Well-differentiated pancreatic neuroendocrine tumours (PanNETs) and poorly differentiated pancreatic neuroendocrine carcinomas (PanNECs): concepts, issues and a practical diagnostic approach to high-grade (G3) cases

CEP55, A Promising Prognostic Biomarker for Pancreatic Neuroendocrine Neoplasms, Promotes Tumor Progression Through Activation of PI3K/AKT/mTOR Pathway

Pancreatic neuroendocrine neoplasms (pNENs) exhibit significant heterogeneity, and the effectiveness of traditional classification methods in predicting tumor biological behavior and patient prognosis is limited. This study aims to reveal potential biomarkers to predict the prognosis of pNENs and explore the underlying mechanisms. Four mRNA sequencing datasets of pNENs were included in the study. CEP55, TPX2, and BIRC2 were identified as overlapping DEGs and were significantly associated with the clinical characteristics and prognosis of pNENs. The nomogram, which incorporated independent prognostic risk factors such as CEP55 expression, tumor grade, and TNM stage, demonstrated higher predictive efficiency than traditional methods. We found that knockdown of CEP55 resulted in the inhibition of proliferation, migration, and invasion in pNENs cells, while a reverse trend was observed in CEP55-overexpressing cells. Furthermore, CEP55 was found to enhance the PI3K/AKT/mTOR pathway in pNENs through its interaction with PI3K-p110. Everolimus, an mTOR inhibitor, was shown to counteract the effects of CEP55 overexpression both in vivo and in vitro. In conclusion, CEP55 may enhance the proliferation, invasion, and migration of pNENs by activating the PI3K/AKT/mTOR pathway through its interaction with PI3K. It may serve as a valuable prognostic marker and a promising therapeutic target.

Development and validation of a CT-based nomogram to preoperative prediction of pancreatic neuroendocrine tumors (pNETs) grade

BACKGROUND/PURPOSE

It is challenging to determine the pancreatic neuroendocrine tumors (pNETs) malignancy grade noninvasively. We aim to establish a CT - based diagnostic nomogram to predict the tumor grade of pNETs.

METHODS

The patients with pathologically confirmed pNETs were recruited in two centers between January 2009 and November 2020. PNETs were subdivided into three grades according to the 2017 World Health Organization classification: low-grade G1 NETs, intermediate-grade G2 NETs, and high-grade G3 NETs. The features on the CT images were carefully evaluated. To build the nomogram, multivariable logistic regression analysis was performed on the imaging features selected by LASSO to generate a combined indicator for estimating the tumor grade.

RESULTS

A total of 162 pNETs (training set n = 114, internal validation set n = 21, external validation set, n = 48) were admitted, including 73 (45.1%) G1 and 89 (54.9%) G2/3. A nomogram comprising the tumor margin, tumor size, neuroendocrine symptoms and the enhanced ratio on portal vein phase images of tumor was established to predict the malignancy grade of pNETs. The mean AUC for the nomogram was 0.848 (95% CI, 0.918-0.953). Application of the developed nomogram in the internal validation dataset still yielded good discrimination (AUC, 0.835; 95% CI, 0.915-0.954). The externally validated nomogram yielded a slightly lower AUC of 0.770 (95% CI, 0.776-0.789).

CONCLUSIONS

The nomogram model demonstrated good performance in preoperatively predicting the malignancy grade of pNETs, and can provide clinicians with a simple, practical, and non-invasive tool for personalized management of pNETs patients.

Anti-phosphohistone H3 (PHH3) as a proliferation marker to assess mitotic activity and to grade neuroendocrine neoplasms of hepatopancreaticobiliary (HPB) system

BACKGROUND

The world health organization (WHO) classification of neuroendocrine neoplasms (NENs, i.e. neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs)) of the gastrointestinal system involves grading of these tumors by mitotic count (i.e. H and E mitotic index or Haematoxylin and Eosin mitotic index [HE-MI] and Mindbomb E3 ubiquitin protein ligase 1 labelling index (MIB1-LI) into Grade 1 (G1), Grade 2 (G2), or Grade 3 (G3). However, the assessment of HE-MI and MIB1-LI is hindered by several factors that contribute to discordance between these two grading methods. Clinical data demonstrate the dependency of prognosis on grade.

OBJECTIVES

The objective of this study was to compare the grading of NENs of the hepatopancreatobiliary (HPB) system using Anti-phosphohistone H3 mitotic index (i.e. PHH3-MI), HE-MI and MIB1-LI.

MATERIALS AND METHODS

In a cohort of 140 NENs selected from January 2011 to August 2019, the concordance and correlation between HE-MI, MIB1-LI and PHH3-MI grading methods were analysed using Cohen's weighted kappa ( κ ) statistics and Spearman's correlation (ρ), respectively. Receiver operating characteristic (ROC) curve and cut-off analyses were done to determine optimal PHH3-MI cut-off values to grade NENs.

RESULTS

The rates of discordance between HE-MI vs. MIB1-LI, PHH3-MI vs. MIB1-LI and PHH3-MI vs. HE-MI were 52% ( κ =0.416), 29% ( κ =0.64) and 41% ( κ =0.508), respectively. There was a significant correlation between the grading methods. PHH3-MI had good overall sensitivity and specificity at cut-offs 2 and 17 in distinguishing between G1 vs. G2, and G2 vs. G3 tumors, respectively.

CONCLUSION

PHH3 immunolabeling allowed for quick and easy identification of mitotic figures (MF). It had the highest concordance with MIB1-LI. At cut-off values of 2 and 17, there was good overall sensitivity and specificity. The interobserver agreement was excellent.

Progression of Low-Grade Neuroendocrine Tumors (NET) to High-Grade Neoplasms Harboring the NEC-Like Co-alteration of RB1 and TP53

High-grade or grade 3 epithelial neuroendocrine neoplasms (G3 NEN) are now divided into grade 3 well-differentiated neuroendocrine tumor (G3 NET) and neuroendocrine carcinoma (NEC), both defined by Ki-67 > 20% and/or > 20 mitoses per 2 mm2. NET and NEC are thought to be distinct tumors with different genetic profiles: NEC classically harbors co-alteration of TP53 and RB1, whereas NET genetics are site-dependent with frequent alterations in MEN1, ATRX, DAXX, and TSC1/2 in pancreatic NETs. Progression from NET to NEC is considered rare and is not well described. While both TP53 and RB1 alterations were initially thought to be rare in NET, recent work has demonstrated the former in up to 35% of high-grade G3 NET and the latter in rare high-grade NEN that progressed from NET. Here, we describe the clinical, pathologic, and molecular features associated with tumor evolution in a series of five patients that had low-grade NET that progressed to high-grade NEN with co-alteration of RB1 and TP53, similar to NEC. Morphology of the high-grade neoplasms remained well-differentiated in some cases despite RB1/TP53 co-alteration and had some NEC-like features in other cases. All five patients died of disease, with a mean overall survival of 41 months from the first metastatic disease and 12 months from acquisition of RB1/TP53 co-alteration. Our data demonstrate that low-grade NET can progress via the acquisition of both TP53 and RB1 alteration, similar to NEC, but whether this represents a transformation from NET to NEC remains unclear.

Critical appraisal of the adequacy of surgical indications for non-functioning pancreatic neuroendocrine tumours

BACKGROUND

The lack of preoperative prognostic factors to accurately predict tumour aggressiveness in non-functioning pancreatic neuroendocrine tumours may result in inappropriate management decisions. This study aimed to critically evaluate the adequacy of surgical treatment in patients with resectable non-functioning pancreatic neuroendocrine tumours and investigate preoperative features of surgical appropriateness.

METHODS

A retrospective study was conducted on patients who underwent curative surgery for non-functioning pancreatic neuroendocrine tumours at San Raffaele Hospital (2002-2022). The appropriateness of surgical treatment was categorized as appropriate, potential overtreatment and potential undertreatment based on histologic features of aggressiveness and disease relapse within 1 year from surgery (early relapse).

RESULTS

A total of 384 patients were included. Among them, 230 (60%) received appropriate surgical treatment, whereas the remaining 154 (40%) underwent potentially inadequate treatment: 129 (34%) experienced potential overtreatment and 25 (6%) received potential undertreatment. The appropriateness of surgical treatment was significantly associated with radiological tumour size (P < 0.001), tumour site (P = 0.012), surgical technique (P < 0.001) and year of surgical resection (P < 0.001). Surgery performed before 2015 (OR 2.580, 95% c.i. 1.570 to 4.242; P < 0.001), radiological tumour diameter < 25.5 mm (OR 6.566, 95% c.i. 4.010 to 10.751; P < 0.001) and pancreatic body/tail localization (OR 1.908, 95% c.i. 1.119 to 3.253; P = 0.018) were identified as independent predictors of potential overtreatment. Radiological tumour size was the only independent determinant of potential undertreatment (OR 0.291, 95% c.i. 0.107 to 0.791; P = 0.016). Patients subjected to potential undertreatment exhibited significantly poorer disease-free survival (P < 0.001), overall survival (P < 0.001) and disease-specific survival (P < 0.001).

CONCLUSIONS

Potential overtreatment occurs in nearly one-third of patients undergoing surgery for non-functioning pancreatic neuroendocrine tumours. Tumour diameter emerges as the sole variable capable of predicting the risk of both potential surgical overtreatment and undertreatment.

