Conundrums and Caveats in Neuroendocrine Tumors of the Pancreas

Diagnostic Approaches to Neuroendocrine Neoplasms of Unknown Primary Site

ABSTRACT

Neuroendocrine tumors (NETs) are relatively uncommon heterogeneous neoplasms arising from endocrine and neuronal origin cells showing highly variable clinical behavior. By the time these tumors are discovered, up to 14% of patients with histologically proven NETs have metastasis, with the liver as the most frequently affected organ. Sometimes, no known primary site can be identified via routine imaging. Neuroendocrine tumors of unknown origin carry a poorer prognosis (compared with metastatic NETs with a known primary site) because of a lack of tailored surgical intervention and appropriate medical therapy (eg, chemotherapy or targeted therapy). A multimethod approach is frequently used in the trial to accurately determine the primary site for NETs of unknown primary sites and may include clinical, laboratory, radiological, histopathological, and surgical data. New molecular techniques using the genomic approach to identify the molecular signature have shown promising results. Various imaging modalities include ultrasound, computed tomography (CT), dual-energy CT, magnetic resonance imaging, and functional and hybrid imaging (positron emission tomography/CT, positron emission tomography/magnetic resonance imaging); somatostatin receptor imaging with new tracers is frequently used in an attempt for localization of the primary site.

Combined deletion of MEN1, ATRX and PTEN triggers development of high-grade pancreatic neuroendocrine tumors in mice

Pancreatic neuroendocrine tumors (PanNETs) are a heterogeneous group of tumors that exhibit an unpredictable and broad spectrum of clinical presentations and biological aggressiveness. Surgical resection is still the only curative therapeutic option for localized PanNET, but the majority of patients are diagnosed at an advanced and metastatic stage with limited therapeutic options. Key factors limiting the development of new therapeutics are the extensive heterogeneity of PanNETs and the lack of appropriate clinically relevant models. In that context, genomic sequencing of human PanNETs revealed recurrent mutations and structural alterations in several tumor suppressors. Here, we demonstrated that combined loss of MEN1, ATRX, and PTEN, tumor suppressors commonly mutated in human PanNETs, triggers the development of high-grade pancreatic neuroendocrine tumors in mice. Histopathological evaluation and gene expression analyses of the developed tumors confirm the presence of PanNET hallmarks and significant overlap in gene expression patterns found in human disease. Thus, we postulate that the presented novel genetically defined mouse model is the first clinically relevant immunocompetent high-grade PanNET mouse model.

Overview of the 2022 WHO Classification of Neuroendocrine Neoplasms

In this review, we detail the changes and the relevant features that are applied to neuroendocrine neoplasms (NENs) in the 2022 WHO Classification of Endocrine and Neuroendocrine Tumors. Using a question-and-answer approach, we discuss the consolidation of the nomenclature that distinguishes neuronal paragangliomas from epithelial neoplasms, which are divided into well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). The criteria for these distinctions based on differentiation are outlined. NETs are generally (but not always) graded as G1, G2, and G3 based on proliferation, whereas NECs are by definition high grade; the importance of Ki67 as a tool for classification and grading is emphasized. The clinical relevance of proper classification is explained, and the importance of hormonal function is examined, including eutopic and ectopic hormone production. The tools available to pathologists for accurate classification include the conventional biomarkers of neuroendocrine lineage and differentiation, INSM1, synaptophysin, chromogranins, and somatostatin receptors (SSTRs), but also include transcription factors that can identify the site of origin of a metastatic lesion of unknown primary site, as well as hormones, enzymes, and keratins that play a role in functional and structural correlation. The recognition of highly proliferative, well-differentiated NETs has resulted in the need for biomarkers that can distinguish these G3 NETs from NECs, including stains to determine expression of SSTRs and those that can indicate the unique molecular pathogenetic alterations that underlie the distinction, for example, global loss of RB and aberrant p53 in pancreatic NECs compared with loss of ATRX, DAXX, and menin in pancreatic NETs. Other differential diagnoses are discussed with recommendations for biomarkers that can assist in correct classification, including the distinctions between epithelial and non-epithelial NENs that have allowed reclassification of epithelial NETs in the spine, in the duodenum, and in the middle ear; the first two may be composite tumors with neuronal and glial elements, and as this feature is integral to the duodenal lesion, it is now classified as composite gangliocytoma/neuroma and neuroendocrine tumor (CoGNET). The many other aspects of differential diagnosis are detailed with recommendations for biomarkers that can distinguish NENs from non-neuroendocrine lesions that can mimic their morphology. The concepts of mixed neuroendocrine and non-neuroendocrine (MiNEN) and amphicrine tumors are clarified with information about how to approach such lesions in routine practice. Theranostic biomarkers that assist patient management are reviewed. Given the significant proportion of NENs that are associated with germline mutations that predispose to this disease, we explain the role of the pathologist in identifying precursor lesions and applying molecular immunohistochemistry to guide genetic testing.

