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.
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.