[Bioinformatics-Based Screening and Validation of Biomarkers for Sudden Death in Leukemia]

To identify biomarkers for sudden death in leukemia through common genes across leukemia subtypes using bioinformatics technology, and to validate them in a specific case repository of sudden death in leukemia, thereby providing reference for cause of death determination in leukemia-related sudden death and cause of death analysis in medical malpractice cases.

Differentially expressed genes (DEGs) common across different types of leukemia were identified using the GEO database (GSE13159 dataset). Enrichment analyses were performed using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, and enriched pathways were mapped to routine clinical laboratory parameters. Case data from patients who died suddenly due to stroke, respiratory failure, sudden cardiac death, and infectious shock, were collected and divided into the case group(leukemia sudden death group) and the control group(non-leukemia sudden death group) for validation. The Wilcoxon rank sum test and univariate logistic regression were used to screen biomarkers. A multivariate logistic regression model was constructed based on univariate logistic regression results to predict whether a sudden death patient had leukemia. Model performance was evaluated using receiver operator characteristic (ROC) curves and area under the curve (AUC).

A total of 540 DEGs shared across four leukemia subtypes were significantly enriched in pathways related to cell cycle, inflammatory immunity, and coagulation. The pathway enrichment results showed clear correspondence with routine clinical laboratory parameters. Compared with the control group, the case group exhibited overall characteristics of low white blood cell counts (mean: 2.42×10⁹/L), low platelet counts (mean: 23×10⁹/L), and low interleukin-6 (IL-6) levels (mean: 386.0 pg/mL). Based on the univariate logistic regression results, IL-6 and platelet count were included in a multivariate logistic regression model. The model yielded an AUC of 0.828.

The enrichment pattern of DEGs in leukemia sudden death biomarkers is consistent with the shared molecular mechanisms of uncontrolled leukemia cell proliferation, immune evasion, and hypercoagulable state. The combination of blood routine test parameters and IL-6 can be used for the differential diagnosis of sudden death in leukemia, providing objective evidence for auxiliary determination of cause of death in leukemia sudden death cases and offering a quantitative reference for cause of death analysis in medical malpractice identification.