Chromothripsis is a novel biomarker for prognosis and differentiation diagnosis of pancreatic neuroendocrine neoplasms

This study aimed to identify the role of chromothripsis as a novel biomarker in the prognosis and differentiation diagnosis of pancreatic neuroendocrine neoplasms (pNENs). We conducted next-generation gene sequencing in a cohort of 30 patients with high-grade (G3) pNENs. As a reference, a similar analysis was also performed on 25 patients with low-grade (G1/G2) pancreatic neuroendocrine tumors (pNETs). Chromothripsis and its relationship with clinicopathological features and prognosis were investigated. The results showed that DNA damage response and repair gene alteration and TP53 mutation were found in 29 and 11 patients, respectively. A total of 14 out of 55 patients had chromothripsis involving different chromosomes. Chromothripsis had a close relationship with TP53 alteration and higher grade. In the entire cohort, chromothripsis was associated with a higher risk of distant metastasis; both chromothripsis and metastasis (ENETS Stage IV) suggested a significantly shorter overall survival (OS). Importantly, in the high-grade pNENs group, chromothripsis was the only independent prognostic indicator significantly associated with a shorter OS, other than TP53 alteration or pathological pancreatic neuroendocrine carcinomas (pNECs) diagnosis. Chromothripsis can guide worse prognosis in pNENs, and help differentiate pNECs from high-grade (G3) pNETs.

Recent developments in the diagnosis of pancreatic neuroendocrine neoplasms

INTRODUCTION

Pancreatic Neuroendocrine Neoplasms (PanNENs) are characterized by a highly heterogeneous clinical and biological behavior, making their diagnosis challenging. PanNENs diagnostic work-up mainly relies on biochemical markers, pathological examination, and imaging evaluation. The latter includes radiological imaging (i.e. computed tomography [CT] and magnetic resonance imaging [MRI]), functional imaging (i.e. 68Gallium [68 Ga]Ga-DOTA-peptide PET/CT and Fluorine-18 fluorodeoxyglucose [18F]FDG PET/CT), and endoscopic ultrasound (EUS) with its associated procedures.

AREAS COVERED

This review provides a comprehensive assessment of the recent advancements in the PanNENs diagnostic field. PubMed and Embase databases were used for the research, performed from inception to October 2023.

EXPERT OPINION

A deeper understanding of PanNENs biology, recent technological improvements in imaging modalities, as well as progresses achieved in molecular and cytological assays, are fundamental players for the achievement of early diagnosis and enhanced preoperative characterization of PanNENs. A multimodal diagnostic approach is required for a thorough disease assessment.

Radiomics analysis from magnetic resonance imaging in predicting the grade of nonfunctioning pancreatic neuroendocrine tumors: a multicenter study

OBJECTIVES

To explore the potential of radiomics features to predict the histologic grade of nonfunctioning pancreatic neuroendocrine tumor (NF-PNET) patients using non-contrast sequence based on MRI.

METHODS

Two hundred twenty-eight patients with NF-PNETs undergoing MRI at 5 centers were retrospectively analyzed. Data from center 1 (n = 115) constituted the training cohort, and data from centers 2-5 (n = 113) constituted the testing cohort. Radiomics features were extracted from T2-weighted images and the apparent diffusion coefficient. The least absolute shrinkage and selection operator was applied to select the most important features and to develop radiomics signatures. The area under receiver operating characteristic curve (AUC) was performed to assess models.

RESULTS

Tumor boundary, enhancement homogeneity, and vascular invasion were used to construct the radiological model to stratify NF-PNET patients into grade 1 and 2/3 groups, which yielded AUC of 0.884 and 0.684 in the training and testing groups. A radiomics model including 4 features was constructed, with an AUC of 0.941 and 0.871 in the training and testing cohorts. The fusion model combining the radiomics signature and radiological characteristics showed good performance in the training set (AUC = 0.956) and in the testing set (AUC = 0.864), respectively.

CONCLUSION

The developed model that integrates radiomics features with radiological characteristics could be used as a non-invasive, dependable, and accurate tool for the preoperative prediction of grade in NF-PNETs.

CLINICAL RELEVANCE STATEMENT

Our study revealed that the fusion model based on a non-contrast MR sequence can be used to predict the histologic grade before operation. The radiomics model may be a new and effective biological marker in NF-PNETs.

KEY POINTS

The diagnostic performance of the radiomics model and fusion model was better than that of the model based on clinical information and radiological features in predicting grade 1 and 2/3 of nonfunctioning pancreatic neuroendocrine tumors (NF-PNETs). Good performance of the model in the four external testing cohorts indicated that the radiomics model and fusion model for predicting the grades of NF-PNETs were robust and reliable, indicating the two models could be used in the clinical setting and facilitate the surgeons' decision on risk stratification. The radiomics features were selected from non-contrast T2-weighted images (T2WI) and diffusion-weighted imaging (DWI) sequence, which means that the administration of contrast agent was not needed in grading the NF-PNETs.

The association between jaundice and poorly differentiated pancreatic neuroendocrine neoplasms (Ki67 index > 55.0%)

BACKGROUND

Jaundice occurs in some pancreatic disease. However, its occurrences and role in pancreatic neuroendocrine neoplasms (PNENs) has not been well studied. In this study we showed the association between jaundice and the risk of high grade and poorly differentiated PNENs.

METHODS

Ninety-three patients with head-neck PNENs were included. Poorly differentiated pancreatic neuroendocrine neoplasms were defined by a ki67 index > 55.0%. Logistic regression was used to show the association between demographic information, clinical signs and symptoms and the risk of poorly differentiated tumors. A nomogram model was developed to predict poorly differentiated tumor.

RESULTS

Eight of 93 PNEN patients (8.6%) had jaundice. The age and ki67 index in patients with jaundice were significantly higher than those patients without jaundice. All jaundice occurred in patients with grade 3 PNENs. Mutivariable regression analysis showed that age (odds ratio(OR) = 1.10, 95% confidence interval (CI):1.02-1.19), tumor size (OR = 1.42, 95%CI:1.01-2.00) and jaundice (OR = 14.98, 95%CI: 1.22-184.09) were associated with the risk of poorly differentiated PNENs. The age and size combination showed a good performance in predicting poorly differentiated PNENs (area under the curve (AUC) = 0.81, 95% CI: 0.71-0.90). The addition of jaundice further improved the age- and size-based model (AUC = 0.86, 95% CI: 0.78-0.91). A nomogram was developed based on age, tumor size and jaundice.

CONCLUSION

Our data showed that jaundice was associated with the risk of high grade PNENs and poorly differentiated PNENs.

Prognostic value of tumor-to-parenchymal contrast enhancement ratio on portal venous-phase CT in pancreatic neuroendocrine neoplasms

OBJECTIVES

We aimed to evaluate the prognostic value of tumor-to-parenchymal contrast enhancement ratio on portal venous-phase CT (CER on PVP) and compare its prognostic performance to prevailing grading and staging systems in pancreatic neuroendocrine neoplasms (PanNENs).

METHODS

In this retrospective study, data on 465 patients (development cohort) who underwent upfront curative-intent resection for PanNEN were used to assess the performance of CER on PVP and tumor size measured by CT (CT-Size) in predicting recurrence-free survival (RFS) using Harrell's C-index and to determine their optimal cutoffs to stratify RFS using a multi-way partitioning algorithm. External data on 184 patients (test cohort) were used to validate the performance of CER on PVP in predicting RFS and overall survival (OS) and compare its predictive performance with those of CT-Size, 2019 World Health Organization classification system (WHO), and the 8th American Joint Committee on Cancer staging system (AJCC).

RESULTS

In the test cohort, CER on PVP showed C-indexes of 0.83 (95% confidence interval [CI], 0.74-0.91) and 0.84 (95% CI, 0.73-0.95) for predicting RFS and OS, respectively, which were higher than those for the WHO (C-index: 0.73 for RFS [p = .002] and 0.72 for OS [p = .004]) and AJCC (C-index, 0.67 for RFS [p = .002] and 0.58 for OS [p = .002]). CT-Size obtained C-indexes of 0.71 for RFS and 0.61 for OS.

CONCLUSIONS

CER on PVP showed superior predictive performance on postoperative survival in PanNEN than current grading and staging systems, indicating its potential as a noninvasive preoperative prognostic tool.

KEY POINTS

• In pancreatic neuroendocrine neoplasms, the tumor-to-parenchymal enhancement ratio on portal venous-phase CT (CER on PVP) showed acceptable predictive performance of postoperative outcomes. • CER on PVP showed superior predictive performance of postoperative survival over the current WHO classification and AJCC staging system.

Diagnostic role and prognostic value of tumor markers in high-grade gastro-enteropancreatic neuroendocrine neoplasms

OBJECTIVES

High-grade gastro-enteropancreatic neuroendocrine neoplasms (GEP-NENs) are a heterogeneous group of rare tumors of two different types: well differentiated neuroendocrine tumors grade 3 (NETs G3) and poorly differentiated neuroendocrine carcinomas (NECs). This study aimed to explore the value of eight common preoperative markers in differentiating NETs G3 from NECs and the prognosis prediction of high-grade GEP-NENs.

METHODS

Seventy-two patients diagnosed with high-grade GEP-NENs who underwent surgery at our institution were recruited for this study. Demographic and clinicopathological characteristics, preoperative serum tumor markers, and survival data were collected and analyzed. Kaplan-Meier methods were used to analyze survival rates, and a Cox regression model was used to perform multivariate analyses.

RESULTS

Serum carcinoembryonic antigen (CEA) was dramatically higher in NECs than in NETs G3 (P = 0.025). After follow-up, 57 of the 72 patients remained for survival analysis. Elevated serum carbohydrate antigen 19-9 (CA19-9), CEA, cancer antigen 125 and sialic acid (SA) levels indicated poorer survival of high-grade GEP-NEN patients. Only CA19-9 (HR: 6.901, 95% CI: 1.843 to 25.837, P = 0.004) was regarded as an independent risk factor for overall survival. Serum CA19-9 (HR: 4.689, 95% CI: 1.127 to 19.506, P = 0.034) was also regarded as an independent factor for overall survival in NECs.

