Epigenetics meets genetics in acute myeloid leukemia: clinical impact of a novel seven-gene score

Identification of Novel DNA Methylation Prognostic Biomarkers for AML With Normal Cytogenetics

PURPOSE

AML is a hematologic cancer that is clinically heterogeneous, with a wide range of clinical outcomes. DNA methylation changes are a hallmark of AML but are not routinely used as a criterion for risk stratification. The aim of this study was to explore DNA methylation markers that could risk stratify patients with cytogenetically normal AML (CN-AML), currently classified as intermediate-risk.

MATERIALS AND METHODS

DNA methylation profiles in whole blood samples from 77 patients with CN-AML in The Cancer Genome Atlas (LAML cohort) were analyzed. Individual 5'-cytosine-phosphate-guanine-3' (CpG) sites were assessed for their ability to predict overall survival. The output was validated using DNA methylation profiles from bone marrow samples of 79 patients with CN-AML in a separate data set from the Gene Expression Omnibus.

RESULTS

In the training set, using DNA methylation data derived from the 450K array, we identified 2,549 CpG sites that could potentially distinguish patients with CN-AML with an adverse prognosis (intermediate-poor) from those with a more favorable prognosis (intermediate-favorable) independent of age. Of these, 25 CpGs showed consistent prognostic potential across both the 450K and 27K array platforms. In a separate validation data set, nine of these 25 CpGs exhibited statistically significant differences in 2-year survival. These nine validated CpGs formed the basis for a combined prognostic biomarker panel, which includes an 8-CpG Somatic Panel and the methylation status of cg23947872. This panel displayed strong predictive ability for 2-year survival, 2-year progression-free survival, and complete remission in the validation cohort.

CONCLUSION

This study highlights DNA methylation profiling as a promising approach to enhance risk stratification in patients with CN-AML, potentially offering a pathway to more personalized treatment strategies.

MethScore as a new comprehensive DNA methylation-based value refining the prognosis in acute myeloid leukemia

BACKGROUND

Changes in DNA methylation are common events in the pathogenesis of acute myeloid leukemia (AML) and have been repeatedly reported as associated with prognosis. However, studies integrating these numerous and potentially prognostically relevant DNA methylation changes are lacking. Therefore, we aimed for an overall evaluation of these epigenetic aberrations to provide a comprehensive NGS-based approach of DNA methylation assessment for AML prognostication.

RESULTS

We designed a sequencing panel targeting 239 regions (approx. 573 kb of total size) described in the literature as having a prognostic impact or being associated with AML pathogenesis. Diagnostic whole-blood DNA samples of adult AML patients divided into a training (n = 128) and a testing cohort (n = 50) were examined. The libraries were prepared using SeqCap Epi Enrichments System (Roche) and sequenced on MiSeq instrument (Illumina). Altogether, 1935 CpGs affecting the survival (p < 0.05) were revealed in the training cohort. A summarizing value MethScore was then calculated from these significant CpGs. Patients with lower MethScore had markedly longer overall survival (OS) and event-free survival (EFS) than those with higher MethScore (p < 0.001). The predictive ability of MethScore was verified on the independent testing cohort for OS (p = 0.01). Moreover, the proof-of-principle validation was performed using the TCGA dataset.

CONCLUSIONS

We showed that comprehensive NGS-based approach of DNA methylation assessment revealed a robust epigenetic signature relevant to AML outcome. We called this signature MethScore and showed it might serve as a strong prognostic marker able to refine survival probability of AML patients.

Preleukemic single-cell landscapes reveal mutation-specific mechanisms and gene programs predictive of AML patient outcomes

Acute myeloid leukemia (AML) and myeloid neoplasms develop through acquisition of somatic mutations that confer mutation-specific fitness advantages to hematopoietic stem and progenitor cells. However, our understanding of mutational effects remains limited to the resolution attainable within immunophenotypically and clinically accessible bulk cell populations. To decipher heterogeneous cellular fitness to preleukemic mutational perturbations, we performed single-cell RNA sequencing of eight different mouse models with driver mutations of myeloid malignancies, generating 269,048 single-cell profiles. Our analysis infers mutation-driven perturbations in cell abundance, cellular lineage fate, cellular metabolism, and gene expression at the continuous resolution, pinpointing cell populations with transcriptional alterations associated with differentiation bias. We further develop an 11-gene scoring system (Stem11) on the basis of preleukemic transcriptional signatures that predicts AML patient outcomes. Our results demonstrate that a single-cell-resolution deep characterization of preleukemic biology has the potential to enhance our understanding of AML heterogeneity and inform more effective risk stratification strategies.

Predictive value of DNA methylation patterns in AML patients treated with an azacytidine containing induction regimen

BACKGROUND

Acute myeloid leukemia (AML) is a heterogeneous disease with a poor prognosis. Dysregulation of the epigenetic machinery is a significant contributor to disease development. Some AML patients benefit from treatment with hypomethylating agents (HMAs), but no predictive biomarkers for therapy response exist. Here, we investigated whether unbiased genome-wide assessment of pre-treatment DNA-methylation profiles in AML bone marrow blasts can help to identify patients who will achieve a remission after an azacytidine-containing induction regimen.

RESULTS

A total of n = 155 patients with newly diagnosed AML treated in the AMLSG 12-09 trial were randomly assigned to a screening and a refinement and validation cohort. The cohorts were divided according to azacytidine-containing induction regimens and response status. Methylation status was assessed for 664,227 500-bp-regions using methyl-CpG immunoprecipitation-seq, resulting in 1755 differentially methylated regions (DMRs). Top regions were distilled and included genes such as WNT10A and GATA3. 80% of regions identified as a hit were represented on HumanMethlyation 450k Bead Chips. Quantitative methylation analysis confirmed 90% of these regions (36 of 40 DMRs). A classifier was trained using penalized logistic regression and fivefold cross validation containing 17 CpGs. Validation based on mass spectra generated by MALDI-TOF failed (AUC 0.59). However, discriminative ability was maintained by adding neighboring CpGs. A recomposed classifier with 12 CpGs resulted in an AUC of 0.77. When evaluated in the non-azacytidine containing group, the AUC was 0.76.

CONCLUSIONS

Our analysis evaluated the value of a whole genome methyl-CpG screening assay for the identification of informative methylation changes. We also compared the informative content and discriminatory power of regions and single CpGs for predicting response to therapy. The relevance of the identified DMRs is supported by their association with key regulatory processes of oncogenic transformation and support the idea of relevant DMRs being enriched at distinct loci rather than evenly distribution across the genome. Predictive response to therapy could be established but lacked specificity for treatment with azacytidine. Our results suggest that a predictive epigenotype carries its methylation information at a complex, genome-wide level, that is confined to regions, rather than to single CpGs. With increasing application of combinatorial regimens, response prediction may become even more complicated.

Modern Risk Stratification of Acute Myeloid Leukemia in 2023: Integrating Established and Emerging Prognostic Factors

An accurate estimation of AML prognosis is complex since it depends on patient-related factors, AML manifestations at diagnosis, and disease genetics. Furthermore, the depth of response, evaluated using the level of MRD, has been established as a strong prognostic factor in several AML subgroups. In recent years, this rapidly evolving field has made the prognostic evaluation of AML more challenging. Traditional prognostic factors, established in cohorts of patients treated with standard intensive chemotherapy, are becoming less accurate as new effective therapies are emerging. The widespread availability of next-generation sequencing platforms has improved our knowledge of AML biology and, consequently, the recent ELN 2022 recommendations significantly expanded the role of new gene mutations. However, the impact of rare co-mutational patterns remains to be fully disclosed, and large international consortia such as the HARMONY project will hopefully be instrumental to this aim. Moreover, accumulating evidence suggests that clonal architecture plays a significant prognostic role. The integration of clinical, cytogenetic, and molecular factors is essential, but hierarchical methods are reaching their limit. Thus, innovative approaches are being extensively explored, including those based on "knowledge banks". Indeed, more robust prognostic estimations can be obtained by matching each patient's genomic and clinical data with the ones derived from very large cohorts, but further improvements are needed.

Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers

Combining omics data from different layers using integrative methods provides a better understanding of the biology of a complex disease such as cancer. The discovery of biomarkers related to cancer development or prognosis helps to find more effective treatment options. This study integrates multi-omics data of different cancer types with a network-based approach to explore common gene modules among different tumors by running community detection methods on the integrated network. The common modules were evaluated by several biological metrics adapted to cancer. Then, a new prognostic scoring method was developed by weighting mRNA expression, methylation, and mutation status of genes. The survival analysis pointed out statistically significant results for GNG11, CBX2, CDKN3, ARHGEF10, CLN8, SEC61G and PTDSS1 genes. The literature search reveals that the identified biomarkers are associated with the same or different types of cancers. Our method does not only identify known cancer-specific biomarker genes, but also proposes new potential biomarkers. Thus, this study provides a rationale for identifying new gene targets and expanding treatment options across cancer types.

Downregulation of IRAIN long non-coding RNA predicts unfavourable clinical outcome in acute myeloid leukaemia patients

BACKGROUND

Although it has been shown that the long non-coding RNA (lncRNA) insulin-like growth factor type 1 receptor (IGF1R) antisense imprinted non-protein coding RNA (IRAIN) is downregulated in leukaemia cell lines, its usefulness as a prognostic marker in acute myeloid leukaemia (AML) has not yet been thoroughly investigated. Here, we sought to determine whether the expression of IRAIN is associated with clinical outcome of AML patients.

SUBJECTS & METHODS

Using quantitative real-time polymerase chain reaction (qRT-PCR), IRAIN expression levels were assessed in peripheral blood leukocyte samples from 150 patients with AML and 50 healthy controls. Analysis was done on the relationship between IRAIN expression and clinical outcomes in AML patients.

RESULTS

When compared to healthy controls, IRAIN expression was markedly reduced in AML patients (P = 0.019). IRAIN expression could distinguish French-American-British (FAB) subtypes of AML (P = 0.024). Low IRAIN expression status was associated with shorter event-free survival (EFS) in the non-t(15;17) cytogenetically abnormal AML subset (P = 0.004). IRAIN downregulation was identified as an independent adverse prognostic marker for complete remission (CR) not only in the in the non-t(15;17) cytogenetically abnormal AML subset (P = 0.006) but also in the AML-M4/M5 subgroup (P = 0.033).

CONCLUSION

Aberrantly low IRAIN expression is closely associated with lower CR rates in AML patients, particularly in non-t(15;17) cytogenetically abnormal AML and M4/M5 AML, suggesting that the determination of IRAIN expression level at diagnosis provides valuable prognostic information, serves as a promising biomarker for evaluating treatment response, and helps predicting clinical outcome of AML patients.

Early response evaluation by single cell signaling profiling in acute myeloid leukemia

Aberrant pro-survival signaling is a hallmark of cancer cells, but the response to chemotherapy is poorly understood. In this study, we investigate the initial signaling response to standard induction chemotherapy in a cohort of 32 acute myeloid leukemia (AML) patients, using 36-dimensional mass cytometry. Through supervised and unsupervised machine learning approaches, we find that reduction of extracellular-signal-regulated kinase (ERK) 1/2 and p38 mitogen-activated protein kinase (MAPK) phosphorylation in the myeloid cell compartment 24 h post-chemotherapy is a significant predictor of patient 5-year overall survival in this cohort. Validation by RNA sequencing shows induction of MAPK target gene expression in patients with high phospho-ERK1/2 24 h post-chemotherapy, while proteomics confirm an increase of the p38 prime target MAPK activated protein kinase 2 (MAPKAPK2). In this study, we demonstrate that mass cytometry can be a valuable tool for early response evaluation in AML and elucidate the potential of functional signaling analyses in precision oncology diagnostics.

An immunity and pyroptosis gene-pair signature predicts overall survival in acute myeloid leukemia

Treatment responses of patients with acute myeloid leukemia (AML) are known to be heterogeneous, posing challenges for risk scoring and treatment stratification. In this retrospective multi-cohort study, we investigated whether combining pyroptosis- and immune-related genes improves prognostic classification of AML patients. Using a robust gene pairing approach, which effectively eliminates batch effects across heterogeneous patient cohorts and transcriptomic data, we developed an immunity and pyroptosis-related prognostic (IPRP) signature that consists of 15 genes. Using 5 AML cohorts (n = 1327 patients total), we demonstrate that the IPRP score leads to more consistent and accurate survival prediction performance, compared with 10 existing signatures, and that IPRP scoring is widely applicable to various patient cohorts, treatment procedures and transcriptomic technologies. Compared to current standards for AML patient stratification, such as age or ELN2017 risk classification, we demonstrate an added prognostic value of the IPRP risk score for providing improved prediction of AML patients. Our web-tool implementation of the IPRP score and a simple 4-factor nomogram enables practical and robust risk scoring for AML patients. Even though developed for AML patients, our pan-cancer analyses demonstrate a wider application of the IPRP signature for prognostic prediction and analysis of tumor-immune interplay also in multiple solid tumors.

Comprehensive Analysis of a Ferroptosis Pattern and Associated Prognostic Signature in Acute Myeloid Leukemia

Ferroptosis is a widespread form of programmed cell death. The environment of cancer cells makes them vulnerable to ferroptosis, including AML cells, yet the specific association between ferroptosis and AML outcome is little known. In this study, we utilized ferroptosis-related genes to distinguish two subtypes in TCGA cohort, which were subsequently validated in independent AML cohorts. The subtypes were linked with tumor-related immunological abnormalities, mutation landscape and pathway dysregulation, and clinical outcome. Further, we developed a 13-gene prognostic model for AML from DEG analysis in the two subtypes. A risk score was calculated for each patient, and then the overall group was stratified into high- and low-risk groups; the higher risk score correlated with short survival. The model was validated in both independent AML cohorts and pan-cancer cohorts, which demonstrated robustness and extended the usage of the model. A nomogram was constructed that integrated risk score, FLT3-ITD, TP53, and RUNX1 mutations, and age. This model had the additional value of discriminating the sensitivity of several chemotherapeutic drugs and ferroptosis inducers in the two risk groups, which increased the translational value of this model as a potential tool in clinical management. Through integrated analysis of ferroptosis pattern and its related model, our work shed new light on the relationship between ferroptosis and AML, which may facilitate clinical application and therapeutics.

A 29-gene signature associated with NOX2 discriminates acute myeloid leukemia prognosis and survival

The molecular complexity displayed in acute myeloid leukemia (AML) hinders patient stratification and treatment decisions. Previous studies support the utility of using specific gene panels for this purpose. Focusing on two salient features of AML, the production of reactive oxygen species (ROS) by NADPH oxidases (NOX) and metabolism, we aimed to identify a gene panel that could improve patient stratification. A pairwise comparison of AML versus healthy gene expression revealed the downregulation of four members of the NOX2 complex including CYBB (coding for NOX2) in AML patients. We analyzed the expression of 941 genes related to metabolism and found 28 genes with expression correlated to CYBB. This panel of 29 genes (29G) effectively divides AML samples according to their prognostic group. The robustness of 29G was confirmed by 6 AML cohort datasets with a total of 1821 patients (overall accuracies of 85%, 78%, 80%, 75%, 59% and 83%). An expression index (EI) was developed according to the expression of the selected discriminatory genes. Overall Survival (OS) was higher for low 29G expression index patients than for the high 29G expression index group, which was confirmed in three different datasets with a total of 1069 patients. Moreover, 29G can dissect intermediate‐prognosis patients in four clusters with different OS, which could improve the current AML stratification scheme. In summary, we have found a gene signature (29G) that can be used for AML classification and for OS prediction. Our results confirm NOX and metabolism as suitable therapeutic targets in AML.

A validation study of potential prognostic DNA methylation biomarkers in patients with acute myeloid leukemia using a custom DNA methylation sequencing panel

BACKGROUND

Multiple studies have reported the prognostic impact of DNA methylation changes in acute myeloid leukemia (AML). However, these epigenetic markers have not been thoroughly validated and therefore are still not considered in clinical practice. Hence, we aimed to independently verify results of selected studies describing the relationship between DNA methylation of specific genes and their prognostic potential in predicting overall survival (OS) and event-free survival (EFS).

