Identification of oxeiptosis-associated lncRNAs and prognosis-related signature to predict the immune status in gastric cancer

鉴定与氧化应激相关的长链非编码RNA及其预后相关特征,以预测胃癌的免疫状态

阅读:1

Abstract

As a novel form of cell death, oxeiptosis is mainly caused by oxidative stress and has been defined to contribute to the cellular death program in cancer. However, the precise involvement of oxeiptosis-related long non-coding RNAs (lncRNAs) within gastric cancer (GC) remains elusive. Thus, our study was aimed to elucidate the pivotal effect of hub oxeiptosis-related lncRNAs on GC by comprehensively analyzing lncRNA and gene expression data obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, we constructed a risk signature (risk-sig) using lncRNAs and further evaluated its prognostic significance. We successfully identified thirteen lncRNAs closely related with oxeiptosis that exhibited significant relevance to the prognosis of GC, forming the foundation of our meticulously constructed risk-sig. Notably, our clinical analyses unveiled a strong correlation between the risk-sig and crucial clinical parameters including overall survival (OS), gender, TNM stage, grade, M stage, and N stage among GC patients. Intriguingly, the diagnostic accuracy of this risk-sig surpassed that of conventional clinicopathological characteristics, underscoring its potential as a highly informative prognostic tool. In-depth mechanistic investigations further illuminated a robust association between this risk-sig and fundamental biological processes such as tumor stemness, immune cell infiltration, and immune subtypes. These findings provide valuable insights into the complex interplay between oxeiptosis-related lncRNAs and the intricate molecular landscape of GC. Ultimately, leveraging the risk scores derived from our comprehensive analysis, we successfully developed a nomogram that enables accurate prediction of GC prognosis. Collectively, our study established a solid foundation for the integration of thirteen hub oxeiptosis-related lncRNAs into a clinically applicable risk-sig, potentially revolutionizing prognostic assessment in GC and facilitating the development of innovative therapeutic strategies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。