Dave, KirtanPazos, A.Tamarashvili, NatiaVázquez-Naya, JoséMunteanu, Cristian-Robert2026-02-102026-02-102025-11-19Dave, K.; Pazos-García, A.; Tamarashvili, N.; Vázquez-Naya, J.; Munteanu, C.R. Integrated Transcriptomic Analysis of S100A8/A9 as a Key Biomarker and Therapeutic Target in Sepsis Pathogenesis and AI Drug Repurposing. Int. J. Mol. Sci. 2025, 26 (22), 11186. https://doi.org/10.3390/ijms2622111861422-0067https://hdl.handle.net/2183/47310The data presented in this study are available in the NCBI Gene Expression Omnibus (GEO) at https://www.ncbi.nlm.nih.gov/geo/ (accessed on 3 March 2025), under accession numbers GSE196117 (bulk RNA-seq) and GSE167363 (single-cell RNA-seq). These datasets were derived from publicly available resources [GEO] [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=%20GSE196117 (accessed on 3 March 2025), https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE167363 (accessed on 3 March 2025)] [GSE196117, GSE167363].[Abstract]: Sepsis is a life-threatening condition driven by a dysregulated immune response, leading to systemic inflammation and multi-organ failure. Among the key molecular regulators, S100A8/A9 has emerged as a critical damage-associated molecular pattern (DAMP) protein, amplifying pro-inflammatory signaling via the Toll-like receptor 4 (TLR4) and receptor for advanced glycation end products (RAGE) pathways. Elevated S100A8/A9 levels correlate with disease severity, making it a promising biomarker and therapeutic target. To unravel the role of S100A8/A9 in sepsis, we integrate scRNA-seq and RNA-seq approaches. scRNA-seq enables cell-type-specific resolution of immune responses, uncovering cellular heterogeneity, state transitions, and inflammatory pathways at the single-cell level. In contrast, RNA-seq provides a comprehensive view of global transcriptomic alterations, allowing robust statistical analysis of differentially expressed genes. The integration of both approaches enables precise deconvolution of immune cell contributions, validation of cell-specific markers, and identification of potential therapeutic targets. Our findings highlight the S100A8/A9-driven inflammatory cascade, its impact on immune cell interactions, and its potential as a diagnostic and prognostic biomarker in sepsis. Eight protein targets resulted from the integrative transcriptomics studies (corresponding to S100A8, S100A9, S100A6, NAMPT, FTH1, B2M, KLF6 and SRGN) have been used to predict interaction affinities with 2958 ChEMBL approved drugs, by using a pre-trained AI models (PLAPT) in order to point directions on drug repurposing in sepsis. The strongest predicted interactions have been confirmed with molecular docking and molecular dynamics analysis. This study underscores the power of combining high-throughput transcriptomics to advance our understanding of sepsis pathophysiology and develop precision medicine strategies.engAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/S100A8/A9TLR4scRNA-seqAI-driven drug repurposingNAMPTBioinformaticsjournal articleopen access10.3390/ijms262211186