RESULTS

Fourteen studies (published 2011-2019) comprising of 27 genes were subjected to validation by a custom NGS-based sequencing panel in 178 newly diagnosed non-M3 AML patients treated by 3 + 7 induction regimen. The results were considered as successfully validated, if both the log-rank test and multivariate Cox regression analysis had a p-value ≤ 0.05. The predictive role of DNA methylation was confirmed for three studies comprising of four genes: CEBPA (OS: p = 0.02; EFS: p = 0.03), PBX3 (EFS: p = 0.01), LZTS2 (OS: p = 0.05; EFS: p = 0.0003), and NR6A1 (OS: p = 0.004; EFS: p = 0.0003). For all of these genes, higher methylation was an indicator of longer survival. Concurrent higher methylation of both LZTS2 and NR6A1 was highly significant for survival in cytogenetically normal (CN) AML group (OS: p < 0.0001; EFS: p < 0.0001) as well as for the whole AML cohort (OS: p = 0.01; EFS < 0.0001). In contrast, for two studies reporting the poor prognostic effect of higher GPX3 and DLX4 methylation, we found the exact opposite, again linking higher GPX3 (OS: p = 0.006; EFS: p < 0.0001) and DLX4 (OS: p = 0.03; EFS = 0.03) methylation to a favorable treatment outcome. Individual gene significance levels refer to the outcomes of multivariate Cox regression analysis.

CONCLUSIONS

Out of twenty-seven genes subjected to DNA methylation validation, a prognostic role was observed for six genes. Therefore, independent validation studies are necessary to reveal truly prognostic DNA methylation changes and to enable the introduction of these promising epigenetic markers into clinical practice.

Clinical and molecular relevance of genetic variants in the non-coding transcriptome of patients with cytogenetically normal acute myeloid leukemia

Expression levels of long non-coding RNA (lncRNA) have been shown to associate with clinical outcome of patients with cytogenetically normal acute myeloid leukemia (CN-AML). However, the frequency and clinical significance of genetic variants in the nucleotide sequences of lncRNA in AML patients is unknown. Herein, we analyzed total RNA sequencing data of 377 younger adults (aged <60 years) with CN-AML, who were comprehensively characterized with regard to clinical outcome. We used available genomic databases and stringent filters to annotate genetic variants unequivocally located in the non-coding transcriptome of AML patients. We detected 981 variants, which are recurrently present in lncRNA that are expressed in leukemic blasts. Among these variants, we identified a cytosine-to-thymidine variant in the lncRNA RP5-1074L1.4 and a cytosine-to-thymidine variant in the lncRNA SNHG15, which independently associated with longer survival of CN-AML patients. The presence of the SNHG15 cytosine-to-thymidine variant was also found to associate with better outcome in an independent dataset of CN-AML patients, despite differences in treatment protocols and RNA sequencing techniques. In order to gain biological insights, we cloned and overexpressed both wild-type and variant versions of the SNHG15 lncRNA. In keeping with its negative prognostic impact, overexpression of the wild-type SNHG15 associated with higher proliferation rate of leukemic blasts when compared with the cytosine-to-thymidine variant. We conclude that recurrent genetic variants of lncRNA that are expressed in the leukemic blasts of CN-AML patients have prognostic and potential biological significance.

Independent component analysis based gene co-expression network inference (ICAnet) to decipher functional modules for better single-cell clustering and batch integration

With the tremendous increase of publicly available single-cell RNA-sequencing (scRNA-seq) datasets, bioinformatics methods based on gene co-expression network are becoming efficient tools for analyzing scRNA-seq data, improving cell type prediction accuracy and in turn facilitating biological discovery. However, the current methods are mainly based on overall co-expression correlation and overlook co-expression that exists in only a subset of cells, thus fail to discover certain rare cell types and sensitive to batch effect. Here, we developed independent component analysis-based gene co-expression network inference (ICAnet) that decomposed scRNA-seq data into a series of independent gene expression components and inferred co-expression modules, which improved cell clustering and rare cell-type discovery. ICAnet showed efficient performance for cell clustering and batch integration using scRNA-seq datasets spanning multiple cells/tissues/donors/library types. It works stably on datasets produced by different library construction strategies and with different sequencing depths and cell numbers. We demonstrated the capability of ICAnet to discover rare cell types in multiple independent scRNA-seq datasets from different sources. Importantly, the identified modules activated in acute myeloid leukemia scRNA-seq datasets have the potential to serve as new diagnostic markers. Thus, ICAnet is a competitive tool for cell clustering and biological interpretations of single-cell RNA-seq data analysis.

Expression and prognostic relevance of long noncoding RNAs CRNDE and AOX2P in adult acute myeloid leukemia

INTRODUCTION

Several long noncoding RNAs (lncRNAs) have been demonstrated to play a critical role in the tumorigenesis of acute myeloid leukemia (AML), and altered expression of certain lncRNAs has been recognized as a potential prognostic marker in AML patients. Here, we sought to determine whether the expression of the lncRNA colorectal neoplasia differentially expressed (CRNDE) and aldehyde oxidase 2 pseudogene (AOX2P) is associated with clinicopathological features and clinical outcome of patients with AML.

METHODS

CRNDE and AOX2P expression levels were measured in diagnostic blood samples from 200 adult patients with de novo AML, along with 50 healthy control blood samples, using quantitative real-time polymerase chain reaction (qRT-PCR). The association of CRNDE and AOX2P expression with the clinicopathological characteristics and outcome of AML patients was analyzed.

RESULTS

Upregulated CRNDE expression was independently associated with lower complete remission (CR) rates in the whole cohort of AML (P < .001). AOX2P overexpression was identified as an independent adverse prognostic marker for CR in the CN-AML (P = .009) and non-t (15;17) AML (P < .001) subgroups. Patients with high CRNDE expression had a significantly shorter event-free survival (EFS, whole cohort of AML: P = .017; CN-AML: P = .001; non-t (15;17) AML: P = .006) and inferior overall survival (OS, whole cohort of AML: P = .002; t(15;17) AML: P = .001) than those with low CRNDE expression. EFS and OS did not differ significantly between patients with high AOX2P expression and those with low expression.

CONCLUSION

Aberrantly upregulated CRNDE expression and, to a lesser extent, AOX2P overexpression, are associated with poor prognosis in AML patients, suggesting that the determination of CRNDE and, perhaps, AOX2P, expression level at diagnosis provides valuable prognostic information, allows refinement of risk stratification, and helps clinical decision-making in AML.

A clinical prediction model identifies a subgroup with inferior survival within intermediate risk acute myeloid leukemia

Intermediate risk acute myeloid leukemia (AML) comprises around 50% of AML patients and is featured with heterogeneous clinical outcomes. The study aimed to generate a prediction model to identify intermediate risk AML patients with an inferior survival. We performed targeted next generation sequencing analysis for 121 patients with 2017 European LeukemiaNet-defined intermediate risk AML, revealing 122 mutated genes, with 24 genes mutated in > 10% of patients. A prognostic nomogram characterized by white blood cell count ≥10×10⁹/L at diagnosis, mutated DNMT3A and genes involved in signaling pathways was developed for 110 patients who were with clinical outcomes. Two subgroups were identified: intermediate low risk (ILR; 43.6%, 48/110) and intermediate high risk (IHR; 56.4%, 62/110). The model was prognostic of overall survival (OS) and relapse-free survival (RFS) (OS: Concordance index [C-index]: 0.703, 95%CI: 0.643-0.763; RFS: C-index: 0.681, 95%CI 0.620-0.741), and was successfully validated with two independent cohorts. Allogeneic hematopoietic stem cell transplantation (alloHSCT) reduced the relapse risk of IHR patients (3-year RFS: alloHSCT: 40.0±12.8% vs. chemotherapy: 8.6±5.8%, P= 0.010). The prediction model can help identify patients with an unfavorable prognosis and refine risk-adapted therapy for intermediate risk AML patients.

Prognostic Prediction of Cytogenetically Normal Acute Myeloid Leukemia Based on a Gene Expression Model

Acute myeloid leukemia (AML) refers to a heterogeneous group of hematopoietic malignancies. The well-known European Leukemia Network (ELN) stratifies AML patients into three risk groups, based primarily on the detection of cytogenetic abnormalities. However, the prognosis of cytogenetically normal AML (CN-AML), which is the largest AML subset, can be hard to define. Moreover, the clinical outcomes associated with this subgroup are diverse. In this study, using transcriptome profiles collected from CN-AML patients in the BeatAML cohort, we constructed a robust prognostic Cox model named NEST (Nine-gEne SignaTure). The validity of NEST was confirmed in four external independent cohorts. Moreover, the risk score predicted by the NEST model remained an independent prognostic factor in multivariate analyses. Further analysis revealed that the NEST model was suitable for bone marrow mononuclear cell (BMMC) samples but not peripheral blood mononuclear cell (PBMC) samples, which indirectly indicated subtle differences between BMMCs and PBMCs. Our data demonstrated the robustness and accuracy of the NEST model and implied the importance of the immune dysfunction in the leukemogenesis that occurs in CN-AML, which shed new light on the further exploration of molecular mechanisms and treatment guidance for CN-AML.

