Identification of Key Genes and Pathways Associated with RUNX1 Mutations in Acute Myeloid Leukemia Using Bioinformatics Analysis

Missense mutations of GPER1 in breast invasive carcinoma: Exploring gene expression, signal transduction and immune cell infiltration with insights from cellular pharmacology

G protein-coupled estrogen receptor 1 (GPER1) plays a crucial role in the progression of breast cancer and has emerged as a promising therapeutic target. However, while missense mutations in GPER1 have been detected in breast invasive carcinoma (BIC) samples, the resulting molecular, cellular and pharmacological changes remain unclear. The present study categorized BIC samples from The Cancer Genome Atlas database based on mutation information available in the cBioPortal database. Subsequently, survival analysis was conducted and the samples screened for differentially expressed genes (DEGs). Using these DEGs, the present study performed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, protein-protein interaction network analysis and hub gene selection. After assessing the prognostic value of hub genes, the immune cell infiltration between mutant and wild-type (WT) groups was analyzed. Finally, a luciferase reporter system was used to assess the cyclic AMP (cAMP) production mediated by GPER1 following treatment with the agonist G-1 for each mutation. The results revealed a significant decrease in progression-free survival and disease-specific survival in the GPER1 mutant group compared with the WT group. Gene expression analysis identified 60 DEGs, all of which were upregulated and significantly enriched in GO terms related to tumor progression, such as organic anion transport, glycosaminoglycan binding and monoatomic ion-gated channel activity. DEGs were also significantly enriched in the PI3K-Akt signaling pathway in KEGG. Hub gene selection and prognostic evaluation identified three genes significantly associated with survival: IL33, STAB2 and CFTR. Immune cell infiltration analysis revealed a significant decrease in CD8 T cell content in the GPER1 mutant group compared with the WT group. Luciferase reporter assays demonstrated that four missense mutations in GPER1 (L129M, E218Q, S235F and A345G) significantly attenuated the induction of cyclic adenosine monophosphate production mediated by its agonist. These findings provided valuable insights for the design of breast cancer drugs targeting GPER1 and for precision medicine initiatives.

Protein Arginine Methyltransferases as Therapeutic Targets in Hematological Malignancies

Arginine methylation is a common post-translational modification affecting protein activity and the transcription of target genes when methylation occurs on histone tails. There are nine protein arginine methyltransferases (PRMTs) in mammals, divided into subgroups depending on the methylation they form on a molecule of arginine. During the formation and maturation of the different types of blood cells, PRMTs play a central role by controlling cell differentiation at the transcriptional level. PRMT enzymatic activity is necessary for many cellular processes in hematological malignancies, such as the activation of cell cycle and proliferation, inhibition of apoptosis, DNA repair processes, RNA splicing, and transcription by methylating histone tails' arginine. Chemical tools have been developed to inhibit the activity of PRMTs and have been tested in several models of hematological malignancies, including primary samples from patients, xenografts into immunodeficient mice, mouse models, and human cell lines. They show a significant effect by reducing cell viability and increasing the overall survival of mice. PRMT5 inhibitors have a strong therapeutic potential, as phase I clinical trials in hematological malignancies that use these molecules show promising results, thus, underlining PRMT inhibitors as useful therapeutic tools for cancer treatment in the future.

PP1, PKA and DARPP-32 in breast cancer: A retrospective assessment of protein and mRNA expression

