ABSTRACT

Pancreatic neuroendocrine neoplasms (PNENs) are a heterogenous group of relatively rare pancreatic malignancies with a unique biology and pathophysiology. Over the last few years, there have been significant improvements in imaging and treatment strategies, which have led to advances in patient’s management and quality of life (QOL). Yet, in practice, there are still a number of unanswered questions. For example, it remains a challenge to choose the optimal treatment sequence from the plethora of options and to properly monitor PNEN patients. Therefore, in this chapter, recent advances in the pathophysiology, diagnosis, monitoring, and management of these neoplasms will be summarized and placed in a historical context. For complete coverage of all related areas of Endocrinology, please visit our on-line FREE web-text, WWW.ENDOTEXT.ORG.

INTRODUCTION

Pancreatic neuroendocrine neoplasms (PNENs) are an uncommon subset of neuroendocrine neoplasms (NENs) originating from endocrine cells (1-3). PNENs represent 1-2% of all pancreatic neoplasms and according to the Surveillance, Epidemiology and End Results (SEER) program, the annual age-adjusted incidence has risen from 0.32/100,000 persons in 2004 to 0.48/100,000 persons in 2021 (2, 4-7). Improvements in and a wider availability of high-quality imaging techniques and a well-established classification system are believed to be major factors in the increasing incidence of PNENs (5, 8, 9).

PNENs can be divided into both functional (10-40%) and non-functional (60-90%) neoplasms (2, 6, 7, 10, 11). Functional PNENs (F-PNENs) are characterized by a specific clinical course and symptoms due to excessive hormone production (e.g., insulin, gastrin) (10-12). The most frequent, recognized F-PNENs are listed in Table 1 (1). Less common F-PNENs include somatostatinomas, ACTHomas and PNENs that cause carcinoid syndrome, acromegaly, or hypercalcemia (2). Patients with non-functional PNENs (NF-PNENs) lack symptoms related to clinical hormonal syndromes and are therefore usually diagnosed at a more advanced stage with characteristically large primary tumors (70% >5 cm) and liver metastasis in more than 60% of the cases (2, 9, 12, 13). NF-PNENs are hence frequently discovered by chance on imaging studies performed due to nonspecific abdominal pain, often caused by tumor bulk (2, 9, 12, 14). Although NF-PNENs do not secrete peptides causing clinical syndromes, they characteristically secrete a number of other peptides including chromogranin A (CgA) and pancreatic polypeptide (PP). However, elevated levels of PP or CgA are not specific for NF-PNENs as they are also observed in patients with renal failure and inflammatory conditions (2, 9, 12-14).

CLASSIFICATION AND STAGING

The World Health Organization (WHO) classification from 2019 (Table 2) takes into account both differentiation status and proliferation rate of the tumor. The former is determined through a histological examination of tumor morphology in which well-differentiated neuroendocrine tumors (NETs) can be distinguished from poorly differentiated neuroendocrine carcinomas (NECs). A grade is then assigned based on the proliferation rate assessed via Ki-67 index and mitotic count. Well-differentiated NETs can be divided into low grade (G1), intermediate grade (G2), and high grade (G3) tumors that have respective Ki-67 values of <3%, 3-20%, and >20% or mitotic counts of <2, 2-20, and >20 per 2mm³ (10 high power fields (HPF)). In the poorly-differentiated NEC group (small and large cell types), only high grade G3 tumors with a Ki-67 value >20 are found. In addition, neoplasms exist that consist of neuroendocrine cells as well as non-neuroendocrine adenocarcinoma or squamous carcinoma cells (i.e., mixed non-neuroendocrine-neuroendocrine neoplasms (MiNEN)) (3, 6-8, 15, 16). Depending on tumor grade and primary site, the 5-year survival varies between 15-95% and median overall survival (OS) from approximately 12 years for patients with G1 to 10 months in patients with G3 PNENs (3, 17). PNENs most often occur sporadically, but can also occur in patients with various inherited disorders (2, 18). For example, PNENs develop in 80-100% of patients with Multiple Endocrine Neoplasia type 1 (MEN1), in 10-17% of patients with von Hippel-Lindau syndrome (VHL), and occasionally in patients with tuberous sclerosis and neurofibromatosis (3, 18).

PNENs are also classified based on the tumor-node-metastasis (TNM) classification which estimates the prognosis of the tumors based on the anatomy of the tumor (3). Previously there was no generally accepted staging system, so in Europe usually the European Neuroendocrine Tumor Society (ENETS) staging system was applied, while in America the America Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) system was being used (19-21). In the 7^th edition of the AJCC/UICC, the same ordering system was employed for PNENs as for pancreatic adenocarcinoma (PAAD), but due to biological differences between both tumor types, this staging system proved to have some limitations (19, 20). Consequently, in the revised 8^th edition of the AJCC/UICC, the classification system of ENETS was implemented (21). Two research groups demonstrated that the system employed in this 8^th edition was superior to that of the 7^th edition as well as the ENETS staging system and should be considered as golden standard (20, 22).