CONCLUSIONS

Serum CEA levels can be used to distinguish NETs G3 from NECs. Preoperative CA19-9, CEA, cancer antigen 125 and SA levels have predictive value in the prognosis of high-grade GEP-NENs. Preoperative CA19-9, neuron-specific enolase, and SA levels can predict the prognosis of NECs.

Integrated Genomic and Clinicopathologic Approach Distinguishes Pancreatic Grade 3 Neuroendocrine Tumor From Neuroendocrine Carcinoma and Identifies a Subset With Molecular Overlap

Distinguishing grade 3 pancreatic neuroendocrine tumor (G3 PanNET) from neuroendocrine carcinoma (PanNEC) is a known diagnostic challenge, and accurate classification is critical because clinical behavior and therapies differ. Although current recommendations suggest that immunohistochemistry for p53, Rb, ATRX, and DAXX can distinguish most cases, some cases remain difficult to classify using this approach. In this study, we reviewed 47 high-grade neoplasms originally diagnosed as pancreatic neuroendocrine neoplasms. In addition to the currently recommended stains, we performed capture-based sequencing of approximately 500 cancer genes and immunohistochemistry for p16 and trypsin or chymotrypsin. Using an integrated molecular and clinicopathologic approach, 42 (89%) of 47 cases had a clear final diagnosis of either G3 PanNET (n = 17), PanNEC (n = 17), or mixed acinar-NEC (n = 8). The 17 G3 PanNETs demonstrated frequent alterations in MEN1 (71%), DAXX (47%), ATRX (24%), TSC2 (35%), SETD2 (42%), and CDKN2A (41%). Contrary to prior reports, TP53 alterations were also common in G3 PanNETs (35%) but were always mutually exclusive with CDKN2A alterations in this group. The 17 PanNECs demonstrated frequent alterations in TP53 (88%), cell cycle genes RB1 (47%), CCNE1/CCND1 (12%), CDKN2A (29%), and in KRAS (53%) and SMAD4 (41%); TP53 was coaltered with a cell cycle gene in 76% of PanNECs. Diffuse strong p16 staining was observed in 69% of PanNECs in contrast to 0% of G3 PanNETs. The 8 acinar-NECs had recurrent alterations in ATM (25%), APC (25%), and STK11 (25%). Five cases remained difficult to classify, 3 of which exhibited overlapping molecular features with alterations in MEN1 with or without ATRX, and RB1 with or without TP53, making it unclear whether to classify as PanNET or PanNEC. Our data demonstrate that molecular profiling and immunohistochemistry for p16 greatly improve the diagnostic accuracy of high-grade pancreatic neuroendocrine neoplasms and identify a subset of rare cases with overlapping features of both PanNET and PanNEC.

Reprint of: The Diagnostic and Prognostic Utility of Incorporating DAXX, ATRX, and Alternative Lengthening of Telomeres (ALT) to the Evaluation of Pancreatic Neuroendocrine Tumors (PanNETs)

Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms with increasing incidence and an ill-defined pathobiology. Although many PanNETs are indolent and remain stable for years, a subset may behave aggressively and metastasize widely. Thus, the increasing and frequent detection of PanNETs presents a treatment dilemma. Current prognostic systems are susceptible to interpretation errors, sampling issues, and do not accurately reflect the clinical behavior of these neoplasms. Hence, additional biomarkers are needed to improve the prognostic stratification of patients diagnosed with a PanNET. Recent studies have identified alterations in death domain-associated protein 6 (DAXX) and alpha-thalassemia/mental retardation X-linked (ATRX), as well as alternative lengthening of telomeres (ALT), as promising prognostic biomarkers. This review summarizes the identification, clinical utility, and specific nuances in testing for DAXX/ATRX by immunohistochemistry and ALT by telomere-specific fluorescence in situ hybridization in PanNETs. Furthermore, a discussion on diagnostic indications for DAXX, ATRX, and ALT status is provided to include the distinction between PanNETs and pancreatic neuroendocrine carcinomas (PanNECs), and determining pancreatic origin for metastatic neuroendocrine tumors in the setting of an unknown primary.

Digital Image Analysis of Ki67 Heterogeneity Improves the Diagnosis and Prognosis of Gastroenteropancreatic Neuroendocrine Neoplasms

Ki67 is a reliable grading and prognostic biomarker of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). The intratumor heterogeneity of Ki67, correlated with tumor progression, is a valuable factor that requires image analysis. The application of digital image analysis (DIA) enables new approaches for the assessment of Ki67 heterogeneity distribution. We investigated the diagnostic utility of Ki67 heterogeneity parameters in the classification and grading of GEP-NENs and explored their clinical values with regard to their prognostic relevance. The DIA algorithm was performed on whole-slide images of 102 resection samples with Ki67 staining. Good agreement was observed between the manual and DIA methods in the hotspot evaluation (R² = 0.94, P < .01). Using the grid-based region of interest approach, score-based heat maps provided a distinctive overview of the intratumoral distribution of Ki67 between neuroendocrine carcinomas and neuroendocrine tumors. The computation of heterogeneity parameters related to DIA-determined Ki67 showed that the coefficient of variation and Morisita-Horn index were directly related to the classification and grading of GEP-NENs and provided insights into distinguishing high-grade neuroendocrine neoplasms (grade 3 neuroendocrine tumor vs neuroendocrine carcinoma, P < .01). Our study showed that a high Morisita-Horn index correlated with poor disease-free survival (multivariate analysis: hazard ratio, 56.69), which was found to be the only independent predictor of disease-free survival in patients with GEP-NEN. These spatial biomarkers have an impact on the classification and grading of tumors and highlight the prognostic associations of tumor heterogeneity. Digitization of Ki67 variations provides a direct and objective measurement of tumor heterogeneity and better predicts the biological behavior of GEP-NENs.

The diagnostic and prognostic utility of incorporating DAXX, ATRX, and alternative lengthening of telomeres to the evaluation of pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of neoplasms with increasing incidence and an ill-defined pathobiology. Although many PanNETs are indolent and remain stable for years, a subset may behave aggressively and metastasize widely. Thus, the increasing and frequent detection of PanNETs presents a treatment dilemma. Current prognostic systems are susceptible to interpretation errors, sampling issues, and do not accurately reflect the clinical behavior of these neoplasms. Hence, additional biomarkers are needed to improve the prognostic stratification of patients diagnosed with a PanNET. Recent studies have identified alterations in death domain-associated protein 6 (DAXX) and alpha-thalassemia/mental retardation X-linked (ATRX), as well as alternative lengthening of telomeres (ALT), as promising prognostic biomarkers. This review summarizes the identification, clinical utility, and specific nuances in testing for DAXX/ATRX by immunohistochemistry and ALT by telomere-specific fluorescence in situ hybridization in PanNETs. Furthermore, a discussion on diagnostic indications for DAXX, ATRX, and ALT status is provided to include the distinction between PanNETs and pancreatic neuroendocrine carcinomas (PanNECs), and determining pancreatic origin for metastatic neuroendocrine tumors in the setting of an unknown primary.

Preoperative assessment of microvessel density in nonfunctioning pancreatic neuroendocrine tumors (NF-PanNETs)

BACKGROUND

Hypervascularization is a typical feature of pancreatic neuroendocrine tumors, and it frequently allows their recognition at imaging studies. However, the density of microvessels in pancreatic neuroendocrine tumors changes according to their biological behavior, and a low microvessel density is associated with higher disease aggressiveness. The primary aim was to investigate the relationship between microvessel density and aggressiveness of nonfunctioning pancreatic neuroendocrine tumors. The secondary aim was to evaluate the ability of contrast-enhanced computed tomography and contrast-enhanced endoscopic ultrasound in predicting tumor microvessel density.

METHODS

The patients who underwent surgery for nonfunctioning pancreatic neuroendocrine tumors (n = 66) with an available preoperative contrast-enhanced computed tomography (n = 39) and/or contrast-enhanced endoscopic ultrasound (n = 37) performed at San Raffaele Hospital (2016-2020) were included. The tumor vascularization was assessed by CD-34 staining, contrast-enhanced computed tomography, and contrast-enhanced endoscopic ultrasound. Median microvessel density (165 microvessels/mm2) was chosen as the cutoff to define low microvessel density and high microvessel density.

RESULTS

The patients with a low microvessel density showed a significantly higher frequency of nodal metastases (P = .026), G2-G3 tumors (P = .022), and death domain-associated protein/α-thalassemia/mental retardation syndrome X-linked loss (P = .011) compared to patients with high microvessel density. The contrast-enhanced computed tomography tumor density in the arterial phase was significantly higher in patients with high microvessel density compared to those with low microvessel density (P = .016). The patients with a low microvessel density showed a significantly higher frequency of contrast-enhanced endoscopic ultrasound arterial hypoenhancement (P = .042) and late washout (P = .034). Contrast-enhanced computed tomography arterial hypoenhancement (P = .007) and contrast-enhanced endoscopic ultrasound late washout (P = .048) independently predicted a low microvessel density in the patients who underwent contrast-enhanced computed tomography and contrast-enhanced endoscopic ultrasound, respectively.

CONCLUSION

A low microvessel density represents a marker of aggressiveness in the patients with nonfunctioning pancreatic neuroendocrine tumors. Contrast-enhanced computed tomography and contrast-enhanced endoscopic ultrasound are reliable and easily available tools for preoperative assessment of microvessel density.

