bioRxivBioinformaticsPreprint
Dysregulation of "Don't Eat Me" Signaling-Related Genes in Sepsis: A Targeted Transcriptomic Analysis
Abstract
Sepsis remains a life-threatening condition with limited therapeutic options targeting immune dysregulation. The CD47-SIRP "dont eat me" signaling axis, well characterized in tumor immune evasion, has not been systematically investigated in the context of sepsis. In this study, we performed a targeted transcriptomic analysis of phagocytosis- and "dont eat me" -related genes using the GSE228541 dataset (14 sepsis patients, 15 healthy controls). We identified 8 significantly differentially expressed genes within the curated gene panel. Key changes included downregulation of CD47 (logFC = -0.88, FDR = 5.6 x 10-4) and marked upregulation of PRTN3 (logFC = 2.68, FDR = 6.1 x 10-4). Gene Ontology (GO) enrichment demonstrated prominent alterations in pathways including negative regulation of phagocytosis (GO:0050765, FDR = 7.6 x 10-22), endocytosis, and inflammatory responses. Co-expression network analysis identified SNX3, DYSF, and PLSCR1 as hub genes within this regulatory module. Immune infiltration analysis showed increased M1 macrophage polarization and neutrophil activation in sepsis. Using LASSO regression, we constructed a 6-gene diagnostic signature (PLSCR1, SNX3, DYSF, PRTN3, CSK, CD47) that discriminated sepsis from controls with good performance (AUC = 0.933 in the test subset). Downregulation of CD47 suggests impaired "self" recognition, which may contribute to aberrant phagocytosis during sepsis. Elevated PRTN3 is consistent with neutrophil activation and extracellular trap formation, linking innate immune activation to tissue injury. This targeted transcriptomic analysis reveals coordinated transcriptional reprogramming of phagocytosis-regulatory genes in sepsis and supports the CD47-SIRP axis as a candidate therapeutic target for further investigation.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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