{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T06:40:52Z","timestamp":1763534452549,"version":"3.45.0"},"reference-count":59,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:00:00Z","timestamp":1763510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100019446","name":"Medical and Health Science and Technology Development Project of Shandong Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100019446","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Sepsis, a life-threatening condition with persistently high mortality, involves dysregulated immune responses and programmed cell death (PCD). However, the specific roles and interactions of diverse PCD pathways in sepsis pathogenesis remain incompletely understood. This study aimed to systematically characterize PCD patterns and their clinical relevance in sepsis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We integrated three bulk transcriptomic datasets (81 controls, 165 sepsis patients) and one single-cell RNA sequencing (scRNA-seq) dataset (4 controls, 4 early sepsis patients, 52,315 cells) from public databases. Gene set variation analysis (GSVA) quantified activity of 13 PCD pathways. Immune infiltration was assessed via single-sample gene set enrichment analysis (ssGSEA). A cell death-associated signature (CDS) risk score was developed using least absolute shrinkage and selection operator (LASSO) regression. scRNA-seq analysis identified cell-type-specific PCD activation and intercellular communication using Seurat, AUCell, and CellPhoneDB. Additionally, an independent RNA-seq cohort generated from our own sequencing of sepsis patients and healthy controls was used for external validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Transcriptomic analysis identified 5,591 differentially expressed genes enriched in immune and cell death pathways. Four PCD pathways-ferroptosis, disulfidptosis, NETosis, and entotic cell death-were significantly upregulated in sepsis and strongly correlated with immune cell infiltration, such as activated dendritic cells and neutrophils. The CDS risk score, based on 18 core PCD genes, showed excellent diagnostic accuracy across both public microarray datasets (AUC = 0.961 and 0.844) and our independent high-throughput RNA-seq dataset (AUC = 0.975). scRNA-seq revealed monocytes as dominant effectors, exhibiting heightened activation of ferroptosis, entotic death, and netotic pathways alongside metabolic reprogramming, including enhanced glutathione metabolism and oxidative phosphorylation (OXPHOS). Furthermore, monocyte-centric intercellular communication was dysregulated in sepsis, featuring upregulated MIF-CXCR4, ANXA1-FPR2, and HLA-KIR signaling axes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>By integrating public microarray and single-cell transcriptomic data with independent high-throughput sequencing validation, this study analysis identifies ferroptosis, disulfidptosis, netotic death, and entotic death as key dysregulated PCD pathways in sepsis, with monocytes serving as central hubs integrating PCD, metabolic reprogramming, and immune communication. The\u00a0CDS risk score provides a robust diagnostic and stratification tool. Targeting monocyte-driven PCD-metabolism-communication networks offers promising avenues for precision immunotherapy in sepsis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2025.1685533","type":"journal-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T06:35:33Z","timestamp":1763534133000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Comprehensive analysis of the role of diverse programmed cell death patterns in sepsis"],"prefix":"10.3389","volume":"16","author":[{"given":"Xiaotongning","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zihao","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaonan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunyu","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anqi","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuo","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,11,19]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1007\/s00134-017-4683-6","article-title":"Surviving sepsis campaign: international guidelines for management of sepsis and septic shock: 2016","volume":"18","author":"Andrew","year":"2017","journal-title":"Crit Care Med"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.0288","article-title":"Assessment of clinical criteria for sepsis: for the third international consensus definitions for sepsis and septic shock (Sepsis-3)","volume":"315","author":"Seymour","year":"2016","journal-title":"Jama"},{"key":"B3","doi-asserted-by":"publisher","first-page":"5376","DOI":"10.3390\/ijms20215376","article-title":"The pathogenesis of sepsis and potential therapeutic targets","volume":"20","author":"Huang","year":"2019","journal-title":"Int J Mol