175 Pathway enrichment analysis of acute myeloid leukemia pathogenesis: a focus on JAK-STAT signalling pathway

Acute myeloid leukemia (AML) is a highly heterogeneous hematologic neoplasm with poor survival outcomes. However, the routine clinical features are not sufficient to accurately predict the prognosis of AML. The expression of hypoxia-related genes was associated with survival outcomes of a variety of hematologic and lymphoid neoplasms. We established an 18-gene signature-based hypoxia-related prognosis model (HPM) and a complex model that consisted of the HPM and clinical risk factors using machine learning methods. Both two models were able to effectively predict the survival of AML patients, which might contribute to improving risk classification. Differentially expressed genes analysis, Gene Ontology (GO) categories, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to reveal the underlying functions and pathways implicated in AML development. To explore hypoxia-related changes in the bone marrow immune microenvironment, we used CIBERSORT to calculate and compare the proportion of 22 immune cells between the two groups with high and low hypoxia-risk scores. Enrichment analysis and immune cell composition analysis indicated that the biological processes and molecular functions of drug metabolism, angiogenesis, and immune cell infiltration of bone marrow play a role in the occurrence and development of AML, which might help us to evaluate several hypoxia-related metabolic and immune targets for AML therapy.

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Network Pharmacology and Experimental Validation Reveal the Effects of Chidamide Combined With Aspirin on Acute Myeloid Leukemia-Myelodysplastic Syndrome Cells Through PI3K/AKT Pathway

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.685954 ◽

2021 ◽

Vol 9 ◽

Author(s):

Simin Liang ◽

Xiaojia Zhou ◽

Duo Cai ◽

Fernando Rodrigues-Lima ◽

Jianxiang Chi ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Combination Treatment ◽

Myeloid Leukemia ◽

Experimental Validation ◽

Cell Counting ◽

Akt Pathway ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Acute Myeloid

Chidamide (CDM), a novel histone deacetylase inhibitor, is currently used for patients with peripheral T-cell lymphoma. Aspirin (ASA), an anti-inflammatory drug, has been shown to exert anticancer activity. Herein, we investigated the effect of CDM combined with ASA on myelodysplastic syndromes-derived acute myeloid leukemia (AML-MDS) cells and explored the underlying mechanism. The putative targets of CDM and ASA were predicted by network pharmacology approach. GO functional and KEGG pathway enrichment analyses were performed by DAVID. Furthermore, experimental validation was conducted by Cell Counting Kit-8 assay, Flow cytometry and Western blotting. Network pharmacology analysis revealed 36 AML-MDS-related overlapping genes that were targets of CDM and ASA, while 10 hub genes were identified by the plug-in cytoHubba in Cytoscape. Pathway enrichment analysis indicated CDM and ASA significantly affected PI3K/AKT signaling pathway. Functional experiments demonstrated that the combination of CDM and ASA had a remarkable synergistic anti-proliferative effect by blocking the cell cycle in G0/G1 phase and inducing apoptosis. Mechanistically, the combination treatment significantly down-regulated the phosphorylation levels of PI3K and AKT. In addition, insulin-like growth factor 1 (IGF-1), an activator of PI3K/AKT pathway, reversed the effects of the combination treatment. Our findings suggested that CDM combined with ASA exerted a synergetic inhibitory effect on cell growth by inactivating PI3K/AKT pathway, which might pave the way for effective treatments of AML-MDS.

