Endocrine Abstracts

Background: No effective blood biomarker exists to detect and clinically manage bronchopulmonary (BP) neuroendocrine tumors. We developed a blood-based 51 neuroendocrine tumor (NET)-specific transcript set to diagnose and monitor gastroenteropancreatic NETs. In this study, we examined whether the signature functioned in lung NETs. Thereafter, we examined performance metrics to assess clinical utility. The multianalyte gene signature accurately diagnosed the tumor and in addition differentiated stable from progressive disease as determined by RECIST criteria.

Methodology: Gene expression was evaluated in: i) publicly-available BPNET transcriptomes (GSE35679); ii) two BPNET cell lines; and iii) BPNET tissue with paired blood (n=7). A pilot study assessed blood gene expression in 25 small bowel NETs and 25 BPNETs and a separate validation study in age- and gender-matched BPNETs/controls (n=25 each) was undertaken. Gene expression measured by real-time PCR was scored (0–100%; normal:<14%). Data was assessed by regression analyses, hierarchical clustering, Fisher’s and non-parametric evaluations.

Results: All 51 genes were identified in BPNET transcriptomes, tumor tissues and cell lines. Significant correlations were evident between paired tumor and blood (R²:0.63–0.91, P<0.001). In the pilot study, blood gene expression was highly correlated (R²:0.91, P=1.7×10⁻¹⁵) between small bowel NET and BPNET. In the validation cohort, all 25 BPNETs exhibited a positive score compared to only 20% of controls (P<0.0001). Transcript scores were significantly elevated (P<0.0001) in BPNETs (57±28%) compared to controls (4±5%). BPNETs with progressive disease (85±11%) exhibited higher scores than stable disease (32±7%, P<0.0001).

Conclusion: Blood measurements of NET-specific genes accurately diagnosed bronchopulmonary carcinoids and distinguished stable from progressive disease. We envisage this marker panel to have clinical utility as a liquid biopsy able to identify disease and monitor progression in real-time.