Cyclic AMP–dependent protein kinase A (PKA) and protein phosphatase 1 (PP1) are proteins involved in numerous essential signalling pathways that modulate physiological and pathological functions. Both PP1 and PKA can be inhibited by dopamine‐ and cAMP‐regulated phosphoprotein 32 kD (DARPP‐32). Using immunohistochemistry, PKA and PP1 expression was determined in a large primary breast tumour cohort to evaluate associations between clinical outcome and clinicopathological criteria (n > 1100). In addition, mRNA expression of PKA and PP1 subunits was assessed in the METABRIC data set (n = 1980). Low protein expression of PKA was significantly associated with adverse survival of breast cancer patients; interestingly, this relationship was stronger in ER‐positive breast cancer patients. PP1 protein expression was not associated with patient survival. PKA and PP1 subunit mRNA was also assessed; PPP1CA, PRKACG and PRKAR1B were associated with breast cancer–specific survival. In patients with high expression of DARPP‐32, low expression of PP1 was associated with adverse survival when compared to high expression in the same group. PKA expression and PP1 expression are of significant interest in cancer as they are involved in a wide array of cellular processes, and these data indicate PKA and PP1 may play an important role in patient outcome.

MicroRNA-363-3p promote the development of acute myeloid leukemia with RUNX1 mutation by targeting SPRYD4 and FNDC3B

BACKGROUND

Runt-related transcription factor 1 (RUNX1) is one of the most frequently mutated genes in most of hematological malignancies, especially in acute myeloid leukemia. In the present study, we aimed to identify the key genes and microRNAs based on acute myeloid leukemia with RUNX1 mutation. The newly finding targeted genes and microRNA associated with RUNX1 may benefit to the clinical treatment in acute myeloid leukemia.

MATERIAL/METHODS

The gene and miRNA expression data sets relating to RUNX1 mutation and wild-type adult acute myeloid leukemia (AML) patients were downloaded from The Cancer Genome Atlas database. Differentially expressed miRNAs and differentially expressed genes (DEGs) were identified by edgeR of R platform. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed by Metascape and Gene set enrichment analysis. The protein-protein interaction network and miRNA-mRNA regulatory network were performed by Search Tool for the Retrieval of Interacting Genes database and Cytoscape software.

RESULTS

A total of 27 differentially expressed miRNAs (25 upregulated and 2 downregulated) and 561 DEGs (429 upregulated and 132 downregulated) were identified. Five miRNAs (miR-151b, miR-151a-5p, let-7a-2-3p, miR-363-3p, miR-20b-5p) had prognostic significance in AML. The gene ontology analysis showed that upregulated DEGs suggested significant enrichment in MHC class II protein complex, extracellular structure organization, blood vessel development, cell morphogenesis involved in differentiation, embryonic morphogenesis, regulation of cell adhesion, and so on. Similarly, the downregulated DEGs were mainly enriched in secretory granule lumen, extracellular structure organization. In the gene set enrichment analysis of Kyoto Encyclopedia of Genes and Genomes pathways, the RUNX1 mutation was associated with adherent junction, WNT signaling pathway, JAK-STAT signaling pathway, pathways in cancer, cell adhesion molecules CAMs, MAPK signaling pathway. Eleven genes (PPBP, APP, CCR5, HLA-DRB1, GNAI1, APLNR, P2RY14, C3AR1, HTR1F, CXCL12, GNG11) were simultaneously identified by hub gene analysis and module analysis. MicroRNA-363-3p may promote the development of RUNX1 mutation AML, targeting SPRYD4 and FNDC3B. In addition, the RUNX1 mutation rates in patient were obviously correlated with age, white blood cell, FAB type, risk(cyto), and risk(molecular) (P < .05).

CONCLUSION

Our findings have indicated that multiple genes and microRNAs may play a crucial role in RUNX1 mutation AML. MicroRNA-363-3p may promote the development of RUNX1 mutation AML by targeting SPRYD4 and FNDC3B.

Functional Genetic Variants in ATG10 Are Associated with Acute Myeloid Leukemia

Simple Summary

Acute myeloid leukemia (AML) is a hematological neoplasm with a very poor survival rate. To date, diagnostic tools to monitor individuals at higher risk of developing AML are scarce. Single nucleotide polymorphisms (SNPs) have emerged as good candidates for disease prevention. AML is characterized by altered autophagy, a vital mechanism to remove and recycle unnecessary or dysfunctional cellular components. ATG10 is one of the autophagy core genes involved in the autophagosome formation. We hypothesize that SNPs located in regulatory regions of the ATG10 gene could predispose individuals to AML development. We therefore genotyped three SNPs within the ATG10 locus. We identified the ATG10_rs3734114 as a potential risk factor for developing AML, whereas the ATG10_rs1864182 was associated with decreased risk. These findings highlight ATG10 as a key regulator of susceptibility to AML. Furthermore, we believe that ATG10 SNPs could be exploited in the clinical setting as an AML prevention strategy.

