HCP5, as the sponge of miR-1291, facilitates AML cell proliferation and restrains apoptosis via increasing PIK3R5 expression

Construction of an immune-related prognostic signature and lncRNA-miRNA-mRNA ceRNA network in acute myeloid leukemia

The progression of acute myeloid leukemia (AML) is influenced by the immune microenvironment in the bone marrow and dysregulated intracellular competing endogenous RNA (ceRNA) networks. Our study utilized data from UCSC Xena, The Cancer Genome Atlas Program, the Gene Expression Omnibus, and the Immunology Database and Analysis Portal. Using Cox regression analysis, we identified an immune-related prognostic signature. Genomic analysis of prognostic messenger RNA (mRNA) was conducted through Gene Set Cancer Analysis (GSCA), and a prognostic ceRNA network was constructed using the Encyclopedia of RNA Interactomes. Correlations between signature mRNAs and immune cell infiltration, checkpoints, and drug sensitivity were assessed using R software, gene expression profiling interactive analysis (GEPIA), and CellMiner, respectively. Adhering to the ceRNA hypothesis, we established a potential long noncoding RNA (lncRNA)/microRNA (miRNA)/mRNA regulatory axis. Our findings pinpointed 9 immune-related prognostic mRNAs (KIR2DL1, CSRP1, APOBEC3G, CKLF, PLXNC1, PNOC, ANGPT1, IL1R2, and IL3RA). GSCA analysis revealed the impact of copy number variations and methylation on AML. The ceRNA network comprised 14 prognostic differentially expressed lncRNAs (DE-lncRNAs), 6 prognostic DE-miRNAs, and 3 prognostic immune-related DE-mRNAs. Correlation analyses linked these mRNAs' expression to 22 immune cell types and 6 immune checkpoints, with potential sensitivity to 27 antitumor drugs. Finally, we identified a potential LINC00963/hsa-miR-431-5p/CSRP1 axis. This study offers innovative insights for AML diagnosis and treatment through a novel immune-related signature and ceRNA axis. Identified novel biomarkers, including 2 mRNAs (CKLF, PNOC), 1 miRNA (hsa-miR-323a-3p), and 10 lncRNAs (SNHG25, LINC01857, AL390728.6, AC127024.5, Z83843.1, AP002884.1, AC007038.1, AC112512, AC020659.1, AC005921.3) present promising candidates as potential targets for precision medicine, contributing to the ongoing advancements in the field.

Comprehensive analysis of immune-related lncRNAs in AML patients uncovers potential therapeutic targets and prognostic biomarkers

Purpose

The objective of this study was to provide theoretically feasible strategies by understanding the relationship between the immune microenvironment and the diagnosis and prognosis of AML patients. To this end, we built a ceRNA network with lncRNAs as the core and analyzed the related lncRNAs in the immune microenvironment by bioinformatics analysis.

Methods

AML transcriptome expression data and immune-related gene sets were obtained from TCGA and ImmPort. Utilizing Pearson correlation analysis, differentially expressed immune-related lncRNAs were identified. Then, the LASSO-Cox regression analysis was performed to generate a risk signature consisting immune-related lncRNAs. Accuracy of signature in predicting patient survival was evaluated using univariate and multivariate analysis. Next, GO and KEGG gene enrichment and ssGSEA were carried out for pathway enrichment analysis of 183 differentially expressed genes, followed by drug sensitivity and immune infiltration analysis with pRRophetic and CIBERSORT, respectively. Cytoscape was used to construct the ceRNA network for these lncRNAs.

Results

816 common lncRNAs were selected to acquire the components related to prognosis. The final risk signature established by multivariate Cox and stepwise regression analysis contained 12 lncRNAs engaged in tumor apoptotic and metastatic processes: LINC02595, HCP5, AC020934.2, AC008770.3, LINC01770, AC092718.4, AL589863.1, AC131097.4, AC012368.1, C1RL-AS1, STARD4-AS1, and AC243960.1. Based on this predictive model, high-risk patients exhibited lower overall survival rates than low-risk patients. Signature lncRNAs showed significant correlation with tumor-infiltrating immune cells. In addition, significant differences in PD-1/PD-L1 expression and bleomycin/paclitaxel sensitivity were observed between risk groups.

Conclusion

LncRNAs related to immune microenvironment were prospective prognostic and therapeutic options for AML.

HCP5 prevents ubiquitination-mediated UTP3 degradation to inhibit apoptosis by activating c-Myc transcriptional activity

Inducing cancer cell apoptosis through cytotoxic reagents is the main therapeutic strategy for diverse cancer types. However, several antiapoptotic factors impede curative cancer therapy by driving cancer cells to resist cytotoxic agent-induced apoptosis, thus leading to refractoriness and relapse. To define critical antiapoptotic factors that contribute to chemoresistance in esophageal squamous cell carcinoma (ESCC), we generated two pairs of parental and apoptosis-resistant cell models through cisplatin (DDP) induction and then performed whole-transcriptome sequencing. We identified the long noncoding RNA (lncRNA) histocompatibility leukocyte antigen complex P5 (HCP5) as the chief culprit for chemoresistance. Mechanistically, HCP5 interacts with UTP3 small subunit processome component (UTP3) and prevents UTP3 degradation from E3 ligase tripartite motif containing 29 (TRIM29)-mediated ubiquitination. UTP3 then recruits c-Myc to activate vesicle-associated membrane protein 3 (VAMP3) expression. Activated VAMP3 suppresses caspase-dependent apoptosis and eventually leads to chemoresistance. Accordingly, the expression level of the HCP5/UTP3/c-Myc/VAMP3 axis in chemoresistant patients is significantly higher than that in chemosensitive patients. Thus, our study demonstrated that the HCP5/UTP3/c-Myc/VAMP3 axis plays an important role in the inhibition of cancer cell apoptosis and that HCP5 may be a promising chemosensitivity target for cancer treatment.