Low-grade Neuroendocrine Tumor of the Cervix: Report of 3 Cases of a Rare Neoplasm With Review of the Literature

Neuroendocrine neoplasms are uncommon in the cervix with almost all representing neuroendocrine carcinomas (NECs), either small cell or large cell type. Cervical low-grade neuroendocrine tumors (NETs) are extremely rare with few recent reports using contemporary modern diagnostic criteria. We report 3 cases of cervical NET in patients aged 32 to 57 yr and undertake a review of the literature. The first case was a pure grade 2 NET with pelvic lymph node metastasis (FIGO stage IIIC1). In the second case, a grade 1 NET was associated with high-grade squamous intraepithelial lesion, adenocarcinoma in situ and human papillomavirus (HPV)-associated adenocarcinoma and was FIGO stage IA1. The third patient underwent chemoradiotherapy following a biopsy diagnosis of a high-grade NEC which was radiologically FIGO stage IIIC1 and salvage hysterectomy revealed residual tumor with features of a grade 1 NET. In all cases, the NET was diffusely positive with at least 2 of the neuroendocrine markers chromogranin, synaptophysin, and CD56. The first tumor was p16 negative and the third exhibited block-type immunoreactivity. Molecular tests revealed high risk HPV types 18 and 51 in the third case but no HPV in the first case. p16 immunohistochemistry and HPV molecular testing was not available in the second case. The patients remain disease free with follow-up ranging from 2 to 8 yr. Since a combination of NET and NEC is extremely rare at all sites due to a different pathogenesis, we speculate that in the third case, the NET developed out of the NEC as a "maturation" phenomenon secondary to chemoradiotherapy.

Quantitative analysis of enhanced CT in differentiating well-differentiated pancreatic neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas

OBJECTIVE

To identify quantitative CT features for distinguishing well-differentiated pancreatic neuroendocrine tumors (PNETs) from poorly differentiated pancreatic neuroendocrine carcinomas (PNECs).

MATERIALS AND METHODS

Seventeen patients with PNECs and 131 patients with PNETs confirmed by biopsy or surgery were retrospectively included. General demographic (sex, age) and CT quantitative parameters (arterial/portal absolute enhancement, arterial/portal relative enhancement ratio, arterial/portal enhancement ratio) were collected. Univariate and multivariate logistic regression analyses were performed to confirm independent variables for differentiating PNECs from PNETs. Receiver operating characteristic (ROC) curves for each quantitative parameter were generated to determine their diagnostic ability.

RESULTS

PNECs had a much lower mean arterial/portal absolute enhancement value (19.5 ± 11.0 vs. 78.8 ± 47.2; 28.1 ± 15.8 vs. 77.0 ± 39.4), arterial/portal relative enhancement ratio (0.57 ± 0.36 vs. 2.03 ± 1.31; 0.80 ± 0.52 vs. 1.99 ± 1.13), and arterial/portal enhancement ratio (0.62 ± 0.27 vs. 1.22 ± 0.49; 0.74 ± 0.19 vs. 1.21 ± 0.36) than PNETs (all p < 0.001). After multivariable analysis, arterial absolute enhancement (odds ratio [OR]: 0.96, 95% confidence interval [CI]: 0.93, 0.99) and portal absolute enhancement (OR: 0.96, 95% CI: 0.92, 0.99) were independent factors for differentiating PNECs from PNETs. For each quantitative parameter, arterial lesion enhancement yielded the highest diagnostic performance, with an area under the curve (AUC) of 0.922 (95% CI: 0.867-0.960), followed by portal absolute enhancement.

CONCLUSIONS

Arterial/portal absolute enhancements were independent predictors with good diagnostic accuracy for differentiating between PNETs and PNECs. Quantitative parameters of enhanced CT can distinguish PNECs from PNETs.

KEY POINTS

• PNECs were hypovascular and had a much lower enhanced CT attenuation in both arterial and portal phases than well-differentiated PNETs. • Quantitative parameters derived from enhanced CT can be used to distinguish PNECs from PNETs. • Arterial absolute enhancement and portal absolute enhancement were independent predictive factors for differentiating between PNETs and PNECs.

Recent advances in diagnosis and treatment of gastroenteropancreatic neuroendocrine neoplasms

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are a rare group of tumors originating from neuroendocrine cells of the digestive system. Their incidence has increased over the last decades. The specific pathogenetic mechanisms underlying GEP-NEN development have not been completely revealed. Unfunctional GEP-NENs are usually asymptomatic; some grow slowly and thus impede early diagnosis, which ultimately results in a high rate of misdiagnosis. Therefore, many GEP-NEN patients present with later staged tumors. Motivated hereby, research attention for diagnosis and treatment for GEP-NENs increased in recent years. The result of which is great progress in clinical diagnosis and treatment. According to the most recent clinical guidelines, improved grading standards can accurately define poorly differentiated grade 3 neuroendocrine tumors and neuroendocrine carcinomas (NECs), which are subclassified into large and small cell NECs. Combining different functional imaging methods facilitates precise diagnosis. The expression of somatostatin receptors helps to predict prognosis. Genetic analyses of mutations affecting death domain associated protein (DAXX), multiple endocrine neoplasia type 1 (MEN 1), alpha thalassemia/intellectual disability syndrome X-linked (ATRX), retinoblastoma transcriptional corepressor 1 (RB 1), and mothers against decapentaplegic homolog 4 (SMAD 4) help distinguishing grade 3 NENs from poorly differentiated NECs. The aim of this review is to summarize the latest research progress on diagnosis and treatment of GEP-NENs.

Predictive Factors for Resistant Disease with Medical/Radiologic/Liver-Directed Anti-Tumor Treatments in Patients with Advanced Pancreatic Neuroendocrine Neoplasms: Recent Advances and Controversies

Purpose: Recent advances in the diagnosis, management and nonsurgical treatment of patients with advanced pancreatic neuroendocrine neoplasms (panNENs) have led to an emerging need for sensitive and useful prognostic factors for predicting responses/survival. Areas covered: The predictive value of a number of reported prognostic factors including clinically-related factors (clinical/laboratory/imaging/treatment-related factors), pathological factors (histological/classification/grading), and molecular factors, on therapeutic outcomes of anti-tumor medical therapies with molecular targeting agents (everolimus/sunitinib/somatostatin analogues), chemotherapy, radiological therapy with peptide receptor radionuclide therapy, or liver-directed therapies (embolization/chemoembolization/radio-embolization (SIRTs)) are reviewed. Recent findings in each of these areas, as well as remaining controversies and uncertainties, are discussed in detail, particularly from the viewpoint of treatment sequencing. Conclusions: The recent increase in the number of available therapeutic agents for the nonsurgical treatment of patients with advanced panNENs have raised the importance of prognostic factors predictive for therapeutic outcomes of each treatment option. The establishment of sensitive and useful prognostic markers will have a significant impact on optimal treatment selection, as well as in tailoring the therapeutic sequence, and for maximizing the survival benefit of each individual patient. In the paper, the progress in this area, as well as the controversies/uncertainties, are reviewed.

Lung neuroendocrine neoplasms: recent progress and persistent challenges

This review summarizes key recent developments relevant to the pathologic diagnosis of lung neuroendocrine neoplasms, including carcinoids, small cell lung carcinoma (SCLC), and large cell neuroendocrine carcinoma (LCNEC). Covered are recent insights into the biological subtypes within each main tumor type, progress in pathological diagnosis and immunohistochemical markers, and persistent challenging areas. Highlighted topics include highly proliferative carcinoids and their distinction from small cell and large cell neuroendocrine carcinomas (NECs), the evolving role of Ki67, the update on the differential diagnosis of NEC to include thoracic SMARCA4-deficient undifferentiated tumors, the recent data on SCLC transcriptional subtypes with the emergence of POU2F3 as a novel marker for the diagnosis of SCLC with low/negative expression of standard neuroendocrine markers, and the update on the diagnosis of LCNEC, particularly in biopsies. There has been remarkable recent progress in the understanding of the genetic and expression-based profiles within each type of lung neuroendocrine neoplasm, and it is hoped that these insights will enable the development of novel diagnostic, prognostic, and predictive biomarkers to aid in the pathologic assessment of these tumors in the future.

Genetic and immunohistochemical profiling of small cell and large cell neuroendocrine carcinomas of the breast

Neuroendocrine carcinomas (NEC) of the breast are exceedingly rare tumors, which are classified in the WHO system as small cell (SCNEC) and large cell (LCNEC) carcinoma based on indistinguishable features from their lung counterparts. In contrast to lung and enteropancreatic NEC, the genomics of breast NEC have not been well-characterized. In this study, we examined the clinicopathologic, immunohistochemical, and genetic features of 13 breast NEC (7 SCNEC, 4 LCNEC, 2 NEC with ambiguous small versus large cell morphology [ANEC]). Co-alterations of TP53 and RB1 were identified in 86% (6/7) SCNEC, 100% (2/2) ANEC, and 50% (2/4) LCNEC. The one SCNEC without TP53/RB1 alteration had other p53 pathway aberrations (MDM2 and MDM4 amplification) and was immunohistochemically RB negative. PIK3CA/PTEN pathway alterations and ZNF703 amplifications were each identified in 46% (6/13) NEC. Two tumors (1 SCNEC, 1 LCNEC) were CDH1 mutated. By immunohistochemistry, 100% SCNEC (6/6) and ANEC (2/2) and 50% (2/4) LCNEC (83% NEC) showed RB loss, compared to 0% (0/8) grade 3 neuroendocrine tumors (NET) (p < 0.001) and 38% (36/95) grade 3 invasive ductal carcinomas of no special type (IDC-NST) (p = 0.004). NEC were also more often p53 aberrant (60% vs 0%, p = 0.013), ER negative (69% vs 0%, p = 0.005), and GATA3 negative (67% vs 0%, p = 0.013) than grade 3 NET. Two mixed NEC had IDC-NST components, and 69% (9/13) of tumors were associated with carcinoma in situ (6 neuroendocrine DCIS, 2 non-neuroendocrine DCIS, 1 non-neuroendocrine LCIS). NEC and IDC-NST components of mixed tumors were clonally related and immunophenotypically distinct, lacking ER and GATA3 expression in NEC relative to IDC-NST, with RB loss only in NEC of one ANEC. The findings provide insight into the pathogenesis of breast NEC, underscore their classification as a distinct tumor type, and highlight genetic similarities to extramammary NEC, including highly prevalent p53/RB pathway aberrations in SCNEC.