Pancreatic Neuroendocrine Neoplasms: Landscape and Horizon

CONTEXT.—

Since the initial description of pancreatic endocrine physiology and the recognition of islet cell tumors in the 1800s, there have been noteworthy advances in the pathobiology of pancreatic neuroendocrine neoplasms (PanNENs), and definition of the important distinction between well-differentiated neuroendocrine tumor (PanNET) and poorly differentiated neuroendocrine carcinoma (PanNEC). The evolving knowledge has resulted in a continuous update in terminology, classification, and grading system for this group of neoplasms. Pancreatic neuroendocrine tumors associated with hereditary conditions have been linked to unique molecular and genetic events, and sporadic PanNETs have specific gene signatures. Based on accumulative experience and knowledge, therapeutic strategies have been defined for this group of neoplasms.

OBJECTIVE.—

To review the evolution and description of the pathologic-genomic evolution of PanNENs, and to facilitate accurate pathologic interpretation for the corresponding clinical management.

DATA SOURCES.—

Literature review of published studies and author's own work.

CONCLUSIONS.—

Evolving experience and knowledge have established subtypes of pancreatic neuroendocrine neoplasms, based on their genotype and phenotype. Accurate pathologic interpretation of the specific neoplasm has significant implications for therapy and prognosis.

Histopathologist-level quantification of Ki-67 immunoexpression in gastroenteropancreatic neuroendocrine tumors using semiautomated method

The role of Ki-67 index in determining the prognosis and management of gastroenteropancreatic neuroendocrine tumors (GEP-NETs) has become more important yet presents a challenging assessment dilemma. Although the precise method of Ki-67 index evaluation has not been standardized, several methods have been proposed, and each has its pros and cons. Our study proposes an imaging semiautomated informatics framework [semiautomated counting (SAC)] using the popular biomedical imaging tool "ImageJ" to quantify Ki-67 index of the GEP-NETs using camera-captured images of tumor hotspots. It aims to assist pathologists in achieving an accurate and rapid interpretation of Ki-67 index and better reproducibility of the results with minimal human interaction and calibration. Twenty cases of resected GEP-NETs with Ki-67 staining that had been done for diagnostic purposes have been randomly selected from the pathology archive. All of these cases were reviewed in a multidisciplinary cancer center between 2012 and 2019. For each case, the Ki-67 immunostained slide was evaluated and five camera-captured images at 40 × magnification were taken. Prints of images were used by three pathologists to manually count the tumor cells. The digital versions of the images were used for the semiautomated cell counting using ImageJ. Statistical analysis of the Ki-67 index correlation between the proposed method and the MC revealed strong agreement on all the cases evaluates ( n = 20 ), with an intraclass correlation coefficient of 0.993, "95% CI: 0.984 to 0.997." The results obtained from the SAC are promising and demonstrate the capability of this methodology for the development of reproducible and accurate semiautomated quantitative pathological assessments. ImageJ features are investigated carefully and accurately fine-tuned to obtain the optimal sequence of steps that will accurately calculate Ki-67 index. SAC is able to accurately grade all the cases evaluated perfectly mating histopathologists' manual grading, providing reliable and efficient solution for Ki-67 index assessment.

