ABSTRACT: Characterization of mRNA and microRNA expression profiles in solid-pseudopapillary neoplasm of pancreas, ductal adenocarcinoma and pancreatic neuroendocrine tumors
Project description:Solid-pseudopapillary neoplasm of pancreas(SPN), ductal adenocarcinoma(PCA), neuroendocrine tumor(NET) and non-neoplastic pancreas. To investigate the specific gene expression of SPN compared to other types of pancreatic tumor, we analyzed large-scale gene expressioin analysis to identify the molecular signature that may affect SPN tumorigenesis. Differentially expressed genes were analyzed on SPNs, PCAs, NETs and Non-neoplastic tissues. Solid-pseudopapillary neoplasm (SPN) is an uncommon pancreatic tumor with distinct clinicopathologic features. SPNs are characterized by mutations in exon 3 of CTNNB1. However, little is known about the gene and microRNA expression profiles of SPNs. Thus, we sought to characterize SPN-specific gene expression and identify the signaling pathways activated in these tumors. The mRNA expression profile of 14 SPNs, 6 pancreatic adenocarcinomas (PCAs), 6 pancreatic neuroendocrine tumors (NETs), and five non-neoplastic pancreatic tissues were analyzed.
Project description:Solid-pseudopapillary neoplasm of pancreas (SPN), ductal adenocarcinoma (PCA), neuroendocrine tumor (NET) and non-neoplastic pancreas. comparison with gene expression of tumors and non-tumors To investigate the specific microRNA expression of SPN compared to other types of pancreatic tumor, we analyzed large-scale microRNA expressioin analysis to identify the molecular signature that may affect SPN tumorigenesis with mRNA expression profiles. Differentially expressed microRNAs were analyzed on SPNs, PCAs, NETs and Non-neoplastic tissues.
Project description:Solid-pseudopapillary neoplasm of pancreas (SPN), ductal adenocarcinoma (PCA), neuroendocrine tumor (NET) and non-neoplastic pancreas. comparison with gene expression of tumors and non-tumors
Project description:Solid-pseudopapillary neoplasm of pancreas(SPN), ductal adenocarcinoma(PCA), neuroendocrine tumor(NET) and non-neoplastic pancreas. To investigate the specific gene expression of SPN compared to other types of pancreatic tumor, we analyzed large-scale gene expressioin analysis to identify the molecular signature that may affect SPN tumorigenesis. Differentially expressed genes were analyzed on SPNs, PCAs, NETs and Non-neoplastic tissues.
Project description:To characterize pancreatic solid pseudopapillary neoplasm at protein level, we performed mass spectromery-based proteome analysis using clinical FFPE tissue samples.
Project description:MicroRNA (miRNA) expression profiles have been described in pancreatic ductal adenocarcinoma (PDAC), but these have not been compared with premalignant lesions. We wished to identify miRNA expression profiles in pancreatic cystic tumors with low malignant potential (serous microcystic adenomas) and high malignant potential (mucinous cystadenoma and intraductal papillary mucinous neoplasm (IPMN)) and compare these to PDAC and carcinoma-ex-IPMN (CEI). n= 20 samples Benign Pancreatic Cystic Tumour (n=7 Microcystic, n= 6 Mucinous, n= 7 IPMN) were compared with n= 9 samples of carcinoma ex IPMN and n= 14 samples of pancreatic cancer (adenocarcinoma) for known homo sapiens miRNAs (mirbase 13).
Project description:Serous (cystic) neoplasm (SCN) of the pancreas is usually benign cystic neoplasm and has unique biological characteristics that are different from those found in the normal pancreatic tissue or pancreatic ductal adenocarcinoma (PDAC) tissue. In order to investigate molecular mechanisms involved in the unique biological phenotypes of, we compared gene expression profiles of SCN tissues with those of normal pancreatic tissues or those of PDAC tissues.
Project description:MicroRNA (miRNA) expression profiles have been described in pancreatic ductal adenocarcinoma (PDAC), but these have not been compared with premalignant lesions. We wished to identify miRNA expression profiles in pancreatic cystic tumors with low malignant potential (serous microcystic adenomas) and high malignant potential (mucinous cystadenoma and intraductal papillary mucinous neoplasm (IPMN)) and compare these to PDAC and carcinoma-ex-IPMN (CEI).
Project description: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 2578 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 versus 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.