Natural History of Pancreatic Cysts

Non-inflammatory pancreatic cysts: from diagnosis to treatment (97 cases series)

OBJECTIVE

to describe the implications of the diagnosis and treatment of non-inflammatory pancreatic cysts in a series of patients.

METHODS

we included patients with pancreatic cysts ≥1.0 cm, excluding those with a presumptive diagnosis of a pseudocyst. Imaging tests, echoendoscopy, and histopathology determined the diagnosis of the type of cyst. We applied the guidelines of the International Association of Pancreatology, with some modifications, in patients with mucinous or indeterminate lesions.

RESULTS

97 adult patients participated in the study. A cystic neoplasm of the pancreas was diagnosed in 82.5% of cases. Diagnosis was mainly made by magnetic resonance (46% of cases). The two most common diagnoses were intraductal papillary mucinous neoplasm (43.3%) and serous cystadenoma (26%). Twenty-nine patients underwent surgery (33.3%). The most common surgical procedure was distal pancreatectomy associated with splenectomy in 19 cases (65.5%). Among the operated patients, 11 were diagnosed with cancer. None of the followed, non-operated patients had a diagnosis of cancer.

CONCLUSIONS

magnetic resonance showed good accuracy, particularly in the diagnosis of intraductal papillary mucinous neoplasm. The guidelines of the International Association of Pancreatology, as applied in this study, showed a negative predictive value for cancer of 100%. A development of better diagnostic tests can reduce the number of unnecessary operations.

Natural history and optimal treatment strategy of intraductal papillary mucinous neoplasm of the pancreas: Analysis using a nomogram and Markov decision model

BACKGROUND/PURPOSE

With the increase in detection of intraductal papillary mucinous neoplasms (IPMN), a tailored approach is needed. This study was aimed at exploring the natural history of IPMN and suggest optimal treatment based on malignancy risk using a nomogram and Markov decision model.

METHODS

Patients with IPMN who underwent surveillance or surgery were included. Changes in worrisome features/high-risk stigmata and malignancy conversion rate were assessed. Life expectancy and quality-adjusted life year (QALY) were compared using a nomogram predicting malignancy.

RESULTS

Overall, 2006 patients with histologically confirmed or radiologically typical IPMN were enrolled. Of these, 1773 (88.4%), 81 (4.0%), and 152 (7.6%), respectively, had branch duct (BD)-, main duct-, and mixed-type IPMN at initial diagnosis. The cumulative risk of developing worrisome feature or high-risk stigmata was 19.0% and 35.0% at 5- and 10-year follow-up, respectively. The progression of malignancy rate at 10-year follow-up was 79.9% for main and mixed IPMNs and 5.9% for BD-IPMN. Nomogram-based malignancy risk prediction is well correlated with natural history based on pathologic biopsy and shows good stratification of survival. The decision model recommends surgery to maximize survival and QALY especially in those with >35% malignancy risk.

CONCLUSIONS

Compared with main duct- and mixed-type IPMN, which have a high risk of malignancy (79.9%), BD-IPMN is very indolent (5.9%). The nomogram-based decision model suggests surgery rather than surveillance for patients with a high malignancy risk. The optimal treatment strategy between surgery and surveillance should consider patients' health status, malignancy risk, and centers' experience.

Identification of Prognostic Biomarkers by Combined mRNA and miRNA Expression Microarray Analysis in Pancreatic Cancer

Pancreatic cancer is the fourth leading cause for cancer-related death, and early diagnosis is one key to improve the survival rate of this disease. Molecular biomarkers are an important method for diagnostic use in pancreatic cancer. We used data from three mRNA microarray datasets and a microRNA dataset (GSE16515, GSE15471, GSE28735, and GSE41372) to identify potential key genes. Differentially expressed genes (DEGs) and microRNAs (DEMs) were identified. Functional, pathway enrichment, and protein-protein interaction analyses were performed on common DEGs across all datasets. The target genes of the DEMs were identified. DEMs targets that were also DEGs were further scrutinized using overall survival analysis. A total of 236 DEGs and 21 DEMs were identified. There were a total of four DEGs (ECT2, NR5A2, NRP2, and TGFBI), which were also predicted target genes of DEMs. Overall survival analysis showed that high expression levels of three of these genes (ECT2, NRP2, and TGFBI) were associated with poor overall survival for pancreatic cancer patients. The basic expression of DEGs in pancreas stood lower level in various organ tissues. The expression of ECT2 and NRP2 was higher in different pancreatic cancer cell lines than normal pancreas cell line. Knockout of ECT2 by Crispr Cas9 gene editing system decreased proliferation and migration ability in pancreatic cancer cell line MiaPaCa2. In conclusion, we think that data mining method can do well in biomarker screening, and ECT2 and NRP2 can play as potential biomarker or therapy target by Crispr Cas9 in pancreatic cancer.