Abstract

Acute myeloid leukemia (AML) is the most common acute leukemia, characterized by a heterogeneous genetic landscape contributing, among others, to the occurrence of metabolic reprogramming. Autophagy, a key player on metabolism, plays an essential role in AML. Here, we examined the association of three potentially functional genetic polymorphisms in the ATG10 gene, central for the autophagosome formation. We screened a multicenter cohort involving 309 AML patients and 356 healthy subjects for three ATG10 SNPs: rs1864182T>G, rs1864183C>T and rs3734114T>C. The functional consequences of the ATG10 SNPs in its canonical function were investigated in vitro using peripheral blood mononuclear cells from a cohort of 46 healthy individuals. Logistic regression analysis adjusted for age and gender revealed that patients carrying the ATG10_rs1864182G allele showed a significantly decreased risk of developing AML (OR [odds ratio] = 0.58, p = 0.001), whereas patients carrying the homozygous ATG10_rs3734114C allele had a significantly increased risk of developing AML (OR = 2.70, p = 0.004). Functional analysis showed that individuals carrying the ATG10_rs1864182G allele had decreased autophagy when compared to homozygous major allele carriers. Our results uncover the potential of screening for ATG10 genetic variants in AML prevention strategies, in particular for subjects carrying other AML risk factors such as elderly individuals with clonal hematopoiesis of indeterminate potential.

Analyzing the key gene expression and prognostics values for acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is one of the first tumor types sequenced at the whole genome level. However, numbers of the mutated genes expression levels, functions, and prognostics values still unclear.

METHODS

To most ordinary mutated genes were analyzed via cancer virtual cohort discovery analysis platform (CVCDAP), and further investigated the mutational conversions, variant allele frequencies (VAF), driver genes, and potential druggable mutated genes in AML. The top mutated gene mRNA expression levels and the relationship between gene expression levels and prognosis for AML patients were performed by Gene Expression Profiling Interactive Analysis (GEPIA). Moreover, we used the UALCAN dataset to confirm the association between gene expression levels and prognosis for AML patients. Enrichment functions of the top mutated genes of AML were analyzed through Metascape. Finally, the role of these defined genes in cancer pathways and potential drug targets were analyzed by gene set cancer analysis (GSCALite).

RESULTS

The top 20 mutated genes for AML included FLT3, HPS3, ABCA6, PCLO, SLIT2, and other ones. Compared to normal control samples, NPM1 and GABRB3 were significantly downregulated in AML samples, but TP53, DNMT3A, HPS3, FLT3, SENP6, and RUNX1 were significantly overexpressed (all these genes P value <0.01). Overexpression of FLT3 and PCLO indicated a poor prognosis, but the overexpression of SLIT3 functioned as a protector for AML via GEPIA. HSP3 indicates the favorable factor for AML, but overexpression of ABCA6 (P=0.066) may act as the adverse factor by UALCAN analysis. Enrichment function analysis shows the functions of defining genes, including negative regulation of cell differentiation, small GTPase mediated signal transduction, and immune system process. Finally, these genes participate in apoptosis, cell cycle, PI3K/AKT, and RAS/MAPK signaling pathway, and FLT3 is sensitive to 5-Fluorouracil, Methotrexate, ATRA. DNMT3A and IDH2 are resistant to Trametinib. RUNX1 and TP53 were sensitive to I-BET-762 and Tubastatin A.