Enhanced computed tomography features predict pancreatic neuroendocrine neoplasm with Ki-67 index less than 5

BACKGROUND

Several studies have suggested that patients with pancreatic neuroendocrine neoplasm (pNEN) with the Ki-67 index of < 5% are more likely to show better prognosis after clinical intervention. Moreover, the Ki-67 index at 5% has also been suggested as a potential threshold by the 2016 European Neuroendocrine Tumor Society guidelines.

OBJECTIVE

Based on preoperative enhanced computed tomography (CT), this study aimed to investigate imaging characteristics eligible to discriminate the ≤ 5% Ki-67 group from the > 5% Ki-67 group of patients with nonmetastatic pNEN.

METHODS

Patients with pathologically diagnosed pNEN and preoperative multiphase CT were enrolled. Their Ki-67 index was calculated and grouped according to the 5% cutoff value. The following CT imaging characteristics and some serum biomarkers were assessed between the two groups: the diameter, location, tumor margin, calcification, pancreatic atrophy, distal pancreatic duct dilation, vessel involvement, and enhancement pattern characteristics of both arterial phase (AP) and portal vein phase (PVP).

RESULTS

A total of 142 patients with pNEN were enrolled in this study, comprising 104 in the low (Ki-67, 1%-5%) and 38 in the high index group (Ki-67, >5%). Alpha fetoprotein and cancer antigen 125 were significantly different between the two groups (P-values, 0.030 and 0.049, respectively). The diameter (P < 0.0001), margin (P = 0.003), distal main ductal dilation (P = 0.021), vessel involvement (P = 0.002), AP hypoenhancement (P < 0.0001), PVP hypoenhancement (P = 0.003), AP ratio (P = 0.0001), and PVP ratio (P = 0.0003) were significantly different between the low and high index groups. The area under the curve of the multivariate logistic regression model was 0.853.

CONCLUSION

Nonmetastatic pNENs with larger diameter, ill-defined margin, distal main ductal dilation, and tumor hypoenhancement in AP in preoperative enhanced CT tend to have a Ki-67 index of > 5%.The results of this study provide an alternative method to clinicians to decide whether surgery is appropriate.

Discordance between Histopathological grading and Dual Tracer PET-CT findings (68Ga-DOTATATE and FDG) in metastatic Neuroendocrine Neoplasms and outcome of 177Lu-DOTATATE PRRT: does in-vivo molecular PET imaging perform better from 'prediction of tumour biology' viewpoint?

Background and Aim: Discordance between histopathological grading and dual tracer PET-CT (⁶⁸Ga-DOTATATE and FDG) findings in neuroendocrine tumours (NETs), though not typical, can be encountered in real-world scenario. The aim of this study was to assess patients with discordance between WHO 2017 grade predicted molecular PET-CT imaging and the actual dual tracer PET-CT findings (by exploring their histopathological, immunohistochemical and molecular imaging characteristics), with a view to identifying the prognostic determinants effecting outcome in a peptide receptor radionuclide therapy (PRRT) set-up. Methods: Thirty six patients of histopathologically proven inoperable, locally advanced/metastatic NETs, referred for PRRT were included in this study. The cohort was divided into two broad population groups: (a) those with discordance (between WHO 2017 grade predicted molecular imaging and the dual tracer PET-CT findings) and (b) control (showing both FDG and ⁶⁸Ga-DOTATATE uptake). The cohort was divided based on dual tracer PET-CT into: (i) metabolically FDG non-avid and SSTR expressing tumors, (ii) metabolically active and non-⁶⁸Ga-DOTATATE concentrating (SSTR expressing) and (iii) matched imaging characteristics with WHO 2017 grading system (showing both FDG and ⁶⁸Ga-DOTATATE concentrating disease) for statistical analysis. Statistical analyses were done on SPSS 23.0. Descriptive statistics was used to analyze categorical data, multivariate analysis was used to assess the correlation between different variables with progression free survival (PFS) and overall survival (OS). Kaplan-Meier was used for survival analysis to calculate median survival and to analyze the survival based on WHO 2017 grading and dual tracer PET. Cox proportional hazards regression analysis was used to determine predictors of survival (OS and PFS). Results: In the entire cohort (n = 36), 24 patients (66.7%) showed discordance whereas 12 patients (33.3%) were in the control group. Among the patients showing discordance: 14 patients (38.9%) had metabolically inactive and SSTR expressing disease and remaining 10 patients (27.8%) had FDG concentrating and SSTR non-expressing disease. Those in the control group, 12 patients (33.3%) had intermediate grade NETs and showed matched (⁶⁸Ga-DOTATATE and FDG concentrating lesions) disease. Multivariate analysis in patients with discordant findings demonstrated significant correlation of dual tracer PET with overall survival while no significant correlation could be established between WHO grade and overall survival in the discordant subgroups. No significant correlation could be appreciated between PFS and either dual tracer PET or WHO grading. The Kaplan-Meier survival analysis and Cox proportional hazards regression analysis demonstrated dual tracer PET-CT imaging to be significant prognostic determinant and predictor of outcome respectively. Conclusion: In summary, in NET patients with discordance between the two parameters, dual tracer PET-CT with FDG and ⁶⁸Ga-DOTATATE performed better than WHO grading, differentiation status and immunohistochemistry in prognosticating and predicting outcome.

Gastroenteropancreatic neuroendocrine neoplasms G3: Novel insights and unmet needs

According to the 2019 WHO pathology grading system, high-grade gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) can be divided into well differentiated neuroendocrine tumors G3 (NETs G3) and poorly differentiated neuroendocrine carcinomas (NECs). GEP-NETs G3 and GEP-NECs present significant differences in driver genes and disease origin. NETs G3 and NECs have been confirmed to be two distinct diseases with different genetic backgrounds, however, this issue remains controversial. The prognosis of NETs G3 is significantly better than that of NECs. The differential diagnosis of GEP-NETs G3 and GEP-NECs should be combined with the patient's medical history, tumor histopathology, Ki-67 index, DAXX/ATRX, TP53 and Rb expression as well as other immunohistochemical indicators. In addition, the treatment strategies of these two subgroups are very different. Here, we summarize recent findings focused on the genomics, clinical manifestations, diagnosis, treatment and other aspects of high-grade GEP-NENs (G3). This review may help further our understanding of the carcinogenesis, diagnosis and treatment of GEP-NENs G3.

Biliary Strictures and Cholangiocarcinoma - Untangling a Diagnostic Conundrum

Cholangiocarcinoma is an uncommon and highly aggressive biliary tract malignancy with few manifestations until late disease stages. Diagnosis is currently achieved through a combination of clinical, biochemical, radiological and histological techniques. A number of reported cancer biomarkers have the potential to be incorporated into diagnostic pathways, but all lack sufficient sensitivity and specificity limiting their possible use in screening and early diagnosis. The limitations of standard serum markers such as CA19-9, CA125 and CEA have driven researchers to identify multiple novel biomarkers, yet their clinical translation has been slow with a general requirement for further validation in larger patient cohorts. We review recent advances in the diagnostic pathway for suspected CCA as well as emerging diagnostic biomarkers for early detection, with a particular focus on non-invasive approaches.

Imaging of Pancreatic Neuroendocrine Neoplasms

Pancreatic neuroendocrine neoplasms (panNENs) represent the second most common pancreatic tumors. They are a heterogeneous group of neoplasms with varying clinical expression and biological behavior, from indolent to aggressive ones. PanNENs can be functioning or non-functioning in accordance with their ability or not to produce metabolically active hormones. They are histopathologically classified according to the 2017 World Health Organization (WHO) classification system. Although the final diagnosis of neuroendocrine tumor relies on histologic examination of biopsy or surgical specimens, both morphologic and functional imaging are crucial for patient care. Morphologic imaging with ultrasonography (US), computed tomography (CT) and magnetic resonance imaging (MRI) is used for initial evaluation and staging of disease, as well as surveillance and therapy monitoring. Functional imaging techniques with somatostatin receptor scintigraphy (SRS) and positron emission tomography (PET) are used for functional and metabolic assessment that is helpful for therapy management and post-therapeutic re-staging. This article reviews the morphological and functional imaging modalities now available and the imaging features of panNENs. Finally, future imaging challenges, such as radiomics analysis, are illustrated.

What is New in the 2019 World Health Organization (WHO) Classification of Tumors of the Digestive System: Review of Selected Updates on Neuroendocrine Neoplasms, Appendiceal Tumors, and Molecular Testing

CONTEXT.—

The 5th edition of the World Health Organization classification of digestive system tumors discusses several advancements and developments in understanding the etiology, pathogenesis, and diagnosis of several digestive tract tumors.

OBJECTIVE.—

To provide a summary of the updates with a focus on neuroendocrine neoplasms, appendiceal tumors, and the molecular advances in tumors of the digestive system.

DATA SOURCES.—

English literature and personal experiences.

CONCLUSIONS.—

Some of the particularly important updates in the 5th edition are the alterations made in the classification of neuroendocrine neoplasms, understanding of pathogenesis of appendiceal tumors and their precursor lesions, and the expanded role of molecular pathology in establishing an accurate diagnosis or predicting prognosis and response to treatment.

