基于机器学习的急性髓性白血病泛凋亡模式综合分析揭示了预测生存和免疫疗法的特征

IF 2.2 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL
Lanlan Tang, Wei Zhang, Yang Zhang, Wenjun Deng, Mingyi Zhao
{"title":"基于机器学习的急性髓性白血病泛凋亡模式综合分析揭示了预测生存和免疫疗法的特征","authors":"Lanlan Tang,&nbsp;Wei Zhang,&nbsp;Yang Zhang,&nbsp;Wenjun Deng,&nbsp;Mingyi Zhao","doi":"10.1155/2024/5113990","DOIUrl":null,"url":null,"abstract":"<p><i>Objective</i>. We conducted a meticulous bioinformatics analysis leveraging expression data of 226 PANRGs obtained from previous studies, as well as clinical data from AML patients derived from the HOVON database. <i>Methods</i>. Through meticulous data analysis and manipulation, we were able to categorize AML cases into two distinct PANRG clusters and subsequently identify differentially expressed genes (PRDEGs) with prognostic significance. Furthermore, we organized the patient data into two corresponding gene clusters, allowing us to investigate the intricate relationship between the risk score, patient prognosis, and the immune landscape. <i>Results</i>. Our findings disclosed significant associations between the identified PANRGs, gene clusters, patient survival, immune system, and cancer-related biological processes and pathways. Importantly, we successfully constructed a prognostic signature comprising nineteen genes, enabling the stratification of patients into high-risk and low-risk groups based on individually calculated risk scores. Furthermore, we developed a robust and practical nomogram model, integrating the risk score and other pertinent clinical features, to facilitate accurate patient survival prediction. Our comprehensive analysis demonstrated that the high-risk group exhibited notably worse prognosis, with the risk score proving to be significantly correlated with infiltration of most immune cells. The qRT-PCR results revealed significant differential expression patterns of LGR5 and VSIG4 in normal and human leukemia cell lines (HL-60 and MV-4-11). <i>Conclusions</i>. Our findings underscore the potential utility of PANoptosis-based molecular clustering and prognostic signatures as predictive tools for assessing patient survival in AML.</p>","PeriodicalId":13782,"journal":{"name":"International Journal of Clinical Practice","volume":"2024 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine Learning-Based Integrated Analysis of PANoptosis Patterns in Acute Myeloid Leukemia Reveals a Signature Predicting Survival and Immunotherapy\",\"authors\":\"Lanlan Tang,&nbsp;Wei Zhang,&nbsp;Yang Zhang,&nbsp;Wenjun Deng,&nbsp;Mingyi Zhao\",\"doi\":\"10.1155/2024/5113990\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><i>Objective</i>. We conducted a meticulous bioinformatics analysis leveraging expression data of 226 PANRGs obtained from previous studies, as well as clinical data from AML patients derived from the HOVON database. <i>Methods</i>. Through meticulous data analysis and manipulation, we were able to categorize AML cases into two distinct PANRG clusters and subsequently identify differentially expressed genes (PRDEGs) with prognostic significance. Furthermore, we organized the patient data into two corresponding gene clusters, allowing us to investigate the intricate relationship between the risk score, patient prognosis, and the immune landscape. <i>Results</i>. Our findings disclosed significant associations between the identified PANRGs, gene clusters, patient survival, immune system, and cancer-related biological processes and pathways. Importantly, we successfully constructed a prognostic signature comprising nineteen genes, enabling the stratification of patients into high-risk and low-risk groups based on individually calculated risk scores. Furthermore, we developed a robust and practical nomogram model, integrating the risk score and other pertinent clinical features, to facilitate accurate patient survival prediction. Our comprehensive analysis demonstrated that the high-risk group exhibited notably worse prognosis, with the risk score proving to be significantly correlated with infiltration of most immune cells. The qRT-PCR results revealed significant differential expression patterns of LGR5 and VSIG4 in normal and human leukemia cell lines (HL-60 and MV-4-11). <i>Conclusions</i>. Our findings underscore the potential utility of PANoptosis-based molecular clustering and prognostic signatures as predictive tools for assessing patient survival in AML.</p>\",\"PeriodicalId\":13782,\"journal\":{\"name\":\"International Journal of Clinical Practice\",\"volume\":\"2024 1\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Clinical Practice\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/2024/5113990\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Clinical Practice","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/5113990","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

