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一种纳米串基因表达方法可识别去分化脂肪肉瘤中与侵袭性临床行为相关的基因。

A Nanostring gene expression approach identifies aggressive clinical behavior related genes in dedifferentiated liposarcoma.

作者信息

Zalfa Francesca, Manca Paolo, Carotti Simone, Vallese Silvia, Righi Daniela, Taffon Chiara, Nibid Lorenzo, Sbaraglia Marta, Rabitti Carla, Pantano Francesco, Tonini Giuseppe, Dei Tos Angelo Paolo, Vincenzi Bruno, Perrone Giuseppe

机构信息

Operative Research Unit of Predictive Molecular Diagnostic, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.

Research Unit of Microscopic and Ultrastructural Anatomy, Department of Medicine and Surgery, Università Campus Bio-Medico, Rome, Italy.

出版信息

Sci Rep. 2025 Mar 17;15(1):9204. doi: 10.1038/s41598-025-91791-6.

Abstract

Dedifferentiated liposarcoma (DDLPS) is one of the most common subtypes of soft tissue sarcoma with a highly variable clinical behavior. Despite advanced molecular approaches are exploring the genetic panorama of DDLPS progression, to date the driver genes of the aggressive clinical behavior in DDLPS have not been identified yet. Here, we used a Nanostring nCounter approach to study the gene expression profile of 60 selected genes involved in DDLPS progression, in a cohort of DDLPS with aggressive clinical behavior, in comparison to a cohort of DDLPS with indolent clinical behavior. We identified five genes whose expression is significantly and consistently altered in aggressive compared to indolent DDLPS. Moreover, by a clinical outcome analyses we found MAP3K12 gene expression linked with both a higher risk of metastases and death. We envisage that the identified genes could represent the first genes of a genetic signature able to predict the clinical evolution of a DDLPS.

摘要

去分化脂肪肉瘤(DDLPS)是软组织肉瘤最常见的亚型之一,其临床行为高度可变。尽管先进的分子方法正在探索DDLPS进展的基因全貌,但迄今为止,DDLPS侵袭性临床行为的驱动基因尚未确定。在此,我们使用纳米串nCounter方法研究了一组具有侵袭性临床行为的DDLPS中60个参与DDLPS进展的选定基因的基因表达谱,并与一组具有惰性临床行为的DDLPS进行了比较。我们鉴定出五个基因,与惰性DDLPS相比,其在侵袭性DDLPS中的表达有显著且持续的改变。此外,通过临床结果分析,我们发现丝裂原活化蛋白激酶激酶激酶12(MAP3K12)基因表达与转移和死亡风险增加均相关。我们设想,所鉴定的基因可能代表能够预测DDLPS临床进展的首个基因特征的基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fec4/11914264/10695e0c4fe4/41598_2025_91791_Fig1_HTML.jpg

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