Diagnostic and Predictive Role of DLL3 Expression in Gastroenteropancreatic Neuroendocrine Neoplasms

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are a rare and heterogeneous subgroup of tumors with a challenging management because of their extremely variable biological and clinical behaviors. Due to their different prognosis, there is an urgent need to identify molecular markers which would enable to discriminate between grade 3 neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs), despite both being diagnosed mainly on the basis of proliferation index and cell differentiation. DLL3, a negative Notch regulator, is a promising molecular target highly expressed in several tumors with neuroendocrine features. We conducted a retrospective analysis of DLL3, RB1, and PD-L1 expression by immunohistochemistry (IHC), in formalin-fixed, paraffin-embedded (FFPE) samples from 47 patients with GEP-NENs. Then, we correlated the results with patients' clinical features and outcome. The absence of DLL3 expression in 5 well-differentiated GEP-NETs with high-grade features (G3 NET), and the presence of DLL3 in 76.9% of poorly-differentiated NECs (G3 NEC), highlights DLL3 expression as a marker of G3 NECs (p = 0.007). DLL3 expression was correlated with RB1-loss (p < 0.001), negative ⁶⁸ Ga-PET/CT scan (p = 0.001), and an unfavorable clinical outcome, with important implications for treatment response and patient's follow-up. Median progression-free survival (PFS) and overall survival (OS) were 22.7 months (95% CI 6.1-68.8) and 68.8 months (95% CI 26.0-78.1), respectively, in patients with DLL3-negative tumor compared with 5.2 months (95% CI 2.5-18.5) and 9.5 months (95% CI 2.5-25.2), respectively, in patients with DLL3-positive tumor (PFS p = 0.0083, OS p = 0.0071). Therefore, combined with morphological cell analysis, DLL3 could represent a valuable histological marker, for the diagnosis of poorly differentiated NECs. The high percentage of DLL3 expression in NEC patients also highlights a potential opportunity for a DLL3 targeted therapy in this tumor subset.

Increased neutrophil-lymphocyte ratio predicts recurrence in patients with well-differentiated pancreatic neuroendocrine neoplasm based on the 2017 World Health Organization classification

Background

The prognostic values of inflammation-based markers in well-differentiated pancreatic neuroendocrine neoplasms, diagnosed according to the new 2017 World Health Organization classification, have remained unclear. Therefore, we assessed the ability to predict the recurrence of such markers after curative resection in patients with these neoplasms.

Methods

Circulating/systemic neutrophil–lymphocyte, monocyte–lymphocyte, platelet–lymphocyte, and platelet–white cell ratios were evaluated in 120 patients who underwent curative resection for well-differentiated pancreatic neuroendocrine neoplasms without synchronous distant metastasis between 2001 and 2018. Recurrence-free-survival and overall survival were compared using Kaplan–Meier analysis and log-rank tests. Univariate or multivariate analyses, using a Cox proportional hazards model, were used to calculate hazard ratios with 95% confidence intervals.

Results

Univariate analysis demonstrated that preoperative neutrophil–lymphocyte ratio, tumor size, European Neuroendocrine Tumor Society TMN classification, 2017 World Health Organization classification, and venous invasion were associated with recurrence. The optimal preoperative neutrophil–lymphocyte ratio cut-off value was 2.62, based on receiver operating characteristic curve analysis. In multivariate analysis, a higher preoperative neutrophil–lymphocyte ratio (HR = 3.49 95% CI 1.05–11.7; P = 0.042) and 2017 World Health Organization classification (HR = 8.81, 95% CI 1.46–168.2; P = 0.015) were independent recurrence predictors.

Conclusions

The circulating/systemic neutrophil–lymphocyte ratio is a useful and convenient preoperative prognostic marker of recurrence in patients with well-differentiated pancreatic neuroendocrine neoplasm based on the 2017 World Health Organization classification.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12893-021-01178-3.

Diagnosis of digestive system tumours

The WHO Classification of Tumours provides the international standards for the classification and diagnosis of tumours. It enables direct comparisons to be made between different countries. In the new fifth edition, the series has gone digital with the launch of a website as well as a series of books, known widely as the WHO Blue Books. The first volume to be produced is on the classification of Digestive System tumours, replacing the successful 2010 version. It has been rewritten and updated accordingly. This article summarises the major diagnostic innovations that have occurred over the last decade and that have now been incorporated in the classification. As an example, it incorporates the recently proposed classification of neuroendocrine tumours, based on the recognition that neuroendocrine tumours and carcinomas differ substantially in the genetic abnormalities that drive their growth, findings relevant to treatment selection and outcome prediction. Several themes have emerged during the production process. One is the importance of the progression from hyperplasia to dysplasia to carcinoma in the evolution of the malignant process. Advances in imaging techniques and endoscopy have resulted in enhanced access to precancerous lesions in the gastrointestinal and biliary tract, necessitating both changes in classification schema and clinical practice. Diagnosis of tumours is no longer the sole purview of pathologists, and some patients now receive treatment before tissue is obtained, based on clinical, radiological and liquid biopsy results. This makes the classification relevant to many disciplines involved in the care of patients with tumours of the digestive system.

Treatment personalization in gastrointestinal neuroendocrine tumors

The clinical scenario of gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) is continuously changing due to significant improvements in the definition of their molecular landscapes and the introduction of innovative therapeutic approaches. Many efforts are currently employed in the integration of the genetics/epigenetics and clinical information. This is leading to an improvement of tumor classification, prognostic stratification and ameliorating the management of patients based on a personalized approach.

Microscopic Invasion of Nerve Is Associated With Aggressive Behaviors in Pancreatic Neuroendocrine Tumors

Objectives

The role of neural invasion has been reported in cancers. Few studies also showed that neural invasion was related to survival rate in patients with pancreatic neuroendocrine tumor (PNET). The aim of this study is to explore the association between neural invasion and aggressive behaviors in PNET.

Methods

After excluding those patients with biopsy and with missing histological data, a total 197 patients with PNET who underwent surgery were retrospectively analyzed. The demographic data and histological data were obtained. Aggressive behavior was defined based on extra-pancreatic extension including vascular invasion, organ invasion and lymph node metastases. Logistic regression analyses were used to identify risk factor for aggressive behavior. Receiver operating characteristic (ROC) curves were performed to show the performance of nomograms in evaluating aggressive behavior of PNET.

Results

The prevalence of neural invasion in the cohort was 10.1% (n = 20). The prevalence of lymph node metastasis, organ invasion, and vascular invasion in PNET patients with neural invasion was higher than those in patients without neural invasion (p < 0.05). Neural invasion was more common in grade 3 (G3) tumors than G1/G2 (p < 0.01). Tumor size, tumor grade, and neural invasion were independent associated factors of aggressive behavior (p < 0.05) after adjusting for possible cofounders in total tumors and G1/G2 tumors. Two nomograms were developed to predict the aggressive behavior. The area under the ROC curve was 0.84 (95% confidence interval (CI): 0.77–0.90) for total population and was 0.84 (95% CI: 0.78–0.89) for patients with G1/G2 PNET respectively.

Conclusions

Neural invasion is associated with aggressive behavior in PNET. Nomograms based on tumor size, grade and neural invasion show acceptable performances in predicting aggressive behavior in PNET.

Predicting Metastasis Risk in Pancreatic Neuroendocrine Tumors Using Deep Learning Image Analysis

BACKGROUND

The prognosis of patients with pancreatic neuroendocrine tumors (PanNET), the second most common type of pancreatic cancer, varies significantly, and up to 15% of patients develop metastasis. Although certain morphological characteristics of PanNETs have been associated with patient outcome, there are no available morphology-based prognostic markers. Given that current clinical histopathology markers are unable to identify high-risk PanNET patients, the development of accurate prognostic biomarkers is needed. Here, we describe a novel machine learning, multiclassification pipeline to predict the risk of metastasis using morphological information from whole tissue slides.

METHODS

Digital images from surgically resected tissues from 89 PanNET patients were used. Pathologist-annotated regions were extracted to train a convolutional neural network (CNN) to identify tiles consisting of PanNET, stroma, normal pancreas parenchyma, and fat. Computationally annotated cancer or stroma tiles and patient metastasis status were used to train CNN to calculate a region based metastatic risk score. Aggregation of the metastatic probability scores across the slide was performed to predict the risk of metastasis.

RESULTS

The ability of CNN to discriminate different tissues was high (per-tile accuracy >95%; whole slide cancer regions Jaccard index = 79%). Cancer and stromal tiles with high evaluated probability provided F1 scores of 0.82 and 0.69, respectively, when we compared tissues from patients who developed metastasis and those who did not. The final model identified low-risk (n = 76) and high-risk (n = 13) patients, as well as predicted metastasis-free survival (hazard ratio: 4.71) after adjusting for common clinicopathological variables, especially in grade I/II patients.

CONCLUSION

Using slides from surgically resected PanNETs, our novel, multiclassification, deep learning pipeline was able to predict the risk of metastasis in PanNET patients. Our results suggest the presence of prognostic morphological patterns in PanNET tissues, and that these patterns may help guide clinical decision making.

Correlation between contrast enhancement, standardized uptake value (SUV), and diffusion restriction (ADC) with tumor grading in patients with therapy-naive neuroendocrine neoplasms using hybrid 68Ga-DOTATOC PET/MRI

OBJECTIVES

To investigate a correlation between ⁶⁸Ga-DOTATOC PET/MR imaging parameters such as arterial and venous contrast enhancement, diffusion restriction, and maximum standardized uptake value (SUVmax) with histopathological tumor grading in patients with neuroendocrine neoplasms (NEN).

MATERIAL AND METHODS

A total of 26 patients with newly diagnosed, therapy-naive neuroendocrine neoplasms (NEN) were enrolled in this prospective study and underwent ⁶⁸Ga-DOTATOC PET/MRI. Images were evaluated regarding NEN lesion number and location, predominant tumor signal intensity on precontrast T1w and T2w images and on postcontrast arterial and portal venous phase T1w images, apparent diffusion coefficient (ADC) and SUVmax. Histopathological tumor grading was assessed and related to PET/MRI features using Pearson's correlation coefficient and Fisher's exact t-test. A binary logistic regression analysis was performed to evaluate a potential relation with an aggressive tumor biology and odds ratios (OR) were calculated.