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TET2/IDH1/2/WT1 and NPM1 Mutations Influence the RUNX1 Expression Correlations in Acute Myeloid Leukemia

Medicina ◽

10.3390/medicina56120637 ◽

2020 ◽

Vol 56 (12) ◽

pp. 637

Author(s):

Sergiu Pasca ◽

Ancuta Jurj ◽

Ciprian Tomuleasa ◽

Mihnea Zdrenghea

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Mutational Analysis ◽

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Runx1 Expression ◽

Acute Myeloid

Background and objectives: Mutational analysis has led to a better understanding of acute myeloid leukemia (AML) biology and to an improvement in clinical management. Some of the most important mutations that affect AML biology are represented by mutations in genes related to methylation, more specifically: TET2, IDH1, IDH2 and WT1. Because it has been shown in numerous studies that mutations in these genes lead to similar expression profiles and phenotypes in AML, we decided to assess if mutations in any of those genes interact with other genes important for AML. Materials and Methods: We downloaded the clinical data, mutational profile and expression profile from the TCGA LAML dataset via cBioPortal. Data were analyzed using classical statistical methods and functional enrichment analysis software represented by STRING and GOrilla. Results: The first step we took was to assess the 196 AML cases that had a mutational profile available and observe the mutations that overlapped with TET2/IDH1/2/WT1 mutations. We observed that RUNX1 mutations significantly overlap with TET2/IDH1/2/WT1 mutations. Because of this, we decided to further investigate the role of RUNX1 mutations in modulating the level of RUNX1 mRNA and observed that RUNX1 mutant cases presented higher levels of RUNX1 mRNA. Because there were only 16 cases of RUNX1 mutant samples and that mutations in this gene determined a change in mRNA expression, we further observed the correlation between RUNX1 and other mRNAs in subgroups regarding the presence of hypermethylating mutations and NPM1. Here, we observed that both TET2/IDH1/2/WT1 and NPM1 mutations increase the number of genes negatively correlated with RUNX1 and that these genes were significantly linked to myeloid activation. Conclusions: In the current study, we have shown that NPM1 and TET2/IDH1/2/WT1 mutations increase the number of negative correlations of RUNX1 with other transcripts involved in myeloid differentiation.

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Predicting Complete Remission of Acute Myeloid Leukemia: Machine Learning Applied to Gene Expression

Cancer Informatics ◽

10.1177/1176935119835544 ◽

2019 ◽

Vol 18 ◽

pp. 117693511983554 ◽

Cited By ~ 5

Author(s):

Ophir Gal ◽

Noam Auslander ◽

Yu Fan ◽

Daoud Meerzaman

Keyword(s):

Gene Expression ◽

Machine Learning ◽

Acute Myeloid Leukemia ◽

Complete Remission ◽

Myeloid Leukemia ◽

Statistical Significance ◽

Expression Patterns ◽

Pathway Enrichment Analysis ◽

Data Set ◽

Acute Myeloid

Machine learning (ML) is a useful tool for advancing our understanding of the patterns and significance of biomedical data. Given the growing trend on the application of ML techniques in precision medicine, here we present an ML technique which predicts the likelihood of complete remission (CR) in patients diagnosed with acute myeloid leukemia (AML). In this study, we explored the question of whether ML algorithms designed to analyze gene-expression patterns obtained through RNA sequencing (RNA-seq) can be used to accurately predict the likelihood of CR in pediatric AML patients who have received induction therapy. We employed tests of statistical significance to determine which genes were differentially expressed in the samples derived from patients who achieved CR after 2 courses of treatment and the samples taken from patients who did not benefit. We tuned classifier hyperparameters to optimize performance and used multiple methods to guide our feature selection as well as our assessment of algorithm performance. To identify the model which performed best within the context of this study, we plotted receiver operating characteristic (ROC) curves. Using the top 75 genes from the k-nearest neighbors algorithm (K-NN) model ( K = 27) yielded the best area-under-the-curve (AUC) score that we obtained: 0.84. When we finally tested the previously unseen test data set, the top 50 genes yielded the best AUC = 0.81. Pathway enrichment analysis for these 50 genes showed that the guanosine diphosphate fucose (GDP-fucose) biosynthesis pathway is the most significant with an adjusted P value = .0092, which may suggest the vital role of N-glycosylation in AML.

