Next-generation sequencing of endoscopic ultrasound guided microbiopsies from pancreatic cystic neoplasms.

AIMS: Interpretation of cytology samples from pancreatic cysts is challenging. A novel microbiopsy forceps used during endoscopic ultrasound examinations offers new opportunities for histological examination of tissue from pancreatic cysts as well as next-generation sequencing. The aim of this study was to analyse the results of next-generation sequencing of microbiopsies from pancreatic cysts. METHODS AND RESULTS: Microbiopsies from 27 patients were obtained, 23 of which were subjected to next-generation sequencing. Sixteen intraductal papillary mucinous neoplasms harboured mutations in genes regulating cell cycle and repair, and three were without mutations. Most frequent mutations were found in the KRAS and GNAS genes, and these were often concomitant. Three serous cystic neoplasms were without mutations, while with regard to histology, a non-diagnostic microbiopsy harboured a KRAS and a TP53 mutation and was deemed malignant after clinical follow-up. Three patients underwent surgery, and the point mutations detected in the microbiopsies were confirmed in the resected specimens. We identified one resected sample with an additional GNAS mutation which was not identified in the microbiopsy. CONCLUSIONS: Next-generation sequencing of microbiopsies may have the potential to improve diagnostic decision-making.

The effect of postoperative gemcitabine on overall survival in patients with resected pancreatic cancer: A nationwide population-based Danish register study.

Background: Adjuvant chemotherapy following curative resection is the standard treatment for pancreatic adenocarcinoma (PC). Randomized clinical trials using gemcitabine have shown a median overall survival (mOS) of 2 years and a 5-year survival rate of 15-20%. However, the effect of gemcitabine outside these trials is less clear. We examined the effect of postoperative gemcitabine on survival in an unselected cohort of patients receiving curative resection for PC in Denmark during a five-year period. Material and methods: From 1 May 2011 to 30 April 2016, 731 patients treated with curative resection were identified in the Danish Pancreatic Cancer Database (DPCD). Thirty patients died within 10 weeks postoperatively; 78 received other regimens or preoperative chemotherapy and were excluded. Of the remaining 623 patients, the chemotherapy (CT) group (n = 409, 66%) received gemcitabine within 10 weeks after resection, whereas the non-chemotherapy (NCT) group (n = 214, 34%) did not receive CT within 10 weeks. Results: CT patients were slightly younger than NCT patients but did not otherwise differ in baseline characteristics. The CT group showed a mOS of 24 months (95% CI; 21-27) and a 5-year survival rate of 22% (95% CI; 17-27); the NCT group had a mOS of 22 months (95% CI; 16-26, p = .27) and a 5-year survival rate of 26% (95% CI; 19-34, p = .66). Most patients (415/623) had lymph node metastases. Of these patients, those in the CT group (n = 280) had significantly longer mOS [20 months (95% CI; 18-24)] than those in the NCT group (n = 135) [14 months (95% CI; 11-17)]. Conclusions: In this national Danish cohort of PC patients undergoing resection between 2011 and 2016, the survival after postoperative gemcitabine was similar to that reported in previous clinical trials. However, the survival advantage of postoperative gemcitabine was limited to patients with lymph node metastases.

A machine learning predictive model for recurrence of resected distal cholangiocarcinoma: Development and validation of predictive model using artificial intelligence.

INTRODUCTION: Distal Cholangiocarcinoma (dCCA) represents a challenge in hepatobiliary oncology, that requires nuanced post-resection prognostic modeling. Conventional staging criteria may oversimplify dCCA complexities, prompting the exploration of novel prognostic factors and methodologies, including machine learning algorithms. This study aims to develop a machine learning predictive model for recurrence after resected dCCA. MATERIAL AND METHODS: This retrospective multicentric observational study included patients with dCCA from 13 international centers who underwent curative pancreaticoduodenectomy (PD). A LASSO-regularized Cox regression model was used to feature selection, examine the path of the coefficient and create a model to predict recurrence. Internal and external validation and model performance were assessed using the C-index score. Additionally, a web application was developed to enhance the clinical use of the algorithm. RESULTS: Among 654 patients, LNR (Lymph Node Ratio) 15, neural invasion, N stage, surgical radicality, and differentiation grade emerged as significant predictors of disease-free survival (DFS). The model showed the best discrimination capacity with a C-index value of 0.8 (CI 95 %, 0.77%-0.86 %) and highlighted LNR15 as the most influential factor. Internal and external validations showed the model's robustness and discriminative ability with an Area Under the Curve of 92.4 % (95 % CI, 88.2%-94.4 %) and 91.5 % (95 % CI, 88.4%-93.5 %), respectively. The predictive model is available at https://imim.shinyapps.io/LassoCholangioca/. CONCLUSIONS: This study pioneers the integration of machine learning into prognostic modeling for dCCA, yielding a robust predictive model for DFS following PD. The tool can provide information to both patients and healthcare providers, enhancing tailored treatments and follow-up.

Quantitative gene expression of somatostatin receptors and noradrenaline transporter underlying scintigraphic results in patients with neuroendocrine tumors.

AIM: To measure, by a quantitative approach, the gene expression underlying the results of somatostatin receptor (sst) scintigraphy ((111)In-DTPA-octreotide) and noradrenaline transporter (NAT) scintigraphy ((123)I-MIBG) in patients with neuroendocrine (NE) tumors. METHODS: The gene expression of somatostatin receptors 1-5 (sst) and NAT was measured quantitatively by real-time PCR in a group of patients with NE tumors (n = 14) and compared to a group of patients with colorectal adenocarcinomas (n = 15). If available, scintigraphic results were compared with gene expression results (9 octreotide and 3 MIBG scintigraphies). RESULTS: The sst(2) was upregulated in 13 of 14 patients (93%) with NE tumors, and the absolute level of gene expression was highest for sst(2). Gene expression alterations of NAT and the other sst subtypes were more variable. Gene expression of sst(2) was in all cases in agreement with positive octreotide scintigraphies. In 2 of 3 cases where MIBG scintigraphy was positive, NAT was also upregulated. Sst(2) was generally downregulated in the colorectal tumor group with the gene expression of the other receptors being more heterogeneous. CONCLUSIONS: In general, changes in gene expression of sst(2) corresponded with scintigraphic results. Our data support that sst(2) is the best target for visualization of NE tumors, whereas NAT is only a useful target in a subpopulation of NE tumors. Comparison of scintigraphic results with quantitative gene expression may be used to achieve a better understanding of the link between them, which in turn could aid in planning and development of noninvasive molecular imaging of key molecular processes.