[Interpretation on the update of 2022 WHO classification of neuroendocrine tumors].

The 5th edition of the WHO Endocrine and Neuroendocrine Oncology Blue Book, released in 2022, contained some changes in the classification of neuroendocrine tumors. A brief summary of the main changes has been provided in this section. Mainly summarized as changes in naming, differentiation and classification of neuroendocrine tumors, and tumor grading systems related to anatomical locations, morphological characteristics of neuroendocrine tumors in different locations, auxiliary diagnostic and prognostic/therapeutic markers, differential diagnosis and diagnostic difficulties of neuroendocrine tumors.

Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumours in the lungNENomics project.

BACKGROUND: Six thoracic pathologists reviewed 259 lung neuroendocrine tumours (LNETs) from the lungNENomics project, with 171 of them having associated survival data. This cohort presents a unique opportunity to assess the strengths and limitations of current World Health Organization (WHO) classification criteria and to evaluate the utility of emerging markers. PATIENTS AND METHODS: Patients were diagnosed based on the 2021 WHO criteria, with atypical carcinoids (ACs) defined by the presence of focal necrosis and/or 2-10 mitoses per 2 mm2. We investigated two markers of tumour proliferation: the Ki-67 index and phospho-histone H3 (PHH3) protein expression, quantified by pathologists and automatically via deep learning. Additionally, an unsupervised deep learning algorithm was trained to uncover previously unnoticed morphological features with diagnostic value. RESULTS: The accuracy in distinguishing typical from ACs is hampered by interobserver variability in mitotic counting and the limitations of morphological criteria in identifying aggressive cases. Our study reveals that different Ki-67 cut-offs can categorise LNETs similarly to current WHO criteria. Counting mitoses in PHH3+ areas does not improve diagnosis, while providing a similar prognostic value to the current criteria. With the advantage of being time efficient, automated assessment of these markers leads to similar conclusions. Lastly, state-of-the-art deep learning modelling does not uncover undisclosed morphological features with diagnostic value. CONCLUSIONS: This study suggests that the mitotic criteria can be complemented by manual or automated assessment of Ki-67 or PHH3 protein expression, but these markers do not significantly improve the prognostic value of the current classification, as the AC group remains highly unspecific for aggressive cases. Therefore, we may have exhausted the potential of morphological features in classifying and prognosticating LNETs. Our study suggests that it might be time to shift the research focus towards investigating molecular markers that could contribute to a more clinically relevant morpho-molecular classification.

A clinicopathological study of non-functioning pituitary neuroendocrine tumours using the World Health Organization 2022 classification.

Background: The 2022 World Health Organization (WHO) classification of pituitary neuroendocrine tumour (PitNET) supersedes the previous one in 2017 and further consolidates the role of transcription factors (TF) in the diagnosis of PitNET. Here, we investigated the clinical utility of the 2022 WHO classification, as compared to that of 2017, in a cohort of patients with non-functioning PitNET (NF-PitNET). Methods: A total of 113 NF-PitNET patients who underwent resection between 2010 and 2021, and had follow-up at Queen Mary Hospital, Hong Kong, were recruited. Surgical specimens were re-stained for the three TF: steroidogenic factor (SF-1), T-box family member TBX19 (TPIT) and POU class 1 homeobox 1 (Pit-1). The associations of different NF-PitNET subtypes with tumour-related outcomes were evaluated by logistic and Cox regression analyses. Results: Based on the 2022 WHO classification, the majority of NF-PitNET was SF-1-lineage tumours (58.4%), followed by TPIT-lineage tumours (18.6%), tumours with no distinct lineage (16.8%) and Pit-1-lineage tumours (6.2%). Despite fewer entities than the 2017 classification, significant differences in disease-free survival were present amongst these four subtypes (Log-rank test p=0.003), specifically between SF-1-lineage PitNET and PitNET without distinct lineage (Log-rank test p<0.001). In multivariable Cox regression analysis, the subtype of PitNET without distinct lineage (HR 3.02, 95% CI 1.28-7.16, p=0.012), together with tumour volume (HR 1.04, 95% CI 1.01-1.07, p=0.017), were independent predictors of a composite of residual or recurrent disease. Conclusion: The 2022 WHO classification of PitNET is a clinically useful TF and lineage-based system for subtyping NF-PitNET with different tumour behaviour and prognosis.