Gene expression changes contribute to stemness and therapy resistance of relapsed acute myeloid leukemia: roles of SOCS2, CALCRL, MTSS1, and KDM6A

Relapse is associated with therapy resistance and is a major cause of death in acute myeloid leukemia (AML). It is thought to result from the accretion of therapy-refractory leukemic stem cells. Genetic and transcriptional changes that are recurrently gained at relapse are likely to contribute to the increased stemness and decreased therapy responsiveness at this disease stage. Despite the recent approval of several targeted drugs, chemotherapy with cytosine arabinoside and anthracyclines is still the mainstay of AML therapy. Accordingly, a number of studies have investigated genetic and gene expression changes between diagnosis and relapse of patients subjected to such treatment. Genetic alterations recurrently acquired at relapse were identified, but were restricted to small proportions of patients, and their functional characterization is still largely pending. In contrast, the expression of a substantial number of genes was altered consistently between diagnosis and recurrence of AML. Recent studies corroborated the roles of the upregulation of SOCS2 and CALCRL and of the downregulation of MTSS1 and KDM6A in therapy resistance and/or stemness of AML. These findings spur the assumption that functional investigations of genes consistently altered at recurrence of AML have the potential to promote the development of novel targeted drugs that may help to improve the outcome of this currently often fatal disease.

AML displays increased CTCF occupancy associated with aberrant gene expression and transcription factor binding

CCTC-binding factor (CTCF) is a key regulator of gene expression through organization of the chromatin structure. Still, it is unclear how CTCF binding is perturbed in leukemia or in cancer in general. We studied CTCF binding by chromatin immunoprecipitation sequencing in cells from patients with acute myeloid leukemia (AML) and in normal bone marrow (NBM) in the context of gene expression, DNA methylation, and azacitidine exposure. CTCF binding was increased in AML compared with NBM. Aberrant CTCF binding was enriched for motifs for key myeloid transcription factors such as CEBPA, PU.1, and RUNX1. AML with TET2 mutations was characterized by a particularly strong gain of CTCF binding, highly enriched for gain in promoter regions, while AML in general was enriched for changes at enhancers. There was a strong anticorrelation between CTCF binding and DNA methylation. Gain of CTCF occupancy was associated with increased gene expression; however, the genomic location (promoter vs distal regions) and enrichment of motifs (for repressing vs activating cofactors) were decisive for the gene expression pattern. Knockdown of CTCF in K562 cells caused loss of CTCF binding and transcriptional repression of genes with changed CTCF binding in AML, as well as loss of RUNX1 binding at RUNX1/CTCF-binding sites. In addition, CTCF knockdown caused increased differentiation. Azacitidine exposure caused major changes in CTCF occupancy in AML patient cells, partly by restoring a CTCF-binding pattern similar to NBM. We conclude that AML displays an aberrant increase in CTCF occupancy that targets key genes for AML development and impacts gene expression.

Development and validation of a prognostic model for adult patients with acute myeloid leukaemia

Background

The high heterogeneity of acute myeloid leukaemia (AML) reflected in the patient- and disease-related factors accounts for the unsatisfactory prognosis despite the introduction of novel therapeutic approaches and drugs in recent years.

Methods

In the development set (n = 412), parameters including age, hematopoietic cell transplantation-comorbidity index, white blood cell count, hemoglobin, biallelic CEBPA mutations, DNMT3A mutations, FLT3-ITD/NPM1 status, and ELN cytogenetic risk status were identified as independent prognostic factors for overall survival (OS) in the multivariable Cox regression analysis. A nomogram combining these predictors for individual risk estimation was established thereby.

Findings

The prognostic model demonstrated promising performance in the development cohort. The calibration plot, C-index (0.74), along with the 1-, 2- and 3-year area under the receiver operating characteristic curve (AUC, 0.76, 0.79, and 0.74, respectively) in the validation set (n = 238) substantiated the robustness of the model. In addition to stratifying young (age ≤ 60 years) and elderly patients (age > 60 years) into three and two risk groups with significant distinct outcomes, the prognostic model succeeded in distinguishing eligible candidates for hematopoietic stem cell transplantation.

Interpretation

The prognostic model is capable of survival prediction, risk stratification and helping with therapeutic decision-making with the use of easily acquired variables in daily clinical routine.

Funding

This work was supported in part by grants from the National Natural Science Foundation of China (81770141), the National Key R&D Program of China (2016YFE0202800), and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (20161406).

Distinct clinical and biological characteristics of acute myeloid leukemia with higher expression of long noncoding RNA KIAA0125

Expression of long non-coding RNA KIAA0125 has been incorporated in various gene expression signatures for prognostic prediction in acute myeloid leukemia (AML) patients, yet its functions and clinical significance remain unclear. This study aimed to investigate the clinical and biological characteristics of AML bearing different levels of KIAA0125. We profiled KIAA0125 expression levels in bone marrow cells from 347 de novo AML patients and found higher KIAA0125 expression was closely associated with RUNX1 mutation, but inversely correlated with t(8;21) and t(15;17) karyotypes. Among the 227 patients who received standard chemotherapy, those with higher KIAA0125 expression had a lower complete remission rate, shorter overall survival (OS) and disease-free survival (DFS) than those with lower expression. The prognostic significance was validated in both TCGA and GSE12417 cohorts. Subgroup analyses showed that higher KIAA0125 expression also predicted shorter DFS and OS in patients with normal karyotype or non-M3 AML. In multivariable analysis, higher KIAA0125 expression remained an adverse risk factor independent of age, WBC counts, karyotypes, and mutation patterns. Bioinformatics analyses revealed that higher KIAA0125 expression was associated with hematopoietic and leukemic stem cell signatures and ATP-binding cassette transporters, two predisposing factors for chemoresistance.

DNA Methylation Clusters and Their Relation to Cytogenetic Features in Pediatric AML

Acute Myeloid Leukemia (AML) is characterized by recurrent genetic and cytogenetic lesions that are utilized for risk stratification and for making treatment decisions. In recent years, methylation dysregulation has been extensively studied and associated with risk groups and prognosis in adult AML, however, such studies in pediatric AML are limited. Moreover, the mutations in epigenetic genes such as DNMT3A, IDH1 or IDH2 are almost absent or rare in pediatric patients as compared to their abundance in adult AML. In the current study, we evaluated methylation patterns that occur with or independent of the well-defined cytogenetic features in pediatric AML patients enrolled on multi-site AML02 clinical trial (NCT00136084). Our results demonstrate that unlike adult AML, cytosine DNA methylation does not result in significant unique clusters in pediatric AML, however, DNA methylation signatures correlated significantly with the most common and recurrent cytogenetic features. Paired evaluation of DNA methylation and expression identified genes and pathways of biological relevance that hold promise for novel therapeutic strategies. Our results further demonstrate that epigenetic signatures occur complimentary to the well-established chromosomal/mutational landscape, implying that dysregulation of oncogenes or tumor suppressors might be leveraging both genetic and epigenetic mechanisms to impact biological pathways critical for leukemogenesis.

Effects of Alternative Splicing Events on Acute Myeloid Leukemia

As suggested by an increasing amount of evidence, there is alternative splicing (AS) modification within malignancy, which is related to cancer occurrence and development. AS within acute myeloid leukemia (AML) has not yet been systematically analyzed yet. This study analyzed the transcriptomic profiling and corresponding clinical data from AML cases based on The Cancer Genome Atlas (TCGA). In addition, the prediction model, along with the splicing network, was used to analyze the prognosis for AML patients according to the seven different AS event types. Among the 34,984 AS events across the 8830 genes, 2896 AS events were detected among 1905 genes, showing marked correlation with the overall survival of patients. The risk scoring model based on all AS event types was the most efficient in identifying the prognosis for AML patients. Meanwhile, the area under the curve at 1-, 3-, 5-year were 0.852, 0.935, 0.955, respectively. At the same time, the splicing regulating network, which was constituted by 21 splicing factor genes as well as 32 AS events related to survival, was characterized. In conclusion, our predictive model constructed based on the AS events accurately predicts the survival for AML patients. In addition, the network between AS events and splicing factor is established, which may serve as a potential mechanism.