INDUCTION OF PNENS

PNENs are also often referred to as islet cell tumors since it is presumed that they arise from the islets of Langerhans (3, 23, 24). These islets contain A-, B-, D-, D₁-, and D₂-cells that respectively secrete glucagon, insulin, somatostatin, pancreatic polypeptide, and vasoactive intestinal polypeptide (VIP) (25). Logically, the F-PNENs most definitely arise from these cells, but the cell of origin in NF-PNENs is still a matter of debate (26, 27). Chan et al. revealed that NF-PNENs with ATRX, DAXX, and MEN1 mutations (A-D-M mutant) had a worse clinical outcome than A-D-M wild-type (WT) tumors. In addition, they were able to demonstrate, through RNA sequencing and DNA methylation analysis, that the A-D-M mutant PNENs had high ARX and low PDX1 expression which is consistent with the expression profile found in α-cells (28). Cejas et al. found that NF-PNENs could be divided into two subgroups with epigenomes and transcriptomes very similar to those of α- and β-cells, respectively (29). These findings were confirmed by Di Domenico and colleagues who were able to demonstrate that the genome-wide DNA methylation profiles of NF-PNENs were very consistent with the methylation profiles of α- and β-cells (24). Based on these findings, it was hypothesized that NF-PNENs evolve primarily but not exclusively from the α-cell lineage and β-cell lineage (27).

Figure 1.

Visualization of the pancreatic duct glandular structures (PDGs) (arrowheads) in (A) large and (B) small ducts using scanning electron microscopy (SEM). PDGs can occur as single outpouches or form a complex of sac-like dilatations as illustrated in (C). This figure has been adapted from Gastroenterology, Strobel O., Rosow D. E., Rakhlin E. Y., et al., Pancreatic duct glands are distinct ductal compartments that react to chronic injury and mediate Shh-induced metaplasia, 138 (3): 1166-77 © 2010 (30).

Others in turn suggest that PNENs develop from multipotent pancreatic progenitor (MPP) cells in the ductal and islet regions of the pancreas that would be able to generate new pancreatic islet cells (31, 32). However, it remains unclear whether these cells originate in the islets or whether they migrate from the pancreatic ducts to subsequently transform into endocrine cells (33). This hypothesis is strengthened by the fact that early endocrine progenitors in fact appear to originate from a bipotent ductal endocrine progenitor, which in turn originates from MPP cells (34). However, not a lot is known about where these MPP cells are present. One hypothesis states these could be present in the pancreatic duct glandular structures (PDGs) that can be found as specialized compartments with a gland-like outpouching look (Figure 1) in the ductal epithelium (30, 35). The actual origin and location of the MPP that can evolve into islet cells is not known to date and thus needs to be further investigated for a better understanding of the potential origin of PNENs.

MOLECULAR (EPI)GENETICS

DIAGNOSIS AND MONITORING

The gold standard for diagnosing PNENs remains an immunohistochemical examination of the tumor tissue, but imaging and serum markers are also extremely important in the diagnostic process. The clinical presentation often determines the sequence of examinations. For example, patients with F-PNENs will usually undergo a biochemical blood analysis first based on their hormonal symptoms, whereas NF-PNENs are often detected by chance on imaging (25, 52, 53).

Immunohistochemistry

To correctly classify PNENs, tumor morphology and proliferation rates (Ki-67 and mitotic index) should be evaluated in tissue biopsies. These are usually obtained from surgical specimens, percutaneous core biopsies, or preoperative biopsies (52, 54, 55). The latter were mainly derived from endoscopic ultrasound (EUS) guided fine-needle aspirations (FNA) which, in recent years, have been increasingly replaced by fine-needle biopsies (FNB) as these enable histological tissue samples to be obtained, hence immunohistochemistry (IHC) to be performed (56, 57). This immunohistochemical examination is most often initiated by confirming the neuroendocrine differentiation by checking CgA and synaptophysin (SYP) expression (52, 54). Other markers such as neuron-specific enolase (NSE) and CD56 are less specific, hence less useful (58). Next, tumor morphology is assessed to determine whether the PNEN is well- or poorly-differentiated (Figure 2). In general, well-differentiated PNENs are characterized by uniform cells with a finely granular cytoplasm and round to oval nucleus which are arranged in a trabecular, glandular, or tubuloacinar pattern (54, 59). Moreover, typically all cells have a heterogeneous expression of CgA in their cytoplasm, whereas SYP stains more diffusely. Poorly-differentiated PNECs, on the other hand, consist of atypical neoplastic cells that often lack CgA and even SYP (59, 60). Ultimately, tumors are graded by proliferation rate that is influenced by two parameters, Ki-67 and mitotic count. The latter is usually reported as the number of mitoses per mm² which in practice is often complicated by a limited tissue area. The mitotically active regions are then measured again via IHC to determine the Ki-67 index (Figure 3). It is therefore logical that the Ki-67 index is usually higher than the mitotic count since it considers the entire mitotic process and not just the number of mitoses. If both values assign a different grade to the same tumor, the highest grade, associated with the worst prognosis, is assumed (17, 23, 52, 54).

Figure 2.

Hematoxylin-eosin IHC staining of (A) well-differentiated PNET and (B) poorly-differentiated PNEC. This figure has been adapted from Archives of Pathology & Laboratory Medicine, Fang J. M. and Shi J., A clinicopathologic and molecular update of pancreatic neuroendocrine neoplasms with a focus on the new world health organization classification, 143 (11): 1317-1326. © 2019 (59).

Figure 3.

(A) PNEN G1 with Ki-67 index of less than 3%. (B) PNEN G2 with Ki-67 index of 3% to 20%. (C) PNEN G3 with Ki-67 index higher than 20%. This figure has been adapted from Archives of Pathology & Laboratory Medicine, Fang J. M. and Shi J., A clinicopathologic and molecular update of pancreatic neuroendocrine neoplasms with a focus on the new world health organization classification, 143 (11): 1317-1326. © 2019 (59).

