Pancreatic Neuroendocrine Tumors Patients Research Articles

Management of Ileal Neuroendocrine Tumors with Liver Metastases

PurposeAssessment of treating metastatic ileal neuroendocrine tumors (NETs) with complete resection of primary tumor, nodal and liver metastases, plus administration of long-acting somatostatin analogues (SSAs). MethodsA prospective database was queried for patients with ileal or pancreatic NETs with pathology-confirmed liver metastases and tumor somatostatin receptors. Patients did not have MEN-1 and had no previous treatment. The impacts of SSA treatment on the primary outcome of survival and secondary outcome of progression-free survival were assessed with Kaplan–Meier analysis. Log rank test was used to compare overall and progression-free survival among groups. ResultsSeventeen ileal NET patients and 36 pancreatic NET patients who underwent surgical resection between 2001 and 2018, who had pathology-confirmed liver metastases and confirmed tumor somatostatin receptors, did not have MEN-1, and had no previous treatment were identified. Median follow-up for patients with ileal NETs was 80 months (range 0–197 months) and 32 months (range 1–182 months) for pancreatic NETs. Five-year survival was 93% and 72% for ileal and pancreatic NET, respectively. Progression-free 5-year survival was 70% and 36% for ileal and pancreatic NET, respectively. Overall 5-year survival for pNETs was greater in those patients treated with SSA (79%) compared to those who underwent surgery alone (34%, p < 0.01). The average ECOG score was low for surviving patients with ileal (0.15) and pancreatic NET (0.73) indicating a good quality of life. ConclusionsResection of primary lymph node and liver metastatic ileal or pancreatic NETs followed with continued SSAs is associated with an excellent progression-free and overall survival and minimal side effects.

Leveraging machine learning techniques for predicting pancreatic neuroendocrine tumor grades using biochemical and tumor markers.

BACKGROUNDThe incidence of pancreatic neuroendocrine tumors (PNETs) is now increasing rapidly. The tumor grade of PNETs significantly affects the treatment strategy and prognosis. However, there is still no effective way to non-invasively classify PNET grades. Machine learning (ML) algorithms have shown potential in improving the prediction accuracy using comprehensive data.AIMTo provide a ML approach to predict PNET tumor grade using clinical data.METHODSThe clinical data of histologically confirmed PNET cases between 2012 and 2018 were collected. A method of minimum P for the Chi-square test was used to divide the continuous variables into binary variables. The continuous variables were transformed into binary variables according to the cutoff value, while the P value was minimum. Four classical supervised ML models, including logistic regression, support vector machine (SVM), linear discriminant analysis (LDA) and multi-layer perceptron (MLP) were trained by clinical data, and the models were labeled with the pathological tumor grade of each PNET patient. The performance of each model, including the weight of the different parameters, were evaluated.RESULTSIn total, 91 PNET cases were included in this study, in which 32 were G1, 48 were G2 and 11 were G3. The results showed that there were significant differences among the clinical parameters of patients with different grades. Patients with higher grades tended to have higher values of total bilirubin, alpha fetoprotein, carcinoembryonic antigen, carbohydrate antigen 19-9 and carbohydrate antigen 72-4. Among the models we used, LDA performed best in predicting the PNET tumor grade. Meanwhile, MLP had the highest recall rate for G3 cases. All of the models stabilized when the sample size was over 70 percent of the total, except for SVM. Different parameters varied in affecting the outcomes of the models. Overall, alanine transaminase, total bilirubin, carcinoembryonic antigen, carbohydrate antigen 19-9 and carbohydrate antigen 72-4 affected the outcome greater than other parameters.CONCLUSIONML could be a simple and effective method in non-invasively predicting PNET grades by using the routine data obtained from the results of biochemical and tumor markers.

CT radiomics may predict the grade of pancreatic neuroendocrine tumors: a multicenter study.

