Patterns and predictors of pancreatic neuroendocrine tumor prognosis: Are no two leaves alike?

Preoperative prediction of pancreatic neuroendocrine tumor grade based on 68Ga-DOTATATE PET/CT

OBJECTIVE

To establish a prediction model for preoperatively predicting grade 1 and grade 2/3 tumors in patients with pancreatic neuroendocrine tumors (PNETs) based on 68Ga-DOTATATE PET/CT.

METHODS

Clinical data of 41 patients with PNETs were included in this study. According to the pathological results, they were divided into grade 1 and grade 2/3. 68Ga-DOTATATE PET/CT images were collected within one month before surgery. The clinical risk factors and significant radiological features were filtered, and a clinical predictive model based on these clinical and radiological features was established. 3D slicer was used to extracted 107 radiomic features from the region of interest (ROI) of 68Ga-dotata PET/CT images. The Pearson correlation coefficient (PCC), recursive feature elimination (REF) based five-fold cross validation were adopted for the radiomic feature selection, and a radiomic score was computed subsequently. The comprehensive model combining the clinical risk factors and the rad-score was established as well as the nomogram. The performance of above clinical model and comprehensive model were evaluated and compared.

RESULTS

Adjacent organ invasion, N staging, and M staging were the risk factors for PNET grading (p < 0.05). 12 optimal radiomic features (3 PET radiomic features, 9 CT radiomic features) were screen out. The clinical predictive model achieved an area under the curve (AUC) of 0.785. The comprehensive model has better predictive performance (AUC = 0.953).

CONCLUSION

We proposed a comprehensive nomogram model based on 68Ga-DOTATATE PET/CT to predict grade 1 and grade 2/3 of PNETs and assist personalized clinical diagnosis and treatment plans for patients with PNETs.

A Lymph Node Ratio Model for Prognosis of Patients with Pancreatic Neuroendocrine Tumors

The objective of this study was to determine the prognostic value of lymph node (LN) involvement and the LN ratio (LNR) and their effect on recurrence rates and survival in patients with pancreatic neuroendocrine tumors (PNETs) undergoing surgery. This single-center retrospective study reviewed the medical records of 95 consecutive patients diagnosed with PNETs who underwent surgery at our medical center between 1997 and 2017. The retrieved information included patient demographics, pathology reports, treatments, and oncological outcomes. Results: 95 consecutive potentially suitable patients were identified. The 78 patients with PNETs who underwent surgery and for whom there was adequate data were included in the analysis. Their mean ± standard deviation age at diagnosis was 57.4 ± 13.4 years (range 20-82), and there were 50 males (64%) and 28 females (36%). 23 patients (30%) had LN metastases (N1). The 2.5- and 5-year disease-free survival (DFS) rates for the entire cohort were 79.5% and 71.8%, respectively, and their 2- and 5-year overall survival (OS) rates were 85.9% and 82.1%, respectively. The optimal value of the LNR was 0.1603, which correlated with the outcome (2-year OS p = 0.002 HR = 13.4 and 5-year DFS p = 0.016 HR = 7.2, respectively, and 5-year OS and 5-year DFS p = 0.004 HR = 9 and p = 0.001 HR = 10.6, respectively). However, the multivariate analysis failed to show that the LNR was an independent prognostic factor in PNETs. Patients with PNETs grade and stage are known key prognostic factors influencing OS and DFS. According to our results, LNR failed to be an independent prognostic factor.

MEN1 promotes ferroptosis by inhibiting mTOR-SCD1 axis in pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumor (pNET) is the second most common malignant tumors of the pancreas. Multiple endocrine neoplasia 1 ( MEN1) is the most frequently mutated gene in pNETs and MEN1-encoded protein, menin, is a scaffold protein that interacts with transcription factors and chromatin-modifying proteins to regulate various signaling pathways. However, the role of MEN1 in lipid metabolism has not been studied in pNETs. In this study, we perform targeted metabolomics analysis and find that MEN1 promotes the generation and oxidation of polyunsaturated fat acids (PUFAs). Meanwhile lipid peroxidation is a hallmark of ferroptosis, and we confirm that MEN1 promotes ferroptosis by inhibiting the activation of mTOR signaling which is the central hub of metabolism. We show that stearoyl-coA desaturase (SCD1) is the downstream of MEN1-mTOR signaling and oleic acid (OA), a metabolite of SCD1, recues the lipid peroxidation caused by MEN1 overexpression. The negative correlation between MEN1 and SCD1 is further verified in clinical specimens. Furthermore, we find that BON-1 and QGP-1 cells with MEN1 overexpression are more sensitive to everolimus, a widely used drug in pNETs that targets mTOR signaling. In addition, combined use everolimus with ferroptosis inducer, RSL3, possesses a more powerful ability to kill cells, which may provide a new strategy for the comprehensive therapy of pNETs.