Background Sepsis refers to a dysregulated host immune response to infection. It carries a high risk of morbidity and mortality, and its pathogenesis has yet to be fully elucidated. The main aim of this study was to identify prognostic hub genes for sepsis and to predict a competitive endogenous RNA (ceRNA) network that regulates the hub genes. Methods Six transcriptome datasets from the peripheral blood of septic patients were retrieved from the Gene Expression Omnibus (GEO) database. The robust rank aggregation (RRA) method was used to screen differentially expressed genes (DEGs) across these datasets. A comprehensive bioinformatics investigation was conducted, encompassing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses using the “clusterProfiler” package in R, as well as gene set enrichment analysis (GSEA) to further elucidate the biological functions and pathways associated with the DEGs. Weighted gene co-expression network analysis (WGCNA) was performed to identify a module significantly associated with sepsis. Integration of this module with protein–protein interaction (PPI) network analysis facilitated the identification of five hub genes. These hub genes were subsequently validated using an independent dataset and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis of peripheral blood samples from septic patients. The prognostic values of these hub genes were assessed via receiver operating characteristic (ROC) curve analysis. Finally, a ceRNA network regulating the prognostic hub genes was constructed by integrating data from a literature review as well as five online databases. Results RRA analysis identified 164 DEGs across six training cohorts. Bioinformatics analyses revealed concurrent hyperinflammation and immunosuppression in sepsis patients. Five hub genes were identified via WGCNA and PPI network analysis, and their differential expression was verified by the validation dataset (GSE28750) and RT-qPCR analysis in the peripheral blood of septic patients. ROC analysis confirmed four hub genes with prognostic value, and a ceRNA network was predicted to elucidate their regulatory mechanisms. Conclusion This study identified four hub genes (CLEC4D, GPR84, S100A12, and HK3) with significant prognostic value in sepsis and predicted a ceRNA network (NEAT1-hsa-miR-495-3p-ELF1) regulating their expression. The integrated analysis reconfirmed the concurrent presence of hyperinflammation and immunosuppression in hospitalized sepsis patients. These findings enhance the understanding of sepsis pathogenesis and identify potential therapeutic targets.