To develop and validate a radiomics-based nomogram for preoperatively predicting grade 1 and grade 2/3 tumors in patients with pancreatic neuroendocrine tumors (PNETs). One hundred thirty-eight patients derived from two institutions with pathologically confirmed PNETs (104 in the training cohort and 34 in the validation cohort) were included in this retrospective study. A total of 853 radiomic features were extracted from arterial and portal venous phase CT images respectively. Minimum redundancy maximum relevance and random forest methods were adopted for the significant radiomic feature selection and radiomic signature construction. A fusion radiomic signature was generated by combining both the single-phase signatures. The nomogram based on a comprehensive model incorporating the clinical risk factors and the fusion radiomic signature was established, and decision curve analysis was applied for clinical use. The fusion radiomic signature has significant association with histologic grade (p < 0.001). The nomogram integrating independent clinical risk factor tumor margin and fusion radiomic signature showed strong discrimination with an area under the curve (AUC) of 0.974 (95% CI 0.950-0.998) in the training cohort and 0.902 (95% CI 0.798-1.000) in the validation cohort with good calibration. Decision curve analysis verified the clinical usefulness of the predictive nomogram. We proposed a comprehensive nomogram consisting of tumor margin and fusion radiomic signature as a powerful tool to predict grade 1 and grade 2/3 PNET preoperatively and assist the clinical decision-making for PNET patients. • Radiomic signature has strong discriminatory ability for the histologic grade of PNETs. • Arterial and portal venous phase CT imaging are complementary for the prediction of PNET grading. • The comprehensive nomogram outperformed clinical factors in assisting therapy strategy in PNET patients.

Meta-analysis of prognostic biomarkers for pancreatic neuroendocrine tumors (PNETs).

e15688 Background: PNETs are marked by histological heterogeneity and variable clinical outcomes. Other than Ki67 index, reliable circulating or tissue biomarkers for prognosis do not exist. Methods: PubMed was searched through 01/31/2017. Inclusion criteria were: 1) prospective/retrospective cohort with defined source population, boundary dates, and justifications for exclusions; 2) assay of primary tumors; 3) clear descriptions of methods including techniques and controls; 4) use of multivariate proportional hazards modeling adjusted for prognostic factors including but not limited to stage or grade; and 5) reporting adjusted hazard ratios (HR) with 95 % confidence intervals and P values. Studies with &lt; 50 % PNETs were excluded. PNET-specific data was summarized in the table. Results: A total of 2958 manuscripts were identified and 462 manuscripts were reviewed. Only 23 multivariate studies met all inclusion criteria. These altogether analyzed 24 unique targets and 14 were associated with survival. Conclusions: This meta-analysis identified 14 markers associated with survival of PNET patients. Future studies should adhere to the REMARK criteria and incorporate the 2017 WHO grading system for multivariate analysis. 1. I-immunohistochemistry, F-fluorescence in situ hybridization, E-enzyme linked immunosorbent assay, M- methylation specific PCR, P-polymerase chain reaction; 2. O-overall survival, F-disease free survival, S-disease specific survival, P- progression free survival.[Table: see text]

Role of Tumor-Associated Macrophages in the Clinical Course of Pancreatic Neuroendocrine Tumors (PanNETs).

This study evaluated the potential role of immune cells and molecules in the pathogenesis and clinical course of pancreatic neuroendocrine tumors (PanNET). Surgically resected PanNETs (N = 104) were immunohistochemically analyzed for Ki67 index, mitotic rate, macrophage, CD4+ cells, and CD8+ T-cell infiltration, as well as HLA class I, PD-L1, and B7-H3 expression. Results were correlated with clinicopathologic characteristics as well as with disease-free (DFS) and disease-specific (DSS) survival. The median age of the 57 WHO grade 1 and 47 WHO grade 2 patients was 55 years. High intratumoral CD8+ T-cell infiltration correlated with prolonged DFS (P = 0.05), especially when the number of tumor-associated macrophages (TAM) was low. In contrast, high peritumoral CD4+ cell and TAM infiltration was associated with a worse DFS and DSS. PD-L1 and B7-H3 were expressed in 53% and 78% PanNETs, respectively. HLA class I expression was defective in about 70% PanNETs. HLA-A expression correlated with favorable DSS in PD-L1-negative tumors (P = 0.02). TAM infiltration (P = 0.02), WHO grade (P = 0.04), T stage (P = 0.01), and lymph node positivity (P = 0.04) were independent predictors of DFS. TAM infiltration (P = 0.026) and T stage (P = 0.012) continued to be predictors of DFS in WHO grade 1 PanNET patients. TAM infiltration was the sole independent predictor of DSS for WHO grade 1 and 2 patients (P = 0.02). Therefore, this biomarker may contribute to identifying WHO grade 1 patients with poor prognosis. TAM infiltration appears to be the most informative prognostic biomarker in PanNET. It may represent a useful immunotherapeutic target in patients with PanNET.