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Identification of Seven Novel Ferroptosis-Related Long Non - Coding RNA Signatures as a Diagnostic Biomarker for Acute Myeloid Leukemia

10.21203/rs.3.rs-502041/v1 ◽

2021 ◽

Author(s):

Zhiyuan Zheng ◽

Wei Wu ◽

Zehang Lin ◽

Shuhan Liu ◽

Qiaoqian Chen ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Risk Score ◽

Myeloid Leukemia ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Kaplan Meier ◽

Acute Myeloid

Abstract Background: Ferroptosis is a newly discovered type of programmed cell death that participates in the biological processes of various cancers. However, the mechanism by which ferroptosis modulates acute myeloid leukemia (AML) remains unclear. This study aimed to investigate the role of ferroptosis-related long non-coding RNAs (lncRNAs) in AML and establish a corresponding prognostic model.Methods: RNA-sequencing data and clinicopathological characteristics were obtained from The Cancer Genome Atlas database, and ferroptosis-related genes were obtained from the FerrDb database. The “limma” R package, Cox regression, and the least absolute shrinkage and selection operator were used to determine the ferroptosis-related lncRNA signature with the lowest Akaike information criteria (AIC). The risk score of ferroptosis-related lncRNAs was calculated and patients with AML were divided into high- and low-risk groups based on the median risk score. The Kaplan-Meier curve and Cox regression were used to evaluate the prognostic value of the risk score. Finally, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological functions of the ferroptosis-related lncRNAs.Results: Seven ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan-Meier and Cox regression analyses confirmed that risk scores were independent prognostic predictors of AML in both the training and validation groups (All P < 0.05). In addition, the area under the curve (AUC) analysis confirmed that the signatures had a good predictive ability for the prognosis of AML. GSEA and ssGSEA showed that the seven ferroptosis-related lncRNAs were related to glutathione metabolism and tumor immunity.Conclusions: In this study, seven novel ferroptosis-related lncRNA signatures (AP001266.2, AC133961.1, AF064858.3, AC007383.2, AC008906.1, AC026771.1, and KIF26B-AS1) were established. These signatures were shown to accurately predict the prognosis of AML, which would provide new insights into strategies for the development of new AML therapies.

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Identification of a Prognostic Gene Signature Associated with Microenvironment in Acute Myeloid Leukemia

10.21203/rs.3.rs-91594/v1 ◽

2020 ◽

Author(s):

Zhixiang Chen ◽

Luya Ye ◽

Xuechun Wang ◽

Fuquan Tu ◽

Xuezhen Li ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Expression Profiles ◽

Critical Role ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Risk Scores ◽

Acute Myeloid

Abstract Background: Acute myeloid leukemia (AML) is a common hematologic malignancy with poor prognosis. Accumulating reports have indicated that the tumor microenvironment (TME) performs a critical role in the progress of the disease and the clinical outcomes of patients. To date, the role of TME in AML remains clouded due to the complex regulatory mechanisms in it. In this study, We identified key prognostic genes relate to TME in AML and developed a novel gene signature for individualized prognosis assessment. Methods: The expression profiles of AML samples with clinical information were obtained from the Cancer Genome Atlas (TCGA). The ESTIMATE algorithm was applied to calculate the TME relevant immune and stromal scores. The differentially expressed genes (DEGs) were selected based on the immune and stromal scores. Then, the survival analysis was applied to select prognostic DEGs, and these genes were annotated by functional enrichment analysis. A TME relevant gene signature with predictive capability was constructed by a series of regression analyses and performed well in another cohort from the Gene Expression Omnibus (GEO) database. Moreover, we also developed a nomogram with the integration of the gene signature and clinical indicators to establish an individually quantified risk-scoring system. Results: In the AML microenvironment, a total of 181 DEGs with prognostic value were clarified. Then a seven-gene ( IL1R2, MX1, S100A4, GNGT2, ZSCAN23, PLXNB1 and DPY19L2 ) signature with robust prediction was identified, and was validated by an independent cohort of AML samples from the GSE71014. Gene set enrichment analysis (GSEA) of genes in the gene signature revealed these genes mainly enriched in the immune and inflammatory related processes. The correlation between the signature-calculated risk scores and the clinical features indicated that patients with high risk scores were accompanied by adverse survival. Finally, a nomogram with clinical utility was constructed. Conclusion: Our study explored and identified a novel TME relevant seven-gene signature, which could serve as a prognostic indicator for AML. Meanwhile, we also establish a nomogram with clinical significance. These findings might provide new insights into the diagnosis, treatment and prognosis of AML.

