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Updated: Jan 30, 2026

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
Published on: February 27, 2015
Clinical Validation of Targeted Solid Tumor Profiling
1Laboratory for Molecular Diagnostics, Department of Clinical Biology, Jessa Hospital, Hasselt, Belgium. guy.froyen@jessazh.be.
Abstract:
Large-scale tumor profiling studies have generated massive amounts of data that have been instrumental for the detection of recurrent driver mutations in many tumor types. These driver mutations as well as the concurrent passenger mutations are now being used for a more accurate diagnosis of the tumor and prognosis for the patient. Moreover, therapeutic inhibitors toward specific mutations are already on the market and many clinical trials are ongoing to approve novel therapeutic drugs. The broad-range identification of these somatic mutations is key to this tailored personalized medicine approach, which preferentially has to be performed by a multigene multihotspot method such as massive parallel sequencing, also called next generation sequencing (NGS). The implementation of NGS in molecular diagnostics of tumor profiling however, requires a firm validation to minimize the occurrence of false positives and false negatives, thereby yielding highly accurate and robust clinical data.Here, we describe the different performance characteristics as well as quality metrics that should be analyzed for the robust diagnostic validation of tumor profiling in order to meet the requirements of international standards specific for medical laboratories, such as the ISO15189:2012 standard. These metrics include assays that assess the precision, limit of detection, accuracy, sensitivity, specificity, and robustness of the entire workflow from DNA enrichment up to the final report.
Insights
Next-generation sequencing (NGS) enables precise tumor profiling for personalized medicine. Robust validation of NGS methods is crucial for accurate cancer diagnosis and treatment, ensuring reliable clinical data.
Area of Science:
- Oncology
- Genomics
- Molecular Diagnostics
Background:
- Large-scale tumor profiling generates vast data, identifying driver and passenger mutations.
- Somatic mutations are vital for accurate tumor diagnosis, prognosis, and targeted therapies.
- Personalized medicine relies on broad somatic mutation identification via next-generation sequencing (NGS).
Purpose of the Study:
- To describe performance characteristics and quality metrics for diagnostic validation of tumor profiling.
- To ensure NGS implementation in molecular diagnostics meets international medical laboratory standards (e.g., ISO15189:2012).
- To minimize false positives and negatives for highly accurate and robust clinical data.
Main Methods:
- Analysis of performance characteristics and quality metrics for the entire NGS workflow.
- Implementation of assays to assess precision, limit of detection, accuracy, sensitivity, specificity, and robustness.
- Validation aligned with international standards for medical laboratories.
Main Results:
- Detailed description of essential metrics for robust diagnostic validation of tumor profiling.
- Established quality metrics cover the complete workflow from DNA enrichment to final reporting.
- Validation approach ensures adherence to stringent international standards.
Conclusions:
- Robust validation of NGS-based tumor profiling is essential for reliable molecular diagnostics.
- Defined performance characteristics and quality metrics ensure accuracy and robustness in clinical data.
- Adherence to standards like ISO15189:2012 is critical for clinical implementation of NGS in oncology.
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