Surgery does not impact cancer-specific survival for AJCC 8th edition stage I pancreatic neuroendocrine tumors

Background: The role of surgery is unclear for stage I pancreatic neuroendocrine tumors (PNETs) based on AJCC 8th edition staging manual, which excludes high-grade and carcinomas. We examined survival outcomes in patients with stage I PNETs, and evaluated the impact of surgery on overall (OS) and cancer-specific survival (CSS). Methods: Using SEER data from 2007 to 2015 we included well- and moderately-differentiated PNET patients. Poor or undifferentiated neuroendocrine tumors and neuroendocrine carcinomas were excluded. 725 patients were identified and included in the analysis. Survival tables and log-rank, univariable and multivariable Cox regression models were used to examine OS and CSS. Results: Among the 725 patients, the majority underwent surgical treatment (n = 642, 88.6%). Median follow-up for the study population was 24 months. There were 38 overall deaths (5.24% death rate) and 12 cancer-specific deaths (1.66% death rate). All cancer-specific deaths occurred early on; all remaining deaths occurring beyond the 3-year mark were not cancer-related. Median OS and CSS were not reached, with 5-year OS and CSS rates of 91.1% and 98%, respectively for the whole population. OS was significantly lower in the non-surgical group compared to those having surgery, with 5-year OS rates of 65.0% versus 93.5% (log rank <0.01). However, CSS was no different between the two groups with 5-year CSS rates of 95.1% in the non-surgical group and 98.3% in the surgical group (log rank=0.26). On multivariable analysis, surgery was not associated with improved CSS – although it was an independent predictor of OS (see Table). Conclusion: For 8th Edition AJCC stage I PNETs, surgery is not associated with improved CSS. However, it was associated with improved OS, implying a selection bias towards surgery being performed in healthier patients. Based on these data, there is a limited role of surgery for the management of stage I PNETs and surgical treatment should be individualized, as the primary cause of death for these patients is non-cancer related.

Association between genetic polymorphisms in long non-coding RNAs and pancreatic cancer risk.

Long non-coding RNAs (lncRNAs) are emerging as candidate biomarkers of cancer, having regulatory functions in both oncogenic and tumor-suppressive pathways. Concerning pancreatic cancer (PC), deregulation of lncRNAs involved in tumor initiation, invasion, and metastasis seem to play a key role. However, data is scarce about regulatory mechanism of lncRNA expression. The aim of our study was to investigate the contribution of two lncRNAs polymorphisms (rs1561927 and rs4759313 of PVT1 and HOTAIR, respectively) in PC susceptibility. A case-control study was conducted analysing rs1561927 and rs4759313 polymorphisms using DNA collected in a population-based case-control study of pancreatic cancer (111 pancreatic ductal adenocarcinoma cases (PDAC), 56 pancreatic neuroendocrine tumor (PNET), and 125 healthy controls). Regarding the PVT1 rs1561927 polymorphism the G allele was significantly overrepresented in both PDAC and PNET patients compared to the controls, while the presence of the HOTAIR rs4759314 G allele was found to be overrepresented in the PNET patients only compared to the controls. The PVT1 rs1561927 AG/GG genotypes were associated with poor overall survival in PDAC patients. Our results suggested that polymorphisms of these two lncRNA polymorphisms implicated in pancreatic carcinogenesis. Further large-scale and functional studies are needed to confirm our results.

Recommendation of long-term and systemic management according to the risk factors in rectal NETs patients

Rectal neuroendocrine tumors (NETs) are often found as small lesions, which can be treated by endoscopic resection. However, high risk cases with lymph node (LN) metastasis are indication of radical surgery. Furthermore, rectal NETs are often associated with late recurrences and/or multiple cancer development. Therefore, proper surgical indication and patients’ management are required. We investigated the clinicopathological features of 79 rectal NET cases in order to elucidate risk factors for synchronous LN metastasis, recurrence, and multiple cancers. Recently, we reported that in pancreatic NET patients, a loss of heterozygosity (LOH) in PHLDA3 was associated with poorer prognosis, and that LOH of both PHLDA3 and MEN1 was frequently observed. Therefore, PHLDA3 and MEN1 LOH were also assessed in rectal NET patients for their association with clinicopathological features. Of the 79 patients, LN metastases were found in 12.7%, recurrences in 3.8%, and multiple cancers in 30.4% of the subjects. PHLDA3 and MEN1 LOH were found in 60.0% and 66.7% of the subjects, respectively. Lymphatic invasion and WHO classification 2010 were found to be independent risks for LN metastasis. There were three cases of recurrence, all of which occurred more than 3 years after resection and two of which exhibited LN metastasis. Older age and LOH in PHLDA3 were associated with the presence of multiple cancers. Long-term and systemic management of patients with rectal NETs is therefore recommended in accordance with these risk factors.

