Projects per year
Abstract
Predictive tools, utilising biomarkers, aim to objectively assess the potential response to a particular clinical intervention in order to direct treatment. Conventional cancer therapy remains poorly served by predictive biomarkers, despite being the mainstay of treatment for most patients. In contrast, targeted therapy benefits from a clearly defined protein target for potential biomarker assessment.
We discuss potential data sources of predictive biomarkers for conventional and targeted therapy, including patient clinical data and multi-omic biomarkers (genomic, transcriptomic and protein expression). Key examples, either clinically adopted or demonstrating promise for clinical translation, are highlighted. Following this, we provide an outline of potential barriers to predictive biomarker development; broadly discussing themes of approaches to translational research and study/trial design, and the impact of cellular and molecular tumor heterogeneity. Future avenues of research are also highlighted.
We discuss potential data sources of predictive biomarkers for conventional and targeted therapy, including patient clinical data and multi-omic biomarkers (genomic, transcriptomic and protein expression). Key examples, either clinically adopted or demonstrating promise for clinical translation, are highlighted. Following this, we provide an outline of potential barriers to predictive biomarker development; broadly discussing themes of approaches to translational research and study/trial design, and the impact of cellular and molecular tumor heterogeneity. Future avenues of research are also highlighted.
Original language | English |
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Article number | 113854 |
Journal | Advanced Drug Delivery Reviews |
Volume | 176 |
Early online date | 27 Jun 2021 |
DOIs | |
Publication status | Published - Sept 2021 |
Bibliographical note
Funding Information:We would like to thank Queen Elizabeth Hospital Birmingham Charity and The Get A-head Charitable Trust for their continuous support (grant ID: 16/5/741).
Funding Information:
KP acknowledges funding from CRUK (grant ID: C11497/A28789). We acknowledge funding from Cancer Research UK (grant ID: CRUK/13/026; grant ID: CRUK-A12617) and MRC (grant ID: MR/S005498/1). We would like to thank Queen Elizabeth Hospital Birmingham Charity and The Get A-head Charitable Trust for their continuous support (grant ID: 16/5/741). Professor Mehanna is a National Institute for Health Research (NIHR) Senior Investigator. The views expressed in this article are those of the author(s) and not necessarily those of the NIHR, or the Department of Health and Social Care.
Funding Information:
We acknowledge funding from Cancer Research UK (grant ID: CRUK/13/026; grant ID: CRUK-A12617) and MRC (grant ID: MR/S005498/1).
Funding Information:
KP acknowledges funding from CRUK (grant ID: C11497/A28789).
Keywords
- Intra-tumoral heterogeneity
- Liquid biopsy
- Multi-omics
- Predictive biomarker
- Predictive signature
- Predictive tool
- Treatment response
- Trial design
- Tumor microenvironment
ASJC Scopus subject areas
- Pharmaceutical Science
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The Birmingham CRUK Centre Clinical Academic Training Programme
Middleton, G., Brain, K., Thomas, K., Sundar, S., Harper, L. & Tennant, D.
1/04/19 → 31/03/27
Project: Research
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CRUK/13/026: CompARE: Phase III randomised controlled trial Comparing Alternative Regimens for escalating treatment of intermediate and high-risk oropharyngeal cancer
Gaunt, P., Billingham, L., Mehanna, H. & Bowden, S.
Cancer Research Uk, ASTRA ZENECA UK LIMITED, CITY HOSPITAL NHS TRUST
1/11/14 → 31/12/25
Project: Research
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Validating the PredicTR treatment response classifier for oropharyngeal cancer (PredicTR 2)
Nankivell, P., Deeks, J., Kong, A. & Mehanna, H.
1/03/19 → 30/11/21
Project: Research Councils
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Biomarker Classifiers to Predict Prognosis Following Treatment of Oropharyngeal Carcinoma (PredicTr-OPC)
1/12/12 → 30/11/14
Project: Research