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Updated: May 27, 2026

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
[Targeted therapy: the benefit of new oncological tests]
Carolien P Schröder1, Karel G M Moons, E G E Liesbeth de Vries
1Universitair Medisch Centrum Groningen, afd. Medische Oncologie, Groningen, the Netherlands. c.p.schroder@umcg.nl
Abstract:
An increasing number of targeted drug treatments are becoming available for many types of cancer. There is a great need for adequate biomarkers that can predict the effect of targeted therapy in individual cancer patients, in order to determine the correct oncological treatment per patient. This way, non-effective treatments can be spared, side-effects avoided, and costs reduced. Oestrogen receptor (ER) and the human epidermal growth factor receptor 2 (HER2) are examples of standardized tests for breast cancer that have been validated in randomised studies. Data from randomised studies is also expected for gene expression profiles that correlate with tumour growth. Quantifying the predictive value of tests for anticipated treatment effects is costly and time-consuming. Given the increasing availability of targeted agents and diagnostic and prognostic techniques, alternative clinical study designs that can lead to quicker and more efficient verification are being sought in many different domains.
Insights
Finding the right cancer treatment is crucial. New biomarkers are needed to predict targeted therapy effectiveness, sparing patients ineffective treatments and reducing costs.
Area of Science:
- Oncology
- Biomarker Discovery
- Clinical Trial Design
Context:
- Targeted cancer therapies are rapidly advancing.
- Predictive biomarkers are essential for personalized oncology to optimize treatment selection.
- Current validation methods for biomarkers are time-consuming and expensive.
Purpose:
- To highlight the need for efficient biomarker validation for targeted cancer therapies.
- To explore alternative clinical study designs for quicker verification of predictive tests.
- To reduce costs and side effects associated with non-effective cancer treatments.
Summary:
- The increasing availability of targeted cancer drugs necessitates reliable biomarkers to predict treatment response in individual patients.
- Standardized tests like oestrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) exist, but new methods are needed for gene expression profiles.
- Efficient validation of predictive biomarkers is critical to spare patients ineffective treatments, avoid side effects, and lower healthcare costs.
Impact:
- Facilitates personalized cancer treatment selection.
- Reduces healthcare expenditure by avoiding non-effective therapies.
- Accelerates the clinical adoption of novel targeted therapies and diagnostic techniques.
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