Imaging

Regardless of whether a PNEN is functional or non-functional, imaging is critical to assess the extent of the disease by localizing the primary tumor and identifying the size of metastatic disease. Localization is required preoperatively to increase the accuracy of intraoperative techniques and to reduce the need for repeated surgery. Besides, imaging is involved in patient’s management as it allows to monitor tumor growth and evaluate response to treatment (2, 25, 53, 55, 61). A multimodal approach is applied to diagnose and stage PNENs which comprises both anatomical and functional imaging modalities (2, 61-66).

ANATOMIC IMAGING

Anatomical imaging modalities such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are capable of depicting normal and diseased tissue at high spatial resolution (67). Contrast enhanced CT is the most commonly used and preferred modality as it is widely available, renders clear anatomical images of the pancreas, lymph nodes, and liver metastasis and allows to assess vascular invasion and resectability (25, 52, 62, 64, 68, 69). The more recent, multiphase multidetector CT scan exhibits even more advantages including reduced artifacts due to rapid scan time, improved arterial phase images due to accurate contrast medium tracking and improved resolution by generating thinner slices that can be studied in different anatomical planes (61, 65). In addition, the frequent hypervascular nature of PNENs results in typical high contrast uptake in the arterial phase on CT which can aid in differentiating from pancreatic adenocarcinoma. The average sensitivity of contrast-enhanced CT varies from 63% to 83% and detection rates range from 69% to 94.3% (52, 67, 70). It appears that imaging of PNENs is often influenced by their biological heterogeneity. For example, gastrinoma become more apparent on postcontrast images and large NF-PNENs often have a necrotic or cystic appearance which tend to complicate diagnosis with imaging alone. In the latter case, MRI can be useful as cystic neoplasms can be better visualized due to the higher resolution, rendering MRI complementary to CT. MRI displays a similar sensitivity to CT (79%), but has some advantages over CT as it displays a good sensitivity even without administration of contrast agents, employs non-ionizing radiation, and is hence safer for patient follow-up (52, 53, 67). Limitations on the other hand include a higher frequency of motion-related artifacts as well as a longer acquisition time compared to CT (71).

Still, both conventional imaging modalities depend to a large extent on the tumor size (2, 25, 61, 72, 73). More than 70% of PNENs larger than 3 cm are detected, but only 50% of PNENs smaller than 1 cm are identified. As a result, small primary PNENs, especially insulinoma and duodenal gastrinoma, are frequently missed as well as small liver metastases (2, 25, 61, 62, 72-74). For small PNENs, which cannot be detected using CT and MRI, EUS is considered the predominant imaging technique (68). Because of the high spatial resolution of this modality, it is possible to localize even very small lesions (2-3 mm) (3, 74). Additionally, it is feasible to obtain high yield tissue samples by means of an FNA/B that can be used for Ki-67 measurements. Such EUS-FNA/B have a diagnostic accuracy of 80% for pancreatic adenocarcinoma and 46% for PNENs. In patients with proven insulinoma, EUS displays a sensitivity of 94% as a first-line modality. This renders EUS extremely valuable for localizing primary insulinoma (2, 68, 74, 75). However, EUS is not generally available, can be technically challenging, and results are operator dependent. In the hands of an expert, sensitivities of 79 to 100% can be achieved (61).

FUNCTIONAL IMAGING

Prior to the development of the current functional imaging modalities, selective angiography and sampling for hormone gradients were employed. However, due to the highly invasive nature of these techniques, minimally invasive modalities were developed which had a great impact on patient management (2, 53, 64).

Although PNENs exhibit highly heterogeneous biological behavior, 80-100% of PNENs, with the exception of insulinomas (50-70%), overexpress the G-linked protein somatostatin receptors (SSTRs), mainly subtypes SSTR-2 and -5. These receptors interact with somatostatin, a peptide hormone that affects neurotransmission and cell proliferation, but also the secretion of various compounds in the digestive system (2, 52, 62-64, 67, 76). Interestingly, these SSTRs also bind synthetic, radiolabeled somatostatin analogs (SSAs) with high affinity, which constitutes the basis of the primary functional imaging tool for PNENs, namely Somatostatin Receptor Imaging (SRI). SRI will not only allow to stage PNENs, but will also predictively identify patients eligible for SSA therapy (2, 52, 53, 64, 67, 68). One of the first SSAs used to target the SSTRs was octreotide labeled with ¹¹¹Indium via chelator, diethylene-triamine-pentaaceticacid (DTPA). This ¹¹¹In-DTPA-octreotide emits gamma rays that are detected 24 hours after intravenous injection using Single Photon Emission CT (SPECT) or SPECT/CT, the so-called Octreoscan® (53, 62, 64, 70, 77). The Octreoscan® is often combined with CT to improve the anatomic localization making it highly sensitive (77%), detecting 50-70% of primary PNENs, but less of the insulinomas and duodenal gastrinomas (2, 62-64, 68, 78-81). Major drawbacks include the availability and price of ¹¹¹In-DTPA octreotide, the staggering acquisition time as well as the intrinsic shortcomings of SPECT, such as low spatial resolution (8-12 mm) (67, 82).

Positron Emission Tomography (PET) could provide better spatial resolution and greater precision (71). One of the most widely employed PET radiotracers currently used to image tumors is ¹⁸Fluor-labeled deoxy-glucose (¹⁸FDG). For high-grade NETs, especially NECs, ¹⁸FDG-PET/CT is a better choice as nuclear medicine modality as SSTR expression decreases when proliferation rates increase. ¹⁸FDG-PET can even be positive in G2 and G3 NETs. To this date, no cut-off value has been determined. However, it seems like neoplasms with Ki-67 values > 15% are more likely to exhibit a positive ¹⁸FDG-PET/CT, which is also a predictor of a more aggressive course (53, 81, 83, 84). However, ¹⁸FDG-PET/CT appears to be less useful in the majority of PNENs as these often show limited glucose uptake due to a rather slow growth rate (52, 64).