Utility of cytomorphology in distinguishing solid pseudopapillary neoplasm of pancreas from pancreatic neuroendocrine tumor with emphasis on nuclear folds and nuclear grooves.

Pancreatic solid pseudopapillary tumor (SPN) and pancreatic neuroendocrine tumors (Pan-NET) have close resemblance on imaging and cytomorphology, though they differ in their prognosis and treatment strategy. SPNs are low-grade indolent tumors while Pan-NETs harbor malignant potential with propensity to metastasize. We aim to differentiate SPN from Pan-NET based on cyto-morphology; to classify nuclear membrane (NM) irregularities or nuclear folds into four grades and see whether they bear any difference with respect to the two entities. Eighteen and ten confirmed cases of SPN and Pan-NET were included in the study. Smears were assessed for architecture, background changes, cellular, and nuclear features, which were compared between the two study groups. Nuclear folds were classified into four grades. Nuclear folds and nuclear grooves were also compared between the two groups. All SPN patients were females; mean age of 28 years. Pan-NET patients had equal male to female ratio; mean age of 46 years. Both SPN (78%) and Pan-NET (71%) showed predilection for pancreatic head. Mean size of lesion was 4.8 cm and 3.1 cm in SPN and Pan-NET groups. Papillary pattern, branching capillaries, degenerative background were significantly more prominent in SPN; sudden anisonucleosis and cytoplasmic granularity in Pan-NET. Metachromatic matrix, hyaline globules, and nuclear grooves were noted exclusively in SPNs. Nuclear fold grades 2 and 3 were more characteristic of SPN than Pan-NET (P = 0.041 and 0.002, respectively). Cytomorphology is vital in differentiating SPN from Pan-NET with nuclear folds being an important nuclear feature.

Genetic polymorphisms of interleukin 1β and TNF-α genes and their influence on sporadic pancreatic neuroendocrine tumors predisposition risks

Background: A recent study suggested the putative role of TNF-a - 1031 polymorphism in the development of gastroenteropancreatic neuroendocrine tumors. Additionaly, several single nucleotide polymorphisms (SNPs) of the IL-1β gene influence the regulation of its expression and function have been correlated with gastrointestinal cancers, such as gastric, hepatocellular cancer and pancreatic cancer. Methods: The aim of our study was to analyze TNF-a gene and IL-1β polymorphisms as risk factors for pancreatic neuroendocrine tumors using germline DNA collected in a population based case–control study of pancreatic cancer. Results: Our findings suggest a role of TNF-a - 1031 polymorphism in the development of pancreatic neuroendocrine tumors and intraductal papillary mucinous neoplasms. The distribution of genotypes for the -511 IL-1β C/T polymorphism in the pancreatic neuroendocrine tumor patient groups showed significant difference compared to the control group. The -511 CT and TT high-expression genotypes were over-represented in pancreatic neuroendocrine tumors patients. Conclusion: The findings of this study suggested a possible role of IL-1β -511 C/T genotypes in the pathogenesis of pancreatic neuroendocrine tumors and a putative role of TNF-a - 1031 polymorphism in the development of pancreatic neuroendocrine tumor and intraductal papillary mucinous neoplasm.

Genetic polymorphisms of interleukin 1β and TNF-α genes and their influence on sporadic pancreatic neuroendocrine tumors predisposition risks