CONCLUSIONS

Present study showed overexpression of FLT3, ABCA6, and PCLO indicated the poor prognosis of AML, but overexpression of SLIT3 and HSP3 functioned as an AML protector. There are several drugs and small molecules that target the top 20 mutated genes in AML.

Polymorphisms in Neuronal Growth Regulator 1 and Otoancorin Alternate the Susceptibility to Lung Cancer in Chinese Nonsmoking Females

Cell adhesion molecules (CAMs) play crucial roles in the genesis and progress of tumor. We investigated the effects of single nucleotide polymorphisms (SNPs) of CAMs, neuronal growth regulator 1 (NEGR1), and Otoancorin (OTOA) on lung cancer susceptibility in Chinese nonsmoking females. Logistic regression and Cox regression analyses were conducted to investigate the effects of SNPs and environmental factors. For rs3102911, genotype TT carriers decreased the risk of lung cancer with an odds ratio (OR) of 0.635. AA genotypes of rs741718 increased the risk of lung cancer with an OR of 3.527. In stratified analysis, genotype AA carriers of rs741718 had a high susceptibility to lung adenocarcinoma compared with GG and AG genotypes. Analyses of association between SNPs and clinical characteristics revealed that rs3102911 as a protective factor and rs741718 as a risk factor influenced the lung cancer occurrence and progression in nonsmoking females.

miR-18a Inhibitor Suppresses Leukemia Cell Proliferation by Upregulation of PTEN Expression

Background

Leukemia is common in aging adults and has very high mortality worldwide. The present study was designed to investigate the therapeutic efficacy of miR-18a inhibitor against WEHI-3 and THP-1 leukemia cells.

Material/Methods

The changes in miR-18a inhibitor-transfected WEHI-3 and THP-1 cell proliferative potential was measured by use of the Cell Counting Kit-8 assay. Apoptotic changes were analyzed by electron microscopy, and evaluation of PI3K, AKT, mTOR, and PTEN expression was assessed by RT-qPCR assay.

Results

Transfection of miR-18a inhibitor significantly (P<0.05) suppressed the proliferative potential of WEHI-3 and THP4 cells. The WEHI-3 cells showed the presence of characteristic apoptotic bodies on transfection with miR-18a inhibitor at 48 h. Flow cytometry showed that miR-18a inhibitor transfection significantly (P<0.05) increased the WEHI-3 cell percentage in G1 phase. The transfection of miR-18a inhibitor significantly (P<0.05) promoted apoptosis in WEHI-3 cells. In WEHI-3 cells, miR-18a inhibitor transfection markedly suppressed the expression of PI3K, AKT, and mTOR mRNA. The expression of PTEN mRNA was significantly (P<0.05) upregulated by miR-18a inhibitor transfection in WEHI-3 cells.

Conclusions

The present study investigated the therapeutic efficacy of miR-18a inhibitor against WEHI-3 and THP1 leukemia cells. The study demonstrated that miR-18a inhibitor suppressed the proliferative potential of WEHI-3 and THP1 cells and activated apoptotic process through upregulation of PTEN mRNA expression. Therefore, miR-18a inhibitor can be of therapeutic importance for the treatment of leukemia.

Differently Expressed Genes (DEGs) Relevant to Type 2 Diabetes Mellitus Identification and Pathway Analysis via Integrated Bioinformatics Analysis

