Identification of genes with abnormal expression changes in acute myeloid leukemia

Ribosome rescue factor PELOTA modulates translation start site choice for C/EBPα protein isoforms

Translation initiation at alternative start sites can dynamically control the synthesis of two or more functionally distinct protein isoforms from a single mRNA. Alternate isoforms of the developmental transcription factor CCAAT/enhancer-binding protein α (C/EBPα) produced from different start sites exert opposing effects during myeloid cell development. This choice between alternative start sites depends on sequence features of the CEBPA transcript, including a regulatory uORF, but the molecular basis is not fully understood. Here, we identify the factors that affect C/EBPα isoform choice using a sensitive and quantitative two-color fluorescent reporter coupled with CRISPRi screening. Our screen uncovered a role of the ribosome rescue factor PELOTA (PELO) in promoting the expression of the longer C/EBPα isoform by directly removing inhibitory unrecycled ribosomes and through indirect effects mediated by the mechanistic target of rapamycin kinase. Our work uncovers further links between ribosome recycling and translation reinitiation that regulate a key transcription factor, with implications for normal hematopoiesis and leukemogenesis.

Inhibition of NOTCH4 sensitizes FLT3/ITD acute myeloid leukemia cells to FLT3 tyrosine kinase inhibition

Internal tandem duplication mutations of FLT3 (FLT3/ITD) confer poor prognosis in AML. FLT3 tyrosine kinase inhibitors (TKIs) alone have limited and transient clinical efficacy thus calling for new targets for more effective combination therapy. In a loss-of-function RNAi screen, we identified NOTCH4 as one such potential target whose inhibition proved cytotoxic to AML cells, and also sensitized them to FLT3 inhibition. Further investigation found increased NOTCH4 expression in FLT3/ITD AML cell lines and primary patient samples. Inhibition of NOTCH4 by shRNA knockdown, CRISPR-Cas9-based knockout or γ-secretase inhibitors synergized with FLT3 TKIs to kill FLT3/ITD AML cells in vitro. NOTCH4 inhibition sensitized TKI-resistant FLT3/ITD cells to FLT3 TKI inhibition. The combination reduced phospho-ERK and phospho-AKT, indicating inhibition of MAPK and PI3K/AKT signaling pathways. It also led to changes in expression of genes involved in regulating cell cycling, DNA repair and transcription. A patient-derived xenograft model showed that the combination reduced both the level of leukemic involvement of primary human FLT3/ITD AML cells and their ability to engraft secondary recipients. In summary, these results demonstrate that NOTCH4 inhibition synergizes with FLT3 TKIs to eliminate FLT3/ITD AML cells, providing a new therapeutic target for AML with FLT3/ITD mutations.

The biological function of Serpinb9 and Serpinb9-based therapy

Recent breakthroughs in discovering novel immune signaling pathways have revolutionized different disease treatments. SERPINB9 (Sb9), also known as Proteinase Inhibitor 9 (PI-9), is a well-known endogenous inhibitor of Granzyme B (GzmB). GzmB is a potent cytotoxic molecule secreted by cytotoxic T lymphocytes and natural killer cells, which plays a crucial role in inducing apoptosis in target cells during immune responses. Sb9 acts as a protective mechanism against the potentially harmful effects of GzmB within the cells of the immune system itself. On the other hand, overexpression of Sb9 is an important mechanism of immune evasion in diseases like cancers and viral infections. The intricate functions of Sb9 in different cell types represent a fine-tuned regulatory mechanism for preventing immunopathology, protection against autoimmune diseases, and the regulation of cell death, all of which are essential for maintaining health and responding effectively to disease challenges. Dysregulation of the Sb9 will disrupt human normal physiological condition, potentially leading to a range of diseases, including cancers, inflammatory conditions, viral infections or other pathological disorders. Deepening our understanding of the role of Sb9 will aid in the discovery of innovative and effective treatments for various medical conditions. Therefore, the objective of this review is to consolidate current knowledge regarding the biological role of Sb9. It aims to offer insights into its discovery, structure, functions, distribution, its association with various diseases, and the potential of nanoparticle-based therapies targeting Sb9.

Disruption of polyunsaturated fatty acid biosynthesis drives STING-dependent acute myeloid leukemia cell maturation and death

The role of polyunsaturated fatty acid (PUFA) biosynthesis in acute myeloid leukemia (AML) remains largely undefined. A comparative expression analysis of 35 genes encoding fatty acid biosynthesis enzymes showed that fatty acid desaturase 1 (FADS1) was highly expressed across multiple AML subtypes relative to healthy controls and that elevated FADS1 expression correlates with worse overall AML patient survival. Functionally, shRNA-mediated inhibition of FADS1 reduced AML cell growth in vitro and significantly delayed leukemia onset in an AML mouse model. AML cell lines depleted of FADS1 arrested in the G1/S-phase of the cell cycle, acquired characteristics of myeloid maturation and subsequently died. To understand the molecular consequences of FADS1 inhibition, a combination of mass spectrometry-based analysis of complex lipids and gene expression analysis (RNA-seq) was performed. FADS1 inhibition caused AML cells to exhibit significant lipidomic remodeling, including depletion of PUFAs from the phospholipids, phosphatidylserine, and phosphatidylethanolamine. These lipidomic alterations were accompanied by an increase induction of inflammatory and stimulator of interferon genes (STING)-mediated type-1 interferon signaling. Remarkably, genetic deletion of STING largely prevented the AML cell maturation and death phenotypes mediated by FADS1 inhibition. Highlighting the therapeutic implications of these findings, pharmacological blockade of PUFA biosynthesis reduced patient-derived AML cell numbers ex vivo but not that of healthy donor cells. Similarly, STING agonism attenuated patient-derived-AML survival; however, STING activation also reduced healthy granulocyte numbers. Collectively, these data unveil a previously unrecognized importance of PUFA biosynthesis in leukemogenesis and that imbalances in PUFA metabolism can drive STING-mediated AML maturation and death.

Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data

Existing methods for gene regulatory network (GRN) inference rely on gene expression data alone or on lower resolution bulk data. Despite the recent integration of chromatin accessibility and RNA sequencing data, learning complex mechanisms from limited independent data points still presents a daunting challenge. Here we present LINGER (Lifelong neural network for gene regulation), a machine-learning method to infer GRNs from single-cell paired gene expression and chromatin accessibility data. LINGER incorporates atlas-scale external bulk data across diverse cellular contexts and prior knowledge of transcription factor motifs as a manifold regularization. LINGER achieves a fourfold to sevenfold relative increase in accuracy over existing methods and reveals a complex regulatory landscape of genome-wide association studies, enabling enhanced interpretation of disease-associated variants and genes. Following the GRN inference from reference single-cell multiome data, LINGER enables the estimation of transcription factor activity solely from bulk or single-cell gene expression data, leveraging the abundance of available gene expression data to identify driver regulators from case-control studies.

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a new optimization procedure to identify the top network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression.

Dynamic alterations of the transcriptome-wide m6A methylome in cytogenetically normal acute myeloid leukaemia during initial diagnosis and relapse

Accumulating studies have indicated that N6-methyladenosine (m6A) plays an important role in acute myeloid leukaemia (AML). However, little is known about the m6A methylome at a transcriptome-wide scale in AML patients. We obtained three pairs of bone marrow (BM) samples from cytogenetically normal AML patients at the timepoints of diagnosis (AML) and relapse (R_AML) and three BM samples from healthy donors used as normal controls (NCs). Methylated RNA immunoprecipitation next-generation sequencing (MeRIP-Seq) was conducted to identify differences in the m6A methylomes between AML and NC and between R_AML and AML. We identified a total of 11,076 and 11,962 differential m6A peaks in AML and R_AML group, respectively. These dysregulated m6A peaks were detected on all chromosomes, especially chr1, chr19 and chr17, and were mainly enriched in 3' untranslated regions, stop codon and coding sequence regions. Moreover, GO and KEGG analyses indicated that m6A -modified genes were significantly enriched in cancer-related biological functions and pathways. Additionally, we identified a link between the m6A methylome and RNA transcriptome via combined analyses of MeRIP-seq and RNA-seq data. In addition, 5 genes, HSPG2, HOMER3, TSPO2, CXCL12 and FUT1 regulated by m6A modification potentially, were shown to be related to the prognosis of AML patients. Additionally, we detected the mRNA expression of major m6A regulators and potential target mRNA on the leukemogenesis and found that the expression of IGF2BP2, HSPG2 and HOMER3 were upregulated in AML at the time of diagnosis. Moreover, their expression became downregulated after remission and then elevated again at relapse. Our study provides the first data on the differential m6A methylome in AML patients during initial diagnosis and relapse. This study demonstrates a novel relationship between m6A modification and AML relapse and paves the way for further studies aimed at elucidating the epigenic mechanisms involved in the relapse of AML.