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Network Pharmacology-Based Strategy for Predicting Therapy Targets of Tripterygium wilfordii on Acute Myeloid Leukemia

10.21203/rs.3.rs-29959/v1 ◽

2020 ◽

Author(s):

Tingting Fang ◽

Lanqin Liu ◽

wenjun liu

Keyword(s):

Acute Myeloid Leukemia ◽

Chinese Medicine ◽

Signaling Pathway ◽

Myeloid Leukemia ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Overlapping Genes ◽

Tripterygium Wilfordii ◽

Active Ingredients ◽

Acute Myeloid

Abstract Background. Acute myeloid leukemia (AML) is a common malignant tumor of the hematopoietic system. How to extend the survival time of AML patients and improve their prognosis is still a major medical problem. Chinese medicine has a long history in treating AML. Tripterygium wilfordii (TW) is a traditional Chinese medicine. With the deepening of pharmacological research of traditional Chinese medicine, triptolide, one of its active ingredients, has been proven to have a positive effect on the treatment of AML. Therefore，this study aimed on studying the potential therapeutic targets and pharmacological mechanism of TW in Acute myeloid leukemia (AML) based on network pharmacology.Methods. The active components of TW were obtained by network pharmacology through oral bioavailability, drug-likeness filtration. Comparative analysis was used to study the overlapping genes between active ingredient’s targets and AML treatment-related targets. Using STRING database to analyze interactions between overlapping genes. KEGG pathway analysis and Gene Ontology enrichment analysis were conducted in DAVID. These genes were analyzed for survival in OncoLnc database.Key findings. We screened 53 active ingredients, the results of comparative analysis showed that 8 active ingredients had an effect on AML treatment. Based on the active ingredients and overlapping genes, we constructed the Drug-Compounds-Genes-Disease Network. Survival analysis of overlapping genes indicated that some targets possess a significant influence on patients’ survival and prognosis. The enrichment analysis showed that the main pathways of targets are Toll-like receptor signaling pathway, NF-kappa B signaling pathway and HIF-1 signaling pathway.Conclusion. This study, using a network pharmacologic approach, provides another strategy that can help us to understand the mechanisms by which TW treats AML comprehensively.

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Withanolide Metabolites Inhibit PI3K/AKT and MAPK Pro-Survival Pathways and Induce Apoptosis in Acute Myeloid Leukemia Cells

Biomedicines ◽

10.3390/biomedicines8090333 ◽

2020 ◽

Vol 8 (9) ◽

pp. 333

Author(s):

Nosheen Akhtar ◽

Muhammad Waleed Baig ◽

Ihsan-ul Haq ◽

Vinothini Rajeeve ◽

Pedro Rodriguez Cutillas

Keyword(s):

