Villa Chiara, Birtolo Maria Francesca, Perez-Rivas Luis Gustavo, Righi Alberto, Assie Guillaume, Baussart Bertrand, Asioli Sofia
Department of Neuropathology, Hôpital Universitaire Pitié-Salpêtrière, APHP, Sorbonne Université, Paris, France.
Inserm U1016, CNRS UMR 8104, Institut Cochin, Université Paris Descartes-Université de Paris, Paris, France.
Brain Pathol. 2025 Jan;35(1):e13299. doi: 10.1111/bpa.13299. Epub 2024 Aug 25.
Pituitary adenoma/pituitary neuroendocrine tumors (PitNETs) are the second most common primary intracranial tumor and the most frequent neuroendocrine tumors/neoplasms of the human body. Thus, they are one of the most frequent diagnoses in neuropathologist's practise. 2022 5th edition WHO Classification of Endocrine and Neuroendocrine Tumors does not support a grading and/or staging system for PitNETs and argues that histological typing and subtyping are more robust than proliferation rate and invasiveness to stratify tumors. Numerous studies suggest the existence of clinically relevant molecular subgroups encouraging an integrated histo-molecular approach to the diagnosis of PitNETs to deepen the understanding of their biology and overcome the unresolved problem of grading system. The present review illustrates the main issues involved in establishing a grading and a staging system, as well as alternative systems validated by independent series to date. The state of art of the current histological and molecular markers is detailed, demonstrating that a standardized and reproducible clinico-pathological approach, combined with the integration of molecular data may help build a workflow to refine the definition of PitNETs with 'malignant potential' and most importantly, avoid delay in patient treatment. Next molecular studied are needed to validate an integrated histo-molecular grading for PitNETs.
垂体腺瘤/垂体神经内分泌肿瘤(PitNETs)是第二常见的原发性颅内肿瘤,也是人体最常见的神经内分泌肿瘤。因此,它们是神经病理学家实践中最常见的诊断之一。2022年第5版《世界卫生组织内分泌和神经内分泌肿瘤分类》不支持PitNETs的分级和/或分期系统,并认为组织学分型和亚型比增殖率和侵袭性更能可靠地对肿瘤进行分层。大量研究表明存在临床相关的分子亚组,这鼓励采用综合组织学-分子方法来诊断PitNETs,以加深对其生物学的理解并克服分级系统未解决的问题。本综述阐述了建立分级和分期系统所涉及的主要问题,以及迄今为止经独立系列验证的替代系统。详细介绍了当前组织学和分子标志物的现状,表明标准化且可重复的临床病理方法,结合分子数据的整合,可能有助于构建一个工作流程,以完善对具有“恶性潜能”的PitNETs的定义,最重要的是,避免患者治疗延误。接下来需要进行分子研究,以验证PitNETs的综合组织学-分子分级。