Targeting human mitochondrial NAD(P)+-dependent malic enzyme (ME2) impairs energy metabolism and redox state and exhibits antileukemic activity in acute myeloid leukemia

Acute myeloid leukemia (AML) is a fast-growing and highly fatal blood cancer, and recent research has shown that targeting metabolism may be a promising therapeutic approach for treating AML. One promising target is the human mitochondrial NAD(P)+-dependent malic enzyme (ME2), which is involved in the production of pyruvate and NAD(P)H and the regulation of the NAD+/NADH redox balance. Inhibition of ME2 via silencing ME2 or utilizing its allosteric inhibitor disodium embonate (Na2EA) causes a decrease in pyruvate and NADH, leading to a decrease in producing ATP via cellular respiration and oxidative phosphorylation. ME2 inhibition also decreases NADPH levels, resulting in an increase in reactive oxygen species (ROS) and oxidative stress, which ultimately leads to cellular apoptosis. Additionally, ME2 inhibition reduces pyruvate metabolism and the biosynthetic pathway. ME2 silencing inhibits the growth of xenotransplanted human AML cells, and the allosteric ME2 inhibitor Na2EA demonstrates antileukemic activity against immune-deficient mice with disseminated AML. Both of these effects are a result of impaired energy metabolism in mitochondria. These findings suggest that the targeting ME2 may be an effective strategy for treating AML. Overall, ME2 plays an essential role in energy metabolism of AML cells, and its inhibition may offer a promising approach for AML treatment.

Continuous lifelong learning for modeling of gene regulation from single cell multiome data by leveraging atlas-scale external data

Accurate context-specific Gene Regulatory Networks (GRNs) inference from genomics data is a crucial task in computational biology. However, existing methods face limitations, such as reliance on gene expression data alone, lower resolution from bulk data, and data scarcity for specific cellular systems. Despite recent technological advancements, including single-cell sequencing and the integration of ATAC-seq and RNA-seq data, learning such complex mechanisms from limited independent data points still presents a daunting challenge, impeding GRN inference accuracy. To overcome this challenge, we present LINGER (LIfelong neural Network for GEne Regulation), a novel deep learning-based method to infer GRNs from single-cell multiome data with paired gene expression and chromatin accessibility data from the same cell. LINGER incorporates both 1) atlas-scale external bulk data across diverse cellular contexts and 2) the knowledge of transcription factor (TF) motif matching to cis-regulatory elements as a manifold regularization to address the challenge of limited data and extensive parameter space in GRN inference. Our results demonstrate that LINGER achieves 2-3 fold higher accuracy over existing methods. LINGER reveals a complex regulatory landscape of genome-wide association studies, enabling enhanced interpretation of disease-associated variants and genes. Additionally, following the GRN inference from a reference sc-multiome data, LINGER allows for the estimation of TF activity solely from bulk or single-cell gene expression data, leveraging the abundance of available gene expression data to identify driver regulators from case-control studies. Overall, LINGER provides a comprehensive tool for robust gene regulation inference from genomics data, empowering deeper insights into cellular mechanisms.

Data-driven modeling of core gene regulatory network underlying leukemogenesis in IDH mutant AML

Acute myeloid leukemia (AML) is characterized by uncontrolled proliferation of poorly differentiated myeloid cells, with a heterogenous mutational landscape. Mutations in IDH1 and IDH2 are found in 20% of the AML cases. Although much effort has been made to identify genes associated with leukemogenesis, the regulatory mechanism of AML state transition is still not fully understood. To alleviate this issue, here we develop a new computational approach that integrates genomic data from diverse sources, including gene expression and ATAC-seq datasets, curated gene regulatory interaction databases, and mathematical modeling to establish models of context-specific core gene regulatory networks (GRNs) for a mechanistic understanding of tumorigenesis of AML with IDH mutations. The approach adopts a novel optimization procedure to identify the optimal network according to its accuracy in capturing gene expression states and its flexibility to allow sufficient control of state transitions. From GRN modeling, we identify key regulators associated with the function of IDH mutations, such as DNA methyltransferase DNMT1, and network destabilizers, such as E2F1. The constructed core regulatory network and outcomes of in-silico network perturbations are supported by survival data from AML patients. We expect that the combined bioinformatics and systems-biology modeling approach will be generally applicable to elucidate the gene regulation of disease progression.

North American Blastic Plasmacytoid Dendritic Cell Neoplasm Consortium: position on standards of care and areas of need

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematologic malignancy with historically poor outcomes and no worldwide consensus treatment approach. Unique among most hematologic malignancies for its frequent cutaneous involvement, BPDCN can also invade other extramedullary compartments, including the central nervous system. Generally affecting older adults, many patients are unfit to receive intensive chemotherapy, and although hematopoietic stem cell transplantation is preferred for younger, fit individuals, not all are eligible. One recent therapeutic breakthrough is that all BPDCNs express CD123 (IL3Rα) and that this accessible surface marker can be pharmacologically targeted. The first-in-class agent for BPDCN, tagraxofusp, which targets CD123, was approved in December 2018 in the United States for patients with BPDCN aged ≥2 years. Despite favorable response rates in the frontline setting, many patients still relapse in the setting of monotherapy, and outcomes in patients with relapsed/refractory BPDCN remain dismal. Therefore, novel approaches targeting both CD123 and other targets are actively being investigated. To begin to formally address the state of the field, we formed a new collaborative initiative, the North American BPDCN Consortium (NABC). This group of experts, which includes a multidisciplinary panel of hematologists/oncologists, hematopoietic stem cell transplant physicians, pathologists, dermatologists, and pediatric oncologists, was tasked with defining the current standard of care in the field and identifying the most important research questions and future directions in BPDCN. The position findings of the NABC's inaugural meetings are presented herein.

Ribosome rescue factor PELOTA modulates translation start site choice and protein isoform levels of transcription factor C/EBPα

Translation initiation at alternative start sites can dynamically control the synthesis of two or more functionally distinct protein isoforms from a single mRNA. Alternate isoforms of the hematopoietic transcription factor CCAAT-enhancer binding protein α (C/EBPα) produced from different start sites exert opposing effects during myeloid cell development. This alternative initiation depends on sequence features of the CEBPA transcript, including a regulatory upstream open reading frame (uORF), but the molecular basis is not fully understood. Here we identify trans-acting factors that affect C/EBPα isoform choice using a sensitive and quantitative two-color fluorescence reporter coupled with CRISPRi screening. Our screen uncovered a role for the ribosome rescue factor PELOTA (PELO) in promoting expression of the longer C/EBPα isoform, by directly removing inhibitory unrecycled ribosomes and through indirect effects mediated by the mechanistic target of rapamycin (mTOR) kinase. Our work provides further mechanistic insights into coupling between ribosome recycling and translation reinitiation in regulation of a key transcription factor, with implications for normal hematopoiesis and leukemiagenesis.

A statistical network pre-processing method to improve relevance and significance of gene lists in microarray gene expression studies

Background

Microarrays can perform large scale studies of differential expressed gene (DEGs) and even single nucleotide polymorphisms (SNPs), thereby screening thousands of genes for single experiment simultaneously. However, DEGs and SNPs are still just as enigmatic as the first sequence of the genome. Because they are independent from the affected biological context. Pathway enrichment analysis (PEA) can overcome this obstacle by linking both DEGs and SNPs to the affected biological pathways and consequently to the underlying biological functions and processes.

Results

To improve the enrichment analysis results, we present a new statistical network pre-processing method by mapping DEGs and SNPs on a biological network that can improve the relevance and significance of the DEGs or SNPs of interest to incorporate pathway topology information into the PEA. The proposed methodology improves the statistical significance of the PEA analysis in terms of computed p value for each enriched pathways and limit the number of enriched pathways. This helps reduce the number of relevant biological pathways with respect to a non-specific list of genes.

