Clinical Research Papers:

A liquid biopsy for bronchopulmonary/lung carcinoid diagnosis

Mark Kidd, Irvin M. Modlin _, Ignat Drozdov, Harry Aslanian, Lisa Bodei, Somer Matar and Kyung-Min Chung

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Oncotarget. 2018; 9:7182-7196. https://doi.org/10.18632/oncotarget.23820

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Mark Kidd1, Irvin M. Modlin2, Ignat Drozdov1, Harry Aslanian2, Lisa Bodei3, Somer Matar1 and Kyung-Min Chung1

1Wren Laboratories, Brandford, CT, USA

2Yale University School of Medicine, New Haven, CT, USA

3Memorial Sloan Kettering Cancer Center, New York, NY, USA

Correspondence to:

Irvin M. Modlin, email: [email protected]

Keywords: biomarker; bronchopulmonary; carcinoid; liquid biopsy; lung

Received: September 22, 2017     Accepted: December 15, 2017     Published: December 29, 2017


No effective blood biomarker exists to detect and clinically manage bronchopulmonary (BP) neuroendocrine tumors (NET). We developed a blood-based 51 NET-specific transcript set for diagnosis and monitoring and evaluated clinical performance metrics. It accurately diagnosed the tumor and differentiated stable from progressive disease as determined by RECIST criteria. Gene expression was evaluated in: a) publicly available BPNET transcriptomes (GSE35679); b) two BPNET cell-lines; and c) BPNET tissue with paired blood (n = 7). Blood gene expression was assessed in 194 samples including controls, benign lung diseases, malignant lung diseases and small bowel NETs. A separate validation study in 25 age- and gender-matched BPNETs/controls was performed. Gene expression measured by real-time PCR was scored (0–100%; normal: < 14%). Regression analyses, Principal Component Analysis (PCA), hierarchical clustering, Fisher’s and non-parametric evaluations were undertaken. All 51 genes were identified in BPNET transcriptomes, tumor samples and cell-lines. Significant correlations were evident between paired tumor and blood (R2:0.63–0.91, p < 0.001). PCA and hierarchical clustering identified blood gene expression was significantly different between lung cancers and benign diseases, including BPNETs. Gene expression was highly correlated (R2: 0.91, p = 1.7 x 10-15) between small bowel and BPNET. For validation, all 25 BPNETs were positive compared to 20% controls (p < 0.0001). 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). Blood measurements accurately diagnosed bronchopulmonary carcinoids, distinguishing stable from progressive disease. This marker panel will have clinical utility as a diagnostic liquid biopsy able to define disease activity and progression in real-time.

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