The development of new PET/CT radiotracers has been a major breakthrough in PNEN imaging. ¹¹Carbon-5-hydroxytryptophan-labeled or ⁶⁸Gallium-labeled SSAs including DOTA-tyrosine-3-octreotide (DOTA-TOC), DOTA-octreotate (DOTA-TATE), and DOTA-1-NaI-octreotide (DOTA-NOC) showed better sensitivity and diagnostic accuracy than the conventional imaging studies (Figure 4) and the Octreoscan® (Figure 5) (2, 52, 64, 71, 85-87). A meta-analysis revealed that ⁶⁸Ga-DOTA-SSA PET for the diagnosis of NETs has a pooled sensitivity and specificity of 93% and 91%, respectively (88). Admittedly, the majority of the studies involved heterogenous populations, but most included a sizable minority of 20-30% PNENs. Hence, the overall data, although far from perfect, support use of ⁶⁸Ga-DOTA-SSA PET over the Octreoscan® (89). Moreover, it is highly sensitive for the detection of bony metastases and it might obviate the need for additional radiologic studies. In addition to a higher sensitivity, other advantages of ⁶⁸Ga-DOTA-SSA PET include patient convenience (imaging sessions take 70-90 minutes instead of 24 hours), lower radiation exposure, utility in finding unknown primary PNENs and it can lead to changes in treatment plans in about 33-41% of the patients (67, 89-93). ⁶⁸Ga-DOTA-SSA PET might also be better at quantifying SSTR expression which facilitates targeted therapy such as PRRT (89). Consequently, ⁶⁸Ga-DOTA-SSA PET quickly became the imaging modality of choice (67, 68, 71). However, similar to other imaging studies, false positives may occur due to pancreatic uncinate process activity, inflammation, osteoblastic activity, and splenosis (94). No doubt other PET agents will follow since PNENs express a variety of receptors for which there are potential ligands. For example, insulinomas express SSTRs in 50% of the cases, so tracers targeting the glucagon-like peptide-1 (GLP-1) receptor might be more useful in those patients (80, 95, 96).

Figure 4.

Overview of (A) ⁶⁸Ga-PET/CT, multiphase (B) atrial and (C) portal vein CT scan images from patient with partially cystic PNEN. The arrow indicates a liver metastasis which is only visible on the ⁶⁸Ga-PET/CT scan. This figure has been adapted from Current treatment options in oncology, Morse B., Al-Toubah T. and Montilla-Soler J., Anatomic and functional imaging of neuroendocrine tumors, 21 (9): 75 © 2020 (67).

Figure 5.

Comparison of (A) planar Octreoscan®, (B) Octreoscan®/SPECT/CT fusion, (C) planar ⁶⁸Ga-DOTATOC-PET and (D) ⁶⁸Ga-DOTATOC-PET/CT in the same patient. Images C and D clearly display a more precise delineation of the lesions. This figure has been adapted from International journal of endocrine oncology, Maxwell J. E. and Howe J. R., Imaging in neuroendocrine tumors: and update for the clinician, 2 (2): 159-68 © 2015 (82).

All benefits taken into account, the FDA approved ⁶⁸Ga-DOTATOC PET in 2016 in the US, after being available in Europe for a number of years. Furthermore, with the development of an FDA approved ⁶⁸Ga generator, an on-site cyclotron is no longer required, making this technology more widely available. A multi-society workgroup has recommended that ⁶⁸Ga-DOTA-SSA PET replace use of Octreoscan®, unless it is not accessible, in combination with at least one anatomic imaging technique (66, 70).

MANAGEMENT OF PNENS

With a better understanding of the heterogeneity in PNENs, the number of treatment options has increased substantially over the years. Unfortunately, there is a lack of head-to-head comparison data. Therefore, treatment must be individualized considering the age and overall health of the patient, the specific toxicities of potential treatment(s), costs, and potential impact on quality of life (QOL). Consequently, decisions with regard to patient management must be made by an experienced, multidisciplinary team together with the primary care physician (52). Generally, the management of PNEN patients consists of a series of well-defined steps. These comprise of: 1) establishing a diagnosis, 2) determining localization and extent of tumor, 3) controlling hormone excess state in case of F-PNENs, 4) resecting tumor, if possible, 5) checking for presence of hereditary disease (MEN1), 6) treating advanced and metastatic PNENs, and 7) long-term monitoring for tumor progression (63, 148).

Figure 6.

Possible treatment scheme for PNENs based on functionality and extent of the tumor. This figure has been adapted from Cancers, Akirov A., Larouche V., Alshehri S. et al., Treatment options for pancreatic neuroendocrine tumors, 11 (6) © 2019 (149).

It is crucial to consider grade/differentiation, stage/extent, and functional status of the tumor as different treatment schemes evolved based on these factors (Figure 6). For example, surgery is usually advocated for PNENs that are functional, larger than 2 cm, or intermediate-to-high grade (3, 8, 52). For patients with metastatic disease, the treatment options are extensive and encompass surgical debulking, systemic therapies including chemotherapy, or targeted therapy such as liver-directed therapy and peptide receptor radionucleotide therapy (PRRT) (149). It is not unusual for the management plan to change based on treatment response and disease progression. Failure to respond to treatment or unexpected changes in the tempo of disease due to tumor dedifferentiation and tumor heterogeneity are well-described in PNENs. Accordingly, most patients will receive multiple treatments during the course of their disease, but there is no data on the optimal treatment sequence (52, 105). The various treatment modalities are discussed below.

