five

DataSheet1_TP53 R273C Mutation Is Associated With Poor Prognosis in LGG Patients.docx

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
https://figshare.com/articles/dataset/DataSheet1_TP53_R273C_Mutation_Is_Associated_With_Poor_Prognosis_in_LGG_Patients_docx/19383836
下载链接
链接失效反馈
官方服务:
资源简介:
Purpose: With the progress of cancer immunotherapy, hotspot mutations of common oncogenes and tumor suppressors are becoming new potential therapeutic targets. TP53 R273C mutation is one of the hotspot mutations of TP53, and it has a higher frequency in low-grade glioma (LGG). However, the function of this mutation and its prognostic significance in LGG are not still clear. Methods: To address this question, RNA sequencing, clinical, and SNP data of LGG patients from the TCGA database were downloaded. The Kaplan–Meier (KM) method was used for survival analysis. Immune cell populations in this cohort were assessed via the MCP counter and CIBERSORT. DNA damage/repair scores were calculated by GSVA analysis. WGCNA was conducted to identify genes related to TMB. Results: In the context of IDH1/2 mutation, LGG patients with TP53 R273C mutation had worse prognosis than other mutation types and wild types. This conclusion is still valid in LGG patients who had received chemotherapy or radiotherapy. Considering the 1p19q codeletion status, it was found that patients with both R273C mutation and 1p19q non-codeletion had the worst prognosis. Further analysis showed that LGG patients with TP53 R273C mutation had higher M2 macrophage infiltration and tumor mutation burden (TMB) than that of TP53 wild-type LGG patients, and higher TMB indicates poor prognosis in LGG patients. Furthermore, we identified genes which could be associated with higher M2 macrophage infiltration and TMB in LGG patients with TP53 R273C mutation. Conclusion: The study indicates that TP53 R273C mutation is very likely oncogenic and may be used as an indicator of the prognosis of LGG.
创建时间:
2022-03-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作