BARMR1/FAM92A1, a novel gene encoding BAR domain protein with multi-functions

BARMR1/FAM92A1 encodes a novel BAR domain protein, and is widely expressed during embryonic development and highly expressed in tumor cells. Mutation or deletion of BARMR1/FAM92A1 caused developmental disorder and the BARMR1/FAM92A1 overexpression in tumor cells is associated with poor prognosis. The subcellular location of BARMR1/FAM92A1 determined its biological functions by interacting with different proteins. When colocalized and interacted with CBY at the centrioles/basal bodies of primary cilia, BARMR1/FAM92A1 facilitate ciliogenesis, whilst binded to GAL1 in the nuclei, it promotes cell proliferation, migration, and malignancy of tumor cells.

Prognostic alternative mRNA splicing signatures and associated splicing factors in acute myeloid leukemia

The dysregulation of alternative splicing (AS) has emerged as a mechanism of acute myeloid leukemia (AML). However, the prognostic impact of AS events remains under-explored in AML. Here we report the prognostic value of AS events and associated splicing factors based on three datasets of AML patients. We defined the landscape of AS events in AML and identified 7033 AS events associated with the survival of AML patients. Based on these events, we further developed a composite 15 AS event-based prognostic signature, which was independent of the cytogenetic risk stratification and patient age, and showed a better performance than known gene expression signatures. More importantly, our new signature markedly improved the European LeukemiaNet (ELN) risk classification, indicating a broad applicability in the clinical management of AML. Furthermore, the splicing-regulatory network established the correlations between prognostic AS events and associated splicing factors. The finding was validated by CRISPR-based data, which indicated that the increased expression of RBM39 contributed to the higher exon inclusion of SETD5 and conferred a poor outcome. Together, AS events may serve as a novel assortment of prognosticators for AML and could refine the ELN risk stratification. The splicing regulatory network provides clues regarding the splicing factor-mediated mechanisms of AML.

Acidic leucine-rich nuclear phosphoprotein-32A expression contributes to adverse outcome in acute myeloid leukemia

Background

Acidic leucine-rich nuclear phosphoprotein-32A (ANP32A) is a novel regulator of histone H3 acetylation and promotes leukemogenesis in acute myeloid leukemia (AML). However, its prognostic value in AML remains unclear.

Methods

In this study, we evaluated the prognostic significance of ANP32A expression using two independent large cohorts of cytogenetically normal AML (CN-AML) patients. Multivariable analysis in CN-AML group was also presented. Based on the ANP32A expression, its related genes, dysregulation of pathways, interaction network analysis between microRNAs and target genes, as well as methylation analysis were performed to unveil the complex functions behind ANP32A.

Results

Here we demonstrated overexpression of ANP32A was notably associated with unfavorable outcome in two independent cohorts of CN-AML patients (OS: P=0.012, EFS: P=0.005, n=185; OS: P=0.041, n=232), as well as in European Leukemia Net (ELN) Intermediate-I group (OS: P=0.018, EFS: P=0.045, n=115), National Comprehensive Cancer Network (NCCN) Intermediate Risk AML group (OS: P=0.048, EFS: P=0.039, n=225), and non-M3 AML group (OS: P=0.034, EFS: P=0.011, n=435). Multivariable analysis further validated ANP32A as a high-risk factor in CN-AML group. Multi-omics analysis presented overexpression of ANP32A was associated with aberrant expression of oncogenes and tumor suppressor, up/down-regulation of metabolic and immune-related pathways, dysregulation of microRNAs, and hypomethylation on CpG island and 1st Exon regions.

Conclusions

We proved ANP32A as a novel, potential unfavorable prognosticator and therapeutic target for AML.

Genome-wide identification of FHL1 as a powerful prognostic candidate and potential therapeutic target in acute myeloid leukaemia

Background

Acute myeloid leukaemia (AML) is a malignant haematological tumour with high heterogeneity and mortality. A reliable prognostic assessment is critical for treatment strategies. However, the current prognostic evaluation system of AML is insufficient.

Methods

Genome-wide univariate Cox regression analysis was performed on three independent AML datasets to screen for the prognostic-related genes. Kaplan–Meier survival analysis was employed to verify the efficacy of FHL1 in evaluating overall survival in 1298 de novo AML patients, 648 non-acute promyelocytic leukaemia AML patients and 407 cytogenetically normal AML patients; the data for some of these patients were also used for EFS and RFS validation. Multivariate Cox regression was performed to validate FHL1 as an independent prognostic indicator. WGCNA, GSEA, and gene correlation analysis were applied to explore the mechanism of FHL1 in AML. The synergistic cytocidal effect of FHL1 knockdown was verified in in vitro experiments.

Findings

Comprehensive genome-wide analyses and large-sample validation showed that FHL1 is a powerful prognostic candidate for overall survival, event-free survival, and relapse-free survival in AML and is independent of prognosis-related clinical factors and genetic abnormalities. The molecular mechanism may occur through regulation of FHL1 in leukaemia stem cells, tumour-associated signalling pathways, and transmembrane transport of chemotherapeutic drugs. FHL1-targeted intervention enhances the sensitivity of AML cells to cytarabine.

Interpretation

FHL1 may serve as an evaluation factor for clinical strategy selection, and its targeted intervention may be beneficial for chemotherapy in AML patients.

Von Willebrand factor A domain-containing protein 8 (VWA8) localizes to the matrix side of the inner mitochondrial membrane

VWA8 is a poorly characterized mitochondrial AAA + ATPase protein. The specific submitochondrial localization of VWA8 remains unclear. The purpose of this study was to determine the specific submitochondrial compartment within which VWA8 resides in order to provide more insight into the function of this protein. Bioinformatics analysis showed that VWA8 has a 34 amino acid N-terminal Matrix-Targeting Signal (MTS) that is similar to those in proteins known to localize to the mitochondrial matrix. Experiments in C2C12 mouse myoblasts using confocal microscopy showed that deletion of the VWA8 MTS (vMTS) resulted in cytosolic, rather than mitochondrial, localization of VWA8. Biochemical analysis using differential sub-fractionation of mitochondria isolated from rat liver showed that VWA8 localizes to the matrix side of inner mitochondrial membrane, similar to the inner mitochondrial membrane protein Electron Transfer Flavoprotein-ubiquinone Oxidoreductase (ETFDH). The results of these experiments show that the vMTS is essential for localization to the mitochondrial matrix and that once there, VWA8 localizes to the matrix side of inner mitochondrial membrane.

A 6-Membrane Protein Gene score for prognostic prediction of cytogenetically normal acute myeloid leukemia in multiple cohorts

Background: Cytogenetically normal acute myeloid leukemia (CN-AML) is a large proportion of AMLs with diverse prognostic outcomes. Identifying membrane protein genes as prognostic factors to stratify CN-AML patients will be critical to improve their outcomes.

Purpose: This study aims to identify prognostic factors to stratify CN-AML patients to choose better treatments and improve their outcomes.

Methods: CN-AML data were from TCGA cohort (n = 79) and four GEO datasets. We identified independent prognostic genes by Cox regression and Kaplan-Meier methods, and constructed linear regression model using LASSO algorithm. The prediction error curve was calculated using R package “pec”.

Results: Based on independent prognostic membrane genes, we constructed a regression model for CN-AML prognosis prediction: score = (0.0492 * CD52) - (0.0018 * CD96) + (0.0131 * EMP1) + (0.2058 * TSPAN2) + (0.0234 * STAB1) - (0.3658 * MBTPS1), which was named as MPG6 (6-Membrane Protein Gene) score. Tested in multiple CN-AML datasets, consistent results showed that CN-AML patients with high MPG6 score had poor survival, higher WBC count and shorter EFS. Comparing with other reported scoring models, the benchmark result of MPG6 achieved better association with survival in multiple cohorts. Moreover, by combining with other clinical indicators in CN-AML, MPG6 could improve the performance of survival prediction and serve as a robust prognostic factor.

Conclusions: We identified the MPG6 score as a stable indicator with great potential for clinical application in risk stratification and outcome prediction in CN-AML.

MIR155HG Knockdown Inhibited the Progression of Cervical Cancer by Binding SRSF1

BACKGROUND

As the fourth most common cancer among women worldwide, cervical cancer lead to 311,000 deaths in 2018. Although the treatments have been developed, the survival rate of cervical cancer remains unsatisfactory. In this study, we aimed to identify differentially expressed lncRNAs (DEIncRNAs) between cervical cancer and adjacent normal tissues using bioinformatics analysis, and further to investigate the biological function of the DEIncRNAs in vitro and in vivo.