RESULTS

There was a moderate negative correlation between arterial contrast enhancement and tumor grading (r=-0.35, p = 0.005), while portal venous enhancement showed a weak positive correlation with the Ki-67 index (r = 0.28, p = 0.008) and a non-significant positive correlation with tumor grading (r = 0.19, p = 0.063). Features that were significantly associated with an aggressive tumor biology were the presence of liver metastases (OR 2.6, p = 0.042), T1w hyperintensity in comparison to muscle (OR 12.7, p = 0.0001), arterial phase hyperenhancement (OR 1.4, p = 0.001), diffusion restriction (OR 2.8, p = 0.02) and SUVmax above the hepatic level (OR 7.0, p = 0.001).

CONCLUSION

The study reveals that PET/MRI features might be useful for prediction of NEN grading and thus provide a preliminary assessment of tumor aggressiveness.

High pre-operative fasting blood glucose levels predict a poor prognosis in patients with pancreatic neuroendocrine tumour

BACKGROUND

Hyperglycaemia has been indicated as a pro-tumoural factor; however, the prognostic role of diabetes mellitus (DM) in pancreatic neuroendocrine tumours (panNETs) remains ambiguous, partly due to the effects of anti-diabetic drugs. We hypothesise that the blood sugar level per se affects the outcome of panNETs, and thus, we investigated the prognostic significance of the fasting blood glucose (FBG) level in resected panNET patients with no pre-existing DM.

METHODS

A retrospective cohort study comprising 201 patients with radically resected non-functional panNETs was conducted. A total of 164 patients without pre-existing DM were further studied. An FBG level greater than 5.6 mmol/L was defined as high (otherwise, normal). Survival was evaluated using Kaplan-Meier methods and log-rank tests. Multivariate analyses for survival were performed using the Cox regression model.

RESULTS

High FBG levels were significantly associated with poor overall survival (OS; p = 0.019) and recurrence-free survival (RFS; p = 0.011) in resected patients with panNET who had no pre-existing DM. The multivariable-adjusted hazard ratios (HRs) for mortality and recurrence comparing patients with high and normal FBG levels were 12.19 (95% confidence interval (CI) = 1.15-128.78, p = 0.038) and 2.43 (95% CI = 1.03-5.72, p = 0.042), respectively.

CONCLUSION

A pre-operative FBG level greater than 5.6 mmol/L is associated with poor OS and RFS metastasis for patients with panNET who undergo radical surgical resection.

Neuroendocrine carcinoma and mixed neuroendocrine‒non-neuroendocrine neoplasm of the stomach: a clinicopathological and exome sequencing study

The gene mutation profiles of gastric neuroendocrine neoplasms are incompletely understood. The purpose of this study was to characterize the molecular pathology of poorly differentiated neuroendocrine carcinoma (NEC) and mixed neuroendocrine‒non-neuroendocrine neoplasm (MiNEN) of the stomach. Surgical cases of gastric NEC (n = 7) and MiNEN (n = 6) were examined by clinical review, immunohistochemistry, microsatellite instability (MSI) analysis and whole-exome sequencing. NEC cases consisted of small- (n = 2) and large-cell types (n = 4). All cases of MiNEN were histologically composed of large-cell type NEC and tubular adenocarcinoma. Whole-exome sequencing analysis detected recurrent mutations in TP53 in 8 cases (62%), and they were more frequently observed in MiNEN than in NEC (100% vs. 29%). Frameshift mutations of APC were observed in two cases of MiNEN. One case of large-cell type NEC had a frameshift mutation with loss of heterozygosity in RB1. The other mutated genes (e.g., ARID1 and KRAS) were detected in a single case each. A high level of MSI was confirmed in one case of MiNEN, which harbored mutations in two well-differentiated neuroendocrine tumor (NET)-related genes (MEN1 and ATRX1). In cases of MiNEN, two histological components shared mutations in TP53, APC and ZNF521, whereas alterations in CTNNB1, KMT2C, PTEN and SPEN were observed in neuroendocrine components only. In conclusion, TP53 is a single, frequently mutated gene in gastric NEC and MiNEN, and alterations in other genes are less common, resembling the mutation profiles of gastric adenocarcinomas. Gene mutations frequently observed in well-differentiated NET were uncommon but not entirely exclusive.

Correlation between radiologic features on contrast-enhanced CT and pathological tumor grades in pancreatic neuroendocrine neoplasms

Contrast-enhanced computed tomography (CT) contributes to the increasing detection of pancreatic neuroendocrine neoplasms (PNENs). Nevertheless, its value for differentiating pathological tumor grades is not well recognized. In this report, we have conducted a retrospective study on the relationship between the 2017 World Health Organization (WHO) classification and CT imaging features in 94 patients. Most of the investigated features eventually provided statistically significant indicators for discerning PNENs G3 from PNENs G1/G2, including tumor size, shape, margin, heterogeneity, intratumoral blood vessels, vascular invasion, enhancement pattern in both contrast phases, enhancement degree in both phases, tumor-to-pancreas contrast ratio in both phases, common bile duct dilatation, lymph node metastases, and liver metastases. Ill-defined tumor margin was an independent predictor for PNENs G3 with the highest area under the curve (AUC) of 0.906 in the multivariable logistic regression and receiver operating characteristic curve analysis. The portal enhancement ratio (PER) was shown the highest AUC of 0.855 in terms of quantitative features. Our data suggest that the traditional contrast-enhanced CT still plays a vital role in differentiation of tumor grades and heterogeneity analysis prior to treatment.

Surgical resection of primary tumor is associated with prolonged survival in low-grade pancreatic neuroendocrine tumors

INTRODUCTION

The incidence of pancreatic neuroendocrine tumors (PNETs) is increasing over the past few decades. Surgery for low-grade and small PNETs of less than 2cm and N0M0 is still debated. The purpose of this study is to examine the association between surgical resection and survival in patients with low-grade nonfunctioning PNETs.

MATERIALS AND METHODS

Patients diagnosed with PNETs between 2004 and 2015 were extracted from SEER. Kaplan-Meier methods and Cox proportional hazard models were used to estimate independent predictors in PNETs patients.

RESULTS

A total of 2637 patients (2147 underwent surgical resection and 490 did not undergo surgery) with histologically confirmed low-grade PNETs in this cohort study. Overall survival (OS) and cancer-specific survival (CSS) of patients with surgery was better than those without surgery (log rank test P_OS<0.001, P_CSS<0.001). Multivariate Cox regression analysis showed that surgical status was an independent prognostic factor associated with OS (HR 3.257, 95%CI: 2.635, 4.026) and CSS (HR 3.546, 95%CI: 2.798, 4.493). Subgroup analysis suggested the patients receiving surgery apparently had better OS and CSS regardless of tumor size (all log rank test P_OS<0.001, all log rank test P_CSS<0.001) and SEER stage (all log rank test P_OS<0.001, all log rank test P_CSS<0.001), compared to patients without removal of the primary tumor.

CONCLUSIONS

Surgical resection of primary tumor may have a significant benefit on survival for patients with low-grade nonfunctioning PNETs. To determine the optimal management, grade, stage and tumor size should be considered comprehensively.

Why did they change that? Practical implications of the evolving classification of neuroendocrine tumours of the gastrointestinal tract

Neuroendocrine neoplasms (NENs) of the gastrointestinal tract (GIT) comprise neuroendocrine tumours (NETs) and neuroendocrine carcinomas (NECs). During the last decade the classification and grading of GIT NENs has undergone significant changes, culminating in the World Health Organisation (WHO) 2019 classification. These changes, some of which are attributable to an only partially successful attempt to achieve uniform nomenclature among different organs, include: slight changes to the cut-off used for the Ki-67 proliferative index to distinguish grade 1 from grade 2 NETs; an emphasis on the distinction between grade 3 NETs (low-grade NETs with a high proliferative rate) and NECs which, by definition, are all high grade; classification of tumours with mixed non-neuroendocrine and neuroendocrine differentiation as MiNENs; and replacement of the term 'goblet cell carcinoid' with 'goblet cell adenocarcinoma'. While some of these changes seem minor, even semantic, each was made for very specific reasons which reflect an improved understanding of neuroendocrine neoplasia. The changes have definite implications for pathologists in clinical practice, not all of which may be readily apparent. This review is an attempt to explain the background behind each of the recent changes to the classification of neuroendocrine neoplasms of the gastrointestinal tract and summarise their impact on surgical pathologists - including a guide on how to approach certain recurrent difficulties encountered with the WHO 2019 system in routine clinical practice.

Meta-Analysis of Prognostic Factors for Recurrence of Resected Well-Differentiated Pancreatic Neuroendocrine Tumors

INTRODUCTION

Well-differentiated pancreatic neuroendocrine tumors (WDPNETs) are a group of rare and heterogeneous tumors. However, the prognostic factors for recurrence after curative resection still remain controversial. We aim to illustrate the prognostic factors for recurrence of resected WDPNETs.

METHODS

All relevant articles published through June 2020 were identified via PubMed, Embase, Web of Science, and Cochrane Library. Articles that examined the prognostic factors of WDPNETs were enrolled.

RESULTS

Ten articles were finally included in this study. From 1993 to 2018, 2,863 patients underwent curative resection and 358 patients had recurrence, and the combined recurrence rate was 13%. Furthermore, the pooled data indicated that patients with G2, positive lymph node and surgical resection margin, vascular invasion, and perineural invasion had a decreased disease-free survival for WDPNETs. However, gender, function, and tumor size had no significant relationship with WDPNETs recurrence.