Conclusion

The proposed method provides two-fold enhancements. Network analysis reveals fewer DEGs, by selecting only relevant DEGs and the detected DEGs improve the enriched pathways’ statistical significance, rather than simply using a general list of genes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04936-z.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Studying the potential of upregulated PTGS2 and VEGF-C besides hyper-methylation of PTGS2 promoter as biomarkers of Acute myeloid leukemia

Hereby, we aimed to investigate the expression of prostaglandin-endoperoxide synthase 2 (PTGS2) and Vascular Endothelial Factor-C (VEGF-C) besides the methylation of PTGS2 in AML patients. VEGF-C and PTGS2 expression analysis were evaluated in newly diagnosed AML patients and healthy controls by quantitative Reverse Transcriptase PCR method. Also, PTGS2 methylation status was evaluated by Methylation-Sensitive High-Resolution Melting Curve Analysis (MS-HRM). While 34% of patients were female, the mean age of the patients was 43.41 ± 17.60 years suffering mostly from M4 (48.21%) type of AML. Although methylation level between patients and controls was not significantly different, none of the normal controls showed methylation in the PTGS2 promoter. PTGS2 and VEGF-C levels were elevated in AML cases and correlated with WBC, Platelet, and Hemoglobin levels. The survival of patients with overexpressed VEGF-C and PTGS2 was poorer than others. It can be concluded that PTGS2 and especially VEGF-C expression but not PTGS2 methylation can be considered as diagnostic biomarkers for AML.

Systematic analysis of prognostic significance, functional enrichment and immune implication of STK10 in acute myeloid leukemia

Background

Despite deeper understanding of the genetic landscape of acute myeloid leukemia (AML), the improvement of survival is still a great challenge. STK10 is overexpressed in several cancers with functions varying according to cancer types. But the functions of STK10 in AML has never been reported.

Methods

We analyzed the expression, prognosis and potential functions of STK10 utilizing public web servers. Metascape and the String database were used for functional and protein–protein interaction analyses.

Results

We found STK10 was enriched in blood & immune cells and overexpressed in AML. High STK10 expression was associated with poor overall survival, which was also identified in the subgroups of patients ≤ 60 years old and patients with non-high-risk cytogenetics. We demonstrated genes associated with STK10 were enriched in blood, spleen and bone marrow, influencing the immune function and biological process of AML. ITGB2 and ITGAM might directly interact with STK10 and were associated with poor prognosis. Besides, STK10 was associated with the infiltration of immune cells and immune checkpoints, like HLA-E, CD274 and GAL-9.

Conclusions

The present study was the original description of STK10 in AML and set the stage for developing STK10 as a new prognostic marker or therapeutic target for AML.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01251-7.

DOK2 Has Prognostic and Immunologic Significance in Adults With Acute Myeloid Leukemia: A Novel Immune-Related Therapeutic Target

Background

The role of downstream tyrosine kinase 2 (DOK2), a major member of the DOK family, remains poorly defined in acute myeloid leukemia (AML). Herein, we investigated the expression levels, clinical outcomes, and biological functions of DOK2 in patients with AML.

Methods

Datasets were obtained from the Cancer Genome Atlas (TCGA) database for transcriptomic and clinical information. Nomogram construction and assessment were conducted using Cox regression analysis, receiver operating characteristic (ROC) curves, and calibration plots. Public databases, including the Gene Expression Omnibus, Cancer Cell Line Encyclopedia, LinkedOmics, GeneMANIA, TISIDB, and Gene Set Cancer Analysis, were employed for relevant bioinformatic studies. Moreover, we utilized the CIBERSORT algorithm to evaluate the level of infiltration of immune cells into the bone marrow microenvironment.

Results

We observed that DOK2 transcription levels were markedly upregulated in AML samples (P < 0.001), and its high expression was associated with inferior overall survival (OS) (HR = 2.17, P < 0.001) and disease-free survival (DFS) (HR = 2.50, P < 0.001). ROC curve analysis also showed the reliable diagnostic efficiency of DOK2 in AML. For treatment regimens, patients with high DOK2 expression could significantly prolong OS by receiving hematopoietic stem cell transplantation (HSCT) (P < 0.001), whereas those with low DOK2 expression were more likely to improve DFS by chemotherapy alone rather than HSCT. Nomograms constructed for predicting OS and DFS exhibited satisfactory discrimination and accuracy. Functional enrichment analysis identified that DOK2 was involved in important pathways associated with immune-related activities. Furthermore, CIBERSORT scores reflected negative correlations of DOK2 with activated mast cells and resting CD4+ memory T cells, which indicated its adverse immunomodulatory potential.

Conclusion

We suggest that elevated DOK2 expression could be an unfavorable prognostic indicator of survival in patients with AML. Our findings provide new insights into the role of DOK2 in AML, with promising clinical implications.

Proton export alkalinizes intracellular pH and reprograms carbon metabolism to drive normal and malignant cell growth

Proton export is often considered a detoxifying process in animal cells, with monocarboxylate symporters coexporting excessive lactate and protons during glycolysis or the Warburg effect. We report a novel mechanism by which lactate/H+ export is sufficient to induce cell growth. Increased intracellular pH selectively activates catalysis by key metabolic gatekeeper enzymes HK1/PKM2/G6PDH, thereby enhancing glycolytic and pentose phosphate pathway carbon flux. The result is increased nucleotide levels, NADPH/NADP+ ratio, and cell proliferation. Simply increasing the lactate/proton symporter monocarboxylate transporter 4 (MCT4) or the sodium-proton antiporter NHE1 was sufficient to increase intracellular pH and give normal hematopoietic cells a significant competitive growth advantage in vivo. This process does not require additional cytokine triggers and is exploited in malignancy, where leukemogenic mutations epigenetically increase MCT4. Inhibiting MCT4 decreased intracellular pH and carbon flux and eliminated acute myeloid leukemia-initiating cells in mice without cytotoxic chemotherapy. Intracellular alkalization is a primitive mechanism by which proton partitioning can directly reprogram carbon metabolism for cell growth.

Pre-clinical development of a novel CD3-CD123 bispecific T-cell engager using cross-over dual-variable domain (CODV) format for acute myeloid leukemia (AML) treatment

Novel therapies are needed for effective treatment of AML. In the relapsed setting, prognosis is very poor despite salvage treatment with chemotherapy. Evidence suggests that leukemic stem cells (LSCs) cause relapse. The cell surface receptor CD123 is highly expressed in blast cells and LSCs from AML patients and is a potential therapeutic target. CD123 cross-over dual-variable domain T-cell engager (CD123-CODV-TCE) is a bispecific antibody with an innovative format. One arm targets the CD3εδ subunit of T-cell co-receptors on the surface of T cells, while the other targets CD123 on malignant cells, leading to cell-specific cytotoxic activity. Here, we describe the preclinical activity of CD123-CODV-TCE. CD123-CODV-TCE effectively binds to human and cynomolgus monkey CD3 and CD123 and is a highly potent T-cell engager. It mediates T-cell activation and T-cell-directed killing of AML cells in vitro. In vivo, CD123-CODV-TCE suppresses AML tumor growth in leukemia xenograft mouse models, where it achieves an effective half-life of 3.2 days, which is a significantly longer half-life compared to other bispecific antibodies with no associated Fc fragment. The in vitro safety profile is as expected for compounds with similar modes of action. These results suggest that CD123-CODV-TCE may be a promising therapy for patients with relapsed/refractory AML.

In Silico Methods for the Identification of Diagnostic and Favorable Prognostic Markers in Acute Myeloid Leukemia

Acute myeloid leukemia (AML), the most common type of acute leukemia in adults, is mainly asymptomatic at early stages and progresses/recurs rapidly and frequently. These attributes necessitate the identification of biomarkers for timely diagnosis and accurate prognosis. In this study, differential gene expression analysis was performed on large-scale transcriptomics data of AML patients versus corresponding normal tissue. Weighted gene co-expression network analysis was conducted to construct networks of co-expressed genes, and detect gene modules. Finally, hub genes were identified from selected modules by applying network-based methods. This robust and integrative bioinformatics approach revealed a set of twenty-four genes, mainly related to cell cycle and immune response, the diagnostic significance of which was subsequently compared against two independent gene expression datasets. Furthermore, based on a recent notion suggesting that molecular characteristics of a few, unusual patients with exceptionally favorable survival can provide insights for improving the outcome of individuals with more typical disease trajectories, we defined groups of long-term survivors in AML patient cohorts and compared their transcriptomes versus the general population to infer favorable prognostic signatures. These findings could have potential applications in the clinical setting, in particular, in diagnosis and prognosis of AML.