BACKGROUND The aim of this study was to evaluate the differently expressed genes (DEGs) relevant to type 2 diabetes mellitus (T2DM) and pathway by performing integrated bioinformatics analysis. MATERIAL AND METHODS The gene expression datasets GSE7014 and GSE29221 were downloaded in GEO database, and DEGs from type 2 diabetes mellitus and normal skeletal muscle tissues were identified. Biological function analysis of the DEGs was enriched by GO and KEEG pathway. A PPI network for the identified DEGs was built using the STRING database. RESULTS Thirty top DEGs were identified from 2 datasets: GSE7014 and GSE29221. Of the 30 top DEGs, 20 were up-regulated and 10 were down-regulated. The 20 up-regulated genes were enriched in regulation of mRNA, protein biding, and phospholipase D signaling pathway. The 10 down-regulated genes were enriched in telomere maintenance via semi-conservative replication, AGE-RAGE signaling pathway in diabetic complications, and insulin resistance pathway. In the PPI network of 20 up-regulated DEGs, there were 40 nodes and 84 edges, with an average node degree of 4.2. For the 10 down-regulated DEGs, we found a total of 30 nodes and 105 edges, with an average node degree of 7.0 and local clustering coefficient of 0.812. Among the 30 DEGs, 10 hub genes (CNOT6L, CNOT6, CNOT1, CNOT7, RQCD1, RFC2, PRIM1, RFC4, RFC5, and RFC1) were also identified through Cytoscape. CONCLUSIONS DEGs of T2DM may play an essential role in disease development and may be potential pathogeneses of T2DM.

Identification of prognostic genes in the acute myeloid leukemia microenvironment

The tumor microenvironment (TME) has a strong influence on the progression, therapeutic response, and clinical outcome of acute myeloid leukemia (AML), one of the most common hematopoietic malignancies in adults. In this study, we identified TME-related genes associated with AML prognosis. Gene expression profiles from AML patients were downloaded from TCGA database, and immune and stromal scores were calculated using the ESTIMATE algorithm. Immune scores were correlated with clinical features such as FAB subtypes and patient's age. After categorizing AML cases into high and low score groups, an association between several differentially expressed genes (DEGs) and overall survival was identified. Functional enrichment analysis of the DEGs showed that they were primarily enriched in the immune response, inflammatory response, and cytokine activity, and were involved in signaling processes related to hematopoietic cell lineage, B cell receptor, and chemokine pathways. Two significant modules, dominated respectively by CCR5 and ITGAM nodes, were identified from the PPI network, and 20 hub genes were extracted. A total of 112 DEGs correlated with poor overall survival of AML patients, and 11 of those genes were validated in a separate TARGET-AML cohort. By identifying TME-associated genes, our findings may lead to improved prognoses and therapies for AML.

Weighted Gene Coexpression Network Analysis Identifies Cysteine-Rich Intestinal Protein 1 (CRIP1) as a Prognostic Gene Associated with Relapse in Patients with Acute Myeloid Leukemia

BACKGROUND Acute myeloid leukemia (AML) is associated with a high relapse rate and poor prognosis. This study aimed to use weighted gene coexpression network analysis (WGCNA) of gene coexpression networks to identify candidate prognostic biomarker genes in patients with AML and to investigate the expression of these genes in the human U937 cell line in vitro. MATERIAL AND METHODS RNA-seq data were retrieved from the Cancer Genome Atlas (TCGA) and included bone marrow samples and survival data of patients with AML (N=151), patients who did not relapse after treatment (N=119), and patients with relapse (N=40). Differentially expressed genes were identified, WGCNA was used to detect functional modules, and survival analysis was performed. The Cell Counting Kit-8 (CCK-8) assay investigated the proliferation of U937 cells transfected with short hairpin RNAs (shRNAs), shCRIP1, shHIST1H1C, and shHIST1H1E. RNA-seq analysis identified gene expression following CRIP1 knockdown. RESULTS Eighty-two genes were associated with both relapse and prognosis in patients with AML. There were two prognosis-related gene modules in the coexpression network. In the coexpression network, the histone cluster 1 H1 family member gene, HIST1H1C had the maximum relapse fold change, HIST1H1E had the lowest survival p-value, and the cysteine-rich intestinal protein 1 (CRIP1) gene had the most edge numbers and was significantly associated with poor prognosis (P=0.0165786). RNA-seq data showed that there was a significant difference in gene expression after CRIP1 knockdown in U937 cells. CONCLUSIONS WGCNA of gene coexpression networks identified CRIP1 as a potential prognostic biomarker gene in patients with AML.