[Pulmonary neuroendocrine tumors : Current review]. / Pulmonale neuroendokrine Tumoren : Aktuelle Übersicht.

CLINICAL ISSUE: Neuroendocrine neoplasms of the lung are a heterogenous tumor group. The pathological classification comprises diffuse idiopathic pulmonary neuroendocrine cell hyperplasia, classic neuroendocrine tumors, and neuroendocrine carcinoma. Classic neuroendocrine tumors include typical and atypical carcinoid tumors. DIAGNOSTIC WORK-UP: Imaging plays an important role in diagnosis and can help in identifying the tumor biology. Overall, this tumor group is rare, comprising less than 2% of all thoracic tumors. PRACTICAL RECOMMENDATIONS: In the current review, the various tumors are presented and important aspects regarding pathological classification, imaging modalities, and treatment are described.

Changes in categorization or nomenclature within neuroendocrine tumors.

Abstract: The 5th edition of the World Health Organization (WHO) classification of neuroendocrine neoplasms (NENs) is built to achieve a uniform terminology and to define a similar diagnostic scheme across different anatomic locations. Since the 4th edition, a chapter discussing NENs in nonneuroendocrine organs has been introduced, which proposes a binary system for classification segregating well-differentiated neoplasms, termed neuroendocrine tumors (NETs), and poorly differentiated neoplasms, termed neuroendocrine carcinomas (NECs). A grading system for NETs is based on mitotic index and/or Ki-67 index and/or necrosis, depending on the different locations. Although this approach has been already well established in the digestive system, it modifies and homogenizes the classification of NENs in the urinary tract, in female genital organs, and in the male genital system. In the lung and thymus, the double terminology of carcinoid/NET, already introduced in the 5th edition of the WHO classification of thoracic tumors, is endorsed. This approach undoubtedly helps the multidisciplinary approach for the diagnosis and clinical management of patients affected by these neoplasms, without losing site-specific characteristics that influence the clinical and biological behavior of tumors in different anatomical sites. Other major advances of the new WHO scheme are the homogenization of epidemiological data and the correct integration of data from prospective future studies aimed at the definition of molecular profiles and at the identification of tumor type-specific and patient-specific therapeutic approaches.

[Current WHO classification (2022) of neuroendocrine neoplasms]. / Aktuelle WHO-Klassifikation (2022) neuroendokriner Neoplasien.

CLINICAL ISSUE: After the first description of the "carcinoid tumors" by the pathologist Siegfried Oberndorfer in Munich, the classification system of neuroendocrine neoplasms (NENs) is still a challenge and an evolving concept. METHODICAL INNOVATIONS: The new WHO classification system proposed a framework for universal classification. ACHIEVEMENTS: The new WHO classification system recognizes two distinct families distinguished by genetic, morphology and clinical behaviour: Well differentiated NENs are defined as neuroendocrine tumor (NET G1, G2, G3), while poorly differentiated ones are defined as neuroendocrine carcinoma (NEC, G3) and further subdivided into small and large cell carcinoma. All NENs are characterized by the expression of synaptophysin and chromogranin A, Ki-67 and morphology. MOLECULAR PATHOLOGY: The morphological NEN dichotomy is supported by genetic alterations. NECs show TP53 and RB1 alterations that are absent in NETs and are therefore useful for differentiating between NETs and NECs. PRACTICAL RECOMMENDATIONS: All NENs are divided into well-differentiated neuroendocrine tumor (NET G1, G2, G3) or poorly differentiated neuroendocrine carcinoma (NEC, G3). They are categorized by morphology, mitotic count and immunohistochemistry with synaptophysin, chromogranin and Ki-67.

