High expression of miR-25 predicts favorable chemotherapy outcome in patients with acute myeloid leukemia.
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ABSTRACT:
SUBMITTER: Niu M
PROVIDER: S-EPMC6505210 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
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Project description:The malfunction of SEC61A1 has been linked to several types of cancers, but its role in acute myeloid leukemia (AML) remains poorly understood. In this study, we used a series of bioinformatics analysis techniques, including gene expression profiling and proteomic analysis. Our findings were subsequently validated through a series of in vitro experiments, such as SEC61A1 knockdown in cell lines and RT-qPCR. We discovered a significant up-regulation of SEC61A1 in AML patients compared to healthy controls. AML patients with elevated SEC61A1 expression exhibited reduced overall survival compared to those with lower expression. Moreover, SEC61A1 expression emerged as an independent risk factor for predicting the survival of AML patients undergoing allo-HSCT. Our analysis also revealed an association between high SEC61A1 expression and increased signaling pathways related to cell growth. Our study underscores the importance of SEC61A1 expression as a novel prognostic indicator for predicting survival among AML patients, while also identifying it as a promising therapeutic target.
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Project description:Acute myeloid leukemia (AML) is a devastating blood cancer with high heterogeneity and ill-fated outcome. Despite numerous advances in AML treatment, the prognosis remains poor for a significant proportion of patients. Consequently, it is necessary to accurately and comprehensively identify biomarkers as soon as possible to enhance the efficacy of diagnosis, prognosis and treatment of AML. In this study, we aimed to identify prognostic markers of AML by analyzing the cohorts from TCGA-LAML database and GEO microarray datasets. Interestingly, the transcriptional level of microtubule-associated protein TBCB in AML patients was noticeably increased when compared with normal individuals, and this was verified in two independent cohorts (GSE9476 and GSE13159) and with our AML patients. Furthermore, univariate and multivariate regression analysis revealed that high TBCB expression was an independent poor prognostic factor for AML. GO and GSEA enrichment analysis hinted that immune-related signaling pathways were enriched in up-regulated DEGs between two populations separated by the median expression level of TBCB. By constructing a protein-protein interaction network, we obtained six hub genes, all of which are immune-related molecules, and their expression levels were positively linked to that of TBCB. In addition, the high expression of three hub genes was significantly associated with a poor prognosis in AML. Moreover, we found that the tumor microenvironment in AML with high TBCB expression tended to be infiltrated by NK cells, especially CD56bright NK cells. The transcriptional levels of NK cell inhibitory receptors and their ligands were positively related to that of TBCB, and their high expression levels also predicted poor prognosis in AML. Notably, we found that the down-regulation of TBCB suppressed cell proliferation in AML cell lines by enhancing the apoptosis and cell cycle arrest. Finally, drug sensitivity prediction illustrated that cells with high TBCB expression were more responsive to ATRA and midostaurin but resistant to cytarabine, dasatinib, and imatinib. In conclusion, our findings shed light on the feasibility of TBCB as a potential predictor of poor outcome and to be an alternative target of treatment in AML.
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Project description:BACKGROUND:Acute myeloid leukemia (AML) is a highly heterogeneous malignancy with various outcomes, and therefore needs better risk stratification tools to help select optimal therapeutic options. METHODS:In this study, we identify miRNAs that could predict clinical outcome in a heterogeneous AML population using TCGA dataset. RESULTS:We found that MiR-363 is a novel prognostic factor in AML patients undergoing chemotherapy. In multivariable analyses, high miR-363 remained predictive for shorter OS (HR?=?2.349, P?=?0.012) and EFS (HR?=?2.082, P?=?0.001) independent of other well-known prognostic factors. More importantly, allogeneic hematopoietic stem cell transplantation (allo-HSCT) overcame the adverse outcomes related to high miR-363 expression. In gene expression profiling, high miR-363 expression was positively correlated with the amounts of leukemogenic transcription factors, including Myb, RUNX3, GATA3, IKZF3, ETS1 and MLLT3. Notably, we found that the in silico predicted target genes (EZH2, KLF6 and PTEN) of miR-363 were downregulated in association with high miR-363 expression. CONCLUSIONS:In summary, miR-363 expression may help identify patients in need of strategies to select the optimal therapy between chemotherapeutic and allo-HCST regimens. AML patients with high miR-363 expression may be highly recommended for early allo-HSCT regimen.
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Project description:PurposeOptimized strategies for risk classification are essential to tailor therapy for patients with biologically distinctive disease. Risk classification in pediatric acute myeloid leukemia (pAML) relies on detection of translocations and gene mutations. Long noncoding RNA (lncRNA) transcripts have been shown to associate with and mediate malignant phenotypes in acute myeloid leukemia (AML) but have not been comprehensively evaluated in pAML.MethodsTo identify lncRNA transcripts associated with outcomes, we evaluated the annotated lncRNA landscape by transcript sequencing of 1,298 pediatric and 96 adult AML specimens. Upregulated lncRNAs identified in the pAML training set were used to establish a regularized Cox regression model of event-free survival (EFS), yielding a 37 lncRNA signature (lncScore). Discretized lncScores were correlated with initial and postinduction treatment outcomes using Cox proportional hazards models in validation sets. Predictive model performance was compared with standard stratification methods by concordance analysis.ResultsTraining set cases with positive lncScores had 5-year EFS and overall survival rates of 26.7% and 42.7%, respectively, compared with 56.9% and 76.3% with negative lncScores (hazard ratio, 2.48 and 3.16; P < .001). Pediatric validation cohorts and an adult AML group yielded comparable results in magnitude and significance. lncScore remained independently prognostic in multivariable models, including key factors used in preinduction and postinduction risk stratification. Subgroup analysis suggested that lncScores provide additional outcome information in heterogeneous subgroups currently classified as indeterminate risk. Concordance analysis showed that lncScore adds to overall classification accuracy with at least comparable predictive performance to current stratification methods that rely on multiple assays.ConclusionInclusion of the lncScore enhances predictive power of traditional cytogenetic and mutation-defined stratification in pAML with potential, as a single assay, to replace these complex stratification schemes with comparable predictive accuracy.
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