de Bresser Carolijn J M, de Krijger Ronald R
Department of Vascular Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
Endocr Pathol. 2024 Dec;35(4):279-292. doi: 10.1007/s12022-024-09830-3. Epub 2024 Oct 28.
Pheochromocytomas (PCCs) and paragangliomas (PGLs, together PPGLs) are the most hereditary tumors known. PPGLs were considered benign, but the fourth edition of the World Health Organisation (WHO) classification redefined all PPGLs as malignant neoplasms with variable metastatic potential. The metastatic rate differs based on histopathology, genetic background, size, and location of the tumor. The challenge in predicting metastatic disease lies in the absence of a clear genotype-phenotype correlation among the more than 20 identified genetic driver variants. Recent advances in molecular clustering based on underlying genetic alterations have paved the way for improved cluster-specific personalized treatments. However, despite some clusters demonstrating a higher propensity for metastatic disease, cluster-specific therapies have not yet been widely adopted in clinical practice. Comprehensive genomic profiling and transcriptomic analyses of large PPGL cohorts have identified potential new biomarkers that may influence metastatic potential. It appears that no single biomarker alone can reliably predict metastatic risk; instead, a combination of these biomarkers may be necessary to develop an effective prediction model for metastatic disease. This review evaluates current guidelines and recent genomic and transcriptomic findings, with the aim of accurately identifying novel biomarkers that could contribute to a predictive model for mPPGLs, thereby enhancing patient care and outcomes.
嗜铬细胞瘤(PCCs)和副神经节瘤(PGLs,合称PPGLs)是已知遗传性最强的肿瘤。PPGLs曾被认为是良性肿瘤,但世界卫生组织(WHO)第四版分类将所有PPGLs重新定义为具有不同转移潜能的恶性肿瘤。转移率因肿瘤的组织病理学、遗传背景、大小和位置而异。预测转移性疾病的挑战在于,在已确定的20多种遗传驱动变异中,缺乏明确的基因型-表型相关性。基于潜在基因改变的分子聚类的最新进展为改进特定聚类的个性化治疗铺平了道路。然而,尽管一些聚类显示出更高的转移疾病倾向,但特定聚类的治疗方法尚未在临床实践中广泛应用。对大型PPGL队列的综合基因组分析和转录组分析已经确定了可能影响转移潜能的潜在新生物标志物。似乎没有单一的生物标志物能够可靠地预测转移风险;相反,可能需要这些生物标志物的组合来开发一种有效的转移性疾病预测模型。本综述评估了当前的指南以及最近的基因组和转录组研究结果,旨在准确识别可能有助于建立mPPGLs预测模型的新型生物标志物,从而改善患者护理和治疗结果。