Lack of predictive tools for conventional and targeted cancer therapy: barriers to biomarker development and clinical translation

Nikos Batis; Jill Brooks; Karl Payne; Neil Sharma; Paul Nankivell; Hisham Mehanna

doi:10.1016/j.addr.2021.113854

Lack of predictive tools for conventional and targeted cancer therapy: barriers to biomarker development and clinical translation

Nikos Batis, Jill Brooks, Karl Payne, Neil Sharma, Paul Nankivell, Hisham Mehanna

Research output: Contribution to journal › Article › peer-review

134 Downloads (Pure)

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.

Original language	English
Article number	113854
Journal	Advanced Drug Delivery Reviews
Volume	176
Early online date	27 Jun 2021
DOIs	https://doi.org/10.1016/j.addr.2021.113854
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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.addr.2021.113854Licence: Creative Commons: Attribution (CC BY)

1-s2.0-S0169409X21002465-mainFinal published version, 776 KBLicence: Creative Commons: Attribution (CC BY)

2 Finished
3 Active

The Birmingham CRUK Centre Clinical Academic Training Programme
Middleton, G., Brain, K., Thomas, K., Sundar, S., Harper, L. & Tennant, D.
Cancer Research Uk
1/04/19 → 31/03/27
Project: Research
CRUK/13/026 CompARE Collect: Prospective biological sample collection from patients with intermediate and high risk oropharyngeal cancer recruited to comPARE randomised controlled trial
Batis, N., Nankivell, P., Spruce, R. & Mehanna, H.
Cancer Research Uk
1/08/17 → 31/07/24
Project: Research
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
Validating the PredicTR treatment response classifier for oropharyngeal cancer (PredicTR 2)
Nankivell, P., Deeks, J., Kong, A. & Mehanna, H.
Medical Research Council
1/03/19 → 30/11/21
Project: Research Councils
Biomarker Classifiers to Predict Prognosis Following Treatment of Oropharyngeal Carcinoma (PredicTr-OPC)
Mehanna, H.
Cancer Research UK
1/12/12 → 30/11/14
Project: Research

Cite this

@article{b6e7f4fd560a4493842c0bbf8ba8bc92,

title = "Lack of predictive tools for conventional and targeted cancer therapy: barriers to biomarker development and clinical translation",

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.",

keywords = "Intra-tumoral heterogeneity, Liquid biopsy, Multi-omics, Predictive biomarker, Predictive signature, Predictive tool, Treatment response, Trial design, Tumor microenvironment",

author = "Nikos Batis and Jill Brooks and Karl Payne and Neil Sharma and Paul Nankivell and Hisham Mehanna",

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).",

year = "2021",

month = sep,

doi = "10.1016/j.addr.2021.113854",

language = "English",

volume = "176",

journal = "Advanced Drug Delivery Reviews",

issn = "0169-409X",

publisher = "Elsevier",

}

TY - JOUR

T1 - Lack of predictive tools for conventional and targeted cancer therapy

T2 - barriers to biomarker development and clinical translation

AU - Batis, Nikos

AU - Brooks, Jill

AU - Payne, Karl

AU - Sharma, Neil

AU - Nankivell, Paul

AU - Mehanna, Hisham

N1 - 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).

PY - 2021/9

Y1 - 2021/9

N2 - 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.

AB - 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.

KW - Intra-tumoral heterogeneity

KW - Liquid biopsy

KW - Multi-omics

KW - Predictive biomarker

KW - Predictive signature

KW - Predictive tool

KW - Treatment response

KW - Trial design

KW - Tumor microenvironment

UR - http://www.scopus.com/inward/record.url?scp=85110550875&partnerID=8YFLogxK

U2 - 10.1016/j.addr.2021.113854

DO - 10.1016/j.addr.2021.113854

M3 - Article

C2 - 34192550

SN - 0169-409X

VL - 176

JO - Advanced Drug Delivery Reviews

JF - Advanced Drug Delivery Reviews

M1 - 113854

ER -

Lack of predictive tools for conventional and targeted cancer therapy: barriers to biomarker development and clinical translation

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Projects

The Birmingham CRUK Centre Clinical Academic Training Programme

CRUK/13/026 CompARE Collect: Prospective biological sample collection from patients with intermediate and high risk oropharyngeal cancer recruited to comPARE randomised controlled trial

CRUK/13/026: CompARE: Phase III randomised controlled trial Comparing Alternative Regimens for escalating treatment of intermediate and high-risk oropharyngeal cancer

Validating the PredicTR treatment response classifier for oropharyngeal cancer (PredicTR 2)

Biomarker Classifiers to Predict Prognosis Following Treatment of Oropharyngeal Carcinoma (PredicTr-OPC)

Cite this