MDM2 antagonist clinical response association with a gene expression signature in acute myeloid leukaemia.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhong H
PROVIDER: S-EPMC5104337 | biostudies-literature | 2015 Nov
REPOSITORIES: biostudies-literature
Publications
MDM2 antagonist clinical response association with a gene expression signature in acute myeloid leukaemia.
Zhong Hua H Chen Gong G Jukofsky Lori L Geho David D Han Sung Won SW Birzele Fabian F Bader Sabine S Himmelein Lucia L Cai James J Albertyn Zayed Z Rothe Mark M Essioux Laurent L Burtscher Helmut H Middleton Steven A SA Rueger Ruediger R Chen Lin-Chi LC Dangl Markus M Nichols Gwen G Pierceall William E WE
British journal of haematology 20150408 3
Similar Datasets
Project description:For several decades, few substantial therapeutic advances have been made for patients with acute myeloid leukaemia. However, since 2017 unprecedented growth has been seen in the number of drugs available for the treatment of acute myeloid leukaemia, with several new drugs receiving regulatory approval. In addition to advancing our therapeutic armamentarium, an increased understanding of the biology and genomic architecture of acute myeloid leukaemia has led to refined risk assessment of this disease, with consensus risk stratification guidelines now incorporating a growing number of recurrent molecular aberrations that aid in the selection of risk-adapted management strategies. Despite this promising recent progress, the outcomes of patients with acute myeloid leukaemia remain unsatisfactory, with more than half of patients ultimately dying from their disease. Enrolment of patients into clinical trials that evaluate novel drugs and rational combination therapies is imperative to continuing this progress and further improving the outcomes of patients with acute myeloid leukaemia.
| S-EPMC10230947 | biostudies-literature
Project description:ContextIn many cancers, specific subpopulations of cells appear to be uniquely capable of initiating and maintaining tumors. The strongest support for this cancer stem cell model comes from transplantation assays in immunodeficient mice, which indicate that human acute myeloid leukemia (AML) is driven by self-renewing leukemic stem cells (LSCs). This model has significant implications for the development of novel therapies, but its clinical relevance has yet to be determined.ObjectiveTo identify an LSC gene expression signature and test its association with clinical outcomes in AML.Design, setting, and patientsRetrospective study of global gene expression (microarray) profiles of LSC-enriched subpopulations from primary AML and normal patient samples, which were obtained at a US medical center between April 2005 and July 2007, and validation data sets of global transcriptional profiles of AML tumors from 4 independent cohorts (n = 1047).Main outcome measuresIdentification of genes discriminating LSC-enriched populations from other subpopulations in AML tumors; and association of LSC-specific genes with overall, event-free, and relapse-free survival and with therapeutic response.ResultsExpression levels of 52 genes distinguished LSC-enriched populations from other subpopulations in cell-sorted AML samples. An LSC score summarizing expression of these genes in bulk primary AML tumor samples was associated with clinical outcomes in the 4 independent patient cohorts. High LSC scores were associated with worse overall, event-free, and relapse-free survival among patients with either normal karyotypes or chromosomal abnormalities. For the largest cohort of patients with normal karyotypes (n = 163), the LSC score was significantly associated with overall survival as a continuous variable (hazard ratio [HR], 1.15; 95% confidence interval [CI], 1.08-1.22; log-likelihood P <.001). The absolute risk of death by 3 years was 57% (95% CI, 43%-67%) for the low LSC score group compared with 78% (95% CI, 66%-86%) for the high LSC score group (HR, 1.9 [95% CI, 1.3-2.7]; log-rank P = .002). In another cohort with available data on event-free survival for 70 patients with normal karyotypes, the risk of an event by 3 years was 48% (95% CI, 27%-63%) in the low LSC score group vs 81% (95% CI, 60%-91%) in the high LSC score group (HR, 2.4 [95% CI, 1.3-4.5]; log-rank P = .006). In multivariate Cox regression including age, mutations in FLT3 and NPM1, and cytogenetic abnormalities, the HRs for LSC score in the 3 cohorts with data on all variables were 1.07 (95% CI, 1.01-1.13; P = .02), 1.10 (95% CI, 1.03-1.17; P = .005), and 1.17 (95% CI, 1.05-1.30; P = .005).ConclusionHigh expression of an LSC gene signature is independently associated with adverse outcomes in patients with AML.