Tumor-suppressive MEG3 induces microRNA-493-5p expression to reduce arabinocytosine chemoresistance of acute myeloid leukemia cells by downregulating the METTL3/MYC axis

Background

Chemoresistance serves as a huge obstacle for acute myeloid leukemia (AML) patients. To counteract the chemoresistance in AML cells, we discussed the role of maternally expressed gene 3 (MEG3) in arabinocytosine (AraC) chemoresistance in AML cells.

Methods

MEG3, microRNA (miR)-493-5p, methyltransferase-like 3 (METTL3) and MYC expression in AML cells was determined and then their interactions were also analyzed. Then, the viability and apoptosis of AML cells were determined through loss- and gain- function assay. The level of m6A modification in AML cells was examined. AML mouse models were also established to validate the potential roles of MEG3.

Results

MEG3 and miR-493-5p were downregulated in AML cells, and they were lower in resistant cells than in parental cells. MEG3 led to elevated expression of miR-493-5p which targeted METTL3. METTL3 increased expression of MYC by promoting its m6A levels. Overexpression of MEG3 and miR-493-5p or knockdown of METTL3 inhibited HL-60 and Molm13 cell proliferation and promoted their apoptosis. Overexpressed MEG3 induced heightened sensitivity of AML cells to AraC. However, the suppression of miR-493-5p reversed the effects of overexpressed MEG3 on AML cells.

Conclusions

Collectively, MEG3 could upregulate miR-493-5p expression and suppress the METTL3/MYC axis through MYC m6A methylation, by which MEG3 promoted the chemosensitivity of AML cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03456-x.

N6-Methyladenosine-Related lncRNAs Are Novel Prognostic Markers and Predict the Immune Landscape in Acute Myeloid Leukemia

Background: Acute myelocytic leukemia (AML) is one of the hematopoietic cancers with an unfavorable prognosis. However, the prognostic value of N 6-methyladenosine-associated long non-coding RNAs (lncRNAs) in AML remains elusive.

Materials and Methods: The transcriptomic data of m6A-related lncRNAs were collected from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. AML samples were classified into various subgroups according to the expression of m6A-related lncRNAs. The differences in terms of biological function, tumor immune microenvironment, copy number variation (CNV), and drug sensitivity in AML between distinct subgroups were investigated. Moreover, an m6A-related lncRNA prognostic model was established to evaluate the prognosis of AML patients.

Results: Nine prognosis-related m6A-associated lncRNAs were selected to construct a prognosis model. The accuracy of the model was further determined by the Kaplan–Meier analysis and time-dependent receiver operating characteristic (ROC) curve. Then, AML samples were classified into high- and low-risk groups according to the median value of risk scores. Gene set enrichment analysis (GSEA) demonstrated that samples with higher risks were featured with aberrant immune-related biological processes and signaling pathways. Notably, the high-risk group was significantly correlated with an increased ImmuneScore and StromalScore, and distinct immune cell infiltration. In addition, we discovered that the high-risk group harbored higher IC50 values of multiple chemotherapeutics and small-molecule anticancer drugs, especially TW.37 and MG.132. In addition, a nomogram was depicted to assess the overall survival (OS) of AML patients. The model based on the median value of risk scores revealed reliable accuracy in predicting the prognosis and survival status.

Conclusion: The present research has originated a prognostic risk model for AML according to the expression of prognostic m6A-related lncRNAs. Notably, the signature might also serve as a novel biomarker that could guide clinical applications, for example, selecting AML patients who could benefit from immunotherapy.

Genetic and epigenetic alterations of cyclic AMP response element modulator in rheumatoid arthritis

BACKGROUND

Genetic and epigenetic factors are strongly associated with the autoimmune disease rheumatoid arthritis (RA). Cyclic AMP response element modulator (CREM), a gene related to immune system regulation, has been implicated in various immune-mediated inflammatory processes, although it remains unknown whether CREM is involved in RA.

METHODS

This study enrolled 278 RA patients and 262 controls. Three variants [rs12765063, rs17499247, rs1213386] were identified through linkage disequilibrium and expression quantitative trait locus analysis, and CREM transcript abundance was determined by quantitative real-time polymerase chain reaction. The identified variants were genotyped using the TaqMan Allelic Discrimination assay, and CREM promoter methylation was assessed by bisulphite sequencing. Differences between groups and correlations between variables were assessed with Student's t-tests and Pearson's correlation coefficients. Associations between phenotypes and genotypes were evaluated with logistic regression.

RESULTS

Rheumatoid arthritis patients exhibited increased CREM expression (p < .0001), which was decreased by methotrexate (p = .0223) and biologics (p = .0001), but could not be attributed to CREM variants. Interestingly, rs17499247 displayed a significant association with serositis (p = .0377), and rs1213386 increased the risk of lymphadenopathy (p = .0398). Furthermore, seven CpG sites showed decreased methylation in RA (p = .0477~ p < .0001).

CONCLUSIONS

Collectively, our results indicate that CREM hypomethylation and CREM upregulation occur in RA and that CREM variants are involved in the development of serositis and lymphadenopathy in RA. This study highlights the novel roles of CREM in RA pathophysiology.