ATRX, DAXX or MEN1 mutant pancreatic neuroendocrine tumors are a distinct alpha-cell signature subgroup

The commonly mutated genes in pancreatic neuroendocrine tumors (PanNETs) are ATRX, DAXX, and MEN1. We genotyped 64 PanNETs and found 58% carry ATRX, DAXX, and MEN1 mutations (A-D-M mutant PanNETs) and this correlates with a worse clinical outcome than tumors carrying the wild-type alleles of all three genes (A-D-M WT PanNETs). We performed RNA sequencing and DNA-methylation analysis to reveal two distinct subgroups with one consisting entirely of A-D-M mutant PanNETs. Two genes differentiating A-D-M mutant from A-D-M WT PanNETs were high ARX and low PDX1 gene expression with PDX1 promoter hyper-methylation in the A-D-M mutant PanNETs. Moreover, A-D-M mutant PanNETs had a gene expression signature related to that of alpha-cells (FDR q-value < 0.009) of pancreatic islets including increased expression of HNF1A and its transcriptional target genes. This gene expression profile suggests that A-D-M mutant PanNETs originate from or transdifferentiate into a distinct cell type similar to alpha cells.

In pancreatic neuroendocrine tumors (PanNETs) ATRX, DAXX, and MEN1 are commonly mutated (A-D-M mutant PanNETs). Here, the authors find in a cohort of PanNETS 58% are A-D-M mutant PanNETs, with a worse clinical outcome and differences in gene expression and methylation compared to A-D-M wild type cases- these gene expression differences suggest that A-D-M mutant PanNETs potentially originate from a cell type similar to alpha cells.

Factors influencing Ki67 calculation in neuroendocrine neoplasia

Aim: We compared different methodologies to evaluate Ki67 in neuroendocrine neoplasia (NEN). Patients & methods: ki67 was evaluated using three methods in 70 NEN cases: manual-count, eyeballed estimate made by three pathologists and ImmunoRatio-software. Manual-count was the standard method and agreement with it was evaluated through intraclass correlation (ICC). Results: Agreement between manual-count and eyeballed estimate had ICC: 0.887–0.929. Eyeballed estimate by three pathologists produced upgradation in 5.7–32.9% and downgradation in 5.7% of NEN cases. Agreement for ImmunoRatio-count had ICC: 0.989. Immunoratio produced upgradation in 17.1% and downgradation in 8.5% cases. Agreement between all methods was higher at low-Ki67. Cellularity, immune-cell infiltration, staining and sample quality did not affect agreement. Conclusion: Eyeballed estimate and ImmunoRatio showed good accuracy, especially at low-Ki67.

Attenuation of the retinoblastoma pathway in pancreatic neuroendocrine tumors due to increased cdk4/cdk6

PURPOSE

In mice, genetic changes that inactivate the retinoblastoma tumor suppressor pathway often result in pancreatic neuroendocrine tumors (Pan-NETs). Conversely, in humans with this disease, mutations in genes of the retinoblastoma pathway have rarely been detected, even in genome-wide sequencing studies. In this study, we took a closer look at the role of the retinoblastoma pathway in human Pan-NETs.

EXPERIMENTAL DESIGN

Pan-NET tumors from 92 patients were subjected to immunohistochemical staining for markers of the retinoblastoma pathway. To search for amplifications of retinoblastoma pathway genes, genomic DNAs from 26 tumors were subjected to copy number analysis. Finally, a small-molecule activator of the retinoblastoma pathway was tested for effects on the growth of two Pan-NET cell lines.

RESULTS

A majority of tumors expressed high amounts of Cdk4 or its partner protein cyclin D1. High amounts of phosphorylated Rb1 were present in tumors that expressed high levels of Cdk4 or cyclin D1. The copy numbers of Cdk4 or the analogous kinase gene Cdk6 were increased in 19% of the tumors. Growth of the human Pan-NET cell line QGP1 was inhibited in a xenograft mouse model by the Cdk4/6 inhibitor, PD 0332991, which reactivates the retinoblastoma pathway.

CONCLUSIONS

Inactivation of the retinoblastoma pathway was indicated for most Pan-NETs. Gene amplification and overexpression of Cdk4 and Cdk6 suggests that patients with Pan-NETs may respond strongly to Cdk4/6 inhibitors that are entering clinical trials.