Medical Therapy

Use of medical therapy is limited to those with locally advanced or metastatic disease. Some of the current and promising options for targeted systemic therapy are shown in Figure 7.

Figure 7.

Overview of the current (blue) and promising (red) options for targeted medical therapy in (P)NETs. This figure has been retrieved from Drugs, Herrera-Martinez A. D., Hofland J., Hofland L. J., Targeted Systemic Treatment of Neuroendocrine Tumors: Current Options and Future Perspectives 79:21–42 © 2019 (186).

Figure 8.

Visualization binding affinity of each of the three FDA-approved SSAs to the different SSTR subtypes. This figure was retrieved and adapted from Drugs, Herrera-Martinez A. D., Hofland J., Hofland L. J., et al., Targeted systemic treatment of neuroendocrine tumors: current options and future perspectives, 79:21-42. © 2019 (186).

SOMATOSTATIN ANALOGS

As previously described in the functional imaging section, SSTRs are often highly overexpressed in PNENs. Several SSAs including Octreotide (Sandostatin®) and Lanreotide (Somatuline®), which have affinity for different SSTR subtypes (Figure 8), were therefore marketed. These inhibit hormone secretion and thus reduce clinical symptoms in patients with F-PNENs (149, 186). Additionally, several studies revealed that SSAs are also capable to control tumor growth with a positive impact on PFS. The antiproliferative effect of SSAs in PNETs was confirmed in the Controlled Study of Lanreotide Antiproliferative Response in Neuroendocrine Tumors (CLARINET) trial. A total of 204 patients with well-differentiated, progressive NETs were included who were then randomly assigned to either Lanreotide or placebo treatment for 96 weeks. After 24 weeks, PFS rates were 65.1% and 33.0% in the Lanreotide and placebo groups respectively (Figure 9). The study also demonstrated that there was no significant difference in QOL and OS in both groups (149, 186-189).

Figure 9.

PFS among patients that received Lanreotide (red) or placebo (blue). This figure was retrieved and adapted from The New England journal of medicine, Caplin M. E., Pavel M., Cwikla J. B., et al., Lanreotide in metastatic enteropancreatic neuroendocrine tumors, 371 (3): 224-33 © 2014 (189).

As an extension to the core CLARINET study, the CLARINET open-label extension (OLE) reported long-term safety and additional efficacy data. For this purpose, 88 patients with SD were selected from the core study. Forty-one patients continued their Lanreotide treatment, while 47 patients shifted from placebo to Lanreotide. Safety and tolerability were favorable during a mean treatment period of 40 months. In addition, adverse effects, that were either attributable or not to Lanreotide, were found to improve as duration of treatment, hence exposure, increased. Median PFS in patients who had already received Lanreotide in the core study was estimated at 32.8 months (Figure 10). Of the 32 placebo-treated patients who exhibited progressive disease (PD) in the core study, 17 patients persisted in PD, while the remaining 15 patients had a median time to progression (TTP) of 14 months (187, 190). Based on the findings from the CLARINET trial, the use of SSAs as first-line treatment for symptom relief and tumor control is recommended in the NCCN and ENETS guidelines for advanced, well-differentiated, unresectable PNENs, particularly those with a high burden of liver metastases (149, 188, 191).

Figure 10.

PFS of patients that received Lanreotide in the core and OLE CLARINET study. The OLE data is only visualized for patients that were originally assigned to and continued the Lanreotide treatment. This figure was retrieved and adapted from Endocrine-related cancer, Caplin M. E., Pavel M., Cwikla J. B., et al., Anti-tumor effects of lanreotide for pancreatic and intestinal neuroendocrine tumours: the CLARINET open-label extension study, 23 (3): 191-9 © 2016 (190).

MOLECULAR-TARGETES AGENTS

Newly developed molecular-targeted treatments including Sunitinib and Everolimus (Figure 7) have shown to improve PFS in advanced, metastatic PNENs and represent the most common second line treatments that are currently available (52, 149). An overview of the most recent findings can be found in Table 3.

The tyrosine kinase inhibitor (TKI), Sunitinib, has been approved for the treatment of patients with well-differentiated, unresectable, locally advanced or metastatic PNENs as it displays an antiangiogenic working mechanism. It actually inhibits vascular endothelial growth factor receptors (VEGFR) 1 and 3, stem cell factor (SCF) receptor as well as platelet-derived growth factor receptors (149, 186, 192). A two-cohort phase II study, examining 107 patients with advanced NETs (of which 66 PNENs), reported an overall objective response rate (ORR) of 16.7% and SD in 68% of PNEN patients. Median TTP was 7.7 months in PNENs and 10.2 months in carcinoid patients (193). A phase III multinational, randomized, double-blind, placebo-controlled trial (SUN 1111) confirmed the activity of Sunitinib in patients with advanced, well-differentiated PNENs (Figure 11A). A total of 171 patients were enrolled in this study. Median PFS was 11.4 months in the Sunitinib group compared to 5.5 months in the placebo group, with the latter group having a higher mortality rate (25% vs 10%) (194). A retrospective analysis of the previous phase III trial reported an increased PFS in both the Sunitinib and placebo group (12.6 vs. 5.8 months). Median OS after 5 years were 38.6 and 29.1 months of the Sunitinib and placebo groups, respectively. Important to note here is that 69% of the placebo-treated patients shifted to Sunitinib treatment (195). Sunitinib presented with an acceptable safety profile as the most frequent adverse effects in the sunitinib group included diarrhea, nausea, vomiting, asthenia, and fatigue which can be managed through dose interruption or modification (192, 194, 196).