Sci"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2010.01.022","article-title":"Pattern recognition receptors and inflammation","volume":"140","author":"Takeuchi","year":"2010","journal-title":"Cell"},{"key":"B5","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.ccm.2016.01.011","article-title":"Metabolism, metabolomics, and nutritional support of patients with sepsis","volume":"37","author":"Englert","year":"2016","journal-title":"Clinics chest Med"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1615\/CritRevImmunol.2015015461","article-title":"Pathogenesis of multiple organ failure in sepsis","volume":"35","author":"Rossaint","year":"2015","journal-title":"Crit Reviews\u2122 Immunol"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1038\/cdd.2011.96","article-title":"Molecular definitions of cell death subroutines: recommendations of the nomenclature committee on cell death 2012","volume":"19","author":"Galluzzi","year":"2012","journal-title":"Cell Death Differentiation"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1038\/bjc.1972.33","article-title":"Apoptosis: A basic biological phenomenon with wideranging implications in tissue kinetics","volume":"26","author":"Kerr","year":"1972","journal-title":"Br J Cancer"},{"key":"B9","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1186\/s13046-023-02712-2","article-title":"Disulfidptosis: A new form of programmed cell death","volume":"42","author":"Zheng","year":"2023","journal-title":"J Exp Clin Cancer Res"},{"key":"B10","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1007\/s10495-016-1325-3","article-title":"Apoptosis-induced lymphopenia in sepsis and other severe injuries","volume":"22","author":"Girardot","year":"2017","journal-title":"Apoptosis"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1007\/s10495-021-01663-3","article-title":"Release mechanisms of major damps","volume":"26","author":"Murao","year":"2021","journal-title":"Apoptosis"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.4096","article-title":"Integrating single-cell transcriptomic data across different conditions, technologies, and species","volume":"36","author":"Butler","year":"2018","journal-title":"Nat Biotechnol"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2019.05.031","article-title":"Comprehensive integration of single-cell data","volume":"177","author":"Stuart","year":"2019","journal-title":"cell"},{"key":"B14","doi-asserted-by":"publisher","first-page":"125","DOI":"10.21037\/atm.2020.02.35","article-title":"Single-cell transcriptomics reveals the alteration of peripheral blood mononuclear cells driven by sepsis","volume":"8","author":"Wen","year":"2020","journal-title":"Ann Trans Med"},{"key":"B15","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1093\/nar\/28.1.27","article-title":"Kegg: kyoto encyclopedia of genes and genomes","volume":"28","author":"Kanehisa","year":"2000","journal-title":"Nucleic Acids Res"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1002\/cpbi.5","article-title":"The genecards suite: from gene data mining to disease genome sequence analyses","volume":"54","author":"Stelzer","year":"2016","journal-title":"Curr Protoc Bioinf"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1016\/j.cels.2015.12.004","article-title":"The molecular signatures database hallmark gene set collection","volume":"1","author":"Liberzon","year":"2015","journal-title":"Cell Syst"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkab1028","article-title":"The reactome pathway knowledgebase 2022","volume":"50","author":"Gillespie","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bts034","article-title":"The sva package for removing batch effects and other unwanted variation in high-throughput experiments","volume":"28","author":"Leek","year":"2012","journal-title":"Bioinformatics"},{"key":"B20","doi-asserted-by":"publisher","first-page":"e30619","DOI":"10.1371\/journal.pone.0030619","article-title":"Ngs qc toolkit: A toolkit for quality control of next generation sequencing data","volume":"7","author":"Patel","year":"2012","journal-title":"PloS One"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-019-0201-4","article-title":"Graph-based genome alignment and genotyping with hisat2 and hisat-genotype","volume":"37","author":"Kim","year":"2019","journal-title":"Nat Biotechnol"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.3122","article-title":"Stringtie enables improved reconstruction of a transcriptome from rna-seq reads","volume":"33","author":"Pertea","year":"2015","journal-title":"Nat Biotechnol"},{"key":"B23","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1101\/002832","article-title":"Differential analysis of count data\u2013the deseq2 package","volume":"15","author":"Love","year":"2014","journal-title":"Genome Biol"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1089\/omi.2011.0118","article-title":"Clusterprofiler: an R package for comparing