An Illustrated Review of the Recent 2019 World Health Organization Classification of Neuroendocrine Neoplasms: A Radiologic and Pathologic Correlation.

ABSTRACT: Recent advances in molecular pathology and an improved understanding of the etiology of neuroendocrine neoplasms (NENs) have given rise to an updated World Health Organization classification. Since gastroenteropancreatic NENs (GEP-NENs) are the most common forms of NENs and their incidence has been increasing constantly, they will be the focus of our attention. Here, we review the findings at the foundation of the new classification system, discuss how it impacts imaging research and radiological practice, and illustrate typical and atypical imaging and pathological findings. Gastroenteropancreatic NENs have a highly variable clinical course, which existing classification schemes based on proliferation rate were unable to fully capture. While well- and poorly differentiated NENs both express neuroendocrine markers, they are fundamentally different diseases, which may show similar proliferation rates. Genetic alterations specific to well-differentiated neuroendocrine tumors graded 1 to 3 and poorly differentiated neuroendocrine cancers of small cell and large-cell subtype have been identified. The new tumor classification places new demands and creates opportunities for radiologists to continue providing the clinically most relevant report and on researchers to design projects, which continue to be clinically applicable.

Molecular Classification of Gastrointestinal and Pancreatic Neuroendocrine Neoplasms: Are We Ready for That?

In the last two decades, the increasing availability of technologies for molecular analyses has allowed an insight in the genomic alterations of neuroendocrine neoplasms (NEN) of the gastrointestinal tract and pancreas. This knowledge has confirmed, supported, and informed the pathological classification of NEN, clarifying the differences between neuroendocrine carcinomas (NEC) and neuroendocrine tumors (NET) and helping to define the G3 NET category. At the same time, the identification genomic alterations, in terms of gene mutation, structural abnormalities, and epigenetic changes differentially involved in the pathogenesis of NEC and NET has identified potential molecular targets for precision therapy. This review critically recapitulates the available molecular features of digestive NEC and NET, highlighting their correlates with pathological aspects and clinical characteristics of these neoplasms and revising their role as predictive biomarkers for targeted therapy. In this context, the feasibility and applicability of a molecular classification of gastrointestinal and pancreatic NEN will be explored.

Molecular typing and mutational characterization of rectal neuroendocrine neoplasms.

BACKGROUND: Rectal neuroendocrine neoplasms (NENs) are rare neoplasms with limited understanding of its genomic alterations and molecular typing. METHODS: The paraffin-embedded tissue specimens of 38 patients with rectal NENs after surgery were subjected to whole gene sequencing (WGS), and mutation profilings were drawn to identify high-frequency mutation genes, copy-number variations (CNVs), tumor mutation burden (TMB), signal pathways, mutation signatures, DNA damage repair (DDR) genes, and molecular types. The differences of mutated genes and signaling pathways in different pathological grades and metastatic/non-metastatic groups were compared. It helped to search for potential targets. RESULTS: C > T and T > C transitions are the most common base substitutions in rectal NENs. DNA mismatch repair deficiency, DNA base modifications, smoking and exposure to ultraviolet light might play a role in the occurrence of rectal NENs. DAXX, KMT2C, BCL2L1, LTK, MERTK, SPEN, PKN1, FAT3, and LRP2 mutations were found in only low-grade rectal NETs, whereas APC, TP53, NF1, SOX9, and BRCA1 mutations were common in high-grade rectal NECs/MiNENs. These genes helped in distinguishing poorly-differentiated or well-differentiated rectal NENs. Alterations in P53, Wnt and TGFß signaling pathways were more pronounced in rectal NECs and MiNENs. Alterations in Wnt, MAPK and PI3K/AKT signaling pathways promoted metastases. Rectal NENs were classified into two molecular subtypes by cluster analysis based on the mutant genes and signaling pathways combined with clinicopathological features. Patients with mutations in the LRP2, DAXX, and PKN1 gene showed a trend of well-differentiated and early-stage tumors with less metastasis (p = 0.000). CONCLUSIONS: This study evaluated risk factors for regional lymphatic and/or distant metastases, identified high-frequency mutated genes, mutation signatures, altered signaling pathways through NGS. Rectal NENs were divided into two molecular types. This helps to evaluate the likelihood of metastasis, formulate follow-up strategies for patients and provide a target for future research on precision treatment of rectal NENs. PARP inhibitors, MEK inhibitors, mTOR/AKT/PI3K and Wnt signaling pathway inhibitors may be effective drugs for the treatment of metastatic rectal NENs.