Bimodal expression of RHOH during myelomonocytic differentiation: Implications for the expansion of AML differentiation therapy

RhoH is an unusual member of the Rho family of small GTP‐binding proteins in that it lacks GTPase activity. Since the RhoH protein is constantly bound by GTP, it is constitutively active and controlled predominantly by changes in quantitative expression. Abnormal levels of RHOH gene transcripts have been linked to a range of malignancies including acute myeloid leukemia (AML). One of the hallmarks of AML is a block in the normal program of myeloid differentiation. Here we investigate how myeloid differentiation is controlled by the quantitative expression of RHOH. Our analysis demonstrates that increasingly mature myeloid cells express progressively lower levels of RHOH. However, as monocytic myeloid cells terminally differentiate into macrophages, RHOH expression is up‐regulated. This up‐regulation is not apparent in AML where myeloid differentiation is blocked at stages of low RHOH expression. Nevertheless, when the up‐regulation of RHOH is forced, then terminal macrophage differentiation is induced and the Cdc42 and Wnt intracellular signalling pathways are repressed. These results indicate that RHOH induction is a driver of terminal differentiation and might represent a means of effecting AML differentiation therapy. The potential of this therapeutic strategy is supported by forced up‐regulation of RHOH reducing the ability of AML cells to produce tumours in vivo.

Deciphering molecular heterogeneity in pediatric AML using a cancer vs. normal transcriptomic approach

BACKGROUND

Still 30-40% of pediatric acute myeloid leukemia (pedAML) patients relapse. Delineation of the transcriptomic profile of leukemic subpopulations could aid in a better understanding of molecular biology and provide novel biomarkers.

METHODS

Using microarray profiling and quantitative PCR validation, transcript expression was measured in leukemic stem cells (LSC, n = 24) and leukemic blasts (L-blast, n = 25) from pedAML patients in comparison to hematopoietic stem cells (HSCs, n = 19) and control myeloblasts (C-blast, n = 20) sorted from healthy subjects. Gene set enrichment analysis was performed to identify relevant gene set enrichment signatures, and functional protein associations were identified by STRING analysis.

RESULTS

Highly significantly overexpressed genes in LSC and L-blast were identified with a vast majority not studied in AML. CDKN1A, CFP, and CFD (LSC) and HOMER3, CTSA, and GADD45B (L-blast) represent potentially interesting biomarkers and therapeutic targets. Eleven LSC downregulated targets were identified that potentially qualify as tumor suppressor genes, with MYCT1, PBX1, and PTPRD of highest interest. Inflammatory and immune dysregulation appeared to be perturbed biological networks in LSC, whereas dysregulated metabolic profiles were observed in L-blast.

CONCLUSION

Our study illustrates the power of taking into account cell population heterogeneity and reveals novel targets eligible for functional evaluation and therapy in pedAML.

IMPACT

Novel transcriptional targets were discovered showing a significant differential expression in LSCs and blasts from pedAML patients compared to their normal counterparts from healthy controls. Deregulated pathways, including immune and metabolic dysregulation, were addressed for the first time in children, offering a deeper understanding of the molecular pathogenesis. These novel targets have the potential of acting as biomarkers for risk stratification, follow-up, and targeted therapy. Multiple LSC-downregulated targets endow tumor suppressor roles in other cancer entities, and further investigation whether hypomethylating therapy could result into LSC eradication in pedAML is warranted.

High HSPA8 expression predicts adverse outcomes of acute myeloid leukemia

Background

Acute myeloid leukemia (AML) remains one of the most common hematological malignancies, posing a serious challenge to human health. HSPA8 is a chaperone protein that facilitates proper protein folding. It contributes to various activities of cell function and also is associated with various types of cancers. To date, the role of HSPA8 in AML is still undetermined.

Methods

In this study, public datasets available from the TCGA (Cancer Genome Atlas) and GEO (Gene Expression Omnibus) were mined to discover the association between the expression of HSPA8 and clinical phenotypes of CN-AML. A series of bioinformatics analysis methods, including functional annotation and miRNA-mRNA regulation network analysis, were employed to investigate the role of HSPA8 in CN-AML.

Results

HSPA8 was highly expressed in the AML patients compared to the healthy controls. The high HSPA8 expression had lower overall survival (OS) rate than those with low HSPA8 expression. High expression of HSPA8 was also an independent prognostic factor for overall survival (OS) of CN-AML patients by multivariate analysis. The differential expressed genes (DEGs) associated with HSPA8 high expression were identified, and they were enriched PI3k-Akt signaling, cAMP signaling, calcium signaling pathway. HSPA8 high expression was also positively associated with micro-RNAs (hsa-mir-1269a, hsa-mir-508-3p, hsa-mir-203a), the micro-RNAs targeted genes (VSTM4, RHOB, HOBX7) and key known oncogenes (KLF5, RAN, and IDH1), and negatively associated with tumor suppressors (KLF12, PRKG1, TRPS1, NOTCH1, RORA).

Conclusions

Our research revealed HSPA8 as a novel potential prognostic factor to predict the survival of CN-AML patients. Our data also revealed the possible carcinogenic mechanism and the complicated microRNA-mRNA network associated with the HSPA8 high expression in AML.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08193-w.

Homer2 and Homer3 Act as Novel Biomarkers in Diagnosis of hepatitis B virus-induced Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is one of the most common causes of cancer‐related mortality worldwide. Early detection of HCC can significantly improve patients' outcomes. An increasing number of studies have validated that Homer is dysregulated in cancers and may serve as diagnostic markers. In the present study, we investigated the expression profile and diagnostic significance of Homer2 and Homer3 in hepatitis B virus-induced HCC (HBV-HCC).

Methods: Quantitative real-time PCR (QRT-PCR), western blot analysis and immunohistochemistry analysis.

Results: Homer2 and Homer3 were downregulated in HCC. The expression of Homer2 was associated with tumor differentiation grade (P= 0.012) and total protein (TP) level (P= 0.032). Homer3 was related to tumor size (P= 0.010), tumor nodes (P= 0.026) and γ-glutamyl transferase (GGT) level (P= 0.001). The receiver operating characteristic curve analyses indicated that the combination of Homer2, Homer3 and AFP possessed a high accuracy (AUC=0.900) to diagnose HCC cases from healthy controls.

Conclusion: Our data indicated that Homer2 and Homer3 were downregulated in HCC and might be potential diagnostic marker for HCC.

Disruptive natural selection by male reproductive potential prevents underexpression of protein-coding genes on the human Y chromosome as a self-domestication syndrome

Background

In population ecology, the concept of reproductive potential denotes the most vital indicator of chances to produce and sustain a healthy descendant until his/her reproductive maturity under the best conditions. This concept links quality of life and longevity of an individual with disease susceptibilities encoded by his/her genome. Female reproductive potential has been investigated deeply, widely, and comprehensively in the past, but the male one has not received an equal amount of attention. Therefore, here we focused on the human Y chromosome and found candidate single-nucleotide polymorphism (SNP) markers of male reproductive potential.

