Infiltration pattern predicts metastasis and progression better than the T-stage and grade in pancreatic neuroendocrine tumors: a proposal for a novel infiltration-based morphologic grading

Subgrading of G2 Pancreatic Neuroendocrine Tumors as 2A (Ki67 3% to < 10%) Versus 2B (10% to ≤ 20%) Identifies Behaviorally Distinct Subsets in Keeping with the Evolving Management Protocols

BACKGROUND

Grade 1/2 PanNETs are mostly managed similarly, typically without any adjunct treatment with the belief that their overall metastasis rate is low. In oncology literature, Ki67-index of 10% is increasingly being used as the cutoff in stratifying patients to different protocols, although there are no systematic pathology-based studies supporting this approach.

METHODS

Ki67-index was correlated with clinicopathologic parameters in 190 resected PanNETs. A validation cohort (n = 145) was separately analyzed.

RESULTS

In initial cohort, maximally selected rank statistics method revealed 12% to be the discriminatory cutoff (close to 10% rule of thumb). G2b cases had liver/distant metastasis rate of almost threefold higher than that of G2a and showed significantly higher frequency of all histopathologic signs of aggressiveness (tumor size, perineural/vascular invasion, infiltrative growth pattern, lymph node metastasis). In validation cohort, these figures were as striking. When all cases were analyzed together, compared with G1, the G2b category had nine times higher liver/distant metastasis rate (6.1 vs. 58.5%; p < 0.001) and three times higher lymph node metastasis rate (20.5 vs. 65.1%; p < 0.001).

CONCLUSIONS

G2b PanNETs act very similar to G3, supporting management protocols that regard them as potential therapy candidates. Concerning local management, metastatic behavior in G2b cases indicate they may not be as amenable for conservative approaches, such as watchful waiting or enucleation. This substaging should be considered into diagnostic guidelines, and clinical trials need to be devised to determine the more appropriate management protocols for G2b (10% to ≤ 20%) group, which shows liver/distant metastasis in more than half of the cases, which at minimum warrants closer follow-up.

Neoplastic Progression in Neuroendocrine Neoplasms of the Pancreas

CONTEXT.—

Pancreatic neuroendocrine neoplasms (PanNENs) represent a heterogeneous group of epithelial tumors of the pancreas showing neuroendocrine differentiation. These neoplasms are classified into well-differentiated pancreatic neuroendocrine tumors (PanNETs), which include G1, G2, and G3 tumors, and poorly differentiated pancreatic neuroendocrine carcinomas (PanNECs), which are G3 by definition. This classification mirrors clinical, histologic, and behavioral differences and is also supported by robust molecular evidence.

OBJECTIVE.—

To summarize and discuss the state of the art regarding neoplastic progression of PanNENs. A better comprehension of the mechanisms underpinning neoplastic evolution and progression of these neoplasms may open new horizons for expanding biologic knowledge and ultimately for addressing new therapeutic strategies for patients with PanNENs.

DATA SOURCES.—

Literature review of published studies and the authors' own work.

CONCLUSIONS.—

PanNETs can be seen as a unique category, where G1-G2 tumors may progress to G3 tumors mainly driven by DAXX/ATRX mutations and alternative lengthening of telomeres. Conversely, PanNECs display totally different histomolecular features more closely related to pancreatic ductal adenocarcinoma, including TP53 and Rb alterations. They seem to derive from a nonneuroendocrine cell of origin. Even the study of PanNEN precursor lesions corroborates the rationale of considering PanNETs and PanNECs as separate and distinct entities. Improving the knowledge regarding this dichotomous distinction, which guides tumor evolution and progression, will represent a critical basis for PanNEN precision oncology.

Radiologic tumor border can further stratify prognosis in patients with pancreatic neuroendocrine tumor

BACKGROUND AND OBJECTIVES

Pancreatic neuroendocrine tumor (PanNET), although rare in incidence, is increasing in recent years. Several clinicopathologic and molecular factors have been suggested for patient stratification due to the extensive heterogeneity of PanNETs. We aimed to discover the prognostic role of assessing the tumor border of PanNETs with pre-operative computed tomography (CT) images and correlate them with other clinicopathologic factors.

METHODS

The radiologic, macroscopic, and microscopic tumor border of 183 surgically resected PanNET cases was evaluated using preoperative CT images (well defined vs. poorly defined), gross images (expansile vs. infiltrative), and hematoxylin and eosin-stained slides (pushing vs. infiltrative). The clinicopathologic and prognostic significance of the tumor border status was compared with other clinicopathologic factors.