METHODS

The expression profiles from two microarray datasets (GSE6791 and GSE63514) were downloaded from GEO for analysis of DEIncRNAs between cervical cancer and adjacent normal cervical tissues. Among all DEIncRNAs, MIR155HG upregulation was identified and selected for further investigation. The effect of MIR155HG knockdown on proliferation, apoptosis and invasion in SiHa and Hela cells were evaluated. In addition, Western blot, RNA immunoprecipitation (RIP) and cell cycle assays were performed to determine the binding target of MIR155HG. Furthermore, the effect of MIR155HG knockdown on tumor growth in vivo was investigated.

RESULTS

The level of MIR155HG was found to be significantly upregulated in cervical cancer tissue compared with adjacent cervical tissue. Knockdown of MIR155HG notably inhibited the proliferation of SiHa and Hela cells by inducing apoptosis. In addition, MIR155HG knockdown decreased cell invasion. Moreover, tumor growth in xenograft was significantly inhibited by MIR155HG knockdown in vivo. Additionally, SRSF1 was identified as the binding protein of MIR155HG.

CONCLUSION

Our findings demonstrated that MIR155HG knockdown inhibited the progression of cervical cancer by binding SRSF1, inspiring the usage of MIR155HG as a potential novel therapy target for the treatment of cervical cancer.

Lineage tracing of acute myeloid leukemia reveals the impact of hypomethylating agents on chemoresistance selection

Chemotherapy-resistant cancer recurrence is a major cause of mortality. In acute myeloid leukemia (AML), chemorefractory relapses result from the complex interplay between altered genetic, epigenetic and transcriptional states in leukemic cells. Here, we develop an experimental model system using in vitro lineage tracing coupled with exome, transcriptome and in vivo functional readouts to assess the AML population dynamics and associated molecular determinants underpinning chemoresistance development. We find that combining standard chemotherapeutic regimens with low doses of DNA methyltransferase inhibitors (DNMTi, hypomethylating drugs) prevents chemoresistant relapses. Mechanistically, DNMTi suppresses the outgrowth of a pre-determined set of chemoresistant AML clones with stemness properties, instead favoring the expansion of rarer and unfit chemosensitive clones. Importantly, we confirm the capacity of DNMTi combination to suppress stemness-dependent chemoresistance development in xenotransplantation models and primary AML patient samples. Together, these results support the potential of DNMTi combination treatment to circumvent the development of chemorefractory AML relapses.

The development of post-chemotherapy resistance is a significant issue in the management of AML. Here, Caiado et al. suggest that the issue might be circumvented via upfront combination with hypomethylating agents that shape the clonal dynamics and transcriptional landscape of relapsing AML

Development and Validation of a Novel RNA Sequencing-Based Prognostic Score for Acute Myeloid Leukemia

Background

Recent progress in sequencing technologies allows us to explore comprehensive genomic and transcriptomic information to improve the current European LeukemiaNet (ELN) system of acute myeloid leukemia (AML).

Methods

We compared the prognostic value of traditional demographic and cytogenetic risk factors, genomic data in the form of somatic aberrations of 25 AML-relevant genes, and whole-transcriptome expression profiling (RNA sequencing) in 267 intensively treated AML patients (Clinseq-AML). Multivariable penalized Cox models (overall survival [OS]) were developed for each data modality (clinical, genomic, transcriptomic), together with an associated prognostic risk score.

Results

Of the three data modalities, transcriptomic data provided the best prognostic value, with an integrated area under the curve (iAUC) of a time-dependent receiver operating characteristic (ROC) curve of 0.73. We developed a prognostic risk score (Clinseq-G) from transcriptomic data, which was validated in the independent The Cancer Genome Atlas AML cohort (RNA sequencing, n = 142, iAUC = 0.73, comparing the high-risk group with the low-risk group, hazard ratio [HR]_OS = 2.42, 95% confidence interval [CI] = 1.51 to 3.88). Comparison between Clinseq-G and ELN score iAUC estimates indicated strong evidence in favor of the Clinseq-G model (Bayes factor = 26.78). The proposed model remained statistically significant in multivariable analysis including the ELN and other well-known risk factors (HR_os = 2.34, 95% CI = 1.30 to 4.22). We further validated the Clinseq-G model in a second independent data set (n = 458, iAUC = 0.66, adjusted HR_OS = 2.02, 95% CI = 1.33 to 3.08; adjusted HR_EFS = 2.10, 95% CI = 1.42 to 3.12).

Conclusions

Our results indicate that the Clinseq-G prediction model, based on transcriptomic data from RNA sequencing, outperforms traditional clinical parameters and previously reported models based on genomic biomarkers.

Methylation and transcriptome analysis reveal lung adenocarcinoma-specific diagnostic biomarkers

Background

DNA methylation can regulate the role of long noncoding RNAs (lncRNAs) in the development of lung adenocarcinoma (LUAD). The present study aimed to identify methylation-driven lncRNAs and mRNAs as biomarkers in the prognosis of LUAD using bioinformatics analysis.

Methods

Differentially expressed RNAs were obtained using the edge R package from 535 LUAD tissues and 59 adjacent non-LUAD tissues. Differentially methylated genes were obtained using the limma R package from 475 LUAD tissues and 32 adjacent non-LUAD tissues. Methylation-driven mRNA and lncRNA were obtained using the MethylMix R package from 465 LUAD tissues with matched DNA methylation and RNA expression and 32 non-LUAD tissues with DNA methylation. Gene ontology and ConsensusPathDB pathway analysis were performed to identify functional enrichment of methylation-driven mRNAs. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of each variable for predicting the prognosis of LUAD. Kaplan–Meier curve analysis of DNA methylation and gene expression might provide potential prognostic biomarkers for LUAD patients.

Results

A total of 99 methylation-driven mRNAs and 17 methylation-driven lncRNAs were obtained. Univariate and multivariate Cox regression analysis showed that 6 lncRNAs (FOXE1, HOXB13-AS1_2, VMO1, HIST1H3F, AJ003147.8, ASXL3) were retrieved to construct a predictive model associated with overall survival in LUAD patients. Combined DNA methylation and gene expression survival analysis revealed that 4 lncRNAs (AC023824.1, AF186192.1, LINC01354 and WASIR2) and 8 mRNAs (S1PR1, CCDC181, F2RL1, EFS, KLHDC9, MPV17L, GKN2, ITPRIPL1) might act as independent biomarkers for the prognosis of LUAD.

Conclusions

Methylation-driven lncRNA and mRNA contribute to the survival of LUAD, and 4 lncRNAs and 8 mRNAs might be potential biomarkers for the prognosis of LUAD.

Aberrant DNA Methylation in Acute Myeloid Leukemia and Its Clinical Implications

Acute myeloid leukemia (AML) is a heterogeneous disease that is characterized by distinct cytogenetic or genetic abnormalities. Recent discoveries in cancer epigenetics demonstrated a critical role of epigenetic dysregulation in AML pathogenesis. Unlike genetic alterations, the reversible nature of epigenetic modifications is therapeutically attractive in cancer therapy. DNA methylation is an epigenetic modification that regulates gene expression and plays a pivotal role in mammalian development including hematopoiesis. DNA methyltransferases (DNMTs) and Ten-eleven-translocation (TET) dioxygenases are responsible for the dynamics of DNA methylation. Genetic alterations of DNMTs or TETs disrupt normal hematopoiesis and subsequently result in hematological malignancies. Emerging evidence reveals that the dysregulation of DNA methylation is a key event for AML initiation and progression. Importantly, aberrant DNA methylation is regarded as a hallmark of AML, which is heralded as a powerful epigenetic marker in early diagnosis, prognostic prediction, and therapeutic decision-making. In this review, we summarize the current knowledge of DNA methylation in normal hematopoiesis and AML pathogenesis. We also discuss the clinical implications of DNA methylation and the current therapeutic strategies of targeting DNA methylation in AML therapy.

Nuclear FAM289-Galectin-1 interaction controls FAM289-mediated tumor promotion in malignant glioma

Background

FAM92A1–289(abbreviated FAM289) is recognized as one of the newly-discovered putative oncogenes. However, its role and molecular mechanisms in promoting cancer progression has not yet been elucidated. This study was performed to reveal its oncogenic functions and molecular mechanisms in human glioblastoma multiforme (GBM) cell models with knockdown or overexpression of FAM289 in vitro and in vivo.

