列线图
胰腺癌
肿瘤微环境
比例危险模型
免疫系统
肿瘤科
内科学
癌症
生物
医学
癌症研究
作者
Yanling Wang,Weiyu Ge,Shengbai Xue,Jiujie Cui,Xiaofei Zhang,Daiyuan Shentu,Liwei Wang
标识
DOI:10.21203/rs.3.rs-1645540/v1
摘要
Abstract Background : Cuproptosis is a novel cell death pathway, and the regulatory mechanism in pancreatic cancer (PC) remains to be explored. We determined whether cuproptosis-related lncRNAs (CRLs) could predict prognosis in pancreatic cancer. Methods and results : First, we identified 30 prognostic cuproptosis-related lncRNAs by Pearson correlation and univariate Cox regression analyses. Next, we constructed the cuproptosis-related lncRNAs prognostic model based on seven CRLs screened by the least absolute shrinkage and selection operator (LASSO) Cox analysis. Following this, we calculated the risk score for pancreatic cancer patients according to the formula and divided patients into high and low-risk groups. In our prognostic model, PC patients with higher risk scores had poorer outcomes. Based on several prognostic features, a predictive nomogram was established in PC. Furthermore, we investigated the tumor immune landscape using CIBERSORT and ESTIMATE. The tumor microenvironment in the high-risk group was more immunosuppressive than that in the low-risk group, with lower infiltration of CD8+ T cells and higher M2 macrophages. Finally, we performed the functional enrichment analysis of 181 differentially expressed genes (DEGs) between risk groups. Our results revealed that endocrine and metabolic pathways were potential regulatory pathways between risk groups. Conclusion : Cuproptosis-related lncRNAs can be applied to predict pancreatic cancer prognosis, which is closely correlated with the tumor metabolism and immune microenvironment.
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