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Anna Malczewska, Kjell E Oberg, and Beata Kos-Kudła

Introduction: The absence of a reliable, universal biomarker is a significant limitation in neuroendocrine neoplasia (NEN) management. We prospectively evaluated two CgA assays, (NEOLISA, EuroDiagnostica,) and (CgA ELISA, Demeditec Diagnostics (DD)) and compared the results to the NETest.

Methods: NEN cohort (n=258): pancreatic, n=67; small intestine, n=40; appendiceal, n=10; rectal, n=45; duodenal, n=9; gastric, n=44; lung, n=43. Image-positive disease (IPD) (n=123), image and histology negative (IND) (n=106), and image negative and histology positive (n=29). CgA metrics: NEOLISA, ULN: 108ng/mL, DD: ULN: 99ng/mL. Data: mean ±SEM. NETest: qRT-PCR - multianalyte analyses, ULN: 20. All samples de-identified and assessed blinded. Statistics: Mann-Whitney U-test, Pearson correlation and McNemar-test.

Results: CgA positive in 53/258 (NEOLISA), 32 (DD) and NETest-positive in 157/258. In image positive disease (IPD, n=123), NEOLISA-positive: 33% and DD: 19%. NETest-positive: 122/123 (99%; McNemar’s Chi2=79-97, p<0.0001). NEOLISA was more accurate than DD (p=0.0003). In image negative disease (IND), CgA was NEOLISA-positive (11%), DD (8%), p=NS, and NETest (33%). CgA assays could not distinguish progressive (PD) from stable disease (SD) or localized from metastatic disease (MD). NETest was significantly higher in PD (47±5) than SD (29±1, p=0.0009). NETest levels in MD (35±2) were elevated versus localized disease (24±1.3, p=0.008).

Conclusions: NETest, a multigenomic mRNA biomarker, was ~99% accurate in the identification of NEN disease. The CgA assays detected NEN disease in 19-33%. Multigenomic blood analysis using NETest is more accurate than CgA and should be considered the biomarker standard of care.

Open access

Anna Malczewska, Magdalena Witkowska, Karolina Makulik, Agnes Bocian, Agata Walter, Joanna Pilch-Kowalczyk, Wojciech Zajęcki, Lisa Bodei, Kjell E Oberg, and Beata Kos-Kudła

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.