Related Experiment Video
Updated: Oct 31, 2025
Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
Published on: December 9, 2015
Lack of predictive tools for conventional and targeted cancer therapy: Barriers to biomarker development and clinical
Nikolaos Batis1, Jill M Brooks1, Karl Payne1
1Institute of Head and Neck Studies and Education (InHANSE), Institute of Cancer and Genomic Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham, United Kingdom.
Abstract:
Predictive tools, utilising biomarkers, aim to objectively assessthe potentialresponse toa 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 andmulti-omicbiomarkers (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.
Insights
Predictive biomarkers are crucial for guiding cancer treatment. This study explores data sources, challenges, and future directions for developing these essential tools in both conventional and targeted cancer therapies.
Area of Science:
- Oncology
- Biomarker Research
- Translational Medicine
Background:
- Conventional cancer therapies lack robust predictive biomarkers.
- Targeted therapies show promise with specific protein targets for biomarker assessment.
- Biomarkers are essential for directing personalized cancer treatment strategies.
Purpose of the Study:
- To explore potential data sources for predictive biomarkers in cancer therapy.
- To highlight key examples of biomarkers in clinical use or translation.
- To outline barriers and future research directions in predictive biomarker development.
Main Methods:
- Discussion of patient clinical data as a biomarker source.
- Exploration of multi-omic biomarkers (genomic, transcriptomic, protein expression).
- Review of clinically adopted and promising biomarkers for translation.
Main Results:
- Identified patient clinical data and multi-omic data as key sources for predictive biomarkers.
- Highlighted successful examples of predictive biomarkers in oncology.
- Outlined challenges including translational research, study design, and tumor heterogeneity.
Conclusions:
- Predictive biomarker development is critical for advancing cancer treatment.
- Addressing translational research, trial design, and tumor heterogeneity is key.
- Further research is needed to overcome barriers and realize the full potential of predictive biomarkers.
More Related Videos
07:59Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
Published on: September 8, 2023
10:46A Flow Cytometry-Based Cell Surface Protein Binding Assay for Assessing Selectivity and Specificity of an Anticancer Aptamer
Published on: September 13, 2022
Related Concept Videos
02:57Targeted Cancer Therapies
There are several types of targeted therapies against...
02:50Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...