WHO updates in head and neck - neuroendocrine neoplasms

Page 1: Overview of the 2022 WHO Classification of Head and Neck Neuroendocrine Neoplasms

Introduction

  • The article provides an overview of the 2022 WHO classification of head and neck neuroendocrine neoplasms (NENs), adopting a question-answer model.

  • Neuroendocrine neoplasms include both epithelial and special neoplasms arising from different regions, including the upper aerodigestive tract and salivary glands.

Key Terminology

  • Neuroendocrine Tumors (NETs): Well-differentiated epithelial neoplasms, graded as G1, G2, or G3 based on necrosis and mitotic activity.

  • Neuroendocrine Carcinomas (NECs): Poorly differentiated tumors, subdivided into small and large cell types, exhibiting high mitotic activity and specific cytomorphological features.

Classification Details

  • The 2022 WHO classification aligns with IARC/WHO terminology frameworks. It restricts NEC classification to poorly differentiated epithelial neoplasms.

  • NETs are distinguished by differentiation grades:

    • G1 NET: No necrosis, <2 mitoses per 2 mm², Ki67 < 20%

    • G2 NET: Necrosis or 2-10 mitoses per 2 mm², Ki67 < 20%

    • G3 NET: >10 mitoses per 2 mm² or Ki67 > 20%

  • NECs (>10 mitoses per 2 mm², Ki67 > 20%) are categorized as small cell or large cell based on cytomorphology.

  • Head and neck NETs typically show no aberrant p53 expression or loss of RB reactivity.

  • The classification emphasizes the correlation of morphology with immunohistochemical findings in diagnosing neuroendocrine neoplasms.

Page 2: Historical Perspective and Classification Evolution

Historical Context

  • Neuroendocrine neoplasms have been historically contentious regarding their origins, with debates on a common neural crest origin.

  • The classification has evolved:

    • Term "carcinoid tumors" introduced by Oberndorfer in 1907.

    • Williams and Sandler's 1963 classification included various NENs based on embryological development.

Current Classification Framework

  • The current classification incorporates changes reflecting the diverse morphology and behavior of NENs.

  • It aligns with the broader IARC/WHO nomenclature, classifying all NENs by differentiation status and proliferative features.

WHO Classification Tables

  • The historical and the 2022 WHO classifications table summarizes various neuroendocrine tumors, illustrating the progression of classification methods.

Page 3: Nomenclature Changes and New Diagnostic Categories

New Diagnostic Framework

  • The 2022 classification introduces nomenclature changes impacting the diagnosis of NENs:

    • The term neuroendocrine carcinoma is now limited to poorly differentiated epithelial NENs.

    • Well differentiated mucosal NENs are now termed NETs, characterized by low, intermediate, or high-grade status.

Immunohistochemical Biomarkers

  • The importance of biomarkers in confirming neuroendocrine nature and differentiation of tumors is emphasized:

    • Examples include neuroendocrine differentiation markers like INSM1, synaptophysin, and chromogranin-A.

    • A careful correlation between morphology and immunohistochemical findings is critical for accurate diagnosis.

Page 4: Role of Cytokeratin in Diagnosis

Cytokeratins in Neuroendocrine Neoplasms

  • Cytokeratin immunohistochemistry is essential for confirming the epithelial nature of NENs, helping distinguish them from paragangliomas (PGLs).

Immunohistochemical Characterization

  • Specificity of cytokeratin staining assists in identifying unique NEN types, such as PitNETs. A focus on particular stains like CAM5.2 and AE1/AE3 is advised to differentiate these tumors.

Page 5: Distinguishing NECs from NETs

Proliferative Activity in NENs

  • Understanding the Ki67 labeling index is crucial to differentiate between NECs and NETs, with NECs exhibiting higher proliferation rates (>55% Ki67).

  • Aberrant p53 expression is commonly associated with NECs.

Further Diagnostics

  • The role of automated imaging techniques for assessing Ki67 is underscored for limited biopsies.

Page 6: Molecular Techniques in Diagnostics

Molecular Immunohistochemistry

  • The application of molecular techniques helps define paragangliomas and distinguish them from NENs.

  • The use of biomarkers such as haploinsufficiency in succinate dehydrogenase aids in diagnosing PGLs.

Page 7: Statistical Relevance of Ki67

Ki67 and Prognosis

  • Ki67 labeling index is an important prognostic marker across NEN types, predicting aggressive behavior and potential metastasis.

Page 8: Middle Ear Neuroendocrine Tumors (MeNET)

Pathological Features of MeNETs

  • MeNETs arise from middle ear mucosa and exhibit diverse growth patterns sharing neuroendocrine characteristics.

  • Histological criteria for MeNET diagnosis include specific cell morphology and expression of neuroendocrine markers.

Page 9: Ectopic Pituitary Neuroendocrine Tumors (PitNETs)

Characteristics of PitNETs

  • Ectopic PitNETs show invasive growth patterns, requiring imaging correlation for diagnosis.

  • Immunohistochemical profiling helps establish the origin of these tumors, utilizing specific transcription factor markers.

Page 10: Classification of PitNETs

Detailed Histologic Subtyping

  • The 2022 WHO classification necessitates a detailed histological assessment of PitNETs to predict clinical outcomes.

Page 11: Examination of PitNET Features

Diagnostic Confirmation

  • Confirmation of a NEN's origin is essential, requiring a mix of morphological and immunohistochemical evaluations.

Page 12: Well-Differentiated Neuroendocrine Tumors

Characteristics of NETs in the Upper Aerodigestive Tract

  • NETs are now recognized for their occurrence in different head and neck sites, including the larynx.

Page 13: Poorly Differentiated Neuroendocrine Carcinomas

Characteristics and Distinctions

  • NECs are characterized by distinct cytomorphologies and behaviors that set them apart from NETs.

Page 14: Neuroendocrine Carcinomas and Their Differential Diagnosis

Various NECs

  • The differential diagnosis for NECs involves considering a range of neoplasms and recognizing the importance of immunohistochemical staining.

Page 15: Merkel Cell Carcinoma

Distinctive Features of MCC

  • MCC is highlighted for its unique presentation and distinct diagnostic criteria in the revised classification.

Page 16: Current Research and Unmet Needs

Gaps in Knowledge

  • The field continues to face challenges, particularly regarding classification, epidemiology, and genomics of head and neck NENs.

Conclusion

  • The review posits the WHO classification as pivotal for guiding research and improving diagnostic accuracy for neuroendocrine tumors.