Diffuse large B-cell lymphoma (DLBCL) is biologically heterogeneous and is associated with variable clinical outcomes. We aimed to develop a tumor-associated macrophage (TAM)-related ferroptosis–glycolysis prognostic signature and to explore selected signature genes in preclinical models. This retrospective multi-cohort computational prognostic biomarker-development study integrated public single-cell and bulk transcriptomic datasets. GSE10846 was used for feature selection, model fitting, and parameter tuning, whereas GSE32918, GSE69051, and TCGA-DLBC were used as model-selection validation cohorts. Exploratory immune, genomic, and computational drug-sensitivity analyses were performed. Signature-gene expression was assessed in 27 archived DLBCL tissues, and GCLC and SLC1A5 were further examined in TAM-related preclinical models in vitro and in vivo. An 11-gene TAM-related ferroptosis–glycolysis signature (TAMFGS) was developed. The time-dependent AUCs (95% CIs) were 0.978 (0.966–0.990), 0.986 (0.976–0.995), and 0.982 (0.966–0.999) at 1, 3, and 5 years, respectively, in GSE10846; 0.622 (0.524–0.720), 0.608 (0.515–0.702), and 0.619 (0.524–0.715) in GSE32918; 0.516 (0.286–0.747), 0.741 (0.548–0.934), and 0.754 (0.516–0.993) at 1, 2, and 3 years, respectively, in GSE69051; and 0.929 (0.850–1.000), 0.674 (0.382–0.966), and 0.677 (0.402–0.952) at 1, 3, and 5 years, respectively, in TCGA-DLBC. In GSE10846, the continuous TAMFGS score remained associated with overall survival after adjustment for available covariates (HR, 1.094; 95% CI, 1.082–1.106; p < 0.001). Exploratory analyses identified associations between TAMFGS and immune-related transcriptomic estimates and computationally predicted drug sensitivity. GCLC or SLC1A5 knockdown was associated with ferroptosis-associated molecular changes and an M1-like inflammatory shift in the THP-1-derived TAM model and was associated with reduced DLBCL growth in preclinical models. In retrospective transcriptomic DLBCL cohorts, TAMFGS was associated with overall survival. GCLC and SLC1A5 emerged as TAM-related candidate genes that warrant further mechanistic and prospective validation.
Yingjun Wang, Lai Wei, Jie-Ting Wang et al.· European Journal of Medical...· 0 citations
OBJECTIVE
To investigate the clinical features and risk factors for progression from acute-phase autoimmune encephalitis (AE) with epileptic seizures to autoimmune encephalitis-associated epilepsy (AEAE).
METHODS
We retrospectively analyzed clinical data from patients with acute-phase autoimmune encephalitis presenting with seizures between January 2016 and July 2024 at two clinical centers. Following a minimum follow-up of one year, patients were categorized into the ASSAE group or the AEAE group. Multivariable logistic regression identified independent predictors. Model performance was assessed by ROC analysis with bootstrap validation (B = 1000) and calibration testing.
RESULTS
32 patients (22.9%) progressed to AEAE. Multivariable logistic regression identified symptom of prodromal infection as a protective factor (OR: 0.336, 95% CI: 0.131-0.862), while the number of ASMs at discharge was identified as a significant clinical indicator of AEAE development (OR: 2.854, 95% CI: 1.551-5.255). The model demonstrated good discrimination (bootstrap AUC: 0.766, 95% CI: 0.684-0.841) and excellent calibration (Hosmer-Lemeshow P = 0.849).
CONCLUSION
Among patients with acute-phase AE and seizures, the number of ASMs at discharge and the absence of prodromal infection symptom are probable clinical indicators for predicting AEAE. These findings may facilitate early risk stratification and optimize management strategies for patients with AE-related seizures.
Qianqian Liu, Lang Shen, Xia Cai et al.· Seizure· 0 citations
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