Project description:Background MicroRNAs are important regulators of transcription in hematopoiesis. Their expression deregulations were described in association with pathogenesis of some hematological malignancies. This study provides integrated microRNA expression profiling at different phases of chronic myeloid leukemia (CML) with the aim to select CML specific miRNAs and find new possible biomarkers. The functions of in silico filtered targets are in this report annotated and discussed in relation to CML pathogenesis. Results Using microarrays we identified differential expression profiles of 49 miRNAs in CML patients at diagnosis, in hematological relapse, therapy failure, blast crisis and major molecular response. The expression deregulation of miR-150, miR-20a, miR-17, miR-19a, miR-103, miR-144, miR-155, miR-181a, miR-221 and miR-222 in CML was confirmed by real-time quantitative PCR and in silico analyses identified targeted genes of these miRNAs encoding proteins that are involved in cell cycle, growth inhibition, MAPK, ErBb, transforming growth factor beta and p53 signaling pathways that are related to CML. Validated miR-150 decreased levels were detected in patients at diagnosis, in blast crisis and 67% of hematological relapses and showed significant negative correlation with miR-150 proved target MYB and with BCR-ABL transcript level. Conclusions This study revealed microRNAs that may be related to the CML pathogenesis and may reflect transformation from chronic to accelerated phases. The obtained expression patterns in peripheral blood total leukocytes during the course of CML suggest specific miRNAs as possible biomarkers. The annotated functions of in silico filtered targets of selected miRNAs outline mechanisms whereby microRNAs may be involved in CML pathogenesis. Twenty four patient samples of total leukocytes from peripheral blood were used to prepare pools representing different CML phases for microarray analysis: diagnosis (n=5, Dg), major molecular response (n=5, MMR), therapy failure (n=5, TF), hematological relapse (n=5, Hr), and blast crisis (n=4, BC). Eleven healthy donors of age median 60 (range 45 - 78) and man/woman ratio 3/2 following CML incidence were used to create a control pool.

Project description:Multiple myeloma (MM) remains incurable despite the introduction of novel agents and a relapsing course is observed in the majority of patients. Although the development of genomic technologies has greatly improved our understanding of MM pathogenesis, the mechanisms underlying relapse have been less investigated. In this study, an integrative analysis of DNA copy number, DNA methylation and gene expression was conducted in matched diagnosis and relapse samples from 17 MM patients. Overall, the acquisition of abnormalities at relapse was much more frequent than the lost of lesions present at diagnosis, and DNA losses were significantly more frequent at relapse than in diagnosis samples. Interestingly, copy number abnormalities involving more than 100 Mb of DNA at relapse significantly impact the gene expression of these samples, provoking a particular deregulation of IL-8 pathway. On the contrary, no relevant modifications of gene expression were observed in those samples with less than 100 Mb affected by chromosomal changes. Although different statistical approaches were used to uncover genes whose abnormal expression at relapse was regulated by DNA methylation, only two genes significantly deregulated in relapse samples (SORL1 and GLT1D1) showed a negative methylation-expression correlation. A deeper analysis demonstrated that DNA methylation was involved in regulation of SORL1 expression in MM. Finally, relevant changes in gene expression observed in relapse samples, such us downregulation of CD27 and P2RY8, were not apparently preceded by alterations in corresponding DNA. Taken together, these results showed that genomic heterogeneity, both at the DNA and RNA level, is a hallmark of MM transition from diagnosis to relapse. Please note that an a first step all analyses were carried out independently in each series, being the number of samples of 40 in methylation, 38 in SNP and 34 in expression series. In the next step, association studies were performed only in the overlapping samples, being 34 matching samples between expression and methylation and 32 samples between expression and SNP data.

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B-ALL relapse analysis

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