Cuprotosis Programmed-Cell-Death-Related lncRNA Signature Predicts Prognosis and Immune Landscape in PAAD Patients

Author:

Chi HaoORCID,Peng GaogeORCID,Wang Rui,Yang Fengyi,Xie Xixi,Zhang Jinhao,Xu Ke,Gu Tao,Yang Xiaoli,Tian Gang

Abstract

In terms of mortality and survival, pancreatic cancer is one of the worst malignancies. Known as a unique type of programmed cell death, cuprotosis contributes to tumor cell growth, angiogenesis, and metastasis. Cuprotosis programmed-cell-death-related lncRNAs (CRLs) have been linked to PAAD, although their functions in the tumor microenvironment and prognosis are not well understood. This study included data from the TCGA-PAAD cohort. Random sampling of PAAD data was conducted, splitting the data into two groups for use as a training set and test set (7:3). We searched for differentially expressed genes that were substantially linked to prognosis using univariate Cox and Lasso regression analysis. Through the use of multivariate Cox proportional risk regression, a risk-rating system for prognosis was developed. Correlations between the CRL signature and clinicopathological characteristics, tumor microenvironment, immunotherapy response, and chemotherapy sensitivity were further evaluated. Lastly, qRT-PCR was used to compare CRL expression in healthy tissues to that in tumors. Some CRLs are thought to have strong correlations with PAAD outcomes. These CRLs include AC005332.6, LINC02041, LINC00857, and AL117382.1. The CRL-based signature construction exhibited outstanding predictive performance and offers a fresh approach to evaluating pre-immune effectiveness, paving the way for future studies in precision immuno-oncology.

Funder

Luzhou Applied Basic Research Projects

Southwest Medical University

Key Research and Development Project of the Science & Technology Department of Sichuan Province

Publisher

MDPI AG

Subject

General Medicine

Reference88 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3