EGFR and KRAS quality assurance schemes in pathology: generating normative data for molecular predictive marker analysis in targeted therapy.

Thunnissen E, Bovée JV, Bruinsma H, van den Brule AJ, Dinjens W, Heideman DA, Meulemans E, Nederlof P, van Noesel C, Prinsen CF, Scheidel K, van de Ven PM, de Weger R, Schuuring E, Ligtenberg M.

Source

Department of Pathology, Vrije Universteit Medical Centre, Amsterdam, The Netherlands. e.thunnissen@vumc.nl

Abstract

INTRODUCTION:

The aim of this study was to compare the reproducibility of epidermal growth factor receptor (EGFR) immunohistochemistry (IHC), EGFR gene amplification analysis, and EGFR and KRAS mutation analysis among different laboratories performing routine diagnostic analyses in pathology in The Netherlands, and to generate normative data.

METHODS:

In 2008, IHC, in-situ hybridisation (ISH) for EGFR, and mutation analysis for EGFR and KRAS were tested. Tissue microarray sections were distributed for IHC and ISH, and tissue sections and isolated DNA with known mutations were distributed for mutation analysis. In 2009, ISH and mutation analysis were evaluated. False-negative and false-positive results were defined as different from the consensus, and sensitivity and specificity were estimated.

RESULTS:

In 2008, eight laboratories participated in the IHC ring study. In only 4/17 cases (23%) a consensus score of ≥75% was reached, indicating that this analysis was not sufficiently reliable to be applied in clinical practice. For EGFR ISH, and EGFR and KRAS mutation analysis, an interpretable result (success rate) was obtained in ≥97% of the cases, with mean sensitivity ≥96% and specificity ≥95%. For small sample proficiency testing, a norm was established defining outlier laboratories with unsatisfactory performance.

CONCLUSIONS:

The result of EGFR IHC is not a suitable criterion for reliably selecting patients for anti-EGFR treatment. In contrast, molecular diagnostic methods for EGFR and KRAS mutation detection and EGFR ISH may be reliably performed with high accuracy, allowing treatment decisions for lung cancer.