Results

Examining in silico (i.e., using our earlier created Web-service SNP_TATA_Z-tester) all 1206 unannotated SNPs within 70 bp proximal promoters of all 63 Y-linked genes, we found 261 possible male-reproductive-potential SNP markers that can significantly alter the binding affinity of TATA-binding protein (TBP) for these promoters. Among them, there are candidate SNP markers of spermatogenesis disorders (e.g., rs1402972626), pediatric cancer (e.g., rs1483581212) as well as male anxiety damaging family relationships and mother’s and children’s health (e.g., rs187456378). First of all, we selectively verified in vitro both absolute and relative values of the analyzed TBP–promoter affinity, whose Pearson’s coefficients of correlation between predicted and measured values were r = 0.84 (significance p <  0.025) and r = 0.98 (p <  0.025), respectively. Next, we found that there are twofold fewer candidate SNP markers decreasing TBP–promoter affinity relative to those increasing it, whereas in the genome-wide norm, SNP-induced damage to TBP–promoter complexes is fourfold more frequent than SNP-induced improvement (p <  0.05, binomial distribution). This means natural selection against underexpression of these genes. Meanwhile, the numbers of candidate SNP markers of an increase and decrease in male reproductive potential were indistinguishably equal to each other (p <  0.05) as if male self-domestication could have happened, with its experimentally known disruptive natural selection. Because there is still not enough scientific evidence that this could have happened, we discuss the human diseases associated with candidate SNP markers of male reproductive potential that may correspond to domestication-related disorders in pets.

Conclusions

Overall, our findings seem to support a self-domestication syndrome with disruptive natural selection by male reproductive potential preventing Y-linked underexpression of a protein.

Identifying disease-associated signaling pathways through a novel effector gene analysis

Background

Signaling pathway analysis methods are commonly used to explain biological behaviors of disease cells. Effector genes typically decide functional attributes (associated with biological behaviors of disease cells) by abnormal signals they received. The signals that the effector genes receive can be quite different in normal vs. disease conditions. However, most of current signaling pathway analysis methods do not take these signal variations into consideration.

Methods

In this study, we developed a novel signaling pathway analysis method called signaling pathway functional attributes analysis (SPFA) method. This method analyzes the signal variations that effector genes received between two conditions (normal and disease) in different signaling pathways.

Results

We compared the SPFA method to seven other methods across 33 Gene Expression Omnibus datasets using three measurements: the median rank of target pathways, the median p-value of target pathways, and the percentages of significant pathways. The results confirmed that SPFA was the top-ranking method in terms of median rank of target pathways and the fourth best method in terms of median p-value of target pathways. SPFA’s percentage of significant pathways was modest, indicating a good false positive rate and false negative rate. Overall, SPFA was comparable to the other methods. Our results also suggested that the signal variations calculated by SPFA could help identify abnormal functional attributes and parts of pathways. The SPFA R code and functions can be accessed at https://github.com/ZhenshenBao/SPFA.

AML risk stratification models utilizing ELN-2017 guidelines and additional prognostic factors: a SWOG report

Background

The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. Despite the identification of many prognostic factors, relatively few have made their way into clinical practice.

Methods

In order to assess and improve the performance of the European LeukemiaNet guidelines, we developed novel prognostic models using the biomarkers from the guidelines, age, performance status and select transcript biomarkers. The models were developed separately for mononuclear cells and viable leukemic blasts from previously untreated acute myeloid leukemia patients (discovery cohort, N = 185) who received intensive chemotherapy. Models were validated in an independent set of similarly treated patients (validation cohort, N = 166).

Results

Models using European LeukemiaNet guidelines were significantly associated with clinical outcomes and, therefore, utilized as a baseline for comparisons. Models incorporating age and expression of select transcripts with biomarkers from European LeukemiaNet guidelines demonstrated higher area under the curve and C-statistics but did not show a substantial improvement in performance in the validation cohort. Subset analyses demonstrated that models using only the European LeukemiaNet guidelines were a better fit for younger patients (age < 55) than for older patients. Models integrating age and European LeukemiaNet guidelines visually showed more separation between risk groups in older patients. Models excluding results for ASXL1, CEBPA, RUNX1 and TP53, demonstrated that these mutations provide a limited overall contribution to risk stratification across the entire population, given the low frequency of mutations and confounding risk factors.

Conclusions

While European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification.

Evaluation of cyclin A1-specific T cells as a potential treatment for acute myeloid leukemia

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the only curative option for relapsed or refractory acute myeloid leukemia (AML). However, more than half ultimately experience disease relapse that is associated with a dismal median survival of just 6 months, highlighting the need for novel therapies. In the current study we explore the therapeutic potential of targeting cyclin A1 (CCNA1), a cancer-testis antigen that is overexpressed in malignant blasts and leukemic stem cells. We demonstrate the immunogenicity of this antigen to native T cells, with >90% of donors screened mounting a specific response. The expanded cells were Th1 polarized, polyfunctional, and cytotoxic toward CCNA1+/HLA-matched tumor cell lines. Furthermore, these cells were exquisitely specific for CCNA1 and exhibited no reactivity against other cyclin family members, including CCNA2, which shares 56% homology with CCNA1 and is ubiquitously expressed in dividing cells. Lastly, the detection of CCNA1-specific T cells in AML patients post-HSCT was associated with prolonged disease remission, suggesting the protective potential of such endogenous cells. Taken together, our findings demonstrate the feasibility of targeting CCNA1 and the potential for therapeutic benefit associated with the adoptive transfer of reactive cells.

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.

Vitamin D Receptor Controls Cell Stemness in Acute Myeloid Leukemia and in Normal Bone Marrow

Vitamin D (VD) is a known differentiating agent, but the role of VD receptor (VDR) is still incompletely described in acute myeloid leukemia (AML), whose treatment is based mostly on antimitotic chemotherapy. Here, we present an unexpected role of VDR in normal hematopoiesis and in leukemogenesis. Limited VDR expression is associated with impaired myeloid progenitor differentiation and is a new prognostic factor in AML. In mice, the lack of Vdr results in increased numbers of hematopoietic and leukemia stem cells and quiescent hematopoietic stem cells. In addition, malignant transformation of Vdr-/- cells results in myeloid differentiation block and increases self-renewal. Vdr promoter is methylated in AML as in CD34+ cells, and demethylating agents induce VDR expression. Association of VDR agonists with hypomethylating agents promotes leukemia stem cell exhaustion and decreases tumor burden in AML mouse models. Thus, Vdr functions as a regulator of stem cell homeostasis and leukemic propagation.

Imputation of Gene Expression Data in Blood Cancer and Its Significance in Inferring Biological Pathways

Purpose: Gene expression data generated from microarray technology is often analyzed for disease diagnostics and treatment. However, this data suffers with missing values that may lead to inaccurate findings. Since data capture is expensive, time consuming, and is required to be collected from subjects, it is worthwhile to recover missing values instead of re-collecting the data. In this paper, a novel but simple method, namely, DSNN (Doubly Sparse DCT domain with Nuclear Norm minimization) has been proposed for imputing missing values in microarray data. Extensive experiments including pathway enrichment have been carried out on four blood cancer dataset to validate the method as well as to establish the significance of imputation.

Methods: A new method, namely, DSNN, was proposed for missing value imputation on gene expression data. Method was validated on four dataset, CLL, AML, MM (Spanish data), and MM (Indian data). All the dataset were downloaded from GEO repository. Missing values were introduced in the original data from 10 to 90% in steps of 10% because method validation requires ground truth. Quantitative results on normalized mean square error (NMSE) between the ground truth and imputed data were computed. To further validate and establish the significance of the proposed imputation method, two experiments were carried out on the data imputed with the proposed method, data imputed with the state-of-art methods, and data with missing values. In the first experiment, classification of normal vs. cancer subjects was carried out. In the second experiment, biological significance of imputation was ascertained by identifying top candidate tumor drivers using the existing state-of-the-art SPARROW algorithm, followed by gene list enrichment analysis on top candidate drivers.

Results: Quantitative NMSE results of the DSNN method were compared with three state-of-the-art imputation methods. DSNN method was observed to perform better compared to these other methods both at high as well as low observable data. Experiment-1 demonstrated superior results on classification with imputation compared to that performed on missing data matrix as well as compared to classification on imputed data with existing methods. In experiment-2, cancer affected pathways were discovered with higher significance in the data imputed with the proposed method compared to those discovered with the missing data matrix.

Conclusion: Missing value problem in microarray data is a serious problem and can adversely influence downstream analysis. A novel method, namely, DSNN is proposed for missing value imputation. The method is validated quantitatively on the application of classification and biologically by performing pathway enrichment analysis.