Methods

To elucidate the molecular mechanisms underlying FAM289-mediated tumor progression, the protein-protein interaction between FAM289 and Galectin-1 was verified by co-immunoprecipitation, followed by an analysis of the expression and activity of Galectin-1-associated signaling molecules. Knockdown and overexpression of FAM289 in glioma cells were applied for investigating the effects of FAM289 on cell growth, migration and invasion. The determination of FAM289 expression was performed in specimens from various stages of human gliomas.

Results

FAM289-galectin-1 interaction and concomitant activation of the extracellular signal-regulated kinase (ERK) pathway participated in FAM289-mediated tumor-promoting function. Since the expression of DNA methyl transferase 1 (DNMT1) and DNA methyl transferase 3B (DNMT3B) was regulated by FAM289 in U251 and U87-MG glioma cells, Galectin-1 interaction with FAM289 may promote FAM289 protein into the cell nucleus and activate the ERK pathway, thereby upregulating DNMTs expression. Drug resistance tests indicated that FAM289-mediated TMZ resistance was through stem-like property acquisition by activating the ERK pathway. The correlation between FAM289, Galectin-1 expression and the clinical stage of gliomas was also verified in tissue samples from glioblastoma patients.

Conclusions

Our results suggest that high expression of FAM289 in GBM tissues correlated with poor prognosis. FAM289 contributes to tumor progression in malignant glioma by interacting with Galectin-1 thereby promoting FAM289 protein translocation into the cell nucleus. FAM289 in the nucleus activated the ERK pathway, up regulated DNMTs expression and induced stem-like property gene expression which affects drug resistance of glioma cells to TMZ. This study provided functional evidence for FAM289 to be developed as a therapeutic target for cancer treatment.

Electronic supplementary material

The online version of this article (10.1186/s13046-019-1393-7) contains supplementary material, which is available to authorized users.

Transcriptional networks in acute myeloid leukemia

Acute myeloid leukemia (AML) is a complex disease characterized by a diverse range of recurrent molecular aberrations that occur in many different combinations. Components of transcriptional networks are a common target of these aberrations, leading to network-wide changes and deployment of novel or developmentally inappropriate transcriptional programs. Genome-wide techniques are beginning to reveal the full complexity of normal hematopoietic stem cell transcriptional networks and the extent to which they are deregulated in AML, and new understandings of the mechanisms by which AML cells maintain self-renewal and block differentiation are starting to emerge. The hope is that increased understanding of the network architecture in AML will lead to identification of key oncogenic dependencies that are downstream of multiple network aberrations, and that this knowledge will be translated into new therapies that target these dependencies. Here, we review the current state of knowledge of network perturbation in AML with a focus on major mechanisms of transcription factor dysregulation, including mutation, translocation, and transcriptional dysregulation, and discuss how these perturbations propagate across transcriptional networks. We will also review emerging mechanisms of network disruption, and briefly discuss how increased knowledge of network disruption is already being used to develop new therapies.

The Emerging Role of H3K9me3 as a Potential Therapeutic Target in Acute Myeloid Leukemia

Growing evidence has demonstrated that epigenetic dysregulation is a common pathological feature in human cancer cells. Global alterations in the epigenetic landscape are prevalent in malignant cells across different solid tumors including, prostate cancer, non-small-cell lung cancer, renal cell carcinoma, and in haemopoietic malignancy. In particular, DNA hypomethylation and histone hypoacetylation have been observed in acute myeloid leukemia (AML) patient blasts, with histone methylation being an emerging area of study. Histone 3 lysine 9 trimethylation (H3K9me3) is a post-translational modification known to be involved in the regulation of a broad range of biological processes, including the formation of transcriptionally silent heterochromatin. Following the observation of its aberrant methylation status in hematological malignancy and several other cancer phenotypes, recent studies have associated H3K9me3 levels with patient outcome and highlighted key molecular mechanisms linking H3K9me3 profile with AML etiology in a number of large-scale meta-analysis. Consequently, the development and application of small molecule inhibitors which target the histone methyltransferases or demethylase enzymes known to participate in the oncogenic regulation of H3K9me3 in AML represents an advancing area of ongoing study. Here, we provide a comprehensive review on how this particular epigenetic mark is regulated within cells and its emerging role as a potential therapeutic target in AML, along with an update on the current research into advancing the generation of more potent and selective inhibitors against known H3K9 methyltransferases and demethylases.

The Regulatory Roles of Long Noncoding RNAs in Acute Myeloid Leukemia

In this post-genomic era, long noncoding RNAs (lncRNAs) are rapidly gaining recognition for their crucial roles across diverse biological processes and contexts. The human blood system is no exception, where dozens of lncRNAs have been established as regulators of normal and/or malignant hematopoiesis, and where ongoing works continue to uncover novel lncRNA functions. Our review focuses on lncRNAs that are involved in the pathogenesis of acute myeloid leukemia (AML) and the mechanisms through which they control gene expression in this disease context. We also comment on genome-wide sequencing or profiling studies that have implicated large sets of lncRNAs in AML pathophysiology.

SOCS2 is part of a highly prognostic 4-gene signature in AML and promotes disease aggressiveness

Acute myeloid leukemia (AML) is a heterogeneous disease with respect to its genetic and molecular basis and to patients´ outcome. Clinical, cytogenetic, and mutational data are used to classify patients into risk groups with different survival, however, within-group heterogeneity is still an issue. Here, we used a robust likelihood-based survival modeling approach and publicly available gene expression data to identify a minimal number of genes whose combined expression values were prognostic of overall survival. The resulting gene expression signature (4-GES) consisted of 4 genes (SOCS2, IL2RA, NPDC1, PHGDH), predicted patient survival as an independent prognostic parameter in several cohorts of AML patients (total, 1272 patients), and further refined prognostication based on the European Leukemia Net classification. An oncogenic role of the top scoring gene in this signature, SOCS2, was investigated using MLL-AF9 and Flt3-ITD/NPM1c driven mouse models of AML. SOCS2 promoted leukemogenesis as well as the abundance, quiescence, and activity of AML stem cells. Overall, the 4-GES represents a highly discriminating prognostic parameter in AML, whose clinical applicability is greatly enhanced by its small number of genes. The newly established role of SOCS2 in leukemia aggressiveness and stemness raises the possibility that the signature might even be exploitable therapeutically.

High IL2RA mRNA expression is an independent adverse prognostic biomarker in core binding factor and intermediate-risk acute myeloid leukemia

BACKGROUND

Elevated protein expressions of CD markers such as IL2RA/CD25, CXCR4/CD184, CD34 and CD56 are associated with adverse prognosis in acute myeloid leukemia (AML). However, the prognostic value of mRNA expressions of these CD markers in AML remains unclear. Through our pilot evaluation, IL2RA mRNA expression appeared to be the best candidate as a prognostic biomarker. Therefore, the aim of this study is to characterize the prognostic value of IL2RA mRNA expression and evaluate its potential to refine prognostification in AML.

METHODS

In a cohort of 239 newly diagnosed AML patients, IL2RA mRNA expression were measured by TaqMan realtime quantitative PCR. Morphological, cytogenetics and mutational analyses were also performed. In an intermediate-risk AML cohort with 66 patients, the mRNA expression of prognostic biomarkers (BAALC, CDKN1B, ERG, MECOM/EVI1, FLT3, ID1, IL2RA, MN1 and WT1) were quantified by NanoString technology. A TCGA cohort was analyzed to validate the prognostic value of IL2RA. For statistical analysis, Mann-Whitney U test, Fisher exact test, logistic regression, Kaplan-Meier and Cox regression analyses were used.

RESULTS

In AML cohort of 239 patients, high IL2RA mRNA expression independently predicted shorter relapse free survival (RFS, p < 0.001) and overall survival (OS, p < 0.001) irrespective of age, cytogenetics, FLT3-ITD or c-KIT D816V mutational status. In core binding factor (CBF) AML, high IL2RA mRNA expression correlated with FLT3-ITD status (p = 0.023). Multivariable analyses revealed that high IL2RA expression (p = 0.002), along with c-KIT D816V status (p = 0.013) significantly predicted shorter RFS, whereas only high IL2RA mRNA expression (p = 0.014) significantly predicted shorter OS in CBF AML. In intermediate-risk AML in which multiple gene expression markers were tested by NanoString, IL2RA significantly correlated with ID1 (p = 0.006), FLT3 (p = 0.007), CDKN1B (p = 0.033) and ERG (p = 0.030) expressions. IL2RA (p < 0.001) and FLT3 (p = 0.008) expressions remained significant in predicting shorter RFS, whereas ERG (p = 0.008) and IL2RA (p = 0.044) remained significant in predicting shorter OS. Similar analyses in TCGA intermediate-risk AML showed the independent prognostic role of IL2RA in predicting event free survival (p < 0.001) and OS (p < 0.001).

