Predict the Efficacy of BCL-2 Inhibition in Colorectal Cancer Patient-Derived Xenograft Models |
| title_sort | implementing systems modelling and molecular imaging to predict the efficacy of bcl 2 inhibition in colorectal cancer patient derived xenograft models |
| topic | ABT-199 Venetoclax colorectal cancer BCL-2 FOLFOX PDX |
| url | https://www.mdpi.com/2072-6694/12/10/2978 |
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