A novel one-class classification approach to accurately predict disease-gene association in acute myeloid leukemia cancer

Disease causing gene identification is considered as an important step towards drug design and drug discovery. In disease gene identification and classification, the main aim is to identify disease genes while identifying non-disease genes are of less or no significant. Hence, this task can be defined as a one-class classification problem. Existing machine learning methods typically take into consideration known disease genes as positive training set and unknown genes as negative samples to build a binary-class classification model. Here we propose a new One-class Classification Support Vector Machines (OCSVM) method to precisely classify candidate disease genes. Our aim is to build a model that concentrate its focus on detecting known disease-causing gene to increase sensitivity and precision. We investigate the impact of our proposed model using a benchmark consisting of the gene expression dataset for Acute Myeloid Leukemia (AML) cancer. Compared with the traditional methods, our experimental result shows the superiority of our proposed method in terms of precision, recall, and F-measure to detect disease causing genes for AML. OCSVM codes and our extracted AML benchmark are publicly available at: https://github.com/imandehzangi/OCSVM.

KDM3B suppresses APL progression by restricting chromatin accessibility and facilitating the ATRA-mediated degradation of PML/RARα

Background

A hallmark of acute promyelocytic leukemia (APL) is the expression of PML/RARα fusion protein. Treatment with all-trans retinoic acid (ATRA) results in the terminal differentiation of neutrophil granulocytes. However, the underlying mechanisms remain largely unknown. Here, we identify and elucidate a novel differentiation-suppressive model of APL involving the histone demethylase KDM3B, which has been identified as a suppressor of the tumor genes involved in hematopoietic malignancies.

Methods

First, we established a KDM3B knockdown NB4 cell model to determine the functional characteristics of KDM3B by cell proliferation assay and flow cytometry. Then, we performed ChIP-seq and ATAC-seq to search for potential relationships among KDM3B, histone modification (H3K9me1/me2) and the chromatin state. Finally, molecular biological techniques and a multi-omics analysis were used to explore the role of KDM3B in differentiation of the leukemia cells after ATRA treatment.

Results

We found that knocking down KDM3B contributed to the growth of NB4 APL cells via the promotion of cell-cycle progression and blocked granulocytic differentiation. Through global and molecular approaches, we provided futher evidence that knocking down KDM3B altered the global distribution of H3K9me1/me2 and increased the chromatin accessibility. Moreover, knocking down KDM3B inhibited the ATRA-induced degradation of the PML/RARα oncoprotein.

Conclusion

Our study suggested that KDM3B was able to inhibit APL progression by maintaining chromatin in a compact state and facilitating the ATRA-mediated degradation of PML/RARα. Taken together, the results show that KDM3B may be an alternative target for the treatment regimens and the targeted therapy for APL by sustaining the function of PML/RARα fusion protein.

A comprehensive study on genome-wide coexpression network of KHDRBS1/Sam68 reveals its cancer and patient-specific association

Human KHDRBS1/Sam68 is an oncogenic splicing factor involved in signal transduction and pre-mRNA splicing. We explored the molecular mechanism of KHDRBS1 to be a prognostic marker in four different cancers. Within specific cancer, including kidney renal papillary cell carcinoma (KIRP), lung adenocarcinoma (LUAD), acute myeloid leukemia (LAML), and ovarian cancer (OV), KHDRBS1 expression is heterogeneous and patient specific. In KIRP and LUAD, higher expression of KHDRBS1 affects the patient survival, but not in LAML and OV. Genome-wide coexpression analysis reveals genes and transcripts which are coexpressed with KHDRBS1 in KIRP and LUAD, form the functional modules which are majorly involved in cancer-specific events. However, in case of LAML and OV, such modules are absent. Irrespective of the higher expression of KHDRBS1, the significant divergence of its biological roles and prognostic value is due to its cancer-specific interaction partners and correlation networks. We conclude that rewiring of KHDRBS1 interactions in cancer is directly associated with patient prognosis.

Not Only Mutations Matter: Molecular Picture of Acute Myeloid Leukemia Emerging from Transcriptome Studies

The last two decades of genome-scale research revealed a complex molecular picture of acute myeloid leukemia (AML). On the one hand, a number of mutations were discovered and associated with AML diagnosis and prognosis; some of them were introduced into diagnostic tests. On the other hand, transcriptome studies, which preceded AML exome and genome sequencing, remained poorly translated into clinics. Nevertheless, gene expression studies significantly contributed to the elucidation of AML pathogenesis and indicated potential therapeutic directions. The power of transcriptomic approach lies in its comprehensiveness; we can observe how genome manifests its function in a particular type of cells and follow many genes in one test. Moreover, gene expression measurement can be combined with mutation detection, as high-impact mutations are often present in transcripts. This review sums up 20 years of transcriptome research devoted to AML. Gene expression profiling (GEP) revealed signatures distinctive for selected AML subtypes and uncovered the additional within-subtype heterogeneity. The results were particularly valuable in the case of AML with normal karyotype which concerns up to 50% of AML cases. With the use of GEP, new classes of the disease were identified and prognostic predictors were proposed. A plenty of genes were detected as overexpressed in AML when compared to healthy control, including KIT, BAALC, ERG, MN1, CDX2, WT1, PRAME, and HOX genes. High expression of these genes constitutes usually an unfavorable prognostic factor. Upregulation of FLT3 and NPM1 genes, independent on their mutation status, was also reported in AML and correlated with poor outcome. However, transcriptome is not limited to the protein-coding genes; other types of RNA molecules exist in a cell and regulate genome function. It was shown that microRNA (miRNA) profiles differentiated AML groups and predicted outcome not worse than protein-coding gene profiles. For example, upregulation of miR-10a, miR-10b, and miR-196b and downregulation of miR-192 were found as typical of AML with NPM1 mutation whereas overexpression of miR-155 was associated with FLT3-internal tandem duplication (FLT3-ITD). Development of high-throughput technologies and microarray replacement by next generation sequencing (RNA-seq) enabled uncovering a real variety of leukemic cell transcriptomes, reflected by gene fusions, chimeric RNAs, alternatively spliced transcripts, miRNAs, piRNAs, long noncoding RNAs (lncRNAs), and their special type, circular RNAs. Many of them can be considered as AML biomarkers and potential therapeutic targets. The relations between particular RNA puzzles and other components of leukemic cells and their microenvironment, such as exosomes, are now under investigation. Hopefully, the results of this research will shed the light on these aspects of AML pathogenesis which are still not completely understood.

Elevated SPINK2 gene expression is a predictor of poor prognosis in acute myeloid leukemia

Acute myeloid leukemia (AML) has a high mortality rate and its clinical management remains challenging. The aim of the present study was to identify the hub genes involved in AML. In order to do so, the gene expression data of the GSE9476 database, including 26 AML and 10 normal samples, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were then identified via bioinformatics analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed on DEGs. Furthermore, the most upregulated genes were selected for further investigation in the Oncomine, gene expression profiling interactive analysis and UALCAN datasets. In total, 1,744 upregulated and 1,956 downregulated genes were detected. The GO and KEGG results revealed that upregulated genes were enriched in metabolic processes, while downregulated genes were associated with the immune response. Serine protease inhibitor Kazal-type 2 (SPINK2) ranked first among all the upregulated genes and was regarded as a hub gene in the development of AML. The overexpression of SPINK2 was validated in 12 patients with AML from the Linyi Central Hospital and in data from the Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Furthermore, the UALCAN and GEPIA datasets demonstrated that patients with high SPINK2 levels had shorter survival times. In conclusion, the results from the present study revealed that the SPINK2 gene was upregulated in patients with AML and that elevated SPINK2 expression was associated with poor outcomes in these patients.

TNF-α Coordinates Hematopoietic Stem Cell Survival and Myeloid Regeneration

Inflammation coordinates tissue regeneration via damaged cell removal and stem cell activation. Hematopoietic stem cells (HSCs) survive inflammatory stress that kills other blood cells, but the mechanisms underlying this effect remain poorly understood. Here, we find that tumor necrosis factor α (TNF-α) acts differently on HSCs and progenitors, thus facilitating hematopoietic clearance and promoting regeneration. We show that while inducing myeloid progenitor apoptosis, TNF-α promotes HSC survival and myeloid differentiation by activating a strong and specific p65-nuclear factor κB (NF-κB)-dependent gene program that primarily prevents necroptosis rather than apoptosis, induces immunomodulatory functions, and poises HSCs for myeloid cell production. These TNF-α-driven mechanisms are critical for HSC response to inflammatory stress but are also hijacked in aged and malignant HSCs. Our results reveal several TNF-α-mediated pro-survival mechanisms unique to HSCs, highlight an important role for necroptosis in HSC killing, and establish TNF-α as a major pro-survival and pro-regeneration factor for HSCs.

