Micro-RNA Expression Patterns Predict Metastatic Spread in Solid Pseudopapillary Neoplasms of the Pancreas

Solid pseudopapillary neoplasm (SPN) of pancreas is a rare pancreatic neoplasm with a low metastatic potential. Up to 10% of patients with localized disease at presentation will develop systemic metastases, usually in the peritoneum or the liver. Due to the rarity of SPNs and the overall excellent prognosis, reliable prognostic factors to predict malignant biological behavior remain undetermined. Therefore, we aimed to define clinical, histological, and microRNA patterns that are associated with metastatic disease. We conducted a retrospective single center study on all patients operated for SPN of pancreas between 1995 and 2018. Clinical and pathological data were collected, and expression patterns of 2,578 human microRNAs were analyzed using microRNA array (Affimetrix 4.1) in normal pancreases (NPs), localized tumors (LTs), and metastatic tumors (MTs). The diagnosis of SPN was confirmed in 35 patients who included 28 females and 3 males, with a mean age of 33.8 ± 13.9 years. The only clinical factor associated with metastases was tumor size (mean tumor size 5.20 ± 3.78 in LT vs. 8.13± 1.03 in MT, p < 0.012). Microscopic features of malignancy were not associated with metastases, nor were immunohistochemical stains, including the proliferative index KI67. Higher expressions of miR-184, miR-10a, and miR-887, and lower expressions of miR-375, miR-217, and miR-200c were observed in metastatic tissues on microarray, and validated by real-time polymerase chain reaction. Hierarchal clustering demonstrated that the microRNA expression pattern of MTs was significantly different from that of LTs. The only clinical factor associated with metastases of SPN of pancreas was tumor size. Histological features and immunohistological staining were not predictive of metastases. A panel of six microRNAs was differentially expressed in MTs, and these findings could potentially be used to predict tumor behavior. Validation of these results is needed in larger series.