Background: A recent study suggested the putative role of TNF-a - 1031 polymorphism in the development of gastroenteropancreatic neuroendocrine tumors. Additionaly, several single nucleotide polymorphisms (SNPs) of the IL-1β gene influence the regulation of its expression and function have been correlated with gastrointestinal cancers, such as gastric, hepatocellular cancer and pancreatic cancer. Methods: The aim of our study was to analyze TNF-a gene and IL-1β polymorphisms as risk factors for pancreatic neuroendocrine tumors using germline DNA collected in a population based case–control study of pancreatic cancer. Results: Our findings suggest a role of TNF-a - 1031 polymorphism in the development of pancreatic neuroendocrine tumors and intraductal papillary mucinous neoplasms. The distribution of genotypes for the -511 IL-1β C/T polymorphism in the pancreatic neuroendocrine tumor patient groups showed significant difference compared to the control group. The -511 CT and TT high-expression genotypes were over-represented in pancreatic neuroendocrine tumors patients. Conclusion: The findings of this study suggested a possible role of IL-1β -511 C/T genotypes in the pathogenesis of pancreatic neuroendocrine tumors and a putative role of TNF-a - 1031 polymorphism in the development of pancreatic neuroendocrine tumor and intraductal papillary mucinous neoplasm.

Proinsulin Expressing Neuroendocrine Tumors of the Pancreas: An Underrecognized Entity.

Rare cases of pancreatic neuroendocrine tumors (PNETs) that produce only proinsulin (PI) and manifest with hypoglycemia have been reported. Proinsulin expression in PNET has not been systematically studied, and the clinicopathologic features of such tumors remain unknown. We studied expression of PI by immunohistochemistry (IHC) in 136 PNETs from 2 high-volume surgical oncology centers and assessed all available clinicopathologic data. Thirty-six (26%) of PNETs were positive for PI by IHC, most (89%) of which coexpressed insulin IHC. Nine PI-positive tumors represented functional insulinomas. Patients with PI IHC-positive tumors demonstrated significantly lower mean preoperative serum glucose compared with PI-negative PNET patients, even when insulinomas were excluded. No differences in survival between PI IHC-positive and PI IHC-negative tumors were observed. We identified 2 PI-positive PNETs from hypoglycemic patients, which were not insulinomas or other functional variants and in which serum PI was never tested. These may have been undetected proinsulinomas. Proinsulin-expressing PNETs (functional or non) are not uncommon. Patients who present with hypoglycemia and normal insulin levels should be screened for proinsulinoma. Proinsulin IHC could also be used to screen for proinsulinoma. To further elucidate the clinical significance of PI expressing PNETs, prospective studies are required.

Hypervascular lesions of the pancreas: Think before you act

BackgroundThe “classic” CT appearance of pancreatic neuroendocrine tumors (PNETs) is a solid, hypervascular lesion; however, non-PNET diagnoses may appear similar. In addition, some PNETs have a “non-classic” appearance. MethodsDemographic, imaging, endoscopic ultrasound-fine needle aspiration (EUS/FNA) results, and pathology data were analyzed for patients who underwent pancreatectomy for suspected or confirmed diagnosis of PNET from our institutional database. ResultsForty-three patients with a hypervascular lesion on CT had pancreatectomy for a pre-operative diagnosis of PNET. Final pathology revealed PNET in 30 (70%) and non-PNET diagnoses in 13 (30%). EUS/FNA had a sensitivity of 82% for the pre-operative diagnosis of PNET in patients with “classic” CT. Of 13 non-PNET diagnoses, 7 were benign. Among a total of 41 patients with a final diagnosis of PNET, 11 (27%) had “non-classic” CT (5 hypodense solid lesions, 3 isodense solid lesions, and 3 cystic lesions). Among these patients, EUS/FNA had a sensitivity of 100% in diagnosing PNET. ConclusionsConsideration of non-PNET diagnoses is important for patients with hypervascular lesions on CT. Appropriate pre-operative evaluation will optimize treatment plans.

Prognostic significance of Chromogranin A in small pancreatic neuroendocrine tumors