CEBPE expression is an independent prognostic factor for acute myeloid leukemia

Background

Identifying reliable predictive markers is important to make therapeutic decisions, and determine the prognosis for acute myeloid leukemia (AML) patients. However, approximately 50% patients could not be accurately predicted by existing risk factors. It is necessary to identify novel prognostic factors to subdivide the intermediate-risk group or patients without any cytogenetic and molecular abnormalities.

Methods

Kaplan–Meier and Cox regression were used for survival analyses in three independent AML datasets. Analyses integrating both bioinformatics and ChIP-qPCR experiments were performed to explore the role of CEBPE in regulating the expression of known prognostic factors.

Results

CEBPE expression was an independent predictor for both overall survival (OS) and event-free survival (EFS) of AML patients. Moreover, low-expression of CEBPE was found to be associated with high relapse rate. We also proved that differential expression of CEBPE stratified the wild-type patients of multiple genes into good and poor outcomes. In addition, the results showed that no obvious improvement was achieved by allogeneic transplantation in CEBPE high-expressed group, while the survival rate (both OS and EFS) was significantly increased in transplanted patients that with low expression of CEBPE. Finally, we found that CEBPE might regulate the expression of known prognostic factors by localizing on their promoters.

Conclusion

Our findings indicated that CEBPE expression was an independent prognostic factor for AML survival, relapse and allogeneic transplantation, which will provide useful information for outcome prediction and therapeutic decisions.

Electronic supplementary material

The online version of this article (10.1186/s12967-019-1944-x) contains supplementary material, which is available to authorized users.

RUNX1 inhibits proliferation and induces apoptosis of t(8;21) leukemia cells via KLF4-mediated transactivation of P57

RUNX1 is a key transcription factor in hematopoiesis and its disruption is one of the most common aberrations in acute myeloid leukemia. RUNX1 alterations affect its DNA binding capacity and transcriptional activities, leading to the deregulation of transcriptional targets, and abnormal proliferation and differentiation of myeloid cells. Identification of RUNX1 target genes and clarification of their biological functions are of great importance in the search for new therapeutic strategies for RUNX1-altered leukemia. In this study, we identified and confirmed that KLF4, a known tumor suppressor gene, as a direct target of RUNX1, was down-regulated in RUNX1-ETO leukemia. RUNX1 bound to KLF4 promoter in chromatin to activate its transcription, while the leukemogenic RUNX1-ETO fusion protein had little effect on this transactivation. KLF4 was also identified as a novel binding partner of RUNX1. RUNX1 interacted with KLF4 through Runt domain and further co-activated its target genes. However, RUNX1-ETO competed with RUNX1 to bind KLF4 through Runt and ETO domains, and abrogated transcription of KLF4. Finally, overexpression experiments indicated that RUNX1 inhibited proliferation and induced apoptosis of t(8;21) leukemia cells via KLF4-mediated upregulation of P57. These data suggest KLF4 dysregulation mediated by RUNX1-ETO enhances proliferation and retards apoptosis, and provides a potential target for therapy of t(8;21) acute myeloid leukemia.

A germline HLTF mutation in familial MDS induces DNA damage accumulation through impaired PCNA polyubiquitination

Although several causal genes of familial myelodysplastic syndromes (MDS) have been identified, the genetic landscape and the molecular pathogenesis are not totally understood. To explore novel driver genes and their pathogenetic significance, we performed whole-exome sequence analysis of four individuals from a familial MDS pedigree and 10 candidate single-nucleotide variants (C9orf43, CYP7B1, EFHB, ENTPD7, FAM160B2, HELZ2, HLTF, INPP5J, ITPKB, and RYK) were identified. Knockdown screening revealed that Hltf downregulation enhanced colony-forming capacity of primary murine bone marrow (BM) stem/progenitor cells. γH2AX immunofluorescent staining assay revealed increased DNA damage in a human acute myeloid leukemia (AML) cell line ectopically expressing HLTF E259K, which was not observed in cells expressing wild-type HLTF. Silencing of HLTF in human AML cells also led to DNA damage, indicating that HLTF E259K is a loss-of-function mutation. Molecularly, we found that an E259K mutation reduced the binding capacity of HLTF with ubiquitin-conjugating enzymes, methanesulfonate sensitive 2 and ubiquitin-conjugating enzyme E2N, resulting in impaired polyubiquitination of proliferating cell nuclear antigen (PCNA) in HLTF E259K-transduced cells. In summary, our results indicate that a familial MDS-associated HLTF E259K germline mutation induces accumulation of DNA double-strand breaks, possibly through impaired PCNA polyubiquitination.

Repression of Mcl-1 expression by the CDC7/CDK9 inhibitor PHA-767491 overcomes bone marrow stroma-mediated drug resistance in AML

Acute myeloid leukaemia (AML) is an aggressive cancer with 50-75% of patients relapsing even after successful chemotherapy. The role of the bone marrow microenvironment (BMM) in protecting AML cells from chemotherapeutics and causing consequent relapse is increasingly recognised. However the role that the anti-apoptotic Bcl-2 proteins play as effectors of BMM-mediated drug resistance are less understood. Here we show that bone marrow mesenchymal stromal cells (BMSC) provide resistance to AML cells against BH₃-mimetics, cytarabine and daunorubicin, but this is not mediated by Bcl-2 and/or Bcl-X_L as previously thought. Instead, BMSCs induced Mcl-1 expression over Bcl-2 and/or Bcl-X_L in AML cells and inhibition of Mcl-1 with a small-molecule inhibitor, A1210477, or repressing its expression with the CDC7/CDK9 dual-inhibitor, PHA-767491 restored sensitivity to BH₃-mimetics. Furthermore, combined inhibition of Bcl-2/Bcl-X_L and Mcl-1 could revert BMSC-mediated resistance against cytarabine + daunorubicin. Importantly, the CD34⁺/CD38^- leukemic stem cell-encompassing population was equally sensitive to the combination of PHA-767491 and ABT-737. These results indicate that Bcl-2/Bcl-X_L and Mcl-1 act in a redundant fashion as effectors of BMM-mediated AML drug resistance and highlight the potential of Mcl-1-repression to revert BMM-mediated drug resistance in the leukemic stem cell population, thus, prevent disease relapse and ultimately improve patient survival.

FUT4 is involved in PD-1-related immunosuppression and leads to worse survival in patients with operable lung adenocarcinoma

PURPOSE

As an important glycosyltransferase, fucosyltransferase IV (FUT4) is abnormally upregulated in different types of cancers, but its clinical role remains inexplicit. This work aimed to determine the predictive ability of FUT4 in lung adenocarcinoma (LUAD) after curative resection, as well as to explore the role of a possible FUT4 molecular mechanism on LUAD malignant behavior.

METHODS

A total of 273 LUAD patients after curative resection with complete clinicopathological and RNAseq data from The Cancer Genome Atlas (TCGA) cohort were collected. Correlation of FUT4 with overall survival (OS) was analyzed based on TCGA and further validated by online "Kaplan-Meier Plotter" database and IHC in 70 LUAD patients recruited in the First Hospital of China Medical University cohort. Multivariate Cox regression analysis and 1000 bootstrapping were performed to verify the predictive value of FUT4. Gene set enrichment assay (GSEA) was performed to investigate the biological characteristics. Correlation between PD-1 and FUT4 was analyzed based on TCGA cohort and validated by IHC on cohort from our hospital.

RESULTS

Increased FUT4 expression led to reduced overall survival (OS) of LUAD patients based on TCGA (p = 0.006 and 0.001 for dichotomous and trichotomous modeling, respectively) and externally validated in KMPLOTTER (p = 0.01) and by IHC based on cohort from our hospital (p = 0.005 and p = 0.019 for dichotomous and trichotomous modeling, respectively). FUT4 overexpression was an independent high risk factor for OS along with advanced pT stage and pTNM stage (p = 0.001, p = 0.037, and p < 0.001, respectively). GSEA revealed that FUT4 overexpression might correlate with shortened survival of LUAD patients by promoting cell proliferation via ERBB signaling, and suppressing immune response-related pathways. FUT4 expression positively correlated with PD-1 in TCGA (p = 0.026) and validated by IHC on cohort from our hospital (p = 0.029).