[Unification of pathomorphological examination of patients with neuroendocrine tumors of the pituitary gland. Controversial issues of the new classification].

The progressive improvement of the classification using modern analytical methods is an essential tool for the development of precise and personalized approaches to the treatment of pituitary adenomas. In recent years, endocrinologists have witnessed evolutionary changes that have occurred in the histopathological identification of pituitary neoplasms, revealing new possibilities for studying tumorigenesis and predicting biological behavior.The paper considers the historical aspects of the gradual improvement of the classification of pituitary adenomas, as well as the new international 2022 WHO classification, according to which pituitary adenomas are included in the list of neuroendocrine tumors (PitNETs) to reflect the biological aggressiveness of some non-metastatic pituitary adenomas. The characteristics of pituitary adenoma are presented, as well as a list of histological subtypes of aggressive neuroendocrine tumors of the pituitary gland, marked by the main potentials for invasive growth, an increased risk of recurrence and a negative clinical prognosis.The expediency of changing the definition of «pituitary adenoma¼ to «neuroendocrine tumor¼ is discussed. It is emphasized that the introduction of a unified clinical, laboratory and morphological protocol into national clinical practice will help provide comparable comparative studies on the prognosis of the disease and the effectiveness of secondary therapy and also contribute to adequate management of potentially aggressive PitNETs.

The classification of neuroendocrine neoplasms of the lung and digestive system according to WHO, 5th edition: similarities, differences, challenges, and unmet needs.

Neuroendocrine neoplasms (NENs) are a group of disease entities sharing common morphological, ultrastructural and immunophenotypical features, yet with distinct biological behavior and clinical outcome, ranging from benign to frankly malignant. Accordingly, a spectrum of therapeutic options for each single entity is available, including somatostatin analogues (SSA), mTOR-inhibitors, peptide receptor radionuclide therapy (PRRT), non-platinum and platinum chemotherapy. In the last few decades, several attempts have been made to better stratify these lesions refining the pathological classifications, so as to obtain an optimal correspondence between the scientific terminology and, the predictive and prognostic features of each disease subtype, and achieve a global Classification encompassing NENs arising at different anatomical sites. The aim of this review was to analyze, compare and discuss the main features and issues of the latest WHO Classifications of NENs of the lung and the digestive system, in order to point out the strengths and limitations of our current understanding of these complex diseases.

Risk factors for gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs): a three-centric case-control study.

