TY - JOUR T1 - An miRNA Signature Predicts Grading of Pancreatic Neuroendocrine Neoplasms JF - Cancer Genomics - Proteomics JO - Cancer Genomics Proteomics SP - 154 LP - 164 DO - 10.21873/cgp.20370 VL - 20 IS - 2 AU - JAMES SALLER AU - DALEY WHITE AU - BROOKE HOUGH AU - SEAN YODER AU - JUNMIN WHITING AU - DUNG-TSA CHEN AU - ANTHONY MAGLIOCCO AU - DOMENICO COPPOLA Y1 - 2023/03/01 UR - http://cgp.iiarjournals.org/content/20/2/154.abstract N2 - Background/Aim: Grading pancreatic neuroendocrine neoplasms (PNENs) via mitotic rate and Ki-67 index score is complicated by interobserver variability. Differentially expressed miRNAs (DEMs) are useful for predicting tumour progression and may be useful for grading. Patients and Methods: Twelve PNENs were selected. Four patients had grade (G) 1 pancreatic neuroendocrine tumours (PNETs); 4 had G2 PNETs; and 4 had G3 PNENs (2 PNETs and 2 pancreatic neuroendocrine carcinomas). Samples were profiled using the miRNA NanoString Assay. Results: There were 6 statistically significant DEMs between different grades of PNENs. MiR1285-5p was the sole miRNA differentially expressed (p=0.03) between G1 and G2 PNETs. Six statistically significant DEMs (miR135a-5p, miR200a-3p, miR3151-5p, miR-345-5p, miR548d-5p and miR9-5p) (p<0.05) were identified between G1 PNETs and G3 PNENs. Finally, 5 DEMs (miR155-5p, miR15b-5p, miR222-3p, miR548d-5p and miR9-5p) (p<0.05) were identified between G2 PNETs and G3 PNENs. Conclusion: The identified miRNA candidates are concordant with their patterns of dysregulation in other tumour types. The reliability of these DEMs as discriminators of PNEN grades support further investigations using larger patient populations. ER -