Prognostic and Biologic Relevance of Clinically Applicable Long Noncoding RNA Profiling in Older Patients with Cytogenetically Normal Acute Myeloid Leukemia

The role of long noncoding RNAs in the diagnosis, prognosis and therapeutic biomarkers of acute myeloid leukemia

Acute myeloid leukemia (AML) is the abnormal proliferation of immature myeloid blast cells in the bone marrow. Currently, there are no universally recognized biomarkers for the early diagnosis, prognosis and effective treatment of AML to improve the overall survival of patients. Recent studies, however, have demonstrated that long noncoding RNAs (lncRNAs) are promising targets for the early diagnosis, prognosis and treatment of AML. A critical review of available data would be important to identify study gaps and provide perspectives. In this review, we explored comprehensive information on the potential use of lncRNAs as targets for the diagnosis, prognosis, and treatment of AML. LncRNAs are nonprotein-coding RNAs that are approximately 200 nucleotides long and play important roles in the regulation, metabolism and differentiation of tissues. In addition, they play important roles in the diagnosis, prognosis and treatment of different cancers, including AML. LncRNAs play multifaceted roles as oncogenes or tumor suppressor genes. Recently, deregulated lncRNAs were identified as novel players in the development of AML, making them promising prognostic indicators. Given that lncRNAs could have potential diagnostic marker roles, the lack of sufficient evidence identifying specific lncRNAs expressed in specific cancers hampers the use of lncRNAs as diagnostic markers of AML. The complex roles of lncRNAs in the pathophysiology of AML require further scrutiny to identify specific lncRNAs. This review, despite the lack of sufficient literature, discusses the therapeutic, diagnostic and prognostic roles of lncRNAs in AML and provides future insights that will contribute to studies targeting lncRNAs in the diagnosis, treatment, and management of AML.

Long Noncoding RNA Expression Independently Predicts Outcome in Pediatric Acute Myeloid Leukemia

PURPOSE

Optimized 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.

METHODS

To 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.

RESULTS

Training 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.

CONCLUSION

Inclusion 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.

The stem cell-specific long non-coding RNAs in leukemia

Leukemia is defined as a heterogeneous group of hematological cancers whose prevalence is on the rise worldwide. Despite the large body of studies, the etiology of leukemia has not been fully elucidated. Leukemia stem cells (LSCs) are a subpopulation of cancer cells that sustain the growth of the leukemic clone and are the main culprit for the maintenance of the neoplasm. In contrast to most leukemia cells, LSCs are resistant to chemo- and radiotherapy. Several recent studies demonstrated the altered expression profile of long non-coding RNAs (lncRNAs) in LSCs and shed light on the role of lncRNAs in the survival, proliferation, and differentiation of LSCs. LncRNAs are transcripts longer than 200 nucleotides that are implicated in several cellular and molecular processes such as gene expression, apoptosis, and carcinogenesis. Likewise, lncRNAs have shown a prognostic marker in leukemia patients and represent novel treatment options. Herein, we review the current knowledge concerning lncRNAs' implication in the pathogenesis of LSCs and discuss their prognostic, diagnostic, and therapeutic potential.

Somatic mutation-associated risk index based on lncRNA expression for predicting prognosis in acute myeloid leukemia

Objectives: Genomic instability has several implications for acute myeloid leukemia (AML) prognosis. This article aims to construct a somatic mutation-associated risk index (SMRI) of genomic instability for AML to predict prognosis and explore the potential determinants of AML prognosis.Methods: We obtained differentially expressed lncRNAs from genomic instability subtypes and selected six lncRNAs to construct the SMRI through multivariate Cox regression analysis. The median SMRI classified patients into high and low SMRI groups. Kaplan-Meier survival analysis was used to clarify the prognostic differences of SMRI subtypes. Receiver operating characteristic curve analysis was performed to elucidate the value of SMRI as a prognostic indicator. Gene set variation analysis, tumor mutation burden (TMB) analysis, immune infiltration, and immune checkpoint expression analysis were performed to investigate possible causes for the differences in prognosis of SMRI subtypes.Results: The high SMRI group exhibited a poor prognosis, which was characterized by elevated levels of TMB, mutation counts (TP53, NPM1, DNMT3A, and FLT3-TKD), CD8⁺ T cell infiltration, and immune checkpoint (PD-1, PD-L2, CTLA4, LAG3) expression. The SMRI was still associated with prognosis, even after adjustment for age, sex, cytogenetic risk, DNMT3A status, FLT3 status, and NPM1 status. Gene set variation analysis showed that AML with FLT3-ITD mutation, CEBPA mutation, and LSCs (leukemia stem cells) were enriched in the high SMRI group.Conclusion: Our research suggests that the SMRI derived from genomic instability subtypes is a useful biomarker for predicting prognosis and may be beneficial for improving the clinical outcome of patients with AML.