CONCLUSIONS

Increased FUT4 expression led to reduced OS in operable LUAD. FUT4 showed significant correlation with immune response and PD-1 expression.

Integrated bioinformatic analysis of microarray data reveals shared gene signature between MDS and AML

Myeloid disorders, especially myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), cause significant mobility and high mortality worldwide. Despite numerous attempts, the common molecular events underlying the development of MDS and AML remain to be established. In the present study, 18 microarray datasets were selected, and a meta-analysis was conducted to identify shared gene signatures and biological processes between MDS and AML. Using NetworkAnalyst, 191 upregulated and 139 downregulated genes were identified in MDS and AML, among which, PTH2R, TEC, and GPX1 were the most upregulated genes, while MME, RAG1, and CD79B were mostly downregulated. Comprehensive functional enrichment analyses revealed oncogenic signaling related pathway, fibroblast growth factor receptor (FGFR) and immune response related events, 'interleukine-6/interferon signaling pathway, and B cell receptor signaling pathway', were the most upregulated and downregulated biological processes, respectively. Network based meta-analysis ascertained that HSP90AA1 and CUL1 were the most important hub genes. Interestingly, our study has largely clarified the link between MDS and AML in terms of potential pathways, and genetic markers, which shed light on the molecular mechanisms underlying the development and transition of MDS and AML, and facilitate the understanding of novel diagnostic, therapeutic and prognostic biomarkers.

Plexin C1 Marks Liver Cancer Cells with Epithelial Phenotype and Is Overexpressed in Hepatocellular Carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma is an aggressive malignancy of the liver and is ranked as the sixth most common cancer worldwide. There is still room for novel markers to improve the diagnosis and monitoring of HCC. Our observations in cancer databases that PLXNC1 is upregulated in HCC led us to investigate the expression profile of Plexin C1 mRNA and protein in HCC cell lines and tissues.

METHODS

A recombinant protein encompassing part of the extracellular domain of Plexin C1 was used as an antigen for monoclonal antibody development. Transcript and protein levels of Plexin C1 in HCC cell lines were determined by RT-qPCR and Western blotting, respectively. In vivo evaluation of Plexin C1 expression in HCC tissues was accomplished by immunohistochemistry studies in tissue microarrays.

RESULTS

A monoclonal antibody, clone PE4, specific to Plexin C1, was generated. In silico and in vitro analyses revealed a Plexin C1-based clustering of well-differentiated HCC cell lines. Staining of HCC and nontumoral liver tissues with PE4 showed a membrane-localized overexpression of Plexin C1 in tumors (p=0.0118). In addition, this expression was correlated with the histological grades of HCC cases.

CONCLUSIONS

Plexin C1 distinguishes HCC cells of epithelial characteristics from those with the mesenchymal phenotype. Compared to the nontumoral liver, HCC tissues significantly overexpress Plexin C1. The newly generated PE4 antibody can be evaluated in larger HCC cohorts and might be exploited for the examination of Plexin C1 expression pattern in other epithelial malignancies.

JMJD3 facilitates C/EBPβ-centered transcriptional program to exert oncorepressor activity in AML

JMJD3, a stress-inducible H3K27 demethylase, plays a critical regulatory role in the initiation and progression of malignant hematopoiesis. However, how this histone modifier affects in a cell type-dependent manner remains unclear. Here, we show that in contrast to its oncogenic effect in preleukemia state and lymphoid malignancies, JMJD3 relieves the differentiation-arrest of certain subtypes (such as M2 and M3) of acute myeloid leukemia (AML) cells. RNA sequencing and ChIP−PCR analyses revealed that JMJD3 exerts anti-AML effect by directly modulating H3K4 and H3K27 methylation levels to activate the expression of a number of key myelopoietic regulatory genes. Mechanistic exploration identified a physical and functional association of JMJD3 with C/EBPβ that presides the regulatory network of JMJD3. Thus, the leukemia regulatory role of JMJD3 varies in a disease phase- and lineage-dependent manner, and acts as a potential oncorepressor in certain subsets of AML largely by coupling to C/EBPβ-centered myelopoietic program.

Histone demethylase JMJD3 is known to be oncogenic in preleukemic states and T-cell acute lymphocytic leukemia. Here, the authors show that in some acute myeloid leukemia subsets, JMJD3 can actually act as a potential oncorepressor via mediation of C/EBPβ-centered transcriptional programming.

Glycogene expression profiles based on microarray data from cervical carcinoma HeLa cells with partially silenced E6 and E7 HPV oncogenes

Background

Aberrant glycosylation is a characteristic of tumour cells. The expression of certain glycan structures has been associated with poor prognosis. In cervical carcinoma, changes in the expression levels of some glycogenes have been associated with lymph invasion. Human papillomavirus (HPV) infection is one of the most important factors underlying the development of cervical cancer. The HPV oncoproteins E6 and E7 have been implicated in cervical carcinogenesis and can modify the host gene expression profile. The roles of these oncoproteins in glycosylation changes have not been previously reported.

Methods

To determine the effect of the E6 and E7 oncoproteins on glycogene expression we partially silenced the E6 and E7 oncogenes in HeLa cells, we performed a microarray expression assay to identify altered glycogenes and quantified the mRNA levels of glycogenes by RT-qPCR. A protein-protein interaction network was constructed to identify potentially altered glycosylation pathways.

Results

The microarray analysis showed 9 glycogenes that were upregulated and 7 glycogenes that were downregulated in HeLa shE6/E7 cells. Some of these genes participate in glycosylation related to Notch proteins and O-glycans antigens.

Conclusions

Our results support that E6 and E7 oncoproteins could modify glycogene expression the products of which participate in the synthesis of structures implicated in proliferation, adhesion and apoptosis.

Gene mutations and clonal architecture in myelodysplastic syndromes and changes upon progression to acute myeloid leukaemia and under treatment

Knowledge of the molecular and clonal characteristics in the myelodysplastic syndromes (MDS) and during progression to acute myeloid leukaemia (AML) is essential to understand the disease dynamics and optimize treatment. Sequencing serial bone marrow samples of eight patients, we observed that MDS featured a median of 3 mutations. Mutations in genes involved in RNA-splicing or epigenetic regulation were most frequent, and exclusively present in the major clone. Minor subclones were distinguishable in three patients. As the MDS progressed, a median of one mutation was gained, leading to clonal outgrowth. No AML developed genetically independent of a pre-existing clone. The gained mutation mostly affected genes encoding signalling proteins. Additional acquisition of genomic aberrations frequently occurred. Upon treatment, emergence of new clones could be observed. As confirmed by single-cell sequencing, multiple mutations in identical genes in different clones were present within individual patients. DNA-methylation profiling in patients without identification of novel mutations in AML revealed methylation changes in individual genes. In conclusion, our data complement previous observations on the mutational and clonal characteristics in MDS and at progression. Moreover, DNA-methylation changes may be associated with progression in single patients. Redundancy of mutated genes in different clones suggests fertile grounds promoting clonal selection or acquisition.

Similarity of regulatory network between leukemia stem cells and normal hemopoietic stem cells

To reveal the biology of AML, we compared gene-expression profiles between normal hematopoietic cells from 38 healthy donors and leukemic blasts (LBs) from 26 AML patients. We defined the comparison of LB and unselected BM as experiment 1, LB and CD34+ isolated from BM as experiment 2, LB and unselected PB as experiment 3, and LB and CD34+ isolated from PB as experiment 4. Then, protein–protein interaction network of DEGs was constructed to identify critical genes. Regulatory impact factors were used to identify critical transcription factors from the differential co-expression network constructed via reanalyzing the microarray profile from the perspective of differential co-expression. Gene ontology enrichment was performed to extract biological meaning. The comparison among the number of DEGs obtained in four experiments showed that cells did not tend to differentiation and CD34+ was more similar to cancer stem cells. Based on the results of protein–protein interaction network,CREBBP,F2RL1,MCM2, andTP53were respectively the key genes in experiments 1, 2, 3, and 4. From gene ontology analysis, we found that immune response was the most common one in four stages. Our results might provide a platform for determining the pathology and therapy of AML.