UKINETS2017 Poster Presentations (1) (40 abstracts)
Validation of a blood biomarker test for the diagnosis and management of bronchopulmonary neuroendocrine tumors
Irvin Modlin 1 , Mark Kidd 2 , Anna Lewczuk 3 , Kjung-Min Chung 2 , Agnieska Kolasinska-Cwikla 4 , Jaroslaw Cwikla 5 , Anna Lowczak 5 , Anna Doboszynska 5 , Margot Tesselaar 6 , Wieneke Buikhuisen 6 , Anna Malczewska 7 , Beata Kos-Kudla 7 , Matteo Roffinella 8 , Pier Luigi Filosso 8 , Tiny Korse 6 , Mauro Papotti 8 , Lisa Bodei 9 & Ignat Drozdov 2
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.
Article tools
My recent searches
My recently viewed abstracts
Authors
Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
© Bioscientifica 2024 |
Privacy policy |
Cookie settings
BiosciAbstracts
Bioscientifica Abstracts is the gateway to a series of products that provide a permanent, citable record of abstracts for biomedical and life science conferences.
Find out more