CONCLUSION

These findings demonstrated that G2, positive lymph node and surgical resection margin, vascular invasion, and perineural invasion could be prognostic factors for recurrence of resected WDPNETs, indicating that patients with these high-risk factors need closer postoperative follow-up and may benefit from adjuvant therapy.

Predictive significance of tumor budding in postoperative liver metastasis of pancreatic neuroendocrine tumors

BACKGROUND

Although pancreatic neuroendocrine tumors (PNETs) are considered indolent tumors, nearly half of cases metastasize to the liver, which can be lethal. However, effective indicators to predict aggressive behavior have not been well-established.

METHODS

In the current study, we explored the prognostic significance of tumor budding in Grade 1-2 PNETs. Hematoxylin-eosin and immunohistochemically stained slides of surgically removed Grade 1-2 PNETs were evaluated.

RESULTS

Tumor budding, a histomorphological parameter that corresponds to single cells or small cell clusters (<5 cells), was classified as low (0-10 buds) and high (>10 buds) grade. We observed that tumor budding was correlated with aggressive histopathological parameters, such as T stage, lymph node status, metastasis, and vascular invasion (p < .05). Univariate and multivariate analyses showed that high-grade budding was an independent predictive factor for postoperative liver metastasis (p = .012). Moreover, Grade 1-2 PNETs with high-grade budding was associated with worse overall survival and disease-free survival (p = .0015 and p = .0041, respectively).

CONCLUSIONS

We conclude that tumor budding may serve as a valuable parameter in the risk stratification of postoperative liver metastasis and that incorporating tumor budding into histopathological reports may aid in appropriate clinical management.

Usefulness of texture analysis for grading pancreatic neuroendocrine tumors on contrast-enhanced computed tomography and apparent diffusion coefficient maps

PURPOSE

To determine whether texture analysis of contrast-enhanced computed tomography (CECT) and apparent diffusion coefficient (ADC) maps could predict tumor grade (G1 vs G2-3) in patients with pancreatic neuroendocrine tumor (PNET).

MATERIALS AND METHODS

Thirty-three PNETs (22 G1 and 11 G2-3) were retrospectively reviewed. Fifty features were individually extracted from the arterial and portal venous phases of CECT and ADC maps by two radiologists. Diagnostic performance was assessed by receiver operating characteristic curves while inter-observer agreement was determined by calculating intraclass correlation coefficients (ICCs).

RESULTS

G2-G3 tumors were significantly larger than G1. Seventeen features significantly differed among the two readers on univariate analysis, with ICCs > 0.6; the largest area under the curve (AUC) for features of each CECT phase and ADC map was log-sigma 1.0 joint-energy = 0.855 for the arterial phase, log-sigma 1.5 kurtosis = 0.860 for the portal venous phase, and log-sigma 1.0 correlation = 0.847 for the ADC map. The log-sigma 1.5 kurtosis of the portal venous phase showed the largest AUC in the CECT and ADC map, and its sensitivity, specificity, and accuracy were 95.5%, 72.7%, and 87.9%, respectively.

CONCLUSION

Texture analysis may aid in differentiating between G1 and G2-3 PNET.

Pancreatic Neuroendocrine Neoplasms: 2020 Update on Pathologic and Imaging Findings and Classification

Pancreatic neuroendocrine neoplasms (panNENs) are heterogeneous neoplasms with neuroendocrine differentiation that show characteristic clinical, histomorphologic, and prognostic features; genetic alterations; and biologic behavior. Up to 10% of panNENs develop in patients with syndromes that predispose them to cancer, such as multiple endocrine neoplasia type 1, von Hippel-Lindau disease, tuberous sclerosis complex, neurofibromatosis type 1, and glucagon cell adenomatosis. PanNENs are classified as either functioning tumors, which manifest early because of clinical symptoms related to increased hormone production, or nonfunctioning tumors, which often manifest late because of mass effect. PanNENs are histopathologically classified as well-differentiated pancreatic neuroendocrine tumors (panNETs) or poorly differentiated pancreatic neuroendocrine carcinomas (panNECs) according to the 2010 World Health Organization (WHO) classification system. Recent advances in cytogenetics and molecular biology have shown substantial heterogeneity in panNECs, and a new tumor subtype, well-differentiated, high-grade panNET, has been introduced. High-grade panNETs and panNECs are two distinct entities with different pathogenesis, clinical features, imaging findings, treatment options, and prognoses. The 2017 WHO classification system and the eighth edition of the American Joint Committee on Cancer staging system include substantial changes. Multidetector CT, MRI, and endoscopic US help in anatomic localization of the primary tumor, local-regional spread, and metastases. Somatostatin receptor scintigraphy and fluorine 18-fluorodeoxyglucose PET/CT are helpful for functional and metabolic assessment. Knowledge of recent updates in the pathogenesis, classification, and staging of panNENs and familiarity with their imaging findings allow optimal patient treatment. ^©RSNA, 2020.

Homologous Recombination Repair Defect May Predict Treatment Response to Peptide Receptor Radionuclide Therapy for Neuroendocrine Tumors

Lutetium-177-dotatate (177 Lu-dotatate), a form of peptide receptor radionuclide therapy, was approved by the U.S. Food and Drug Administration for the treatment of advanced somatostatin receptor-positive gastroenteropancreatic neuroendocrine tumors (NETs) in 2018 based on the promising results of the NETTER-1 trial for grade 1-2 midgut NETs. Here, we present a patient with a grade 3 pancreatic neuroendocrine tumor and BRCA1 germline mutation who had a significant response to 177 Lu-dotatate.

Pancreatic neuroendocrine tumors G3 and pancreatic neuroendocrine carcinomas: Differences in basic biology and treatment

In 2017 the World Health Organization revised the criteria for classification of pancreatic neuroendocrine neoplasms (pNENs) after a consensus conference at the International Agency for Research on Cancer. The major change in the new classification was to subclassify the original G3 group into well-differentiated pancreatic neuroendocrine tumors G3 (pNETs G3) and poorly differentiated pancreatic neuroendocrine carcinomas (pNECs), which have been gradually proven to be completely different in biological behavior and clinical manifestations in recent years. In 2019 this major change subsequently extended to NENs involving the entire digestive tract. The updated version of the pNENs grading system marks a growing awareness of these heterogeneous tumors. This review discusses the clinicopathological, genetic and therapeutic features of poorly differentiated pNECs and compare them to those of well-differentiated pNETs G3. For pNETs G3 and pNECs (due to their lower incidence), there are still many problems to be investigated. Previous studies under the new grading classification also need to be reinterpreted. This review summarizes the relevant literature from the perspective of the differences between pNETs G3 and pNECs in order to deepen understanding of these diseases and discuss future research directions.

Candidate protein biomarkers in pancreatic neuroendocrine neoplasms grade 3

Pancreatic neuroendocrine neoplasms (PanNENs) are rare tumours that compose 1–2% of all pancreatic tumours. Patients with metastatic grade 3 neoplasia are usually treated with chemotherapy but have a poor progression-free and overall survival. According to the WHO 2017 classification, they are divided into neuroendocrine tumours (NETs) G3 and neuroendocrine carcinomas (NECs). Despite the new classification, new diagnostic and prognostic biomarkers are needed to sub-categorise the patients and to help guide therapy decisions. Blood from 42 patients and 42 healthy controls were screened for the presence of 92 proteins with the Immuno-Oncology panel using the Proximity Extension Assay provided by Olink Biosciences. Immunohistochemical staining of FAS ligand (FASLG) was performed on 16 patient tumour specimens using a commercial antibody. Fifty-four out of 87 evaluable proteins differed significantly in concentration between blood from patients and blood from healthy controls. FASLG was the only protein for which the concentration in blood was significantly lower in patients compared to controls and the levels correlated negatively to Ki-67 index. Seven of 14 evaluable PanNEN G3 specimens showed FASLG immunoreactivity in the tumour cells while there was scattered immunoreactivity in immune cells. Positive FASLG immunoreactivity correlated to well-differentiated morphology. FASLG concentration in blood was significantly lower in patients with pancreatic NENs G3 compared to controls, and the expression in tumour tissue was variable. Furthermore, FASLG was negatively correlated to Ki-67 and was more frequently expressed in well-differentiated tumours. Taken together, these results may suggest a role of FASLG in PanNENs.

CD56 Expression Is Associated with Biological Behavior of Pancreatic Neuroendocrine Neoplasms

Purpose

CD56 is a neural cell adhesion molecule that plays a role in the cohesiveness of neuroendocrine cells. The aim of this study was to explore the biological values of CD56 expression in pancreatic neuroendocrine neoplasms (PNENs) and its role in predicting PNENs grades.

Patients and Methods

A total of 138 patients with histological-proven PNENs was included (66 G1, 46 G2 and 26 G3). The clinicopathological characteristics, including mitosis count, ki67 index, chromogranin A (CgA), synaptophysin (Syn) and CD56 expression, were evaluated. We assessed the diagnostic performance of markers in predicting PNEN G3 and the association between CD56 expression and risk of G3 or organs invasion.

Results

Lack of CD56 immunoreaction (CD56-) was more common in PNEN G3 than G1/G2 (31% vs 0–2%, p < 0.01). The sizes of CD56- tumors were larger than CD56 positive tumors in PNEN G3 (p < 0.01). The odds ratio (OR) of CD56- expression was 13.6 [95% confidence interval (CI): 2.1–88.1] in predicting PNEN G3. The OR of CD56- expression was 6.5 (95% CI: 1.1–38.6) and 31.9 (95% CI: 1.09–938.3) in predicting organs invasion and neuroendocrine carcinoma in PNEN G3, respectively. Tumor size (area under the curve [AUC] = 0.77 and size+CD56- expression [AUC = 0.84]) had acceptable performance in predicating PNEN G3.

Conclusion

Lack of CD56 immunoreaction may be a predictor and biological behavior marker for PNEN G3.