ArticleFrontiers in immunology2023
Integrated analysis of single-cell RNA-seq and chipset data unravels PANoptosis-related genes in sepsis.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 27 citations in OpenAlex.
- Targeting the non-coding RNA-PANoptosis axis: a novel frontier in disease diagnosis and therapy.Apoptosis : an international journal on programmed cell death · 2026Review
- Single-Cell RNA Sequencing Revealed the Role of Interferon-Gamma Related Genes in Primary Sjögren's Syndrome.Journal of cellular and molecular medicine · 2026Article
- PANoptosis in life and death across cell types: From innate immunity to therapeutic implications.Cell chemical biology · 2026Review
- Modeling neonatal immune response to B. pertussis identifies early B cell activation and differentiation.PLoS pathogens · 2026Article
- Immune molecular mechanisms of PANoptosis in sepsis-induced acute kidney injury.Inflammation and regeneration · 2026Review
- Animal models of critical illness in the Asia-Pacific region: current practices, shared challenges, and future directions.Intensive care medicine experimental · 2026Review
- Non-apoptotic Regulated Cell Death Mechanisms in Sepsis and their Therapeutic Potential.Inflammation · 2026Review
- Molecular subtyping and immune microenvironment heterogeneity in pediatric influenza-associated prolonged multiple organ dysfunction syndrome.Translational pediatrics · 2026Article
- Single-Nucleus Transcriptomics Uncovers Xaf1-Driven PANoptosis as a Therapeutic Target in Aminoglycoside-Induced Hearing Loss.Cell proliferation · 2026Article
- Peripheral Blood Mononuclear Cells in Sepsis: Immune Trajectories, Monocyte Dysfunction, and Translational Biomarkers.Journal of inflammation research · 2026Review
- Drug repurposing of sophoridine for sepsis-induced organ injury: from in-depth analysis of a single agent to a multi-target therapeutic paradigm.Frontiers in pharmacology · 2026Review
- Caspases and programmed cell death in sepsis: mechanisms, pathophysiology, and therapeutic targets.Frontiers in immunology · 2026Review
- Integration of RNA-seq and scRNA-seq to investigate the role of cell cycle-related biomarkers in sepsis.PloS one · 2026Article
- PANoptosis nexus in ischemia-reperfusion injury: from integrated cell death mechanisms to novel therapeutic opportunities.Frontiers in immunology · 2026Review
- Single-Cell Profiling Identifies JUNB/SPI1-Driven Inflammatory Programs and Novel Communication Axes in Myeloid Cells of SepsisEndocrine, metabolic & immune disorders drug targets · 2026Article
- PANoptosis in Cytokine Release Syndrome: Bridging the Gap between Inflammation and Cell Death.Current pharmaceutical design · 2026Review
- A Correlation between Sequential Organ Failure Assessment Scores and Biomarkers of Inflammation and Infection in Patients with Sepsis.Current medicinal chemistry · 2026Article
- Identification of potential molecular targets for thyroid cancer using multiple-omics analysis and machine learning.Annals of medicine and surgery (2012) · 2025Article
- Recent advances in biomarkers for detection and diagnosis of sepsis and organ dysfunction: a comprehensive review.European journal of medical research · 2025Review
- Therapeutic targeting of cell death-immune crosstalk in cancer to rewire the tumor immune microenvironment.Molecular cancer · 2025Review
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the outcome. Several studies have indicated that PANoptosis exerts a critical role in tumor initiation and development. Nevertheless, the role of PANoptosis in sepsis has not been fully elucidated. Methods: We obtained Sepsis samples and scRNA-seq data from the GEO database. PANoptosis-related genes were subjected to consensus clustering and functional enrichment analysis, followed by identification of differentially expressed genes and calculation of the PANoptosis score. A PANoptosis-based prognostic model was developed. Results: Unsupervised clustering analysis using 16 PANoptosis-related genes identified three subtypes of sepsis. Kaplan-Meier analysis showed significant differences in patient survival among the subtypes, with different immune infiltration levels. Differential analysis of the subtypes identified 48 DEGs. Boruta algorithm PCA analysis identified 16 DEGs as PANoptosis-related signature genes. We developed PANscore based on these signature genes, which can distinguish different PANoptosis and clinical characteristics and may serve as a potential biomarker. Single-cell sequencing analysis identified six cell types, with high PANscore clustering relatively in B cells, and low PANscore in CD16+ and CD14+ monocytes and Megakaryocyte progenitors. ZBP1, XAF1, IFI44L, SOCS1, and PARP14 were relatively higher in cells with high PANscore. Conclusion: We developed a machine learning based Boruta algorithm for profiling PANoptosis related subgroups with in predicting survival and clinical features in the sepsis.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.