BackgroundIn pancreatic cancer, methods to predict early recurrence (ER) and identify patients at increased risk of relapse are urgently required.PurposeTo develop a radiomic nomogram based on MR radiomics to stratify patients preoperatively and potentially improve clinical practice.Study TypeRetrospective.PopulationWe enrolled 303 patients from two medical centers. Patients with a disease‐free survival ≤12 months were assigned as the ER group (n = 130). Patients from the first medical center were divided into a training cohort (n = 123) and an internal validation cohort (n = 54). Patients from the second medical center were used as the external independent validation cohort (n = 126).Field Strength/Sequence3.0T axial T1‐weighted (T1‐w), T2‐weighted (T2‐w), contrast‐enhanced T1‐weighted (CET1‐w).AssessmentER was confirmed via imaging studies as MRI or CT. Risk factors, including clinical stage, CA19‐9, and radiomic‐related features of ER were assessed. In addition, to determine the intra‐ and interobserver reproducibility of radiomic features extraction, the intra‐ and interclass correlation coefficients (ICC) were calculated.Statistical TestsThe area under the receiver‐operator characteristic (ROC) curve (AUC) was used to evaluate the predictive accuracy of the radiomic signature in both the training and test groups. The results of decision curve analysis (DCA) indicated that the radiomic nomogram achieved the most net benefit.ResultsThe AUC values of ER evaluation for the radiomics signature were 0.80 (training cohort), 0.81 (internal validation cohort), and 0.78 (external validation cohort). Multivariate logistic analysis identified the radiomic signature, CA19‐9 level, and clinical stage as independent parameters of ER. A radiomic nomogram was then developed incorporating the CA19‐9 level and clinical stage. The AUC values for ER risk evaluation using the radiomic nomogram were 0.87 (training cohort), 0.88 (internal validation cohort), and 0.85 (external validation cohort).Data ConclusionThe radiomic nomogram can effectively evaluate ER risks in patients with resectable pancreatic cancer preoperatively, which could potentially improve treatment strategies and facilitate personalized therapy in pancreatic cancer.Level of Evidence: 4Technical Efficacy: Stage 4J. Magn. Reson. Imaging 2020;52:231–245.

Despite the substantial impact of post-translational modifications on programmed cell death 1 ligand 1 (PD-L1), its importance in therapeutic resistance in pancreatic cancer remains poorly defined. Here, we demonstrate that never in mitosis gene A-related kinase 2 (NEK2) phosphorylates PD-L1 to maintain its stability, causing PD-L1-targeted pancreatic cancer immunotherapy to have poor efficacy. We identify NEK2 as a prognostic factor in immunologically “hot” pancreatic cancer, involved in the onset and development of pancreatic tumors in an immune-dependent manner. NEK2 deficiency results in the suppression of PD-L1 expression and enhancement of lymphocyte infiltration. A NEK binding motif (F/LXXS/T) is identified in the glycosylation-rich region of PD-L1. NEK2 interacts with PD-L1, phosphorylating the T194/T210 residues and preventing ubiquitin-proteasome pathway-mediated degradation of PD-L1 in ER lumen. NEK2 inhibition thereby sensitizes PD-L1 blockade, synergically enhancing the anti-pancreatic cancer immune response. Together, the present study proposes a promising strategy for improving the effectiveness of pancreatic cancer immunotherapy.

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