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Updated: May 1, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Profiling cancer gene mutations in clinical formalin-fixed, paraffin-embedded colorectal tumor specimens using
Liangxuan Zhang1, Liangjing Chen, Sachin Sah
1Departments of Oncology Biomarker Development, Biostatistics, and Pathology, Genentech Inc., South San Francisco, California, USA; Technology Development, Asuragen Inc., Austin, Texas, USA.
Purpose:
The success of precision oncology relies on accurate and sensitive molecular profiling. The Ion AmpliSeq Cancer Panel, a targeted enrichment method for next-generation sequencing (NGS) using the Ion Torrent platform, provides a fast, easy, and cost-effective sequencing workflow for detecting genomic "hotspot" regions that are frequently mutated in human cancer genes. Most recently, the U.K. has launched the AmpliSeq sequencing test in its National Health Service. This study aimed to evaluate the clinical application of the AmpliSeq methodology.
Methods:
We used 10 ng of genomic DNA from formalin-fixed, paraffin-embedded human colorectal cancer (CRC) tumor specimens to sequence 46 cancer genes using the AmpliSeq platform. In a validation study, we developed an orthogonal NGS-based resequencing approach (SimpliSeq) to assess the AmpliSeq variant calls.
Results:
Validated mutational analyses revealed that AmpliSeq was effective in profiling gene mutations, and that the method correctly pinpointed "true-positive" gene mutations with variant frequency >5% and demonstrated high-level molecular heterogeneity in CRC. However, AmpliSeq enrichment and NGS also produced several recurrent "false-positive" calls in clinically druggable oncogenes such as PIK3CA.
Conclusion:
AmpliSeq provided highly sensitive and quantitative mutation detection for most of the genes on its cancer panel using limited DNA quantities from formalin-fixed, paraffin-embedded samples. For those genes with recurrent "false-positive" variant calls, caution should be used in data interpretation, and orthogonal verification of mutations is recommended for clinical decision making.
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