O'Farrell et al cancers-12- 2020.pdf (1.27 MB)

Implementing systems modelling and molecular imaging to predict the efficacy of BCL-2 inhibition in colorectal cancer patient-derived xenograft models.

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posted on 23.10.2020, 13:03 by Alice O'Farrell, Monika Jarzabek, Andreas Ulrich Lindner, Steven Carberry, Emer Conroy, Ian 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 Byrne, Jochen Prehn
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. 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-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 18F-FDG-PET could independently support such predictions.

Funding

A systems-based patient stratification tool of Bcl-2 family protein interactions to evaluate acute treatment responses in rectal cancer patients

Health Research Board

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BCL-2 family proteins and cellular bioenergetics in the control of cell survival: Towards novel predictive and prognostic markers for disease progression and therapy responses in colorectal cancer patients

Science Foundation Ireland

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Development of personalised medicine approaches for the clinical application of IAP antagonists in metastatic and high risk early stage colorectal cancer

Science Foundation Ireland

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ColoForetell: A Xenopatient Discovery Platform for the integrated Systems based Identification of Predictive Biomarkers for Targeted Therapies in Metastatic Colorectal Cancer

Science Foundation Ireland

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Advancing a Precision Medicine Paradigm in metastatic Colorectal Cancer: Systems based patient stratification solutions

European Commission

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EurOPDX Distributed Infrastructure for Research on patient-derived cancer Xenografts

European Commission

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Irish Cancer Society Collaborative Cancer Research Centre BREAST-PREDICT (CCRC13GAL)

Science Foundation Ireland Strategic Partnership Programme Precision Oncology Ireland (18/SPP/3522)

Science Foundation Ireland (18/RI/5759)

Science Foundation Ireland and European Regional Development Fund (ERDF) (13/RC/2073)

Dutch Cancer Society (KWF Kankerbestrijding) (12085/2018-2)

TRANSCAN Joint Transnational Call 2016 (JTC2016 "CLEARLY" no UM 2017-8295)

Optimal Management of Gender-­Specific Cancers via Efficient Use of Protein Profiling, Digital Pathology and Systems Medicine Tools (OPTi-­PREDICT)

Science Foundation Ireland

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History

Associated research data files

https://www.mdpi.com/2072-6694/12/10/2978/s1

Comments

The original article is available at https://www.mdpi.com

Published Citation

O’Farrell AC, Jarzabek MA, Lindner AU, Carberry S, Conroy E. Miller IS, Connor K, Shiels L, Zanella ER, Lucantoni F, Lafferty A, White K, Meyer Villamandos M, Dicker P, Gallagher WM, Keek SA, Sanduleanu S, Lambin P, Woodruff HC, Bertotti A, Trusolino L, Byrne AT, Prehn JHM. Implementing systems modelling and molecular imaging to predict the efficacy of BCL-2 inhibition in colorectal cancer patient-derived xenograft models. Cancers 2020;12: 2978.

Publication Date

14 October 2020

PubMed ID

33066609

Department/Unit

  • Physiology and Medical Physics
  • Public Health and Epidemiology

Research Area

  • Cancer

Publisher

MDPI

Version

  • Published Version (Version of Record)

Licence

Exports