曲美替尼
神经母细胞瘤RAS病毒癌基因同源物
医学
淋巴管瘤病
MEK抑制剂
西罗莫司
靶向治疗
MAPK/ERK通路
肿瘤科
癌症研究
内科学
淋巴系统
生物信息学
免疫学
克拉斯
生物
遗传学
癌症
结直肠癌
激酶
作者
Lindsay Zumwalt,Haley Schluterman,Anish Ray,Kenneth Heym
标识
DOI:10.1097/mph.0000000000002990
摘要
Kaposiform lymphangiomatosis (KLA) is a rare and aggressive subtype of complex lymphatic anomalies (CLA), characterized by abnormal lymphatic proliferation leading to distinct clinical manifestations. Despite the complexity of this condition, there is no established standard therapy, and treatment options such as sclerotherapy, laser therapy, and surgery remain variably effective and are limited to symptom management rather than curative. Sirolimus, an mTOR pathway inhibitor, has shown promise as a primary therapy, particularly in patients without a driver mutation. However, in some instances, the genetic landscape of KLA has revealed somatic mutations in the RAS-MAPK pathway, most notably the NRAS variant (c.182A>G, p.Q61R), representing a potential therapeutic target. We present a case of a 4-year-old male who presented with pericardial and pleural effusion s without notable coagulopathy found to harbor an NRAS p.Gln61Arg gene mutation, diagnosed through next-generation sequencing (NGS) analysis. Initial therapy with sirolimus failed to provide optimal benefit with persistent pleural effusion. Subsequent treatment with the MEK inhibitor trametinib led to significant clinical improvement, evidenced by the resolution of effusions and removal of the chest tube. In the short term, no significant adverse effect was reported. Our findings underscore the value of genomic profiling in guiding personalized treatment strategies for rare and complex diseases presenting like KLA. This case highlights the potential of targeted therapies, such as trametinib, in improving clinical outcomes for patients with disease with activating NRAS variants, emphasizing the importance of ongoing research to validate and expand these therapeutic approaches in the management of vascular anomalies.
科研通智能强力驱动
Strongly Powered by AbleSci AI