| S-EPMC4089862 | biostudies-literature
Project description: Not available
| S-EPMC5004378 | biostudies-literature
Project description:Although acute myeloid leukaemia (AML) has long been recognized for its morphological and cytogenetic heterogeneity, recent high-resolution genomic profiling has demonstrated a complexity even greater than previously imagined. This complexity can be seen in the number and diversity of genetic alterations, epigenetic modifications, and characteristics of the leukaemic stem cells. The broad range of abnormalities across different AML subtypes suggests that improvements in clinical outcome will require the development of targeted therapies for each subtype of disease and the design of novel clinical trials to test these strategies. It is highly unlikely that further gains in long-term survival rates will be possible by mere intensification of conventional chemotherapy. In this review, we summarize recent studies that provide new insight into the genetics and biology of AML, discuss risk stratification and therapy for this disease, and profile some of the therapeutic agents currently under investigation.
| S-EPMC3468705 | biostudies-literature
Project description:Acute myeloid leukaemia (AML) is the most common type of adult acute leukaemia and has a poor prognosis. Thus, optimal risk stratification is of greatest importance for reasonable choice of treatment and prognostic evaluation. For our study, a total of 1707 samples of AML patients from three public databases were divided into meta-training, meta-testing and validation sets. The meta-training set was used to build risk prediction model, and the other four data sets were employed for validation. By log-rank test and univariate COX regression analysis as well as LASSO-COX, AML patients were divided into high-risk and low-risk groups based on AML risk score (AMLRS) which was constituted by 10 survival-related genes. In meta-training, meta-testing and validation sets, the patient in the low-risk group all had a significantly longer OS (overall survival) than those in the high-risk group (P < .001), and the area under ROC curve (AUC) by time-dependent ROC was 0.5854-0.7905 for 1 year, 0.6652-0.8066 for 3 years and 0.6622-0.8034 for 5 years. Multivariate COX regression analysis indicated that AMLRS was an independent prognostic factor in four data sets. Nomogram combining the AMLRS and two clinical parameters performed well in predicting 1-year, 3-year and 5-year OS. Finally, we created a web-based prognostic model to predict the prognosis of AML patients (https://tcgi.shinyapps.io/amlrs_nomogram/).
| S-EPMC7176885 | biostudies-literature
Project description:Background: Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults; AML is highly heterogeneous and involves abnormalities at multiple omics levels. Small non-coding RNAs (sncRNAs) present in body fluids are important regulatory molecules and considered promising non-invasive clinical diagnostic biomarkers for disease. However, the signature of sncRNA profile alteration in AML patient serum and bone marrow supernatant is still under exploration. Methods: We examined data for blood and bone marrow samples from 80 consecutive, newly-diagnosed patients with AML and 12 healthy controls for high throughput small RNA-sequencing. Differentially expressed sncRNAs were analysed to reveal distinct patterns between AML patients and controls. Machine learning methods were used to evaluate the efficiency of specific sncRNAs in discriminating individuals with AML from controls. The altered expression level of individual sncRNAs was evaluated by RT-PCR, Q-PCR, and northern blot. Correlation analysis was employed to assess sncRNA patterns between serum and bone marrow supernatant. Results: We identified over 20 types of sncRNA categories beyond miRNAs in both serum and bone marrow supernatant, with highly coordinated expression patterns between them. Non-classical sncRNAs, including rsRNA (62.86%), ysRNA (14.97%), and tsRNA (4.22%), dominated among serum sncRNAs and showed sensitive alteration patterns in AML patients. According to machine learning-based algorithms, the tsRNA-based signature robustly discriminated subjects with AML from controls and was more reliable than that comprising miRNAs. Our data also showed that serum tsRNAs to be closely associated with AML prognosis, suggesting the potential application of serum tsRNAs as biomarkers to assist in AML diagnosis. Conclusions: We comprehensively characterized the expression pattern of circulating sncRNAs in blood and bone marrow and their alteration signature between healthy controls and AML patients. This study enriches research of sncRNAs in the regulation of AML, and provides insights into the role of sncRNAs in AML.
| S-EPMC10008735 | biostudies-literature
Project description:Acute Myeloid Leukaemia (AML) carries a 5 year survival rate of just 24%. Toxic chemotherapy regimens remain the backbone of standard of care for AML. The FLT3 tyrosine kinase is a recognised AML oncogene, with FLT3 activating mutations occurring in approximately one third of all AML patients. However, therapeutic targeting of FLT3 has proven difficult as monotherapy, with the development of drug resistance and relapse. Characterisation of the signalling pathways regulated by mutant FLT3 is required to identify better therapeutic strategies.