RESULTS

A poorly defined radiologic tumor border was observed in 65 PanNET cases (35.5 %), and were more frequent in male patients (P = 0.031), and tumor with larger size, infiltrative macroscopic growth pattern, infiltrative microscopic tumor border, higher tumor grade, higher pT category, lymph node metastasis, lymphovascular and perineural invasions (all, P < 0.001). Patients with PanNET with a poorly defined radiologic tumor border had significantly worse overall survival (OS) and recurrence-free survival (RFS; both, P < 0.001). Multivariable analysis revealed that PanNET with a poorly defined radiologic border is an independent poor prognostic factor for both OS (P = 0.049) and RFS (P = 0.027).

CONCLUSION

Pre-operative CT-based tumor border evaluation can provide additional information regarding survival and recurrence in patients with PanNET.

Pancreatic Neuroendocrine Microtumors (WHO 2022) Are Not Always Low-Grade Neoplasms: A Case with a Highly Increased Proliferation Rate

Traditionally considered non-functional low proliferative benign neuroendocrine proliferations measuring less than 5 mm, pancreatic (neuro)endocrine microadenomas are now classified as pancreatic neuroendocrine microtumors in the 2022 WHO classification of endocrine and neuroendocrine tumors. This case report discussed the features of an incidentally identified 4.7-mm glucagon-expressing pancreatic neuroendocrine microtumor with MEN1 mutation only, chromosomally stable and an epigenetic alpha-like phenotype. The tumor was associated with an unexplained increased proliferation rate in Ki-67 of 15%. There was no associated DAXX/ATRX deficiency. The presented case challenges the conventional thought of a low proliferative disease of the so-called "pancreatic neuroendocrine microadenomas" and provides additional support to the 2022 WHO classification that also requires grading of these neoplasms. Despite exhibiting molecular features of less aggressive behavior, the case also underscores the biological complexity of pancreatic neuroendocrine microtumors. By recognizing the heterogenous spectrum of neuroendocrine neoplasms, the current case also contributes to ongoing discussions on how to optimize the clinical management of such tumors.

Infiltrative Growth Predicts the Risk of Recurrence After Surgery in Well-Differentiated Non-Functioning Pancreatic Neuroendocrine Tumors

The incidence of well-differentiated non-functioning pancreatic neuroendocrine tumors (NF-PanNET) increased during the last decades. The risk of relapse after curative surgery, albeit low, is not negligible; moreover, adjuvant treatment is currently not an option and a reliable predictive model based on prognostic characteristics is urgently needed for tailoring a follow-up strategy. The histological classification of PanNET now relies only on the proliferative activity (mitosis and Ki67) and staging. In contrast to other endocrine neoplasms, the role of infiltrative growth pattern in NF-PanNET is not taken into consideration at present. In the current study, 247 consecutive patients who underwent surgical resection for a NF-PanNET were examined for the histological growth pattern of the tumor. Two distinct patterns (non-infiltrative vs. infiltrative) were described with the latter being further subclassified according to the type of structures invaded by the tumor (non-infiltrative: pattern 1; infiltration of adjacent pancreatic parenchyma and/or peripancreatic soft tissue: pattern 2; invasion of nearby organs and/or major vessels: pattern 3). The infiltrative growth resulted to be strongly associated with a poorer survival compared to a non-infiltrative growth (p < 0.001). In particular, the distinction between pancreatic parenchyma and/or peripancreatic soft tissue invasion versus adjacent organs and/or major vessels invasion was the most powerful predictor of recurrence after surgery at multivariate analysis (pattern 2 vs. pattern 1: HR 10.136, p = 0.028; pattern 3 vs. pattern 1: HR 15.775, p = 0.015). The infiltrative growth pattern could therefore provide additional prognostic information implementing the current grading and staging system.

Silva cumulative score and its relationship with prognosis in Endocervical adenocarcinoma

Background

The Silva system has been demonstrated to have a good predictive value of lymph node metastasis (LNM) in endocervical adenocarcinoma (EAC). Tumours were classified based on the highest identified pattern of invasion in this system, this may not exactly reflect the true situation when it presents with a “mixed pattern” in some cases. Recent study has shown that patients with lymphovascular invasion (LVI) have worse prognosis in EAC. Here we design a Silva cumulative score (SCS) system which also combined the LVI status to explore its prognostic role in EAC patients.