biological themes among gene clusters","volume":"16","author":"Yu","year":"2012","journal-title":"Omics: J Integr Biol"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkv1070","article-title":"Kegg as a reference resource for gene and protein annotation","volume":"44","author":"Kanehisa","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gky1055","article-title":"The gene ontology resource: 20 years and still going strong","volume":"47","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0506580102","article-title":"Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles","volume":"102","author":"Subramanian","year":"2005","journal-title":"Proc Natl Acad Sci"},{"key":"B28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2105-14-7","article-title":"Gsva: gene set variation analysis for microarray and rna-seq data","volume":"14","author":"H\u00e4nzelmann","year":"2013","journal-title":"BMC Bioinf"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1038\/Nmeth.4463","article-title":"Scenic: single-cell regulatory network inference and clustering","volume":"14","author":"Aibar","year":"2017","journal-title":"Nat Methods"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.3389\/fcvm.2020.586871","article-title":"Predicting diagnostic gene biomarkers associated with immune infiltration in patients with acute myocardial infarction","volume":"7","author":"Zhao","year":"2020","journal-title":"Front Cardiovasc Med"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti623","article-title":"Rocr: visualizing classifier performance in R","volume":"21","author":"Sing","year":"2005","journal-title":"Bioinformatics"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1016\/j.immuni.2013.10.003","article-title":"Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer","volume":"39","author":"Bindea","year":"2013","journal-title":"Immunity"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2016.12.019","article-title":"Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade","volume":"18","author":"Charoentong","year":"2017","journal-title":"Cell Rep"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.1158\/2159-8290.CD-21-0316","article-title":"Spatiotemporal immune landscape of colorectal cancer liver metastasis at single-cell level","volume":"12","author":"Wu","year":"2022","journal-title":"Cancer Discov"},{"key":"B35","doi-asserted-by":"publisher","first-page":"1088","DOI":"10.1038\/s41467-021-21246-9","article-title":"Inference and analysis of cell-cell communication using cellchat","volume":"12","author":"Jin","year":"2021","journal-title":"Nat Commun"},{"key":"B36","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btu375","article-title":"Preserving biological heterogeneity with a permuted surrogate variable analysis for genomics batch correction","volume":"30","author":"Parker","year":"2014","journal-title":"Bioinformatics"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.1038\/s41422-019-0164-5","article-title":"The molecular machinery of regulated cell death","volume":"29","author":"Tang","year":"2019","journal-title":"Cell Res"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.956361","article-title":"Ferroptosis in sepsis: the mechanism, the role and the therapeutic potential","volume":"13","author":"Xl","year":"2022","journal-title":"Front Immunol"},{"key":"B39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13054-018-2109-7","article-title":"Plasma myeloperoxidase-conjugated DNA level predicts outcomes and organ dysfunction in patients with septic shock","volume":"22","author":"Maruchi","year":"2018","journal-title":"Crit Care"},{"key":"B40","doi-asserted-by":"publisher","first-page":"e70020","DOI":"10.1111\/jcmm.70020","article-title":"Classification and functional analysis of disulfidptosis-associated genes in sepsis","volume":"28","author":"He","year":"2024","journal-title":"J Cell Mol Med"},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.1038\/s41581-018-0005-7","article-title":"Mechanisms and treatment of organ failure in sepsis","volume":"14","author":"Lelubre","year":"2018","journal-title":"Nat Rev Nephrol"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.1038\/s41418-020-00685-9","article-title":"Loss of ferroportin induces memory impairment by promoting ferroptosis in alzheimer\u2019s disease","volume":"28","author":"Bao","year":"2021","journal-title":"Cell Death Differentiation"},{"key":"B43","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s10565-020-09530-8","article-title":"Human umbilical cord blood\u2013derived mscs exosome attenuate myocardial injury by inhibiting ferroptosis in acute myocardial infarction mice","volume":"37","author":"Song","year":"2021","journal-title":"Cell Biol Toxicol"},{"key":"B44","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1182\/blood-2018-99-110051","article-title":"Padi4 Regulates Net Formation and Inflammatory Cell Death Downstream