A study analyzed genetic lesions in 944 patients with myelodysplastic syndromes (MDS) using high-throughput DNA sequencing and array-based genomic hybridization. The research identified mutations in 104 genes, with 89.5% of patients harboring at least one mutation, and 47 genes showing significant mutations. These mutations were associated with higher risk groups and blast elevation. Survival analysis in 875 patients revealed that 25 out of 48 genes (including PRPF8) significantly affected survival. A novel prognostic model ('Model-1') was developed using 14 genes, dividing patients into four risk groups with 3-year survival rates of 95.2%, 69.3%, 32.8%, and 5.3%. A 'gene-only model' ('Model-2') based on the same 14 genes also showed four risk groups. Both models were validated in a separate cohort of 175 patients, demonstrating reproducibility. The study highlights the importance of large-scale genetic and molecular profiling for subclassification and prognostication in MDS patients. The findings suggest that mutations in genes such as TET2, SF3B1, ASXL1, SRSF2, DNMT3A, and RUNX1 are frequently mutated and associated with poor prognosis. The study also identified correlations between mutations and functional pathways, including RNA splicing, DNA methylation, chromatin modification, and DNA repair. The results indicate that mutations in these pathways are common and may contribute to the clonal evolution of MDS. The study provides a comprehensive landscape of genetic alterations in MDS and demonstrates the potential of molecular markers for improving prognostic models. The models developed in this study outperformed existing models such as the IPSS-R, showing better predictive accuracy for patient survival. The study also emphasizes the importance of integrating genetic and molecular data into clinical practice for more accurate diagnosis and treatment of MDS.A study analyzed genetic lesions in 944 patients with myelodysplastic syndromes (MDS) using high-throughput DNA sequencing and array-based genomic hybridization. The research identified mutations in 104 genes, with 89.5% of patients harboring at least one mutation, and 47 genes showing significant mutations. These mutations were associated with higher risk groups and blast elevation. Survival analysis in 875 patients revealed that 25 out of 48 genes (including PRPF8) significantly affected survival. A novel prognostic model ('Model-1') was developed using 14 genes, dividing patients into four risk groups with 3-year survival rates of 95.2%, 69.3%, 32.8%, and 5.3%. A 'gene-only model' ('Model-2') based on the same 14 genes also showed four risk groups. Both models were validated in a separate cohort of 175 patients, demonstrating reproducibility. The study highlights the importance of large-scale genetic and molecular profiling for subclassification and prognostication in MDS patients. The findings suggest that mutations in genes such as TET2, SF3B1, ASXL1, SRSF2, DNMT3A, and RUNX1 are frequently mutated and associated with poor prognosis. The study also identified correlations between mutations and functional pathways, including RNA splicing, DNA methylation, chromatin modification, and DNA repair. The results indicate that mutations in these pathways are common and may contribute to the clonal evolution of MDS. The study provides a comprehensive landscape of genetic alterations in MDS and demonstrates the potential of molecular markers for improving prognostic models. The models developed in this study outperformed existing models such as the IPSS-R, showing better predictive accuracy for patient survival. The study also emphasizes the importance of integrating genetic and molecular data into clinical practice for more accurate diagnosis and treatment of MDS.