Jentus Maaia Margo, Bakker Leontine, Verstegen Marco, Pelsma Iris, van Wezel Tom, Ruano Dina, Kapiteijn Ellen, Crobach Stijn, Biermasz Nienke, Morreau Hans
Endocr Relat Cancer. 2024 Dec 19;32(1). doi: 10.1530/ERC-24-0070. Print 2025 Jan 1.
The molecular biology of pituitary neuroendocrine tumors (PitNETs) revealed few recurrent mutations and extensive chromosomal alterations, with the latter being the driving force in a subset of these lesions. Addressing the need for an easily applicable diagnostic tool, we conducted a retrospective study of 61 PitNETs operated at a tertiary care center. All cases were subtyped according to the 2022 WHO Classification of Endocrine Tumors. A genome-wide next-generation sequencing panel targeting 1500 single nucleotide polymorphisms (SNPs) was used to classify chromosomal imbalances, loss of heterozygosity, and copy number variations in DNA from formalin-fixed paraffin-embedded tissues. We identified four distinct chromosomal patterns, with varying distribution among different tumor lineages. Forty-two of 61 (69%) PitNETs showed chromosomal alterations. Gonadotroph PitNETs showed mostly quiet genomes. The majority of lactotroph PitNETs (19/20, 95%) were altered, exhibiting a gained genome and a remarkably low recurrence rate. Nine of ten (90%) corticotroph PitNETs harbored chromosomal alterations, of which two aggressive corticotroph tumors and one metastatic corticotroph PitNET showed massive chromosomal losses, leading to near-haploid/near-homozygous genomes. The comparison of the molecular profile of primary and recurrent PitNETs of five patients showed no significant accumulation of alterations over time. A simple genome-wide 1500-SNP test can be used in the identification of outspoken aggressive subsets of PitNETs by the occurrence of a near-haploid/near-homozygous genome. Furthermore, the presence of neoplastic tissue in the resected material can be potentially confirmed for non-gonadotroph PitNETs under suboptimal histological assessment conditions.
垂体神经内分泌肿瘤(PitNETs)的分子生物学研究显示,复发性突变较少,染色体改变广泛,后者是这些病变中一部分的驱动因素。为满足对易于应用的诊断工具的需求,我们对一家三级医疗中心手术的61例PitNETs进行了回顾性研究。所有病例均根据2022年世界卫生组织内分泌肿瘤分类进行亚型分类。使用靶向1500个单核苷酸多态性(SNP)的全基因组下一代测序面板对福尔马林固定石蜡包埋组织中的DNA进行染色体不平衡、杂合性缺失和拷贝数变异分类。我们确定了四种不同的染色体模式,在不同肿瘤谱系中的分布各不相同。61例(69%)PitNETs中有42例显示染色体改变。促性腺激素细胞PitNETs的基因组大多较为稳定。大多数催乳素细胞PitNETs(19/20,95%)发生改变,表现为基因组增加且复发率极低。10例促肾上腺皮质激素细胞PitNETs中有9例(90%)存在染色体改变,其中2例侵袭性促肾上腺皮质激素肿瘤和1例转移性促肾上腺皮质激素细胞PitNET显示大量染色体丢失,导致近乎单倍体/近乎纯合基因组。对5例患者的原发性和复发性PitNETs的分子特征进行比较,结果显示随着时间推移,改变没有显著累积。一种简单的全基因组1500-SNP检测可用于通过近乎单倍体/近乎纯合基因组的出现来识别明显侵袭性的PitNETs亚组。此外,在组织学评估不理想的情况下,对于非促性腺激素细胞PitNETs,可潜在地确认切除材料中存在肿瘤组织。