Acute Myeloid Leukemia ◽

Protein Kinase ◽

Myeloid Leukemia ◽

Therapeutic Potential ◽

Mammalian Target Of Rapamycin ◽

Enrichment Analysis ◽

Label Free ◽

Anticancer Activities ◽

Acute Myeloid Leukemia Cells ◽

Acute Myeloid

Acute myeloid leukemia (AML) is an aggressive disease and, despite advances, its treatment remains challenging. Therefore, it remains important to identify new agents for the management of this disease. Withanolides, a group of steroidal lactones found in Solanaceae plants are of potential interest due to their reported anticancer activities in different settings. In this study we investigated the anti-proliferative effects and mode of action of Solanaceae-derived withanolides in AML cell models; these metabolites include withametelin (WTH) and Coagulansin A (CoA) isolated from Datura innoxia and Withania coagluanse, respectively. Both withanolides inhibited the proliferation of AML cells and induced cell death, with WTH being more potent than CoA in the AML models tested. Quantitative label-free proteomics and phosphoproteomics were employed to define the mechanism of action of the studied withanolides. We identified and quantified 5269 proteins and 17,482 phosphosites in cells treated with WTH, CoA or vehicle control. Withanolides modulated the expression of proteins involved in regulating key cellular processes including cell cycle, metabolism, signaling, protein degradation and gene expression. Enrichment analysis of the phosphoproteomics data against kinase substrates, kinase-kinase relationships and canonical pathways showed that the withanolides decreased the activity of kinases such as phosphoinositide 3-kinase (PI3K), protein kinase B (PKB; also known as RAC-alpha serine/threonine-protein kinase or AKT), mammalian target of rapamycin (mTOR), extracellular signal-regulated protein kinase 1 and 2 (ERK1/2) and the serine/threonine-protein kinase A-Raf (ARAF), while increasing the activation of DNA repair kinases. These results indicate that withanolide metabolites have pleiotropic effects in the modulation of oncogenic pro-survival and pro-apoptotic signaling pathways that regulate the induction of apoptosis. Withanolide mediated apoptosis was confirmed by immunoblotting showing increased expression of cleaved PARP and Caspases 3, 8 and 9 as a result of treatment. Overall, our results suggest that WTH and CoA have therapeutic potential against AML with WTH exhibiting more potent effects and should be explored further.

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Rational for targeting the hedgehog signalling pathway in acute myeloid leukemia with FLT3 mutation

Annals of Translational Medicine ◽

10.21037/atm.2016.10.29 ◽

2016 ◽

Vol 4 (S1) ◽

pp. S53-S53 ◽

Cited By ~ 6

Author(s):

Didier Bouscary

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Signalling Pathway ◽

Hedgehog Signalling ◽

Flt3 Mutation ◽

Hedgehog Signalling Pathway ◽

Acute Myeloid

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The Multi-Omic Prognostic Model of Oxidative Stress-Related Genes in Acute Myeloid Leukemia

Frontiers in Genetics ◽

10.3389/fgene.2021.722064 ◽

2021 ◽

Vol 12 ◽

Author(s):

Chao Dong ◽

Naijin Zhang ◽

Lijun Zhang

Keyword(s):

Oxidative Stress ◽

Acute Myeloid Leukemia ◽

Signaling Pathways ◽

Myeloid Leukemia ◽

Risk Model ◽

Enrichment Analysis ◽

Chemotherapeutic Agents ◽

The Cancer Genome Atlas ◽

Stress Genes ◽

Acute Myeloid

Background: Acute myeloid leukemia (AML) is one of the most common cancers in the world, and oxidative stress is closely related to leukemia. A lot of effort has been made to improve the prognosis of AML. However, the situation remains serious. Hence, we focused on the study of prognostic genes in AML.Materials and Methods: Prognostic oxidative stress genes were screened out. The gene expression profile of AML patients was downloaded from the The Cancer Genome Atlas (TCGA) database. The oxidative stress-related model was constructed, by which the prognosis of AML patients was predicted using the two GEO GSE23143 datasets and the stability of the GSE71014 authentication model.Results: The prognostic oxidative stress genes were screened out in AML, and the prognostic genes were significantly enriched in a large number of pathways based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. There was a complex interaction between prognostic genes and transcription factors. After constructing the prediction model, the clinical predictive value of the model was discussed in a multi-omic study. We investigated the sensitivity of risk score to common chemotherapeutic agents, the influence of signaling pathways on the prognosis of AML patients, and the correlation of multiple genes with immune score and immune dysfunction.Conclusions: A highly effective prognostic risk model for AML patients was established and validated. The association of prognostic oxidative stress genes with drug sensitivity, signaling pathways, and immune infiltration was explored. The results suggested that oxidative stress genes promised to be potential prognostic biomarkers for AML, which may provide a new basis for disease management.

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