The incidence of nonfunctional pancreatic neuroendocrine tumors ≤2cm is rising. The biologic behavior of these tumors is variable; thus, their management remains controversial. Chromogranin A upregulation is a useful diagnostic biomarker of neuroendocrine tumors; however, the prognostic significance of Chromogranin A is unclear. The objective of this study was to determine whether Chromogranin A levels have prognostic value in pancreatic neuroendocrine tumor patients and may help guide management. We evaluated the National Cancer Database over a 10-year period (2004-2013). Patients with pancreatic neuroendocrine tumors measuring ≤2cm, without distant metastases, were identified and categorized as Chromogranin A high (>420ng/mL) or Chromogranin A low (≤420ng/mL), and those lacking data on Chromogranin A levels were excluded from the study. Univariate and multivariate analyses were performed using Cox proportional hazards model. Cut-point determination was performed using the Contal and O'Quigley method. Of the 445 eligible patients, 352 (79%) were Chromogranin A low and 93 (21%) were Chromogranin A high. Median Chromogranin A level was 71ng/mL (interquartile range, 24-294ng/mL). Chromogranin levels were associated with clinical nodal status and grade. Furthermore, on multivariate analysis, Chromogranin A levels (Chromogranin A high versus Chromogranin A low) independently predicted overall survival after controlling for tumor size, grade, clinical nodal status, and academic status of the facility (hazard ratio: 7.90, 95%CI: 2.34-26.69, P = .001). The greatest benefit of surgical resection was noted in patients in the Chromogranin A high subgroup (log-rank P <.001). Serum Chromogranin A levels can be incorporated in surgical decision-making for patients with small pancreatic neuroendocrine tumors. Patients in the Chromogranin A low group can be considered for observation, whereas patients in the Chromogranin A high group should be strongly considered for resection.

Cell-Free DNA From Metastatic Pancreatic Neuroendocrine Tumor Patients Contains Tumor-Specific Mutations and Copy Number Variations.

Background: Detection of tumor-specific alterations in cell-free DNA (cfDNA) has proven valuable as a liquid biopsy for several types of cancer. So far, use of cfDNA remains unexplored for pancreatic neuroendocrine tumor (PNET) patients.Methods: From 10 PNET patients, fresh frozen tumor tissue, buffy coat and plasma samples were collected. Whole-exome sequencing of primary tumor and germline DNA was performed to identify tumor-specific variants and copy number variations (CNVs). Subsequently, tumor-specific variants were quantified in plasma cfDNA with droplet digital PCR. In addition, CNV analysis of cfDNA was performed using shallow whole-genome sequencing.Results: Tumor-specific variants were detected in perioperative plasma samples of two PNET patients, at variant allele fractions (VAFs) of respectively 19 and 21%. Both patients had metastatic disease at time of surgery, while the other patients presented with localized disease. In the metastatic patients, CNV profiles of tumor tissue and cfDNA were significantly correlated. A follow-up plasma sample of a metastatic patient demonstrated an increased VAF (57%) and an increased chromosomal instability, in parallel with an increase in tumor burden.Conclusions: We are the first to report the presence of tumor-specific genetic alterations in cfDNA of metastatic PNET patients and their evolution during disease progression. Additionally, CNV analysis in cfDNA shows potential as a liquid biopsy.

1332P - Detection of mutations and copy number alterations in circulating DNA from pancreatic neuroendocrine tumor patients

1332P - Detection of mutations and copy number alterations in circulating DNA from pancreatic neuroendocrine tumor patients

Analysis of recurrence after the resection of pancreatic neuroendocrine tumors.

Outcomes after recurrence of resected pancreatic neuroendocrine tumors (PNETs) are not well described. We aim to assess the rate and sites of recurrence, and its effect on clinical outcomes. Retrospective chart review of patients (n = 83) who underwent surgical resection of PNETs at 2 institutions. Patients were treated from September2002 to July2010. There were 13 (16%) recurrences. The most common site of recurrence was the liver (9 patients, 9.6%). The most common treatment of recurrences was chemotherapy (5 patients, 36%). The 1-, 3-, and 5-year disease-free survival was 90.9%, 82.7%, and 72.5%, respectively. Median recurrence-free survival was 127 months. The median follow-up for all PNET patients was 25.8 months (range, 1-140 months). The 3-year survival was 97%. The median follow-up of patients after the diagnosis of a recurrence was 13.8 months. The overall survival for those with and without recurrence was 96.3% and 100%, respectively (P = .36). The age ( P = .002) and lymph node ratio ( P < .001) were predictors of recurrence on multivariate analysis. Age and lymph node ratio are significant predictors of recurrence after the resection of PNETs with hepatic metastases being the most common. Survival of patients with recurrence is not significantly different from patients without recurrence.

Correction to: Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy.

The article "Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy," was originally published electronically on the publisher's internet portal without open access.

