NETest liquid biopsy is diagnostic of small intestine and pancreatic neuroendocrine tumors and correlates with imaging

in Endocrine Connections
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  • 1 A Malczewska, Department of Endocrinology and Neuroendocrine Tumors, Department of Pathophysiology and Endocrinology, Medical University of Silesia, Katowice, Poland
  • 2 M Witkowska, Department of Endocrinology and Neuroendocrine Tumors, Department of Pathophysiology and Endocrinology, Katowice, Poland
  • 3 K Makulik, Department of Endocrinology and Neuroendocrine Tumors, Department of Pathophysiology and Endocrinology, Medical University of Silesia, Katowice, Poland
  • 4 A Bocian, Department of Endocrinology and Neuroendocrine Tumors, Department of Pathophysiology and Endocrinology, Medical University of Silesia, Katowice, Poland
  • 5 A Walter, Department of Endocrinology and Neuroendocrine Tumors, Department of Pathophysiology and Endocrinology, Medical University of Silesia, Katowice, Poland
  • 6 J Pilch-Kowalczyk, Department of Radiology and Nuclear Medicine, Medical University of Silesia, Katowice, Poland
  • 7 W Zajęcki, Department of Pathology, Medical University of Silesia, Zabrze, Poland
  • 8 L Bodei, Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, United States
  • 9 K Oberg, Department of Endocrine Oncology, University Hospital, Uppsala, Sweden
  • 10 B Kos-Kudła, Department of Endocrinology and Neuroendocrine Tumors, Department of Pathophysiology and Endocrinology, Medical University of Silesia, Katowice, Poland

Correspondence: Anna Malczewska, Email: malczewska.an@gmail.com

Introduction: Current monoanalyte biomarkers are ineffective in gastroenteropancreatic neuroendocrine tumors (GEP-NETs). NETest, a novel multianalyte signature, provides molecular information relevant to disease biology.

Aim(s): Independently validate NETest to diagnose GEP-NETs and identify progression in a tertiary referral center.

Materials and methods: Cohorts: 67 pancreatic NET (PNETs), 44 small intestine NETs (SINETs), 63 controls. Well-differentiated (WD): PNETs, n=62, SINETs, all (n=44). Disease extent assessment at blood draw: anatomical (n=110)- CT(n=106), MRI(n=7) and/or functional- 68Ga-SSA-PET/CT(n=69) or 18F-FDG-PET/CT (n=8). Image positive disease (IPD) was defined as either CT/MRI or 68Ga-SSA-PET/CT/18F-FDG-PET/CT-positive. Both CT/MRI and 68Ga-SSA-PET/CT-negative in WD-NETs was considered image negative disease (IND). NETest (normal: 20): PCR (spotted plates). Data: mean±SD.

Results: Diagnosis: NETest was significantly increased in NETs (n=111; 26±21) vs. controls (8±4, p<0.0001). 75 (42 PNET, 33 SINET) were image-positive. Eleven (8 PNET, 3 SINET; all WD) were IND. In IPD, NETest was significantly higher (36±22) vs. IND (8±7, p<0.0001). NETest accuracy, sensitivity, specificity: 97%, 99%, 95%.

Concordance with imaging: NETest was 92% (101/110) concordant with anatomical imaging, 94% (65/69) with 68Ga-SSA-PET/CT, 96% (65/68) dual modality (CT/MRI and 68Ga-SSA-PET/CT). In 70 CT/MRI-positive, NETest was elevated in all (37±22). In 40 CT/MRI-negative, NETest was normal (11±10) in 31. In 56 68Ga-SSA-PET/CT-positive, NETest was elevated (36±22) in 55. In 13 68Ga-SSA-PET/CT-negative, NETest was normal (9±8) in 10.

Disease status: NETest was significantly higher in progressive (61±26; n=11) vs. stable disease (29±14; n=64; p<0.0001) (RECIST 1.1).

Conclusion: NETest is an effective diagnostic for PNETs and SINETs. Elevated NETest is as effective as imaging in diagnosis and accurately identifies progression.

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