CONCLUSIONS

High IL2RA mRNA expression is an independent and adverse prognostic factor in AML and specifically stratifies patients to worse prognosis in both CBF and intermediate-risk AML.

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

We have previously shown that expression levels of 48 long noncoding RNAs (lncRNA) can generate a prognostic lncRNA score that independently associates with outcome of older patients with cytogenetically normal acute myeloid leukemia (CN-AML). However, the techniques used to identify and measure prognostic lncRNAs (i.e., RNA sequencing and microarrays) are not tailored for clinical testing. Herein, we report on an assay (based on the nCounter platform) that is designed to produce targeted measurements of prognostic lncRNAs in a clinically applicable manner. We analyzed a new cohort of 76 older patients with CN-AML and found that the nCounter assay yielded reproducible measurements and that the lncRNA score retained its prognostic value; patients with high lncRNA scores had lower complete remission (CR) rates (P = 0.009; 58% vs. 87%), shorter disease-free (P = 0.05; 3-year rates: 0% vs. 21%), overall (OS; P = 0.02, 3-year rates: 10% vs. 29%), and event-free survival (EFS; P = 0.002, 3-year rates: 0% vs. 18%) than patients with low lncRNA scores. In multivariable analyses, the lncRNA score independently associated with CR rates (P = 0.02), OS (P = 0.02), and EFS (P = 0.02). To gain biological insights, we examined our initial cohort of 71 older patients with CN-AML, previously analyzed with RNA sequencing. Genes involved in immune response and B-cell receptor signaling were enriched in patients with high lncRNA scores. We conclude that clinically applicable lncRNA profiling is feasible and potentially useful for risk stratification of older patients with CN-AML. Furthermore, we identify potentially targetable molecular pathways that are active in the high-risk patients with high lncRNA scores.

Acute Myeloid Leukemia (AML) In Elderly: Cytogenetic Characteristics of Patients Treated At Hematology and Pediatric Oncology Center in Casablanca

AIM:

The goals of this paper are: to report the incidence of AML in elderly, to describe cytogenetic characteristics of this population, to observe rare and novel cytogenetic abnormalities and lastly, to compare our finding with that previously reported in the literature.

METHODS:

We conducted a retrospective analysis of 283 patients with acute myeloid leukaemia (AML) treated in our unit, we will report the incidence of AML in elderly, describe cytogenetic characteristics of this population, observe rare and novel cytogenetic abnormalities and compare our finding with that previously reported in the literature.

RESULTS:

Among the 283 patients, 157 (54.4%) patients performed the karyotype, the cytogenetic analysis failed in 17 cases (11%). Prognostic group distribution was found to be favorable in 8 patients (6%) with 6 cases of t (8; 21) and 2 cases of inv (16), intermediate group in 94 patients (67%), including 58 cases (41,5%) with a normal karyotype, and an unfavorable group in 38 patients (27%) including complex karyotype (15%), -5 or del 5q (3%), -7 or del 7q (3.5%), t (9; 22) (2%). Some rare anomalies were observed.

CONCLUSION:

However, the occurrence of a complex karyotype was more frequent than younger patients. In our unit, elderly benefit from supportive care, our study shows that it is a heterogeneous group and our treatment approach have to change especially for the patient from favourable risk group who can benefit from intensive chemotherapy. We have to improve our diagnosis with including molecular genetics that provides a documented substrate for a thoughtfully considered treatment plan.

Developing DNA methylation-based prognostic biomarkers of acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous clonal neoplasm characterized by complex genomic alterations. The incidence of AML increases with age, and most cases experience serious illness and poor prognosis. To explore the relationship between abnormal DNA methylation and the occurrence and development of AML based on the Gene Expression Database (GEO), this study extracted data related to methylation in AML and identified a methylated CpG site that was significantly different in terms of expression and distribution between the primary cells of AML patients, and hematopoietic stem/progenitor cells from normal bone marrow. To further investigate the differences caused by the dysfunction of methylation sites, bioinformatics analysis was used to screen methylation-related biomarkers, and the potential prognostic genes were selected by univariate and multivariate Cox proportional hazards regressions. Finally, five independent prognostic indicators were identified. In addition, these results provide new insight into the molecular mechanisms of methylation.

Genomic prediction of relapse in recipients of allogeneic haematopoietic stem cell transplantation

Allogeneic haematopoietic stem cell transplantation currently represents the primary potentially curative treatment for cancers of the blood and bone marrow. While relapse occurs in approximately 30% of patients, few risk-modifying genetic variants have been identified. The present study evaluates the predictive potential of patient genetics on relapse risk in a genome-wide manner. We studied 151 graft recipients with HLA-matched sibling donors by sequencing the whole-exome, active immunoregulatory regions, and the full MHC region. To assess the predictive capability and contributions of SNPs and INDELs, we employed machine learning and a feature selection approach in a cross-validation framework to discover the most informative variants while controlling against overfitting. Our results show that germline genetic polymorphisms in patients entail a significant contribution to relapse risk, as judged by the predictive performance of the model (AUC = 0.72 [95% CI: 0.63-0.81]). Furthermore, the top contributing variants were predictive in two independent replication cohorts (n = 258 and n = 125) from the same population. The results can help elucidate relapse mechanisms and suggest novel therapeutic targets. A computational genomic model could provide a step toward individualized prognostic risk assessment, particularly when accompanied by other data modalities.

Integrated epigenetic and genetic analysis identifies markers of prognostic significance in pediatric acute myeloid leukemia

Acute myeloid leukemia (AML) may be an epigenetically-driven malignancy because it harbors fewer genomic mutations than other cancers. In recent studies of AML in adults, DNA methylation patterns associate with clinical risk groups and prognosis. However, thorough evaluations of methylation in pediatric AML have not been done. Therefore, we performed an integrated analysis (IA) of the methylome and transcriptome with clinical outcome in 151 pediatric patients from the multi-center AML02 clinical trial discovery cohort. Intriguingly, reduced methylation and increased expression of DNMT3B was associated with worse clinical outcomes (IA p ≤ 10⁻⁵; q ≤ 0.002). In particular, greater DNMT3B expression associated with worse minimal residual disease (MRD; p < 10⁻⁵; q = 0.01), a greater rate of relapse or resistant disease (RR) (p = 0.00006; q = 0.06), and event-free survival (EFS; p = 0.00003; q = 0.04). Also, greater DNMT3B expression associated with greater genome-wide methylation burden (GWMB; R = 0.39; p = 10⁻⁶) and greater GWMB associated with worse clinical outcomes (IA p < 10⁻⁵). In an independent validation cohort of 132 similarly treated AAML0531 clinical trial patients, greater DNMT3B expression associated with greater GWMB, worse MRD, worse RR, and worse EFS (all p < 0.03); also, greater GWMB associated with worse MRD (p = 0.004) and EFS (p = 0.037). These results indicate that DNMT3B and GWMB may have a central role in the development and prognosis of pediatric AML.

Epigenetics and Precision Oncology

Epigenetic alterations such as DNA methylation defects and aberrant covalent histone modifications occur within all cancers and are selected for throughout the natural history of tumor formation, with changes being detectable in early onset, progression, and ultimately recurrence and metastasis. The ascertainment and use of these marks to identify at-risk patient populations, refine diagnostic criteria, and provide prognostic and predictive factors to guide treatment decisions are of growing clinical relevance. Furthermore, the targetable nature of epigenetic modifications provides a unique opportunity to alter treatment paradigms and provide new therapeutic options for patients whose malignancies possess these aberrant epigenetic modifications, paving the way for new and personalized medicine. DNA methylation has proven to be of significant clinical utility for its stability and relative ease of testing. The intent of this review is to elaborate upon well-supported examples of epigenetic precision medicine and how the field is moving forward, primarily in the context of aberrant DNA methylation.