ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Endocrine Abstracts (2017) 52 P02 | DOI: 10.1530/endoabs.52.P02

Validation of a blood biomarker test for the diagnosis and management of bronchopulmonary neuroendocrine tumors

Irvin Modlin1, Mark Kidd2, Anna Lewczuk3, Kjung-Min Chung2, Agnieska Kolasinska-Cwikla4, Jaroslaw Cwikla5, Anna Lowczak5, Anna Doboszynska5, Margot Tesselaar6, Wieneke Buikhuisen6, Anna Malczewska7, Beata Kos-Kudla7, Matteo Roffinella8, Pier Luigi Filosso8, Tiny Korse6, Mauro Papotti8, Lisa Bodei9 & Ignat Drozdov2


1Yale University, New Haven, Connecticut, USA; 2Wren Laboratories, Branford, Connecticut, USA; 3Medical University of Gdansk, Gdansk, Poland; 4Institute of Oncology, Warsaw, Poland; 5University of Warmia and Mazury, Olztyn, Poland; 6Netherlands Cancer Institute, Amsterdam, Netherlands; 7Medical University of Silesia, Katowice, Poland; 8University of Turin, Turin, Italy; 9Memorial Sloan Kettering Cancer Center, New York, New York, USA.


Background: There is currently no effective blood biomarker for lung neuroendocrine neoplasia diagnosis and management. We describe the clinical utility of a 51 neuroendocrine-specific gene expression set in blood to diagnose bronchopulmonary neuroendocrine tumors (BPNETs) and define their clinical status.

Methods: The discovery set included BPNETs (n=154) and controls (n=90), randomly assigned (1:1) to a test and validation set. Specificity was evaluated in: lung adeno (n=54) and squamous cell carcinoma: (n=37), other neuroendocrine neoplasia (n=13), and COPD: (n=18). We assessed clinical efficacy: disease presence versus absence in a surgical cohort (n=45) and progressive versus stable disease (n=154). We measured gene expression (real-time PCR) and chromogranin (ELISA-Euro Diagnostica). Gene expression and CgA levels were evaluated by non-parametric, ROC, Fisher’s test and decision curve analysis.

Findings: Control gene levels were 6±6% and elevated in test (47±3%) and validation (50±3%) cohorts (P<0.0001). Sensitivity and specificities were respectively 94 & 95%; 82 & 93%. The AUC for differentiating carcinoids from controls was 0.98–0.99. Levels were elevated in other lung neuroendocrine neoplasia (59±9%) but were low in non-neuroendocrine lung cancers (23±3%) and COPD (23±0.8%). Progressive disease (n=49) was significantly higher (72±23%; P<0.0001) than stable disease (n=105; 33±17%). The AUC for differentiating progressive/stable was 0.89±0.03. Tumor resection significantly decreased scores (70±7% to 23±3%, P=0.0005). Levels in surgical recurrent or residual disease remained elevated: 66±8%. CgA was elevated in only 38% of carcinoids and levels were unrelated to clinical status (AUC: 0.51±0.05). Decision Curve Analysis confirmed the utility of gene expression analysis (net benefit>75% to a disease risk threshold of 0.92 vs <30% for CgA).

Interpretation: NET-specific gene measurement in blood accurately diagnoses bronchopulmonary carcinoid neoplasia. Gene expression levels identify the effectiveness of surgery and distinguish stable from progressive disease.