Everolimus (Afinitor®) is an oral, protein kinase inhibitor of the mammalian target of rapamycin (mTOR) pathway that displays proven antitumor activity in advanced PNENs, either alone or combined with Octreotide therapy. A multinational phase II study, the RADIANT 1 trial, has reported the efficacy of Everolimus alone and in combination with Octreotide in patients with metastatic PNENs that have progressed on chemotherapy (197). Monotherapy with Everolimus provided SD in 67.8% of patients and a partial response (PR) in 9.6%, while combination therapy resulted in 80% SD and 4.4% PR. Everolimus treatment also led to a decrease in CgA and NSE levels in 50.7% and 68.2% of the patients (Table 4). An early tumor marker response (i.e., > 50% decrease by 4 weeks) was associated with a significantly longer PFS (197). The RADIANT 3 trial, later on, investigated Everolimus as first line therapy in patients with advanced PNENs (Figure11B). Four hundred and ten patients with radiologic progression of disease were randomized to either Everolimus (10 mg once daily) or placebo. The median PFS was 11 months with Everolimus compared to 4.6 months with placebo representing a 65% reduction in estimated risk of progression or death. The proportion of patients alive and progression free at 18 months was 34% with Everolimus compared to 9% with placebo. Toxicities were mostly grade I or II (198). Similar PFS rates were reported regardless of whether patients were chemo-naïve or had received prior chemotherapy (199, 200). Addition of Pasireotide to Everolimus did not improve PFS compared to Everolimus alone (201).

Based on the recent, above-mentioned data, the European Society for Medical Oncology (EMSO) guidelines 2020 recommend the use of molecular-targeted agents such as Sunitinib and Everolimus in advanced, progressive PNENs (G1/G2) (191). Likewise, the North American Neuroendocrine Tumor Society (NANETS) guidelines 2020 recommend both treatments for well-differentiated, metastatic PNETs (G1/G2) (202). Both guidelines state there is no support to use Sunitinib nor Everolimus in treatment of PNET G3 or PNECs (191, 202). When comparing both molecular-targeted agents, response rates appear comparable (Figure 11). Since there has been no trial comparing the two agents directly, choice of agent may be based on the potential side-effects and patient’s overall health. For example, in patients with poorly-controlled hormonal symptoms, especially hyperinsulinism, congestive heart failure, hypertension, high risk of gastrointestinal bleeding or a history of myocardial infarction or stroke, Everolimus is thought to be the preferred choice (194, 202, 203). On the other hand, in patients with poorly controlled diabetes mellitus, pulmonary disease, or high risk of infection, sunitinib would be a more appropriate choice (192, 203). Moreover, up until now several biomarkers have been identified that correlated with the patient’s outcome. An overview of the currently known biomarkers can be found in Table 4 (204).

Table 3.

Results from Most Important Phase II and III Studies of Sunitinib and Everolimus in PNENs

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Study	Patients	Active treatment	PD at entry	ORR	PFS/TTP (months)	Safety and other comments
Sunitinib
Phase II, open label (193)	N = 107 PNETs = 66 Carcinoid = 41	50 mg daily Schedule 4/2*	No	ORR = 16.7% SD = 68% ORR = 2.4% SD = 83%	TTP = 7.7 TTP = 10.2	G3 fatigue: 24.3%
Phase III, RCT, SUN 1111 (194) [Retrospect] (195)	N = 171 Sunitinib = 86 Placebo = 85	37.5 mg daily CDD**	Yes	ORR = 9.3% SD = 63% PD = 14% ORR = 0% SD = 60% PD = 27%	PFS = 11.4 [PFS = 12.6] PFS = 5.5 [PFS = 5.8]	Common AEs: 30%: diarrhea, nausea, asthenia, vomiting and fatigue 10-12%: G3/4 neutropenia and hypertension
Everolimus
Phase II, open label, RADIANT 1 (197)	N = 160 Stratum1 = 155 Stratum2 = 45	10 mg daily 10 mg daily + 30 mg LAR Octreotide	Yes	PR = 9.6% SD = 67.8% PD = 13.9% PR = 4.4% SD = 80% PD = 0%	PFS = 9.7 PFS = 16.7	Specific AEs: 5.2%: G3/4 asthenia 8.9%: G3/4 thrombocytopenia Common AEs: 30%: stomatitis, rash, diarrhea, fatigue, nausea
Phase III, RCT, RADIANT 3 (198)	N = 410 Everolimus = 207 Placebo = 203	10 mg daily	Yes	PR = 5% SD = 73% PR = 2% SD = 51%	PFS = 11 PFS = 4.6	Common AEs: 64%: stomatitis 49%: rash 34%: diarrhea 31%: fatigue 23%: infections

Abbreviations: ORR, objective response rate; PFS, progression-free survival; TTP, time to progression; SD, stable disease; PD, progressive disease; CDD, continuous daily dosing; AE, adverse event; LAR, long-acting release; PR, partial response; RCT, randomized clinical trial

*

Concomitant use of SSA in 27% of PNET patients and 54% of patients with carcinoid tumors.

