Department of Endocrinology and Nutrition Hospital Universitario La Princesa, Universidad Autónoma de Madrid,Instituto de Investigación Princesa, and Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER GCV14/ER/12), Madrid, Spain.
Instituto de Investigación Princesa, Madrid, Spain.
Best Pract Res Clin Endocrinol Metab. 2024 Jul;38(4):101893. doi: 10.1016/j.beem.2024.101893. Epub 2024 Mar 19.
Although predictors of response to first-generation somatostatin receptor ligands (fg-SRLs), and to a lesser extent to pasireotide, have been studied in acromegaly for many years, their use is still not recommended in clinical guidelines. Is there insufficient evidence to use them? Numerous biomarkers including various clinical, functional, radiological and molecular markers have been identified. The first ones are applicable pre-surgery, while the molecular predictors are utilized for patients not cured after surgery. In this regard, factors predicting a good response to fg-SRLs are specifically: low basal GH, a low GH nadir in the acute octreotide test, T2 MRI hypointensity, a densely granulated pattern, high immunohistochemistry staining for somatostatin receptor 2 (SSTR2), and E-cadherin. However, there is still a lack of consensus regarding which of these biomarkers is more useful or how to integrate them into clinical practice. With classical statistical methods, it is complex to define reliable and generalizable cut-off values for a single biomarker. The potential solution to the limitations of traditional methods involves combining systems biology with artificial intelligence, which is currently providing answers to such long-standing questions that may eventually be finally included into the clinical guidelines and make personalized medicine a reality. The aim of this review is to describe the current knowledge of the main fg-SRLs and pasireotide response predictors, discuss their current usefulness, and point to future directions in the research of this field.
虽然第一代生长抑素受体配体（fg-SRL）和帕瑞肽的反应预测因子已在肢端肥大症中研究多年，但它们的应用在临床指南中仍不被推荐。是因为证据不足吗？已经确定了许多生物标志物，包括各种临床、功能、影像学和分子标志物。首先是适用于手术前的，而分子预测因子则用于手术后未治愈的患者。在这方面，预测 fg-SRL 反应良好的因素是：基础 GH 低、奥曲肽急性试验中的 GH 最低点低、T2 MRI 低信号、颗粒密集模式、高免疫组化染色的生长抑素受体 2（SSTR2）和 E-钙黏蛋白。然而，对于这些生物标志物中哪一个更有用，或者如何将它们整合到临床实践中，仍然缺乏共识。使用经典的统计方法，为单个生物标志物定义可靠和可推广的截止值是复杂的。解决传统方法局限性的潜在解决方案涉及将系统生物学与人工智能相结合，这目前正在为这些长期存在的问题提供答案，这些答案最终可能被纳入临床指南，使个性化医疗成为现实。本文的目的是描述主要 fg-SRL 和帕瑞肽反应预测因子的当前知识，讨论它们的当前用途，并指出该领域研究的未来方向。