摘要

目的。我们利用以往研究中获得的 226 个 PANRGs 的表达数据以及 HOVON 数据库中 AML 患者的临床数据进行了细致的生物信息学分析。方法。通过缜密的数据分析和处理,我们将急性髓细胞性白血病病例分为两个不同的 PANRG 群,并随后确定了具有预后意义的差异表达基因 (PRDEG)。此外,我们还将患者数据分为两个相应的基因群,从而研究了风险评分、患者预后和免疫状况之间错综复杂的关系。结果我们的研究结果表明,在已识别的 PANRGs、基因簇、患者生存、免疫系统以及癌症相关的生物过程和通路之间存在重大关联。重要的是,我们成功构建了由 19 个基因组成的预后特征,从而能够根据单独计算的风险评分将患者分为高风险组和低风险组。此外,我们还开发了一个稳健实用的提名图模型,将风险评分和其他相关临床特征整合在一起,以便准确预测患者的生存期。我们的综合分析表明,高风险组的预后明显较差,风险评分与大多数免疫细胞的浸润有显著相关性。qRT-PCR 结果显示,LGR5 和 VSIG4 在正常细胞系和人类白血病细胞系(HL-60 和 MV-4-11)中的表达模式存在明显差异。结论。我们的研究结果强调了基于 PANoptosis 的分子聚类和预后特征作为评估急性髓细胞性白血病患者存活率的预测工具的潜在用途。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning-Based Integrated Analysis of PANoptosis Patterns in Acute Myeloid Leukemia Reveals a Signature Predicting Survival and Immunotherapy

Objective. We conducted a meticulous bioinformatics analysis leveraging expression data of 226 PANRGs obtained from previous studies, as well as clinical data from AML patients derived from the HOVON database. Methods. Through meticulous data analysis and manipulation, we were able to categorize AML cases into two distinct PANRG clusters and subsequently identify differentially expressed genes (PRDEGs) with prognostic significance. Furthermore, we organized the patient data into two corresponding gene clusters, allowing us to investigate the intricate relationship between the risk score, patient prognosis, and the immune landscape. Results. Our findings disclosed significant associations between the identified PANRGs, gene clusters, patient survival, immune system, and cancer-related biological processes and pathways. Importantly, we successfully constructed a prognostic signature comprising nineteen genes, enabling the stratification of patients into high-risk and low-risk groups based on individually calculated risk scores. Furthermore, we developed a robust and practical nomogram model, integrating the risk score and other pertinent clinical features, to facilitate accurate patient survival prediction. Our comprehensive analysis demonstrated that the high-risk group exhibited notably worse prognosis, with the risk score proving to be significantly correlated with infiltration of most immune cells. The qRT-PCR results revealed significant differential expression patterns of LGR5 and VSIG4 in normal and human leukemia cell lines (HL-60 and MV-4-11). Conclusions. Our findings underscore the potential utility of PANoptosis-based molecular clustering and prognostic signatures as predictive tools for assessing patient survival in AML.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
5.30
自引率
0.00%
发文量
274
审稿时长
3-8 weeks
期刊介绍: IJCP is a general medical journal. IJCP gives special priority to work that has international appeal. IJCP publishes: Editorials. IJCP Editorials are commissioned. [Peer reviewed at the editor''s discretion] Perspectives. Most IJCP Perspectives are commissioned. Example. [Peer reviewed at the editor''s discretion] Study design and interpretation. Example. [Always peer reviewed] Original data from clinical investigations. In particular: Primary research papers from RCTs, observational studies, epidemiological studies; pre-specified sub-analyses; pooled analyses. [Always peer reviewed] Meta-analyses. [Always peer reviewed] Systematic reviews. From October 2009, special priority will be given to systematic reviews. [Always peer reviewed] Non-systematic/narrative reviews. From October 2009, reviews that are not systematic will be considered only if they include a discrete Methods section that must explicitly describe the authors'' approach. Special priority will, however, be given to systematic reviews. [Always peer reviewed] ''How to…'' papers. Example. [Always peer reviewed] Consensus statements. [Always peer reviewed] Short reports. [Always peer reviewed] Letters. [Peer reviewed at the editor''s discretion] International scope IJCP publishes work from investigators globally. Around 30% of IJCP articles list an author from the UK. Around 30% of IJCP articles list an author from the USA or Canada. Around 45% of IJCP articles list an author from a European country that is not the UK. Around 15% of articles published in IJCP list an author from a country in the Asia-Pacific region.
×
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