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Optimized algorithm for Sanger sequencing-based EGFR mutation analyses in NSCLC biopsies

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Abstract

Pulmonary adenocarcinoma patients harboring EGFR mutations can benefit from tyrosine kinase inhibitor therapy. Reliable molecular analyses and precise pathological reporting of the EGFR mutational status are factors essential for patient treatment and outcome. More than 70 % of all EGFR mutation analyses are performed on non-small cell lung cancer (NSCLC) biopsies. However, biopsies may not be sufficient for mutation analysis due to low tumor content and admixture with non-neoplastic cells. To define the minimal concentration of tumor cells required for reliable EGFR mutational diagnostics by Sanger sequencing and to develop an algorithm for routine diagnostics on biopsy material, we determined total numbers of tumor and non-tumor cells, calculated the tumor cell concentration and serially diluted DNA from EGFR-mutated NSCLC by adding DNA of non-tumor cells from the same section. A counted tumor cell concentration of 30 %, which refers to a histologically estimated concentration of 40 %, is necessary for reliable detection of all mutations. Based on these data, we developed an algorithm for evidence-based EGFR mutation analysis by Sanger sequencing in biopsy specimens, which was subsequently applied to 461 diagnostic cases. Optimized diagnostic testing results in 80 % reliable EGFR mutation analyses of biopsy specimens, while in 20 % of cases re-biopsies had to be recommended.

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Acknowledgements

This study was supported by a research grant from Astra Zeneca. We gratefully acknowledge Wilko Weichert and Wilfried Roth for estimating tumor cell concentrations.

Conflict of interest statement

We declare that we have no conflict of interest.

Author information

Author notes

  1. Hendrik Bläker

    Present address: Institute of Pathology, University Hospital Charité, Campus Mitte, Charitéplatz 1, 10117, Berlin, Germany

Authors and Affiliations

  1. Institute of Pathology, University Hospital Heidelberg, Im Neuenheimer Feld 220/221, 69120, Heidelberg, Germany

    Arne Warth, Roland Penzel, Regine Brandt, Peter Schirmacher & Hendrik Bläker

  2. Institute of Pathology, Charité, Berlin, Germany

    Christine Sers, Manfred Dietel & Hendrik Bläker

  3. Department of Thoracic Oncology, Klinik Löwenstein, Löwenstein, Germany

    Jürgen R. Fischer

  4. Department of Thoracic Oncology, Thoraxklinik Heidelberg, Heidelberg, Germany

    Michael Thomas

  5. Department of Pneumology and Critical Care Medicine, Thoraxklinik Heidelberg, Heidelberg, Germany

    Felix J. F. Herth

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  1. Arne Warth
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  2. Roland Penzel
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  4. Christine Sers
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Corresponding author

Correspondence to Hendrik Bläker.

Additional information

Arne Warth and Roland Penzel contributed equally.

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Warth, A., Penzel, R., Brandt, R. et al. Optimized algorithm for Sanger sequencing-based EGFR mutation analyses in NSCLC biopsies. Virchows Arch 460, 407–414 (2012). https://doi.org/10.1007/s00428-012-1219-x

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  • DOI: https://doi.org/10.1007/s00428-012-1219-x

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