**

Concomitant use of SSA in 26.7% of patients.

Figure 11.

This figure compares the PFS in patients with advanced metastatic PNENs, (A) treated with Sunitinib in the SUN 1111 trial (194) and (B) Everolimus in the RADIANT 3 trial (198). Figure A was retrieved and adapted from The New England journal of medicine, Raymond E., Dahan L., Raoul J. L., et al., Sunitinib malate for the treatment of pancreatic neuroendocrine tumors, 364 (6): 501-13 © 2011 (194). Figure B was retrieved and adapted from The New England journal of medicine, Yao J. C., Shah M. H., Ito T., et al., Everolimus for advanced pancreatic neuroendocrine tumors, 364 (6): 514-23 © 2012 (198).

Table 4.

Current Soluble Biomarkers and Correlations with Outcomes with Targeted Therapies in PNENs

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Study	Biomarker	Results
Sunitinib (204, 205)	VEGF	Increased in 53% of patients after 4 weeks of treatment Return to baseline after 2 weeks off treatment When Sunitinib level > 50 ng/dL higher changes observed No significant difference between PNET and carcinoids
	sVEGFR	Decrease of ≥ 30% in sVEGFR-2 and -3 levels Return to baseline after 2 weeks off treatment Reduction in sVEGFR-3 correlated with better OR and PFS Lower baseline sVEGFR-2 with radiological SD for > 6 months Elevated baseline sVEGFR-2 correlated with improved OS
	IL-8	Increase (>2-fold) in 43% and (>3-fold) in 23% of patients after 4 weeks of treatment Return to baseline after 2 weeks off treatment Increase (1.8-fold) after 4 weeks on treatment
	SDF-1α	Increase (20%) after 4 weeks on treatment Elevated baseline correlated with significantly shorter TTP, PFS and OS
Everolimus (197, 206)	CgA	Increase (> 2-fold) of CgA at baseline correlated with decreased PFS and OS Reduction of > 30% in CgA levels after 4 weeks correlated with increased PFS and OS
	NSE	Elevated NSE levels at baseline correlated with decreased PFS and OS Reduction of > 30% in NSE levels after 4 weeks correlated with improved PFS

Abbreviations: VEGF, vascular endothelial growth factor; sVEGFR, soluble VEGFR; SDF-1α, stromal cell-derived factor 1 alpha. Note: This table was adapted from Molecular Diagnosis and Therapy, Mateo, J., Heymach, J. V. and Zurita, A. J., Biomarkers of response to Sunitinib in gastroenteropancreatic neuroendocrine tumors: current data and clinical outlook, 151-161. © 2012 (204).

CYTOTOXIC CHEMOTHERAPY

There is currently no unanimity on which cytotoxic chemotherapy would be optimal for the treatment of PNENs. Therefore, patient selection is key so factors such as primary tumor site and stage, differentiation, and proliferation index should be considered. Conventional cytotoxic chemotherapy is often used as first-line therapy for metastatic and progressive PNETs or PNECs (149, 207). ENETS guidelines describe the following indications: progression under SSA treatment, worsening clinical symptoms, and/or Ki-67 values > 10% (208). In a neoadjuvant setting, chemotherapy can play a potential role in tumor shrinkage prior to resection (7). Two major types of chemotherapeutic agents can be distinguished namely alkylating and platinum agents (7, 149, 207). In practice these are often combined with antimetabolites and anthracyclines (209). An overview of the most commonly used combinatory therapies and when to employ them is described in more detail below.

Alkylating agents such as Streptozocin, Dacarbazine, and Temozolomide are key in the treatment strategy of PNEN patients since they are often employed as second line treatment after progression under SSA (207). First of all, Streptozocin, a nitrosourea alkylating agent, is taken up by cells via a glucose protein 2 (GLUT2) after which cell damage is induced. Since the compound is associated with significant renal and hematological toxicity in high doses, it is often combined with 5-fluorouracil (5-FU) or Doxorubicin with dose reduction, hence reduced toxicity as a result (2, 149, 209). A comparative, phase III study conducted in 1992 reported that the combinatory therapy of Streptozocin + Doxorubicin provided more favorable results than Streptozocin + 5-FU in patients with advanced PNENs (210). However, the results described in this study have not been confirmed in any subsequent study (163, 209). Kouvaraki and colleagues retrospectively studied 84 PNEC patients treated with Streptozocin, 5-FU and Doxorubicin. Response rate was 39% with 2-year PFS and OS of 41% and 74%, respectively (211). Dacarbazine, a second alkylating agent, serves as a less toxic alternative. A phase II study tested Dacarbazine as a monotherapy in 50 PNEN patients and reported an ORR of 34% and median OS of 19.3 months (212). When combined with 5-FU, the overall response rate and PFS in advanced NENs were 38.2% and 13.9 months, respectively (213). A third alkylating agent that is primarily used as monotherapy for treatment of glioblastoma and melanoma is Temozolomide (163, 209). When combined with other compounds including Capecitabine (214), Bevacizumab (215), Bevacizumab and Octreotide (216), Thalidomide (217) and Everolimus (200) it shows significant activity in advanced PNENs (149, 209). A 2011 retrospective study reported that the combination treatment Capecitabine + Temozolomide (CAPTEM) in 30 chemonaive NEC patients resulted in an ORR of 70% with a PFS of 18 months (214). In 2018, a prospective, randomized phase II trial investigated Temozolomide therapy versus the CAPTEM combination therapy in PNEN patients. PFS was significantly better in the latter group (14.4 vs. 22.7 months) (218). However, a more recent retrospective analysis showed that CAPTEM was not able to improve PFS. Consequently, it was suggested by the authors that CAPTEM might be more useful for tumor shrinkage rather than improving PFS (219).

