Prognostic and immunological implications of heterogeneous cell death patterns in prostate cancer.

IF 5.3 2区 医学 Q1 ONCOLOGY
Ming Wang, Bangshun Dai, Qiushi Liu, Xiansheng Zhang
{"title":"Prognostic and immunological implications of heterogeneous cell death patterns in prostate cancer.","authors":"Ming Wang, Bangshun Dai, Qiushi Liu, Xiansheng Zhang","doi":"10.1186/s12935-024-03462-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Prostate cancer is one of the most common cancers in men with a significant proportion of patients developing biochemical recurrence (BCR) after treatment. Programmed cell death (PCD) mechanisms are known to play critical roles in tumor progression and can potentially serve as prognostic and therapeutic biomarkers in PCa. This study aimed to develop a prognostic signature for BCR in PCa using PCD-related genes.</p><p><strong>Materials and methods: </strong>We conducted an analysis of 19 different modes of PCD to develop a comprehensive model. Bulk transcriptomic, single-cell transcriptomic, genomic, and clinical data were collected from multiple cohorts, including TCGA-PRAD, GSE58812, METABRIC, GSE21653, and GSE193337. We analyzed the expression and mutations of the 19 PCD modes and constructed, evaluated, and validated the model.</p><p><strong>Results: </strong>Ten PCD modes were found to be associated with BCR in PCa, with specific PCD patterns exhibited by various cell components within the tumor microenvironment. Through Lasso Cox regression analysis, we established a Programmed Cell Death Index (PCDI) utilizing an 11-gene signature. High PCDI values were validated in five independent datasets and were found to be associated with an increased risk of BCR in PCa patients. Notably, older age and advanced T and N staging were associated with higher PCDI values. By combining PCDI with T staging, we constructed a nomogram with enhanced predictive performance. Additionally, high PCDI values were significantly correlated with decreased drug sensitivity, including drugs such as Docetaxel and Methotrexate. Patients with lower PCDI values demonstrated higher immunophenoscores (IPS), suggesting a potentially higher response rate to immune therapy. Furthermore, PCDI was associated with immune checkpoint genes and key components of the tumor microenvironment, including macrophages, T cells, and NK cells. Finally, clinical specimens validated the differential expression of PCDI-related PCDRGs at both the gene and protein levels.</p><p><strong>Conclusion: </strong>In conclusion, we developed a novel PCD-based prognostic feature that successfully predicted BCR in PCa patients and provided insights into drug sensitivity and potential response to immune therapy. These findings have significant clinical implications for the treatment of PCa.</p>","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11344416/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Cell International","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12935-024-03462-7","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Prostate cancer is one of the most common cancers in men with a significant proportion of patients developing biochemical recurrence (BCR) after treatment. Programmed cell death (PCD) mechanisms are known to play critical roles in tumor progression and can potentially serve as prognostic and therapeutic biomarkers in PCa. This study aimed to develop a prognostic signature for BCR in PCa using PCD-related genes.

Materials and methods: We conducted an analysis of 19 different modes of PCD to develop a comprehensive model. Bulk transcriptomic, single-cell transcriptomic, genomic, and clinical data were collected from multiple cohorts, including TCGA-PRAD, GSE58812, METABRIC, GSE21653, and GSE193337. We analyzed the expression and mutations of the 19 PCD modes and constructed, evaluated, and validated the model.

Results: Ten PCD modes were found to be associated with BCR in PCa, with specific PCD patterns exhibited by various cell components within the tumor microenvironment. Through Lasso Cox regression analysis, we established a Programmed Cell Death Index (PCDI) utilizing an 11-gene signature. High PCDI values were validated in five independent datasets and were found to be associated with an increased risk of BCR in PCa patients. Notably, older age and advanced T and N staging were associated with higher PCDI values. By combining PCDI with T staging, we constructed a nomogram with enhanced predictive performance. Additionally, high PCDI values were significantly correlated with decreased drug sensitivity, including drugs such as Docetaxel and Methotrexate. Patients with lower PCDI values demonstrated higher immunophenoscores (IPS), suggesting a potentially higher response rate to immune therapy. Furthermore, PCDI was associated with immune checkpoint genes and key components of the tumor microenvironment, including macrophages, T cells, and NK cells. Finally, clinical specimens validated the differential expression of PCDI-related PCDRGs at both the gene and protein levels.

Conclusion: In conclusion, we developed a novel PCD-based prognostic feature that successfully predicted BCR in PCa patients and provided insights into drug sensitivity and potential response to immune therapy. These findings have significant clinical implications for the treatment of PCa.

前列腺癌异质性细胞死亡模式的预后和免疫学意义。
背景:前列腺癌是男性最常见的癌症之一,相当一部分患者在治疗后会出现生化复发(BCR)。众所周知,程序性细胞死亡(PCD)机制在肿瘤进展中起着关键作用,有可能成为 PCa 的预后和治疗生物标志物。本研究旨在利用 PCD 相关基因建立 PCa BCR 的预后特征:我们对 19 种不同的 PCD 模式进行了分析,以建立一个综合模型。我们从TCGA-PRAD、GSE58812、METABRIC、GSE21653和GSE193337等多个队列中收集了大量转录组、单细胞转录组、基因组和临床数据。我们分析了19种PCD模式的表达和突变,并构建、评估和验证了该模型:结果:发现10种PCD模式与PCa中的BCR相关,肿瘤微环境中的各种细胞成分表现出特定的PCD模式。通过Lasso Cox回归分析,我们利用11个基因特征建立了程序性细胞死亡指数(PCDI)。高 PCDI 值在五个独立数据集中得到了验证,发现它与 PCa 患者 BCR 风险的增加有关。值得注意的是,年龄较大、T 和 N 分期较晚与 PCDI 值较高有关。通过将 PCDI 与 T 分期相结合,我们构建了一个具有更强预测能力的提名图。此外,高 PCDI 值与药物敏感性下降(包括多西他赛和甲氨蝶呤等药物)显著相关。PCDI 值较低的患者免疫评分(IPS)较高,表明其对免疫疗法的反应率可能较高。此外,PCDI 还与免疫检查点基因和肿瘤微环境的关键成分有关,包括巨噬细胞、T 细胞和 NK 细胞。最后,临床标本验证了 PCDI 相关 PCDRGs 在基因和蛋白质水平上的差异表达:总之,我们开发出了一种基于 PCD 的新型预后特征,它能成功预测 PCa 患者的 BCR,并能深入了解药物敏感性和对免疫疗法的潜在反应。这些发现对 PCa 的治疗具有重要的临床意义。
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
CiteScore
10.90
自引率
1.70%
发文量
360
审稿时长
1 months
期刊介绍: Cancer Cell International publishes articles on all aspects of cancer cell biology, originating largely from, but not limited to, work using cell culture techniques. The journal focuses on novel cancer studies reporting data from biological experiments performed on cells grown in vitro, in two- or three-dimensional systems, and/or in vivo (animal experiments). These types of experiments have provided crucial data in many fields, from cell proliferation and transformation, to epithelial-mesenchymal interaction, to apoptosis, and host immune response to tumors. Cancer Cell International also considers articles that focus on novel technologies or novel pathways in molecular analysis and on epidemiological studies that may affect patient care, as well as articles reporting translational cancer research studies where in vitro discoveries are bridged to the clinic. As such, the journal is interested in laboratory and animal studies reporting on novel biomarkers of tumor progression and response to therapy and on their applicability to human cancers.
×
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