Gene expression signature predicts relapse in adult patients with cytogenetically normal acute myeloid leukemia

Although ∼80% of adult patients with cytogenetically normal acute myeloid leukemia (CN-AML) achieve a complete remission (CR), more than half of them relapse. Better identification of patients who are likely to relapse can help to inform clinical decisions. We performed RNA sequencing on pretreatment samples from 268 adults with de novo CN-AML who were younger than 60 years of age and achieved a CR after induction treatment with standard "7+3" chemotherapy. After filtering for genes whose expressions were associated with gene mutations known to impact outcome (ie, CEBPA, NPM1, and FLT3-internal tandem duplication [FLT3-ITD]), we identified a 10-gene signature that was strongly predictive of patient relapse (area under the receiver operating characteristics curve [AUC], 0.81). The signature consisted of 7 coding genes (GAS6, PSD3, PLCB4, DEXI, JMY, NRP1, C10orf55) and 3 long noncoding RNAs. In multivariable analysis, the 10-gene signature was strongly associated with relapse (P < .001), after adjustment for the FLT3-ITD, CEBPA, and NPM1 mutational status. Validation of the expression signature in an independent patient set from The Cancer Genome Atlas showed the signature's strong predictive value, with AUC = 0.78. Implementation of the 10-gene signature into clinical prognostic stratification could be useful for identifying patients who are likely to relapse.

Long non-coding RNAs and MYC association in hematological malignancies

Long non-coding RNAs (lncRNAs) have an established role in cell biology. Among their functions is the regulation of hematopoiesis. They characterize the different stages of hematopoiesis in a more lineage-restricted expression pattern than coding mRNAs. They affect hematopoietic stem cell renewal, proliferation, and differentiation of committed progenitors by interacting with master regulators transcription factors. Among these transcription factors, MYC has a prominent role. Similar to MYC's transcriptional activation/amplification of protein coding genes, MYC also regulates lncRNAs' expression profile, while it is also regulated by lncRNAs. Both myeloid and lymphoid malignancies are prone to the association of MYC with lncRNAs. Such interaction inhibits apoptosis, enhances cell proliferation, deregulates metabolism, and promotes genomic instability and resistance to treatment. In this review, we discuss the recent findings that encompass the crosstalk between lncRNAs and describe the pathways that very probably have a pathogenetic role in both acute and chronic hematologic malignancies.

Long Noncoding RNAs in Acute Myeloid Leukemia: Functional Characterization and Clinical Relevance

Acute Myeloid Leukemia (AML) is the most common form of leukemia in adults with an incidence of 4.3 per 100,000 cases per year. Historically, the identification of genetic alterations in AML focused on protein-coding genes to provide biomarkers and to understand the molecular complexity of AML. Despite these findings and because of the heterogeneity of this disease, questions as to the molecular mechanisms underlying AML development and progression remained unsolved. Recently, transcriptome-wide profiling approaches have uncovered a large family of long noncoding RNAs (lncRNAs). Larger than 200 nucleotides and with no apparent protein coding potential, lncRNAs could unveil a new set of players in AML development. Originally considered as dark matter, lncRNAs have critical roles to play in the different steps of gene expression and thus affect cellular homeostasis including proliferation, survival, differentiation, migration or genomic stability. Consequently, lncRNAs are found to be differentially expressed in tumors, notably in AML, and linked to the transformation of healthy cells into leukemic cells. In this review, we aim to summarize the knowledge concerning lncRNAs functions and implications in AML, with a particular emphasis on their prognostic and therapeutic potential.