Research Papers:
Folic-acid metabolism and DNA-repair phenotypes differ between neuroendocrine lung tumors and associate with aggressive subtypes, therapy resistance and outcome
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Abstract
Robert Fred Henry Walter1,2,*, Fabian Dominik Mairinger2,3,*, Robert Werner4, Claudia Vollbrecht3, Thomas Hager2, Kurt Werner Schmid2, Jeremias Wohlschlaeger2,5, Daniel Christian Christoph6
1Ruhrlandklinik Essen, West German Lung Centre, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
2Institute of Pathology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
3Institute of Pathology, Division of Molecular Pathology, Charité, Berlin, Germany
4Department of Pathology, Helios Klinikum Emil von Behring, Berlin, Germany
5Institute of Pathology, Ev.-Luth. Diakonissenkrankenhaus Flensburg, Flensburg, Germany
6Department of Medical Oncology, West German Cancer Centre, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
*These authors have contributed equally to this work
Correspondence to:
Robert Fred Henry Walter, e-mail: [email protected]
Keywords: lung cancer, neuroendocrine pulmonary tumors, folic acid metabolism, DNA repair, NanoString nCounter
Received: January 29, 2016 Accepted: January 30, 2016 Published: February 26, 2016
ABSTRACT
Purpose: 25% of all lung cancer cases are neuroendocrine (NELC) including typical (TC) and atypical carcinoid (AC), large-cell neuroendocrine (LCNEC) and small cell lung cancer (SCLC). Prognostic and predictive biomarkers are lacking.
Experimental Design: Sixty patients were used for nCounter mRNA expression analysis of the folic-acid metabolism (ATIC, DHFR, FOLR1, FPGS, GART, GGT1, SLC19A1, TYMS) and DNA-repair (ERCC1, MLH1, MSH2, MSH6, XRCC1). Phenotypic classification classified tumors (either below or above the median expression level) with respect to the folic acid metabolism or DNA repair.
Results: Expression of FOLR1, FPGS, MLH1 and TYMS (each p<0.0001) differed significantly between all four tumor types. FOLR1 and FPGS associated with tumor differentiation (both p<0.0001), spread to regional lymph nodes (FOLR1 p=0.0001 and FPGS p=0.0038), OS and PFS (FOLR1 p<0.0050 for both and FPGS p<0.0004 for OS).
Phenotypic sorting revealed the Ft-phenotype to be the most prominent expression profile in carcinoids, whereas SCLC presented nearly univocal with the fT and LCNEC with fT or ft. These results were significant for tumor subtype (p<0.0001).
Conclusions: The assessed biomarkers and phenotypes allow for risk stratification (OS, PFS), diagnostic classification and enhance the biological understanding of the different subtypes of neuroendocrine tumors revealing potential new therapy options and clarifying known resistance mechanisms.
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