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Clinical and genetic features of Ph-negative myeloproliferative neoplasms with dual-driver gene positivity.

OBJECTIVES: To investigate the clinical laboratory characteristics and gene mutation features of dual-driver gene positivity in patients with Philadelphia chromosome-negative myeloproliferative neoplasm (Ph-negative MPN). METHODS: We conducted a retrospective analysis of clinical data and genetic test results from 203 newly diagnosed patients with Ph-negative MPN. Of these, 194 had single-driver gene positivity and 9 had dual-driver gene positivity. High-throughput sequencing was used to detect mutations in JAK2, CALR, and MPL. Clinical characteristics and gene mutation profiles were compared between the two patient groups. RESULTS: The incidence of dual-driver gene positivity was 4.4% (9/203), with the most common combinations being JAK2 with CALR (4 patients) and JAK2 with MPL (4 patients). Compared with the single-driver group, the dual-driver group had a significantly higher risk of bleeding [4.1% (8/194) vs. 33.3% (3/9), P = 0.008] and a higher proportion of uncommon mutations [3.6% (7/194) vs. 33.3% (3/9), P = 0.006]. No statistically significant differences were observed between the two groups regarding age, thrombosis incidence, splenomegaly, or routine blood test indicators. During follow-up, 1 patient in the dual-driver group died from cerebrovascular disease. No leukaemia transformation or disease-related deaths occurred among the remaining patients. DISCUSSION: The increased bleeding risk in dual-driver patients may be related to a higher proportion of CALR mutations, elevated platelet counts, and higher variant allele frequencies, though these findings require validation in larger cohorts due to the small sample size. The higher prevalence of uncommon mutations suggests a more complex mutational landscape in this subgroup. CONCLUSION: Patients with Ph-negative MPN and dual-driver gene positivity may have a higher risk of bleeding and a more complex gene mutation profile.

Humans

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans