A four-gene LincRNA expression signature predicts risk in multiple cohorts of acute myeloid leukemia patients

Abstract

Prognostic gene expression signatures have been proposed as clinical tools to clarify therapeutic options in acute myeloid leukemia (AML). However, these signatures rely on measuring large numbers of genes and often perform poorly when applied to independent cohorts or those with older patients. Long intergenic non-coding RNAs (lincRNAs) are emerging as important regulators of cell identity and oncogenesis, but knowledge of their utility as prognostic markers in AML is limited. Here we analyze transcriptomic data from multiple cohorts of clinically annotated AML patients and report that (i) microarrays designed for coding gene expression can be repurposed to yield robust lincRNA expression data, (ii) some lincRNA genes are located in close proximity to hematopoietic coding genes and show strong expression correlations in AML, (iii) lincRNA gene expression patterns distinguish cytogenetic and molecular subtypes of AML, (iv) lincRNA signatures composed of three or four genes are independent predictors of clinical outcome and further dichotomize survival in European Leukemia Net (ELN) risk groups and (v) an analytical tool based on logistic regression analysis of quantitative PCR measurement of four lincRNA genes (LINC4) can be used to determine risk in AML.

Transcriptional networks in acute myeloid leukemia

“…Components of transcriptional networks are a common target of these aberrations, which leads to network‐wide changes and deployment of developmentally inappropriate or novel transcriptional programs. However, despite the wide variety of molecular aberrations observed, clustering of large AML cohorts based on global transcriptomic or epigenomic data generally reveals only a small number of clusters . This may reflect the fact that although the large transcriptional networks in eukaryotic cells have many theoretical states, only a small number of these are stable and accessible.…”

“…However, despite the wide variety of molecular aberrations observed, clustering of large AML cohorts based on global transcriptomic or epigenomic data generally reveals only a small number of clusters. 19,66,238,240,255 This may reflect the fact that although the large transcriptional networks in eukaryotic cells have many theoretical states, only a small number of these are stable and accessible. What is also becoming clearer is that leukemic transcriptional networks are highly plastic, and emerging data suggest that in addition to being implicated in leukemogenesis alterations to transcriptional networks may play a role in AML progression, resistance, and relapse.…”

“…Long noncoding RNAs (lncRNAs, >200 bp) are emerging as key regulators of a growing number of normal biological process including cell differentiation and identity and are differentially expressed in myelodysplastic syndrome and AML . Recent studies have shown that lncRNAs are required for normal hematopoiesis where they regulate HSC activity and function, as well as myeloid and lymphoid differentiation .…”

“…Recent studies have shown that lncRNAs are required for normal hematopoiesis where they regulate HSC activity and function, as well as myeloid and lymphoid differentiation . Expression is cell type specific in human hematopoiesis, and the expression of just four lncRNAs is sufficient to predict patient outcome across multiple AML cohorts . Some lncRNAs, including those that originate from leukemia‐associated genomic regions, function as oncogenic drivers in acute leukemia.…”

“…[248][249][250] Several bioinformatic studies have inferred roles for miRNAs in regulatory networks, 251 Long noncoding RNAs (lncRNAs, >200 bp) are emerging as key regulators of a growing number of normal biological process including cell differentiation and identity 253 and are differentially expressed in myelodysplastic syndrome and AML. [254][255][256][257] Recent studies have shown that lncRNAs are required for normal hematopoiesis where they regulate HSC activity and function, as well as myeloid and lymphoid differentiation. 256,258 Expression is cell type specific in human hematopoiesis, 256 and the expression of just four lncRNAs is sufficient to predict patient outcome across multiple AML cohorts.…”