Pre-therapy Somatostatin Receptor-Based Heterogeneity Predicts Overall Survival in Pancreatic Neuroendocrine Tumor Patients Undergoing Peptide Receptor Radionuclide Therapy

PurposeEarly identification of aggressive disease could improve decision support in pancreatic neuroendocrine tumor (pNET) patients prior to peptide receptor radionuclide therapy (PRRT). The prognostic value of intratumoral textural features (TF) determined by baseline somatostatin receptor (SSTR)-positron emission tomography (PET) before PRRT was analyzed.ProceduresThirty-one patients with G1/G2 pNET were enrolled (G2, n = 23/31). Prior to PRRT with [177Lu]DOTATATE (mean, 3.6 cycles), baseline SSTR-PET computed tomography was performed. By segmentation of 162 (median per patient, 5) metastases, intratumoral TF were computed. The impact of conventional PET parameters (SUVmean/max), imaging-based TF, and clinical parameters (Ki67, CgA) for prediction of both progression-free survival (PFS) and overall survival (OS) after PRRT were evaluated.ResultsWithin a median follow-up of 3.7 years, tumor progression was detected in 21 patients (median, 1.5 years) and 13/31 deceased (median, 1.9 years). In ROC analysis, the TF entropy, reflecting derangement on a voxel-by-voxel level, demonstrated predictive capability for OS (cutoff = 6.7, AUC = 0.71, p = 0.02). Of note, increasing entropy could predict a longer survival (> 6.7, OS = 2.5 years, 17/31), whereas less voxel-based derangement portended inferior outcome (< 6.7, OS = 1.9 years, 14/31). These findings were supported in a G2 subanalysis (> 6.9, OS = 2.8 years, 9/23 vs. < 6.9, OS = 1.9 years, 14/23). Kaplan–Meier analysis revealed a significant distinction between high- and low-risk groups using entropy (n = 31, p < 0.05). For those patients below the ROC-derived threshold, the relative risk of death after PRRT was 2.73 (n = 31, p = 0.04). Ki67 was negatively associated with PFS (p = 0.002); however, SUVmean/max failed in prognostication (n.s.).ConclusionsIn contrast to conventional PET parameters, assessment of intratumoral heterogeneity demonstrated superior prognostic performance in pNET patients undergoing PRRT. This novel PET-based strategy of outcome prediction prior to PRRT might be useful for patient risk stratification.

PO-329 Genomic aberration in pancreatic neuroendocrine tumours (PNET)

IntroductionRare tumours are poorly investigated and therefore heavily limited in possible therapeutic approaches, and subsequently therapeutic success. One such tumour entity, representing only 1%–2% of all pancreatic malignancies is Pancreatic Neuroendocrine tumours (PNET). PNET are cancers of endocrine cells of the islets of Langerhans and only a handful of studies thus far have investigated the genetic makeup of these tumours. Apart from surgery and chemotherapy for localised tumours, the only approved targeted drug for treatment of advanced PNETs is Everolimus, specifically targeting the mTOR protein. Much is still lacking in the area of targeted therapies and possible options for treating metastasized tumours. Our aim is to therefore establish a genetic profile of PNET tumours in order to determine more targets connected to mTOR signalling and consequently, increase options for improved therapy approaches.Material and methodsWe performed deep coverage sequencing, averaging a depth of 1000 reads, using an established in-house PNET panel. Our cohort included Formaldehyde Fixed Paraffin Embedded (FFPE) patient samples comprising of 50 primary tumours of varying grades, and 14 metastases.Results and discussionsUsing variant calling pipelines, we determined single nucleotide variations (SNV) and copy number variations (CNV) in our cohort and elucidated potential heterogeneity within the PNET tumours. Out of the 62 sequenced samples, 26 primary tumours, and 6 metastases showed SNV alterations with the most recurring being MEN1 alterations (50%) irrespective of whether the tumour is primary or metastasis, followed by DAXX (27%) which was exclusively mutated in primary tumours. In addition, mutation in a novel candidate, polycomb protein EED has been determined specifically in G3 PNET and the alteration falls in one of the β-transducing repeat of the protein. CNV was determined in 38 samples with a recurring copy number increase for RICTOR (~37%). Intra-tumour heterogeneity, based on allelic frequency, is evident in some samples while the combined SNV and CNV profile of these patients reveal a clear inter-tumour heterogeneity in PNETs.ConclusionOur study reveals previously identified and novel alterations, which require further investigation at the protein level to determine new possible therapeutic approaches for PNET patients. In addition, our data clearly reveals that due to the high level of inter-tumour heterogeneity present in these tumours, it is vital to consider a more personalised targeted approach to therapy.