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Virchows Arch. 2012 Dec;461(6):629-38. doi: 10.1007/s00428-012-1324-x. Epub 2012 Oct 12.

Correlation of immunohistochemical staining p63 and TTF-1 with EGFR and K-ras mutational spectrum and diagnostic reproducibility in non small cell lung carcinoma.

Author information

1
Department of Pathology, VU University Medical Center, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands. e.thunnissen@vumc.nl

Abstract

For treatment purposes, distinction between squamous cell carcinoma and adenocarcinoma is important. The aim of this study is to examine the diagnostic accuracy on lung cancer small biopsies for the distinction between adenocarcinoma and squamous cell carcinoma and relate these to immunohistochemical and KRAS and EGFR mutation analysis. An interobserver study was performed on 110 prospectively collected biopsies obtained by bronchoscopy or transthoracic needle biopsy of patients with non-small cell lung cancer. The diagnosis was correlated with immunohistochemical (IHC) analysis for markers of adeno- (TTF1 and/or mucin positivity) and squamous cell differentiation (P63 and CK5/6) as well as KRAS and EGFR mutation analysis. Eleven observers independently read H&E-stained slides of 110 cases, resulting in a kappa value of 0.55 ± 0.10. The diagnosis non-small cell lung cancer not otherwise specified was given on average on 29.5 % of the biopsies. A high concordance was observed between hematoxylin-eosin-based consensus diagnosis (≥8/11 readings concordant) and IHC markers. In all cases with EGFR (n = 1) and KRAS (n = 20) mutations, adenodifferentiation as determined by IHC was present and p63 staining was absent. In 2 of 25 cases with a consensus diagnosis of squamous cell carcinoma, additional stainings favored adenodifferentation, and a KRAS mutation was present. P63 is most useful for distinction between EGFR/KRAS mutation positive and negative patients. In the diagnostic work-up of non-small cell lung carcinoma the limited reproducibility on small biopsies is optimized with immunohistochemical analysis, resulting in reliable delineation for predictive analysis.

PMID:
23064619
DOI:
10.1007/s00428-012-1324-x
[Indexed for MEDLINE]

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