# Identification and validation of an endotoxin tolerance–based prognostic model with therapeutic insights in sepsis

## TL;DR

A new gene-based model predicts sepsis mortality risk by tracking immune suppression linked to endotoxin tolerance, validated with clinical and molecular data.

## Contribution

A novel endotoxin tolerance-related gene signature and age-integrated nomogram for sepsis mortality prediction with experimental and computational validation.

## Key findings

- The 10-gene ETG signature showed AUCs of 0.73–0.78 for 28-day mortality prediction.
- Non-survivors had lower FCGR1A, TLR5, and CX3CR1 mRNA and protein levels in PBMCs.
- CX3CR1, FCGR1A, and TLR5 were identified as druggable targets with potential ligands.

## Abstract

Sepsis outcomes remain difficult to predict because immune trajectories are heterogeneous and dynamically shift from early activation to immunosuppression. Endotoxin tolerance (ET) in circulating monocytes/macrophages is a key mechanism of sepsis-associated immunosuppression but has not been systematically leveraged for prognostication. We sought to develop and clinically validate an ET-related gene (ETG) signature for short-term mortality risk stratification.

Public whole-blood transcriptomic datasets were intersected with curated ET gene sets to derive ETG candidates. An ensemble machine-learning framework (108 model/feature-selection combinations across 12 algorithms) was used to build and rank prognostic models for 28-day mortality; the final parsimonious signature (10 ETGs, including IL4R, ATM, CX3CR1, FCGR1A) informed a risk score. A two-variable nomogram (age + ETG risk score) was constructed. Internal performance was assessed by bootstrapped calibration, time-dependent ROC/AUC at 7, 14, and 28 days, and Harrell’s C-index. Experimental validation used a prospective ICU cohort (n=50; 13 survivors, 37 non-survivors). PBMCs were profiled by RT-qPCR and Western blot; CD14+ monocytes were analyzed by flow cytometry for FCGR1A/CD64, CX3CR1, and PD-1. We further explored regulatory context (ceRNA network) and druggability (DGIdb query and molecular docking to CX3CR1, FCGR1A, and TLR5).

The 10-gene ETG signature stratified mortality risk with acceptable discrimination and calibration. AUCs were 0.76 (95% CI 0.69–0.83), 0.78 (0.72–0.83), and 0.73 (0.67–0.78) at 7, 14, and 28 days, respectively; Harrell’s C-index was 0.782. The age-integrated nomogram showed close agreement between predicted and observed survival across timepoints. Functional enrichment indicated immune-response pathways enriched in the low-risk group. In the clinical cohort, non-survivors exhibited lower mRNA and protein levels of FCGR1A, TLR5, and CX3CR1 in PBMCs; flow cytometry revealed reduced proportions of FCGR1A+, CX3CR1+, and PD-1+ CD14+ monocytes (p<0.01). The ceRNA analysis highlighted a putative NEAT1/miR-1287-5p/CX3CR1 axis. Docking suggested plausible ligandability of CX3CR1, FCGR1A, and TLR5, nominating candidates such as valproic acid and CGP-52608 for follow-up testing.

An ET-anchored, 10-gene signature captures a clinically relevant axis of sepsis-associated immunosuppression and enables short-term mortality risk stratification. Integration with age yields a simple nomogram with stable internal performance. Multilayer validation (transcript, protein, single-cell) supports biological plausibility. Prospective multicenter studies with richer clinical annotation and functional assays are warranted to confirm generalizability and to evaluate ET-guided immunomodulatory strategies.