PURPOSE: Risk factors for sporadic GEP-NENs are still not well defined. To identify the main clinical risk factors represents the aim of this study performed by three Italian referral centers for NENs. METHODS: We performed a retrospective case-control study including 148 consecutive sporadic GEP-NENs and 210 age- and sex-matched controls. We collected data on clinical features, cancer family history and other potential risk factors. RESULTS: Mean age was 58.3 ± 15.8 years; 50% males, primary site was pancreas (50.7%), followed by ileum (22.3%). The 62.8% and 29.1% of cases were G1 and G2, respectively; the 40% had locally advanced or metastatic disease at diagnosis. Independent risk factors for GEP-NENs were: family history of non-neuroendocrine GEP cancer (OR 2.16, 95% CI 1.31-3.55, p = 0.003), type 2 diabetes mellitus (T2DM) (OR 2.5, 95% CI 1.39-4.51, p = 0.002) and obesity (OR 1.88, 95% CI 1.18-2.99, p = 0.007). In the T2DM subjects, metformin use was a protective factor (OR 0.28, 95% CI 0.08-0.93, p = 0.049). T2DM was also associated with a more advanced (OR 2.39, 95% CI 1.05-5.46, p = 0.035) and progressive disease (OR 2.47, 95% CI 1.08-5.34, p = 0.03). Stratifying cases by primary site, independent risk factors for pancreatic NENs were T2DM (OR 2.57, 95% CI 1.28-5.15, p = 0.008) and obesity (OR 1.98, 95% CI 1.11-3.52, p = 0.020), while for intestinal NENs family history of non-neuroendocrine GEP cancer (OR 2.46, 95% CI 1.38-4.38, p = 0.003) and obesity (OR 1.90, 95% CI 1.08-3.33, p = 0.026). CONCLUSION: This study reinforces a role for family history of non-neuroendocrine GEP cancer, T2DM and obesity as independent risk factors for GEP-NENs and suggests a role of metformin as a protective factor in T2DM subjects. If confirmed, these findings could have a significant impact on prevention strategies for GEP-NENs.

Automated assessment of Ki-67 proliferation index in neuroendocrine tumors by deep learning.

The Ki-67 proliferation index (PI) is a prognostic factor in neuroendocrine tumors (NETs) and defines tumor grade. Analysis of Ki-67 PI requires calculation of Ki-67-positive and Ki-67-negative tumor cells, which is highly subjective. To overcome this, we developed a deep learning-based Ki-67 PI algorithm (KAI) that objectively calculates Ki-67 PI. Our study material consisted of NETs divided into training (n = 39), testing (n = 124), and validation (n = 60) series. All slides were digitized and processed in the Aiforia® Create (Aiforia Technologies, Helsinki, Finland) platform. The ICC between the pathologists and the KAI was 0.89. In 46% of the tumors, the Ki-67 PIs calculated by the pathologists and the KAI were the same. In 12% of the tumors, the Ki-67 PI calculated by the KAI was 1% lower and in 42% of the tumors on average 3% higher. The DL-based Ki-67 PI algorithm yields results similar to human observers. While the algorithm cannot replace the pathologist, it can assist in the laborious Ki-67 PI assessment of NETs. In the future, this approach could be useful in, for example, multi-center clinical trials where objective estimation of Ki-67 PI is crucial.

Specific cell differentiation in breast cancer: a basis for histological classification.

Breast parenchyma progenitor cells show a high degree of phenotypic plasticity reflected in the wide range of morphology observed in benign and malignant breast tumours. Although there is evidence suggesting that all breast cancer (BC) arises from a common epithelial progenitor or stem cell located at the terminal duct lobular units (TDLUs), BC shows a broad spectrum of morphology with extensive variation in histological type and grade. This is related to the complexity of BC carcinogenesis including initial genetic changes in the cell of origin, subsequent genetic and epigenetic alterations and reprogramming that occur at various stages of BC development and the interplay with the surrounding microenvironment, factors which influence the process of differentiation. Differentiation in BC determines the morphology, which can be measured using histological grade and tumour type. Histological grade, which measures the similarity to the TDLUs, reflects the degree of differentiation whereas tumour type reflects the type of differentiation. Understanding BC phenotypic differentiation facilitates the accurate diagnosis and histological classification of BC with corresponding clinical implications in terms of disease behaviour, prognosis and management plans. In this review, we highlight the potential pathways that BC stem cells follow resulting in the development of different histological types of BC and how knowledge of these pathways impacts our ability to classify BC in diagnostic practice. We also discuss the role of cellular differentiation in producing metaplastic and neuroendocrine carcinomas of the breast and how the latter differ from their counterparts in other organs, with emphasis on clinical relevance.

The genomic landscape of 85 advanced neuroendocrine neoplasms reveals subtype-heterogeneity and potential therapeutic targets.