of Mlkl","volume":"132","author":"D'Cruz","year":"2018","journal-title":"Blood"},{"key":"B45","doi-asserted-by":"publisher","first-page":"e17542","DOI":"10.7717\/peerj.17542","article-title":"Identification of key genes as potential diagnostic biomarkers in sepsis by bioinformatics analysis","volume":"12","author":"Lin","year":"2024","journal-title":"PeerJ"},{"key":"B46","doi-asserted-by":"publisher","DOI":"10.2174\/1566524015666151026100042","article-title":"Entosis: cell-in-cell formation that kills through entotic cell death","volume":"15","author":"Florey","year":"2015","journal-title":"Curr Mol Med"},{"key":"B47","doi-asserted-by":"publisher","DOI":"10.4161\/auto.4237","article-title":"Bh3-only proteins and bh3 mimetics induce autophagy by competitively disrupting the interaction between beclin 1 and bcl-2\/bcl-xl","volume":"3","author":"Maiuri","year":"2007","journal-title":"Autophagy"},{"key":"B48","doi-asserted-by":"publisher","DOI":"10.1080\/15548627.2021.1912270","article-title":"Cul3 (Cullin 3)-mediated ubiquitination and degradation of becn1 (Beclin 1) inhibit autophagy and promote tumor progression","volume":"17","author":"Li","year":"2021","journal-title":"Autophagy"},{"key":"B49","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2023.1253833","article-title":"Machine learning-based identification of cybb and fcar as potential neutrophil extracellular trap-related treatment targets in sepsis","volume":"14","author":"You","year":"2023","journal-title":"Front Immunol"},{"key":"B50","doi-asserted-by":"publisher","first-page":"100569","DOI":"10.1016\/j.medj.2024.12.003","article-title":"Immune-cell signatures of persistent inflammation, immunosuppression, and catabolism syndrome after sepsis","volume":"6","author":"Sun","year":"2025","journal-title":"Med"},{"key":"B51","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1186\/s40779-023-00462-y","article-title":"Single-cell transcriptome profiling of sepsis identifies hla-dr low S100a high monocytes with immunosuppressive function","volume":"10","author":"Yao","year":"2023","journal-title":"Military Med Res"},{"key":"B52","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1002\/jcb.27547","article-title":"Recent advances in endotoxin tolerance","volume":"120","author":"Liu","year":"2019","journal-title":"J Cell Biochem"},{"key":"B53","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1038\/s41590-023-01660-5","article-title":"The pathophysiology of sepsis and precision-medicine-based immunotherapy","volume":"25","author":"Giamarellos-Bourboulis","year":"2024","journal-title":"Nat Immunol"},{"key":"B54","doi-asserted-by":"publisher","first-page":"15149","DOI":"10.1038\/s41598-021-94474-0","article-title":"Proteomics reveals disturbances in the immune response and energy metabolism of monocytes from patients with septic shock","volume":"11","author":"de Azambuja Rodrigues","year":"2021","journal-title":"Sci Rep"},{"key":"B55","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1007\/s00018-024-05338-5","article-title":"Cd74 is a functional mif receptor on activated cd4+ T cells","volume":"81","author":"Zhang","year":"2024","journal-title":"Cell Mol Life Sci"},{"key":"B56","doi-asserted-by":"publisher","DOI":"10.4161\/cbt.8.23.10455","article-title":"Natural killer cells and cancer: regulation by the killer cell ig-like receptors (Kir)","volume":"8","author":"Purdy","year":"2009","journal-title":"Cancer Biol Ther"},{"key":"B57","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1038\/nature10237","article-title":"Hiv-1 adaptation to nk-cell-mediated immune pressure","volume":"476","author":"Alter","year":"2011","journal-title":"Nature"},{"key":"B58","doi-asserted-by":"publisher","DOI":"10.3760\/cma.j.issn.0253-2727.2019.06.008","article-title":"Proteomic analysis and verification of protein expression after upregulation of human cd99 in hodgkin lymphoma cell line L428","volume":"40","author":"Lin","year":"2019","journal-title":"Zhonghua xue ye xue za zhi= Zhonghua Xueyexue Zazhi"},{"key":"B59","doi-asserted-by":"publisher","DOI":"10.1016\/j.cellimm.2018.10.012","article-title":"Triggering of cd99 on monocytes by a specific monoclonal antibody regulates T cell activation","volume":"335","author":"Laopajon","year":"2019","journal-title":"Cell Immunol"}],"container-title":["Frontiers in Immunology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2025.1685533\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T06:35:38Z","timestamp":1763534138000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2025.1685533\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,19]]},"references-count":59,"alternative-id":["10.3389\/fimmu.2025.1685533"],"URL":"https:\/\/doi.org\/10.3389\/fimmu.2025.1685533","relation":{},"ISSN":["1664-3224"],"issn-type":[{"value":"1664-3224","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,19]]},"article-number":"1685533"}}