This meta-analysis was performed to explore the impact of minimal residual disease (MRD) prior to transplantation on the prognosis for patients with acute lymphoblastic leukemia (ALL). A systematic search of PubMed, Embase, and the Cochrane Library was conducted for relevant studies from database inception to March 2016. A total of 21 studies were included. Patients with positive MRD prior to allogeneic stem cell transplantation (allo-SCT) had a significantly higher rate of relapse compared with those with negative MRD (HR = 3.26; P < 0.05). Pre-transplantation positive MRD was a significant negative predictor of relapse-free survival (RFS) (HR = 2.53; P < 0.05), event-free survival (EFS) (HR = 4.77; P < 0.05), and overall survival (OS) (HR = 1.98; P < 0.05). However, positive MRD prior to transplantation was not associated with a higher rate of nonrelapse mortality. Positive MRD before allo-SCT was a predictor of poor prognosis after transplantation in ALL. Not applicable.

Angiogenesis is associated with tumour growth, infiltration, and metastasis. This study aimed to detect the mechanisms of angiogenesis-related genes (ARGs) in multiple myeloma (MM) and to construct a new prognostic model. MM research foundation (MMRF)-CoMMpass cohort, GSE47552, GSE57317, and ARGs were sourced from public databases. Differentially expressed genes (DEGs) in the tumour and control cohorts in GSE47552 were determined through differential expression analysis and were enriched with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was applied to derive modules linked to the ARG scores and obtain module genes in GSE47552. Differentially expressed ARGs (DE-ARGs) were selected for subsequent analyses by overlapping DEGs and module genes. Furthermore, prognostic genes were selected using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Depending on the prognostic genes, a risk model was constructed, and risk scores were determined. Moreover, MM samples from MMRF-CoMMpass were sorted into high- and low-risk teams on account of the median risk score. Additionally, correlations among clinical characteristics, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), immune analysis, immunotherapy predictions and the mRNA‒miRNA‒lncRNA network were carried out. A total of 898 DEGs, 211 module genes, 24 DE-ARGs and three prognostic genes (AKAP12, C11orf80 and EMP1) were selected for this study. Enrichment analysis revealed that the DEGs were related to 86 GO terms, such as ‘cytoplasmic translation’, and 41 KEGG pathways, such as ‘small cell lung cancer’. A prognostic gene-based risk model was created in MMRF-CoMMpass and confirmed with the GSE57317 dataset. Moreover, a nomogram was established on the basis of independent prognostic factors that have proven to be good predictors. In addition, the immune cell infiltration results suggested that memory B cells were enriched in the high-risk group and that immature B cells were enriched in the low-risk group. Finally, the mRNA‒miRNA‒lncRNA network demonstrated that hsa-miR-508-5p was tightly associated with EMP1 and AKAP12. RT‒qPCR was used to validate the expression of the genes associated with prognosis. A new prognostic model of MM associated with ARGs was created and validated, providing a new perspective for exploring the connection between ARGs and MM.

Background: Chronic myeloid leukemia (CML) progression relies on dynamic crosstalk between leukemic cells and vascular niches. Here, we investigate how exosomes and BCR/ABL overexpression influence endothelial functions, aiming to identify key mediators of leukemia-induced microenvironmental remodeling as potential therapeutic targets. Methods: Human umbilical vein endothelial cells (HUVECs) were cultured and divided into four groups: control (Z), treated with K562-derived exosomes (Zexo), BCR-ABL-overexpressing (ZBA), and BCR-ABL-overexpressing with exosome treatment (ZBAexo). Transcriptomic profiling was performed to identify DEGs, followed by functional enrichment and protein–protein interaction network analyses. Gene Set Enrichment Analysis (GSEA) was applied to uncover associated biological pathways. Results: Seven specificized expressed genes in ZBAexo group were identified: CAMK2B , CDC25C , SV2A , MND1 , CDC20 , CLSPN , and GRM1 . These genes are involved in cell cycle, DNA replication, and cell adhesion pathways and show significant correlation with the BCR/ABL fusion gene. Expression of these genes was strongly associated with BCR-ABL. Network analysis revealed the potential regulatory roles of transcription factors CREB1 and NFKB1 . A competing endogenous RNA (ceRNA) network involving miRNAs ( e.g. , miR-16-5p, miR-126-5p) and lncRNAs ( e.g. , AC008124.1, AC064799.2, AGAP11) potentially modulates their expression. Conclusion: This study identifies seven novel candidate biomarkers dysregulated in endothelial cells under combined BCR-ABL and exosomal stimulation, shedding light on the molecular crosstalk between leukemic cells and the vascular niche.