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Updated: Apr 18, 2026

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
Published on: September 20, 2016
Clinical actionability enhanced through deep targeted sequencing of solid tumors
Ken Chen1, Funda Meric-Bernstam2, Hao Zhao1
1Department of Bioinformatics and Computational Biology and.
Background:
Further advances of targeted cancer therapy require comprehensive in-depth profiling of somatic mutations that are present in subpopulations of tumor cells in a clinical tumor sample. However, it is unclear to what extent such intratumor heterogeneity is present and whether it may affect clinical decision-making. To study this question, we established a deep targeted sequencing platform to identify potentially actionable DNA alterations in tumor samples.
Methods:
We assayed 515 formalin-fixed paraffin-embedded (FFPE) tumor samples and matched germline DNA (475 patients) from 11 disease sites by capturing and sequencing all the exons in 201 cancer-related genes. Mutations, indels, and copy number data were reported.
Results:
We obtained a 1000-fold mean sequencing depth and identified 4794 nonsynonymous mutations in the samples analyzed, of which 15.2% were present at <10% allele frequency. Most of these low level mutations occurred at known oncogenic hotspots and are likely functional. Identifying low level mutations improved identification of mutations in actionable genes in 118 (24.84%) patients, among which 47 (9.8%) otherwise would have been unactionable. In addition, acquiring ultrahigh depth also ensured a low false discovery rate (<2.2%) from FFPE samples.
Conclusions:
Our results were as accurate as a commercially available CLIA-compliant hotspot panel but allowed the detection of a higher number of mutations in actionable genes. Our study reveals the critical importance of acquiring and utilizing high sequencing depth in profiling clinical tumor samples and presents a very useful platform for implementing routine sequencing in a cancer care institution.
Insights
Deep sequencing of tumor samples reveals significant intratumor heterogeneity. Identifying low-frequency somatic mutations improves actionable gene detection, crucial for personalized cancer therapy and clinical decision-making.
Area of Science:
- Oncology
- Genomics
- Cancer Research
Background:
- Accurate cancer therapy relies on comprehensive profiling of somatic mutations within tumor subpopulations.
- Intratumor heterogeneity's extent and clinical impact remain incompletely understood.
- A deep targeted sequencing platform was developed to address these knowledge gaps.
Purpose of the Study:
- To establish and validate a deep targeted sequencing platform for identifying actionable DNA alterations.
- To assess the prevalence and clinical significance of intratumor heterogeneity in cancer samples.
- To evaluate the utility of high-depth sequencing for routine cancer care.
Main Methods:
- Analyzed 515 formalin-fixed paraffin-embedded (FFPE) tumor samples and matched germline DNA from 475 patients across 11 disease sites.
- Employed targeted sequencing of all exons in 201 cancer-related genes with a mean depth of 1000-fold.
- Collected data on mutations, insertions/deletions (indels), and copy number variations.
Main Results:
- Identified 4794 nonsynonymous mutations, with 15.2% at <10% allele frequency, often at oncogenic hotspots.
- Detection of low-frequency mutations identified actionable gene alterations in 24.84% of patients, with 9.8% becoming actionable.
- Ultrahigh sequencing depth ensured a low false discovery rate (<2.2%) in FFPE samples.
Conclusions:
- The developed platform matches the accuracy of commercial hotspot panels but detects more actionable gene mutations.
- High sequencing depth is critical for comprehensive profiling of clinical tumor samples.
- This platform is valuable for implementing routine sequencing in cancer care settings.
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