Metastatic and locally-advanced neuroendocrine neoplasms (aNEN) form clinically and genetically heterogeneous malignancies, characterized by distinct prognoses based upon primary tumor localization, functionality, grade, proliferation index and diverse outcomes to treatment. Here, we report the mutational landscape of 85 whole-genome sequenced aNEN. This landscape reveals distinct genomic subpopulations of aNEN based on primary localization and differentiation grade; we observe relatively high tumor mutational burdens (TMB) in neuroendocrine carcinoma (average 5.45 somatic mutations per megabase) with TP53, KRAS, RB1, CSMD3, APC, CSMD1, LRATD2, TRRAP and MYC as major drivers versus an overall low TMB in neuroendocrine tumors (1.09). Furthermore, we observe distinct drivers which are enriched in somatic aberrations in pancreatic (MEN1, ATRX, DAXX, DMD and CREBBP) and midgut-derived neuroendocrine tumors (CDKN1B). Finally, 49% of aNEN patients reveal potential therapeutic targets based upon actionable (and responsive) somatic aberrations within their genome; potentially directing improvements in aNEN treatment strategies.

Recommendations on the pathological report of pituitary tumors. A consensus of experts of the Spanish Society of Endocrinology and Nutrition and the Spanish Society of Pathology.

Pituitary neuroendocrine tumors (PitNETs) constitute, together with other tumors of the sellar region, 15-25% of intracranial neoplasms. In 2017, the World Health Organization proposed a new classification of PitNETs. The main innovation with respect to the 2004 classification was the recommendation to include in the immunohistochemical evaluation of PitNETs the determination of the transcription factors of the 3 pituitary cell lineages: Pit-1, Tpit and SF-1. Additionally, other clinicopathological classifications with a predictive capacity of tumor behavior during follow-up were proposed. Given these changes, it is appropriate to adapt the knowledge generated during the last 15 years to the daily practice of the treatment and monitoring of PitNETs at the Centers of Excellence in Pituitary Pathology. This document includes the positioning of the Spanish Society of Endocrinology and Nutrition (SEEN) and the Spanish Society of Pathology (SEAP) on the classification and denomination of the PitNETs and the information that the pathologist should provide to the clinician to facilitate the treatment and monitoring of these tumors.

Middle Ear "Adenoma": a Neuroendocrine Tumor with Predominant L Cell Differentiation.

This morphological and immunohistochemical study demonstrates that tumors currently known as "middle ear adenomas" are truly well-differentiated epithelial neuroendocrine tumors (NETs) composed of cells comparable to normal intestinal L cells, and therefore, these tumors resemble hindgut NETs. These tumors show consistent expression of glucagon, pancreatic polypeptide, PYY, and the transcription factor SATB2, as well as generic neuroendocrine markers and keratins. The same L cell markers are expressed by cells within the normal middle ear epithelium. These markers define a valuable immunohistochemical profile that can be used for differential diagnosis of middle ear neoplasms, particularly in distinguishing epithelial NETs from paragangliomas. The discovery of neuroendocrine cells expressing the same markers in non-neoplastic middle ear mucosa opens new areas of investigation into the physiology of the normal middle ear and the pathophysiology of middle ear disorders.

Pituitary neuroendocrine tumors: a model for neuroendocrine tumor classification.

The classification of adenohypophysial neoplasms as "pituitary neuroendocrine tumors" (PitNETs) was proposed in 2017 to reflect their characteristics as epithelial neuroendocrine neoplasms with a spectrum of clinical behaviors ranging from small indolent lesions to large, locally invasive, unresectable tumors. Tumor growth and hormone hypersecretion cause significant morbidity and mortality in a subset of patients. The proposal was endorsed by a WHO working group that sought to provide a unified approach to neuroendocrine neoplasia in all body sites. We review the features that are characteristic of neuroendocrine cells, the epidemiology and prognosis of these tumors, as well as further refinements in terms used for other pituitary tumors to ensure consistency with the WHO framework. The intense study of PitNETs has provided information about the importance of cellular differentiation in tumor prognosis as a model for neuroendocrine tumors in different locations.