Individual patient oesophageal cancer 3D models for tailored treatment
Background: A model to predict chemotherapy response would provide a marked clinical benefit, enabling tailored treatment of oesophageal cancer, where less than half of patients respond to the routinely administered chemotherapy. Methods: Cancer cells were established from tumour biopsies taken fro...
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| Format: | Article |
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Impact Journals
2016
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| Online Access: | https://eprints.nottingham.ac.uk/39297/ |
| _version_ | 1848795805031333888 |
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| author | Saunders, John H. Onion, David Collier, Pamela Dorrington, Matthew S. Argent, Richard H. Clarke, Philip A. Reece-Smith, Alex M. Parsons, Simon L. Grabowska, Anna M. |
| author_facet | Saunders, John H. Onion, David Collier, Pamela Dorrington, Matthew S. Argent, Richard H. Clarke, Philip A. Reece-Smith, Alex M. Parsons, Simon L. Grabowska, Anna M. |
| author_sort | Saunders, John H. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Background: A model to predict chemotherapy response would provide a marked clinical benefit, enabling tailored treatment of oesophageal cancer, where less than half of patients respond to the routinely administered chemotherapy.
Methods: Cancer cells were established from tumour biopsies taken from individual patients about to undergo neoadjuvant chemotherapy. A 3D-tumour growth assay (3D-TGA) was developed, in which cancer cells were grown with or without supporting mesenchymal cells, then subjected to chemo-sensitivity testing using the standard chemotherapy administered in clinic, and a novel emerging HDAC inhibitor, Panobinostat.
Results: Individual patient’s cancer cells could be expanded and screened within a clinically applicable timescale of 3 weeks. Incorporating mesenchymal support within the 3D-TGA significantly enhanced both the growth and drug resistance profiles of the patient’s cancer cells. The ex vivo drug response in the presence, but not absence, of mesenchymal cells accurately reflected clinical chemo-sensitivity, as measured by tumour regression grade. Combination with Panobinostat enhanced response and proved efficacious in otherwise chemo-resistant tumours.
Conclusions: This novel method of establishing individual patient oesophageal cancers in the laboratory, from small endoscopic biopsies, enables clinically-relevant chemo-sensitivity testing, and reduces use of animals by providing more refined in vitro models for pre-screening of drugs. The 3D-TGA accurately predicted chemo-sensitivity in patients, and could be developed to guide tailored patient treatment. The incorporation of mesenchymal cells as the stromal cell component of the tumour micro-environment had a significant effect upon enhancing chemotherapy drug resistance in oesophageal cancer, and could prove a useful target for future drug development. |
| first_indexed | 2025-11-14T19:37:55Z |
| format | Article |
| id | nottingham-39297 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:37:55Z |
| publishDate | 2016 |
| publisher | Impact Journals |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-392972020-05-04T18:17:51Z https://eprints.nottingham.ac.uk/39297/ Individual patient oesophageal cancer 3D models for tailored treatment Saunders, John H. Onion, David Collier, Pamela Dorrington, Matthew S. Argent, Richard H. Clarke, Philip A. Reece-Smith, Alex M. Parsons, Simon L. Grabowska, Anna M. Background: A model to predict chemotherapy response would provide a marked clinical benefit, enabling tailored treatment of oesophageal cancer, where less than half of patients respond to the routinely administered chemotherapy. Methods: Cancer cells were established from tumour biopsies taken from individual patients about to undergo neoadjuvant chemotherapy. A 3D-tumour growth assay (3D-TGA) was developed, in which cancer cells were grown with or without supporting mesenchymal cells, then subjected to chemo-sensitivity testing using the standard chemotherapy administered in clinic, and a novel emerging HDAC inhibitor, Panobinostat. Results: Individual patient’s cancer cells could be expanded and screened within a clinically applicable timescale of 3 weeks. Incorporating mesenchymal support within the 3D-TGA significantly enhanced both the growth and drug resistance profiles of the patient’s cancer cells. The ex vivo drug response in the presence, but not absence, of mesenchymal cells accurately reflected clinical chemo-sensitivity, as measured by tumour regression grade. Combination with Panobinostat enhanced response and proved efficacious in otherwise chemo-resistant tumours. Conclusions: This novel method of establishing individual patient oesophageal cancers in the laboratory, from small endoscopic biopsies, enables clinically-relevant chemo-sensitivity testing, and reduces use of animals by providing more refined in vitro models for pre-screening of drugs. The 3D-TGA accurately predicted chemo-sensitivity in patients, and could be developed to guide tailored patient treatment. The incorporation of mesenchymal cells as the stromal cell component of the tumour micro-environment had a significant effect upon enhancing chemotherapy drug resistance in oesophageal cancer, and could prove a useful target for future drug development. Impact Journals 2016-10-06 Article PeerReviewed Saunders, John H., Onion, David, Collier, Pamela, Dorrington, Matthew S., Argent, Richard H., Clarke, Philip A., Reece-Smith, Alex M., Parsons, Simon L. and Grabowska, Anna M. (2016) Individual patient oesophageal cancer 3D models for tailored treatment. Oncotarget . ISSN 1949-2553 http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path%5b%5d=12500 doi:10.18632/oncotarget.12500 doi:10.18632/oncotarget.12500 |
| spellingShingle | Saunders, John H. Onion, David Collier, Pamela Dorrington, Matthew S. Argent, Richard H. Clarke, Philip A. Reece-Smith, Alex M. Parsons, Simon L. Grabowska, Anna M. Individual patient oesophageal cancer 3D models for tailored treatment |
| title | Individual patient oesophageal cancer 3D models for tailored treatment |
| title_full | Individual patient oesophageal cancer 3D models for tailored treatment |
| title_fullStr | Individual patient oesophageal cancer 3D models for tailored treatment |
| title_full_unstemmed | Individual patient oesophageal cancer 3D models for tailored treatment |
| title_short | Individual patient oesophageal cancer 3D models for tailored treatment |
| title_sort | individual patient oesophageal cancer 3d models for tailored treatment |
| url | https://eprints.nottingham.ac.uk/39297/ https://eprints.nottingham.ac.uk/39297/ https://eprints.nottingham.ac.uk/39297/ |