In poorly-differentiated G3 NECs, platinum agent regimens are often used in patients with adequate performance status. The first-line chemotherapy for NEC patients encompasses Cisplatin or Carboplatin combined with Etoposide or Irinotecan, based on the reported results (52, 220-223). Moertel and colleagues investigated the effect of Cisplatin + Etoposide in 45 patients with metastatic NENs, of which 27 were well-differentiated. The ORR was 67% in the 18 poorly-differentiated NECs with complete response (CR) in 17% of the patients, while unfortunately, only 2 patients (17%) of the well-differentiated NEN patients showed a response. Moreover, they reported a median survival of 19 months which was significantly longer than those described in literature (6-7 months). However, toxicity was a major issue (220). These results were confirmed by Mitry and colleagues in 1999 (221). Lower toxicity levels were observed when patients were treated with Carboplatin, but efficacy was similar to that of Cisplatin, rendering Carboplatin a valuable alternative (222, 224). Moreover, Oxaliplatin-based therapy appeared to have a greater activity in advanced PNETs (207).

The role of second-line chemotherapy for NEC patients is currently unknown, but many combinatory options have been examined (223, 225). Capecitabine + Oxaliplatin (CAPOX) and 5-FU + Oxaliplatin (FOLFOX) have been evaluated in two retrospective trials in well-differentiated NENs. ORRs of 26% and 30% were reported, respectively (226, 227). In addition, FOLFIRI and FOLFIRINOX (5-FU-based chemotherapies) have recently proven some effect in NEC patients progressing on platinum-based regimens (225, 228).

QUALITY OF LIFE IN PATIENTS WITH PNENS

The measurement of health-related quality of life (HRQOL) has become essential for evaluating the impact of the disease process and the treatment on patient’s symptoms, social, emotional, physiological, and physical functioning. The European Organization for Research and Treatment of Cancer (EORTC) developed the QLQ-C30 tool for oncology patients (253) and the QLQ-GINET21 tool was specifically developed for a spectrum of NEN patients (28% PNENs) (254). The Norfolk QOLNET was specifically developed for midgut NETs (carcinoids) and may provide some additional advantages for that specific group of patients (231).

The most commonly used QOL tool in GEP-NENs (including PNENs) is the EORTC QLQ-C30 (255). SSAs and Sunitinib have shown to improve HRQOL in diverse groups of GEP-NEN patients (255). In the CLARINET study, QLC-C30 data were mapped to EQ-5D utilities and not surprisingly worse utility values were noted with PD compared to SD. Of note, tumor location (midgut vs. pancreas) did not affect utility (256). PNEN patients treated with everolimus showed stable HRQOL scores as opposed to worse scores in non-PNEN patients (Pavel). PRRT treatment of PNEN patients resulted in significantly improved global health status, social functioning and mitigation of physical complaints (257). Thus, data are emerging on HRQOL in PNEN patients. However, most studies are too heterogenous in terms of patient populations and treatment interventions to draw firm conclusions (258). Moving forward, it will be important for HRQOL to be measured as a key component of clinical trials.

EXPERT COMMENTARY

After many years of frustration, our knowledge regarding the biology, pathophysiology and genetics of (P)NENs increased. This has led to marked improvements in (functional) imaging, with the development of ⁶⁸Gallium-labeled SSAs, as well as targeted treatments such as the tyrosine-kinase inhibitor Sunitinib, and the mTOR inhibitor Everolimus. In addition, PRRT seems to be expanding its role in treatment from midgut to PNENs. In the future, both imaging and treatment options will continue to evolve as more specific imaging agents and therapeutic targets are being developed and evaluated in numerous studies. The relatively uncommon nature of PNENs has made designing and completing randomized studies of adequate power challenging for a single institution. Therefore, we encourage the recent trend of multi-institutional, multinational studies in more homogeneous patient populations. We also strongly agree with the recommendation of NANETS, ENETS and other groups that all of these patients should be entered into clinical trials whenever feasible. Determining study availability and patient eligibility has been greatly facilitated by Clinical trials.gov as well as institutional and organizational websites. Enrolling more patients in clinical trials by overcoming barriers to participation will be required to move patient care forward.

Unfortunately, to date, the optimal treatment(s) and treatment sequences have yet to be defined. The lack of treatment standardization, the plethora of treatments that most patients receive, and different treatment sequences make it extremely difficult to assess the effectiveness of a particular treatment relative to others. Moreover, head-to-head comparisons are lacking as well. Available consensus guidelines establish broad principles, but are generally not helpful in managing a specific patient. Management has become even more complex given the multiplicity of effective treatments for advanced disease, none of which has convincingly been shown to be superior to the other. Hence, an experienced multidisciplinary team is essential to guide management of these patients. Given relative parity of effectiveness, decisions regarding choice of treatment need to be based on multiple considerations, including patient’s overall health, disease burden, symptomatology, rate of progression, treatment toxicity, effect on QOL, and cost. These considerations will usually lead to one treatment being favored over another.

Because of the relatively indolent nature of many (or most) NENs, long-term follow-up to assess differences in treatment outcomes, is required. However, biomarkers that can predict response to a particular therapy are currently not available. We expect that in the future the so-called tumor circulome, especially ctDNA, could play an important role in this as recent studies revealed its potential to diagnose, prognosticate and monitor disease progression.

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