Multi-omics insights into metastatic pheochromocytomas and paragangliomas: Mechanisms, signatures, and prediction models.

IF 2.5
Hormones (Athens, Greece) Pub Date : 2026-06-01 Epub Date: 2026-06-02 DOI:10.1007/s42000-026-00792-1
Yue Zhou, Yunying Cui, Tianyi Li, Anli Tong
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Abstract

Pheochromocytomas and paragangliomas (PPGLs), rare neuroendocrine tumors, have been generally considered, since the 2017 WHO classification, as malignant neoplasms with various metastatic potential. Approximately 10-25% of PPGLs will develop metastases, with a varying 5-year-overall-survial of 40%-77%. Previous studies have extensively elucidated the mechanisms by which SDHB mutations promote tumor metastasis through inducing the pseudohypoxic and hypermethylation phenotype. Recent multi-omics studies further profiled the additional landscape of metastatic PPGLs, involving ATRX/TERT alterations, higher tumor mutational burden, microsatellite instability score, and somatic copy-number alteration, distinct microRNA (miRNA) profiling, aberrant kynurenine metabolic pathway, and immunosuppressive microenvironment, advancing our understanding of metastatic mechanisms. Consequently, beyond conventional predictors (e.g., SDHB mutation status, tumor size and location, levels of dopamine and methoxytyramine, Ki-67 labeling index, and loss of S100), emerging biomarkers for metastasis prediction were discovered and evaluated, including levels of circulating miR-483-5p, plasma succinate, tissue xanthurenic acid, and CDK1 expression, etc. Several scoring systems integrating tumor clinicopathological characteristics have been constructed to predict metastatic PPGLs; however, their clinical utility may be limited by high observer variation and low positive predictive value. Recent prediction models integrating multi-omics signatures of metastatic tumors have also been established, but without validation. This review comprehensively synthesizes current and emerging multi-omics signatures of metastatic PPGLs to elucidate underlying metastatic mechanisms. A systematic review of existing scoring systems and emerging predictive models for metastasis prediction was also conducted to highlight their advantages and limitations in the clinical application.

转移性嗜铬细胞瘤和副神经节瘤的多组学研究:机制、特征和预测模型。
嗜铬细胞瘤和副神经节瘤(PPGLs)是一种罕见的神经内分泌肿瘤,自2017年WHO分类以来,被普遍认为是具有各种转移潜力的恶性肿瘤。大约10-25%的ppgl会发生转移,5年总生存率为40%-77%。以往的研究已经广泛阐明了SDHB突变通过诱导假缺氧和高甲基化表型促进肿瘤转移的机制。最近的多组学研究进一步描绘了转移性PPGLs的其他特征,包括ATRX/TERT改变、更高的肿瘤突变负担、微卫星不稳定性评分、体细胞拷贝数改变、不同的microRNA (miRNA)谱、异常的犬尿氨酸代谢途径和免疫抑制微环境,促进了我们对转移机制的理解。因此,除了传统的预测因子(如SDHB突变状态、肿瘤大小和位置、多巴胺和甲氧基酪胺水平、Ki-67标记指数、S100缺失)外,研究人员还发现并评估了用于转移预测的新兴生物标志物,包括循环miR-483-5p水平、血浆琥珀酸、组织黄嘌呤酸和CDK1表达等。已经建立了几种综合肿瘤临床病理特征的评分系统来预测转移性ppgl;然而,它们的临床应用可能受到高观察者变异和低阳性预测值的限制。整合转移性肿瘤多组学特征的近期预测模型也已建立,但尚未得到验证。这篇综述综合了目前和新兴的转移性ppgl的多组学特征,以阐明潜在的转移机制。我们还对现有的评分系统和新兴的转移预测模型进行了系统回顾,以突出其在临床应用中的优势和局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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