Methods

A total of 120 patients with EAC were included in this study. Clinicopathological characteristics were retrospectively retrieved from the medical records and follow-up data were obtained. The clinicopathological information included age at diagnosis, depth of invasion (DOI), LNM, LVI, Silva classification, and SCS. SCS is a classification system based on the sum score of different Silva pattern which is founded on morphological phenomena. The relationships between the pathological characteristics and prognoses were analyzed.

Results

According to the Silva system, 11 (9.2%), 22 (18.3%) and 87 (72.5%) patients had patterns A, B, and C, respectively. Patients with pattern C had the highest incidence of LVI and LNM (p < 0.05). Although the Kaplan-Meier curves demonstrated that survival decreased with increasing Silva classification for A-C cancers, there was no statistically significant difference [disease-free survival (DFS): p = 0.181; overall survival (OS): p = 0.205]. There were 45 cases presented as mixed-type of Silva patterns. According to the SCS, 23 cases (19.2%) were rated as grade I, 31 cases (25.8%) as grade II and 66 (55.0%) cases as grade III. Patients with SCS grade III had the highest incidence of LVI and LNM (p < 0.05). Kaplan–Meier analysis revealed that patients with higher SCS had significantly shorter DFS and OS than those with lower SCS (p < 0.05). High SCS was an independent predictor of poorer OS and DFS (p < 0.05) in patients with EAC.

Conclusions

The application of the Silva system could effectively predict the LNM of patients and may be helpful in selecting an appropriate surgical procedure. The SCS system we designed showed a good predictive value for DFS and OS in EAC.

"Pure" hepatoid tumors of the pancreas harboring CTNNB1 somatic mutations: a new entity among solid pseudopapillary neoplasms

Hepatoid tumors (HTs) represent a rare group of neoplasms that are histologically similar to hepatocellular carcinoma but arise outside the liver. The current World Health Organization classification recognizes the hepatoid morphology of pancreatic tumors only as a possible variant of pancreatic ductal adenocarcinoma (PDAC). Here, we describe two cases of "pure" HT of the pancreas showing common features and characterized by indolent biological behavior. These tumors were roundish nodules with pushing borders, hyaline globules, and pure hepatoid histology; they were diffusely positive for β-catenin and LEF1 on immunohistochemistry. At next-generation sequencing, both neoplasms harbored only one pathogenic somatic mutation that affected the CTNNB1 gene at exon 3 and showed a loss of heterozygosity on chromosomes 18 and 21. By integrating macroscopic and microscopic features, along with their molecular profiles, we advocate that such tumors represent a distinct entity from PDAC and should be considered a new variant of solid pseudopapillary neoplasms. The recognition of this new neoplastic category may have immediate implications not only for tumor taxonomy but also for clinical practice.

A Nomogram to Accurately Identify Pancreatic Neuroendocrine Tumors Metastasizing to Distant Organs: A Study Based on Two National Population-Based Cohorts From the United States and China

Background:

Distant organ metastasis is the leading cause of death in pancreatic neuroendocrine tumor (pNET) patients. In the present study, we aimed to develop and validate a nomogram that could accurately identify pNET metastasizing to distant organs.

Methods:

The cases extracted from the Surveillance, Epidemiology, and End Results (SEER) program were assigned to the training cohort and validation cohort. The cases from the Chinese Gastrointestinal Neuroendocrine Tumors program were assigned to the external validation cohort. The strategy was developed with the support of a nomogram, and the predictive value of this strategy was evaluated by the receiver operating characteristic (ROC) curve analysis.

Results:

In total, 2024 American cases were involved in the present study. Besides, 1450 and 574 patients were allocated into training and internal validation cohorts, respectively. In addition, 122 Chinese patients were assigned to the external validation cohort. The results of the univariate logistic regression analysis suggested that tumor grade, tumor size, and the number of metastatic lymph nodes were the risk of metastasis to distant organs, and these 3 clinicopathological characteristics were used to develop the nomogram. We observed that the accuracy of the nomogram for predicting metastasis to distant organs was 0.797, 0.819, and 0.837 in the training cohort, internal validation cohort, and external validation cohort, respectively.

Conclusions:

A predictive nomogram was developed and validated, and it showed an acceptable performance in predicting metastasis to distant organs. The results will enable clinicians to identify pNETs, metastasizing to distant organs, and develop an effective individualized therapeutic strategy for these patients.