2019-12-20 | MSV000084730 | MassIVE
Project description:BackgroundThe immune response in the bone marrow microenvironment has implications for progression and prognosis in acute myeloid leukemia (AML). However, few immune-related biomarkers for AML prognosis and immunotherapy response have been identified. We aimed to establish a predictive gene signature and to explore the determinants of prognosis in AML.MethodsImmune-related genes with clinical significance were screened by a weighted gene co-expression network analysis. Seven immune-related genes were used to establish a gene signature by a multivariate Cox regression analysis. Based on the signature, low- and high-risk groups were compared with respect to the immune microenvironment, immune checkpoints, pathway activities, and mutation frequencies. The tumor immune dysfunction and exclusion (TIDE) method was used to predict the response to immune checkpoint blockade (ICB) therapy. The Connectivity Map database was used to explore small-molecule drugs expected to treat high-risk populations.ResultsA seven-gene prognostic signature was used to classify patients into high- and low-risk groups. Prognosis was poorer for patients in the former than in the latter. The high-risk group displayed higher levels of immune checkpoint molecules (LAG3, PD-1, CTLA4, PD-L2, and PD-L1), immune cell infiltration (dendritic cells, T helper 1, and gamma delta T), and somatic mutations (NPM1 and RUNX1). Moreover, hematopoietic stem cell/leukemia stem cell pathways were enriched in the high-risk phenotype. Compared with that in the low-risk group, the lower TIDE score for the high-risk group implied that this group is more likely to benefit from ICB therapy. Finally, some drugs (FLT3 inhibitors and BCL inhibitors) targeting the expression profiles associated with the high-risk group were generated using Connectivity Map.ConclusionThe newly developed immune-related gene signature is an effective biomarker for predicting prognosis in AML and provides a basis, from an immunological perspective, for the development of comprehensive therapeutic strategies.
| S-EPMC9468431 | biostudies-literature
Project description:Acute myeloid leukaemia (AML) is a molecularly and clinically heterogeneous disease, and its incidence is increasing as the populations in Western countries age. Despite major advances in understanding the genetic landscape of AML and its impact on the biology of the disease, standard therapy has not changed significantly in the last three decades. Allogeneic haematopoietic stem cell transplantation remains the best chance for cure, but can only be offered to a minority of younger fit patients. Molecularly targeted drugs aiming at restoring apoptosis in leukaemic cells have shown encouraging activity in early clinical trials and some of these drugs are currently being evaluated in randomised controlled trials. In this review, we discuss the current development of drugs designed to trigger cell death in AML.
| S-EPMC5674101 | biostudies-literature
Project description:Acute myeloid leukaemia (AML) is a group of malignant diseases of the haematopoietic system. AML occurs as the result of mutations in haematopoietic stem/progenitor cells, which upregulate Wnt signalling through a variety of mechanisms. Other mechanisms of Wnt activation in AML have been described such as Wnt antagonist inactivation through promoter methylation. Wnt signalling is necessary for the maintenance of leukaemic stem cells. Several molecules involved in or modulating Wnt signalling have a prognostic value in AML. These include: β-catenin, LEF-1, phosphorylated-GSK3β, PSMD2, PPARD, XPNPEP, sFRP2, RUNX1, AXIN2, PCDH17, CXXC5, LLGL1 and PTK7. Targeting Wnt signalling for tumour eradication is an approach that is being explored in haematological and solid tumours. A number of preclinical studies confirms its feasibility, albeit, so far no reliable clinical trial data are available to prove its utility and efficacy.
| S-EPMC6912424 | biostudies-literature