PANoptosis-Related Optimal Model (PROM): A Novel Prognostic Tool Unveiling Immune Dynamics in Lung Adenocarcinoma

Jianming Peng, Leijie Tong, Rui Liang, Huisen Yan, Xiuling Jiang, Youai Dai
{"title":"PANoptosis-Related Optimal Model (PROM): A Novel Prognostic Tool Unveiling Immune Dynamics in Lung Adenocarcinoma","authors":"Jianming Peng,&nbsp;Leijie Tong,&nbsp;Rui Liang,&nbsp;Huisen Yan,&nbsp;Xiuling Jiang,&nbsp;Youai Dai","doi":"10.1155/ijog/5595391","DOIUrl":null,"url":null,"abstract":"<p><b>Background:</b> PANoptosis, a recently characterized inflammatory programmed cell death modality orchestrated by the PANoptosome complex, integrates molecular mechanisms of pyroptosis, apoptosis, and necroptosis. Although this pathway potentially mediates tumor progression, its role in lung adenocarcinoma (LUAD) remains largely unexplored.</p><p><b>Methods:</b> Through comprehensive single-cell transcriptomic profiling, we systematically identified critical PANoptosis-associated gene signatures. Prognostic molecular determinants were subsequently delineated via univariate Cox proportional hazards regression analysis. We constructed a PANoptosis-related optimal model (PROM) through the integration of 10 machine learning algorithms. The model was initially developed using The Cancer Genome Atlas (TCGA)-LUAD cohort and subsequently validated across six independent LUAD cohorts. Model performance was evaluated using mean concordance index. Furthermore, we conducted extensive multiomics analyses to delineate differential pathway activation patterns and immune cell infiltration profiles between PROM-stratified risk subgroups.</p><p><b>Results:</b> Cellular populations exhibiting elevated PANoptosis signatures demonstrated enhanced intercellular signaling networks. PROM demonstrated superior prognostic capability across multiple validation cohorts. Receiver operating characteristic curve analyses revealed area under the curve values exceeding 0.7 across all seven cohorts, with several achieving values above 0.8, indicating robust discriminative performance. The model score exhibited significant correlation with immunological parameters. Notably, high PROM scores were associated with attenuated immune responses, suggesting an immunosuppressive tumor microenvironment. Multiomics investigations revealed significant alterations in critical oncogenic pathways and immune landscape between PROM-stratified subgroups.</p><p><b>Conclusion:</b> This investigation establishes PROM as a clinically applicable prognostic tool for LUAD risk stratification. Beyond its predictive utility, PROM elucidates PANoptosis-associated immunological and biological mechanisms underlying LUAD progression. These findings provide novel mechanistic insights into LUAD pathogenesis and may inform the development of targeted therapeutic interventions and personalized treatment strategies to optimize patient outcomes.</p>","PeriodicalId":55239,"journal":{"name":"Comparative and Functional Genomics","volume":"2025 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/ijog/5595391","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comparative and Functional Genomics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/ijog/5595391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Background: PANoptosis, a recently characterized inflammatory programmed cell death modality orchestrated by the PANoptosome complex, integrates molecular mechanisms of pyroptosis, apoptosis, and necroptosis. Although this pathway potentially mediates tumor progression, its role in lung adenocarcinoma (LUAD) remains largely unexplored.

Methods: Through comprehensive single-cell transcriptomic profiling, we systematically identified critical PANoptosis-associated gene signatures. Prognostic molecular determinants were subsequently delineated via univariate Cox proportional hazards regression analysis. We constructed a PANoptosis-related optimal model (PROM) through the integration of 10 machine learning algorithms. The model was initially developed using The Cancer Genome Atlas (TCGA)-LUAD cohort and subsequently validated across six independent LUAD cohorts. Model performance was evaluated using mean concordance index. Furthermore, we conducted extensive multiomics analyses to delineate differential pathway activation patterns and immune cell infiltration profiles between PROM-stratified risk subgroups.

Results: Cellular populations exhibiting elevated PANoptosis signatures demonstrated enhanced intercellular signaling networks. PROM demonstrated superior prognostic capability across multiple validation cohorts. Receiver operating characteristic curve analyses revealed area under the curve values exceeding 0.7 across all seven cohorts, with several achieving values above 0.8, indicating robust discriminative performance. The model score exhibited significant correlation with immunological parameters. Notably, high PROM scores were associated with attenuated immune responses, suggesting an immunosuppressive tumor microenvironment. Multiomics investigations revealed significant alterations in critical oncogenic pathways and immune landscape between PROM-stratified subgroups.

Conclusion: This investigation establishes PROM as a clinically applicable prognostic tool for LUAD risk stratification. Beyond its predictive utility, PROM elucidates PANoptosis-associated immunological and biological mechanisms underlying LUAD progression. These findings provide novel mechanistic insights into LUAD pathogenesis and may inform the development of targeted therapeutic interventions and personalized treatment strategies to optimize patient outcomes.

Abstract Image

全景相关最优模型(PROM):揭示肺腺癌免疫动力学的一种新的预后工具
背景:PANoptosis是最近发现的一种由PANoptosome复合物调控的炎性程序性细胞死亡模式,它整合了焦亡、凋亡和坏死的分子机制。尽管这一途径可能介导肿瘤进展,但其在肺腺癌(LUAD)中的作用仍未得到充分研究。方法:通过全面的单细胞转录组学分析,我们系统地鉴定了关键的panoposis相关基因特征。预后的分子决定因素随后通过单变量Cox比例风险回归分析进行描述。我们通过整合10种机器学习算法构建了panoptosis相关的最优模型(PROM)。该模型最初是使用癌症基因组图谱(TCGA)-LUAD队列开发的,随后在六个独立的LUAD队列中进行了验证。采用平均一致性指数评价模型性能。此外,我们进行了广泛的多组学分析,以描绘prom分层风险亚组之间的不同途径激活模式和免疫细胞浸润谱。结果:显示PANoptosis特征升高的细胞群体表明细胞间信号网络增强。在多个验证队列中,PROM显示出优越的预后能力。受试者工作特征曲线分析显示,所有7个队列的曲线下面积值都超过0.7,有几个队列的值超过0.8,表明判别性能稳健。模型评分与免疫参数有显著相关性。值得注意的是,高PROM分数与免疫反应减弱相关,提示免疫抑制肿瘤微环境。多组学研究显示,在prom分层亚组之间,关键的致癌途径和免疫景观发生了显著变化。结论:本研究确立了胎膜早破作为临床应用的LUAD风险分层预后工具。除了预测外,PROM还阐明了LUAD进展背后的panoposis相关的免疫学和生物学机制。这些发现为LUAD的发病机制提供了新的见解,并可能为有针对性的治疗干预和个性化治疗策略的发展提供信息,以优化患者的预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Comparative and Functional Genomics
Comparative and Functional Genomics 生物-生化与分子生物学
自引率
0.00%
发文量
0
审稿时长
2 months
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信