Dataset Information

Transposable Element Expression in Acute Myeloid Leukemia Transcriptome and Prognosis.

ABSTRACT: Over half of the human genome is comprised of transposable elements (TE). Despite large-scale studies of the transcriptome in cancer, a comprehensive look at TE expression and its relationship to various mutations or prognosis has not been performed. We characterized the expression of TE in 178 adult acute myeloid leukemia (AML) patients using transcriptome data from The Cancer Genome Atlas. We characterized mutation specific dysregulation of TE expression using a multivariate linear model. We identified distinct patterns of TE expression associated with specific mutations and transcriptional networks. Genes regulating methylation was not associated with significant change in TE expression. Using an unpenalized cox regression analysis we identified a TE expression signature that predicted prognosis in AML. We identified 14 candidate prognostic TE transcripts (TEP) that classified AML as high/low-risk and this was independent of mutation-based and coding-gene expression based risk-stratification. TEP was able to predict prognosis in independent cohorts of 284 pediatric AML patients and 19 relapsed adult AML patients. This first comprehensive study of TE expression in AML demonstrates that TE expression can serve as a biomarker for prognosis in AML, and provides novel insights into the biology of AML. Studies characterizing its role in other cancers are warranted.

SUBMITTER: Colombo AR

PROVIDER: S-EPMC6219593 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Transposable Element Expression in Acute Myeloid Leukemia Transcriptome and Prognosis.

Colombo Anthony R AR Triche Timothy T Ramsingh Giridharan G

Scientific reports 20181106 1

Over half of the human genome is comprised of transposable elements (TE). Despite large-scale studies of the transcriptome in cancer, a comprehensive look at TE expression and its relationship to various mutations or prognosis has not been performed. We characterized the expression of TE in 178 adult acute myeloid leukemia (AML) patients using transcriptome data from The Cancer Genome Atlas. We characterized mutation specific dysregulation of TE expression using a multivariate linear model. We i ...[more]

PMID: 30401833

Similar Datasets

Project description:AimAcute myeloid leukemia (AML) is a heterogeneous disorder with complex genetic basis and adverse prognosis. Cytogenetics risk, somatic mutations and gene expression profiles are important prognostic factors for AML patients. However, accurate stratification of patient prognosis remains an unsolved problem in AML. This study was to to develop a novel gene profile to accurately classify AML patients into subgroups with different survival probabilities.MethodsSurvival-related genes were determined by Kaplan-Meier survival analysis and multivariate analysis using the expression and clinical data of 405 AML patients from Oregon Health & Science University (OHSU) dataset and validated in The Cancer Genome Atlas (TCGA) database. Feature selection was performed by using the Least Absolute Shrinkage and Selection Operator (LASSO) method. With the LASSO model, a prognostic 85-gene score was established and compared with 2 known gene-expression risk scores. The stratification of AML patients was performed by unsupervised hierarchical clustering of 85 gene expression levels to identify clusters of AML patients with different survival probabilities.ResultsThe LASSO model comprising 85 genes was considered as the optimal model based on relatively high area under curve value (0.83) and the minimum mean squared error. The 85-gene score was associated with increased mortality in AML patients. Hierarchical clustering analysis of the 85 genes revealed 3 subgroups of AML patients in the OHSU dataset. The cluster1 AML patients were associated with more female cases, higher percent of bone marrow blast cells, 85-gene score, cytogenetics risk, more frequent FLT3-ITD, DNMT3A, NP1 mutations, less frequent TP53, RUNX1 mutations, poorer overall survival than cluster2 tumors. The 85-gene score had higher AUC (0.75) than the 5-gene risk score and LSC17 score (0.74 and 0.65).ConclusionsThe 85-gene score is superior to the 2 established prognostic gene signatures in the prediction of prognosis of AML patients.

Dataset Information

Transposable Element Expression in Acute Myeloid Leukemia Transcriptome and Prognosis.

Publications

Transposable Element Expression in Acute Myeloid Leukemia Transcriptome and Prognosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets