Up-regulation of DDIT4 predicts poor prognosis in acute myeloid leukaemia

Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns

Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pathogenesis suggests PCD-related signatures could serve as biomarkers to predict clinical outcomes and drug response. We utilized 13 PCD pathways, including apoptosis, pyroptosis, ferroptosis, autophagy, necroptosis, cuproptosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis to develop predictive models based on 73 machine learning combinations from 10 algorithms. Bulk RNA-sequencing, single-cell RNA-sequencing transcriptomic data, and matched clinicopathological information were obtained from the TCGA-AML, Tyner, and GSE37642-GPL96 cohorts. These datasets were leveraged to construct and validate the models. Additionally, in vitro experiments were conducted to substantiate the bioinformatics findings. The machine learning approach established a 6-gene pan-programmed cell death-related genes index (PPCDI) signature. Validation in two external cohorts showed high PPCDI associated with worse prognosis in AML patients. Incorporating PPCDI with clinical variables, we constructed several robust prognostic nomograms that accurately predicted prognosis of AML patients. Multi-omics analysis integrating bulk and single-cell transcriptomics revealed correlations between PPCDI and immunological features, delineating the immune microenvironment landscape in AML. Patients with high PPCDI exhibited resistance to conventional chemotherapy like doxorubicin but retained sensitivity to dasatinib and methotrexate (FDA-approved drugs for other leukemias), suggesting the potential of PPCDI to guide personalized therapy selection in AML. In summary, we developed a novel PPCDI model through comprehensive analysis of diverse programmed cell death pathways. This PPCDI signature demonstrates great potential in predicting clinical prognosis and drug sensitivity phenotypes in AML patients.

NET-related gene signature for predicting AML prognosis

Acute Myeloid Leukemia (AML) is a malignant blood cancer with a high mortality rate. Neutrophil extracellular traps (NETs) influence various tumor outcomes. However, NET-related genes (NRGs) in AML had not yet received much attention. This study focuses on the role of NRGs in AML and their interaction with the immunological microenvironment. The gene expression and clinical data of patients with AML were downloaded from the TCGA-LAML and GEO cohorts. We identified 148 NRGs through the published article. Univariate Cox regression was used to analyze the association of NRGs with overall survival (OS). The least absolute shrinkage and selection operator were utilized to assess the predictive efficacy of NRGs. Kaplan-Meier plots visualized survival estimates. ROC curves assessed the prognostic value of NRG-based features. A nomogram, integrating clinical information and prognostic scores of patients, was constructed using multivariate logistic regression and Cox proportional hazards regression models. Twenty-seven NRGs were found to significantly impact patient OS. Six NRGs-CFTR, ENO1, PARVB, DDIT4, MPO, LDLR-were notable for their strong predictive ability regarding patient survival. The ROC values for 1-, 3-, and 5-year survival rates were 0.794, 0.781, and 0.911, respectively. In the training set (TCGA-LAML), patients in the high NRG risk group showed a poorer prognosis (p < 0.001), which was validated in two external datasets (GSE71014 and GSE106291). The 6-NRG signature and corresponding nomograms exhibit superior predictive accuracy, offering insights for pre-immune response evaluation and guiding future immuno-oncology treatments and drug selection for AML patients.

Pan-cancer analysis of DDIT4 identifying its prognostic value and function in acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is a hematological malignancy derived from the accumulation of abnormal proliferation of infantile leukocytes in the hematopoietic system. DNA-damage-inducible transcript 4 (DDIT4) acting as a negative regulator of rapamycin inhibitor is involved in various cellular functions. Many studies have suggested that DDIT4 plays a key role in tumorigenesis. However, the role of DDIT4 in AML has been poorly studied.

METHOD

In this study, we analyzed the expression of DDIT4 in AML patients using The Cancer Genome Atlas and real-time polymerase chain reaction. The Chi-square test was used to assess the correlation between DDIT4 and clinical characters in AML patients. Loss-of-function experiments were implemented to investigate the role of DDIT4 in AML carcinogenesis. The R package was applied to evaluate the correlation between DDIT4 expression and immune cells.

RESULTS

Results showed that the expression of DDIT4 was associated with Age, Cytogenetic risk, Cytogenetics and OS event. Moreover, high expression of DDIT4 led to a terrible prognosis. KEGG analysis showed that differently expressed genes (DEGs) were involved in the PI3-Akt signaling pathway. GSEA enrichment analysis displayed DEGs were correlated with apoptosis. Functional experiments presented that knocking down DDIT4 suppressed cell cycle transition/proliferation and facilitated apoptosis. In addition, DDIT4 is associated with immune infiltration.

CONCLUSION

Our research verified that DDIT4 can be used as a prognostic marker and a potential therapeutic target for AML.

Nuclear overexpression of DNA damage-inducible transcript 4 (DDIT4) is associated with aggressive tumor behavior in patients with pancreatic tumors

DNA damage-inducible transcript 4 (DDIT4) is induced in various cellular stress conditions. Several studies showed that the dysregulation of DDIT4 is involved in different malignancies with paradoxical expressions and roles. Therefore, this study investigated the clinical significance, prognostic, and diagnostic value of DDIT4 in different types of pancreatic tumors (PT). The expression of DDIT4 and long non-coding RNA (TPTEP1) in mRNA level was examined in 27 fresh PT samples using Real-time quantitative PCR (RT-qPCR). Moreover, 200 formalin-fixed paraffin-embedded PT tissues, as well as 27 adjacent normal tissues, were collected to evaluate the clinical significance, prognostic, and diagnosis value of DDIT4 expression by immunohistochemistry (IHC) on tissue microarrays (TMA) slides. The results of RT-qPCR showed that the expression of DDIT4 in tumor samples was higher than in normal samples which was associated with high tumor grade (P = 0.015) and lymphovascular invasion (P = 0.048). Similar to this, IHC findings for nucleus, cytoplasm, and membrane localization showed higher expression of DDIT4 protein in PT samples rather than in nearby normal tissues. A statistically significant association was detected between a high level of nuclear expression of DDIT4 protein, and lymphovascular invasion (P = 0.025), as well as advanced TNM stage (P = 0.034) pancreatic ductal adenocarcinoma (PDAC) and in pancreatic neuroendocrine tumor (PNET), respectively. In contrast, a low level of membranous expression of DDIT4 protein showed a significant association with advanced histological grade (P = 0.011), margin involvement (P = 0.007), perineural invasion (P = 0.023), as well as lymphovascular invasion (P = 0.005) in PDAC. No significant association was found between survival outcomes and expression of DDIT4 in both types. It was found that DDIT4 has rational accuracy and high sensitivity as a diagnostic marker. Our results revealed a paradoxical role of DDIT4 expression protein based on the site of nuclear and membranous expression. The findings of this research indicated that there is a correlation between elevated nuclear expression of DDIT4 and the advancement and progression of disease in patients with PT. Conversely, high membranous expression of DDIT4 was associated with less aggressive tumor behavior in patients with PDAC. However, further studies into the prognostic value and biological function of DDIT4 are needed in future studies.

Investigation of distinct gene expression profile patterns that can improve the classification of intermediate-risk prognosis in AML patients

Background: Acute myeloid leukemia (AML) is a heterogeneous type of blood cancer that generally affects the elderly. AML patients are categorized with favorable-, intermediate-, and adverse-risks based on an individual's genomic features and chromosomal abnormalities. Despite the risk stratification, the progression and outcome of the disease remain highly variable. To facilitate and improve the risk stratification of AML patients, the study focused on gene expression profiling of AML patients within various risk categories. Therefore, the study aims to establish gene signatures that can predict the prognosis of AML patients and find correlations in gene expression profile patterns that are associated with risk groups. Methods: Microarray data were obtained from Gene Expression Omnibus (GSE6891). The patients were stratified into four subgroups based on risk and overall survival. Limma was applied to screen for differentially expressed genes (DEGs) between short survival (SS) and long survival (LS). DEGs strongly related to general survival were discovered using Cox regression and LASSO analysis. To assess the model's accuracy, Kaplan-Meier (K-M) and receiver operating characteristic (ROC) were used. A one-way ANOVA was performed to assess for differences in the mean gene expression profiles of the identified prognostic genes between the risk subcategories and survival. GO and KEGG enrichment analyses were performed on DEGs. Results: A total of 87 DEGs were identified between SS and LS groups. The Cox regression model selected nine genes CD109, CPNE3, DDIT4, INPP4B, LSP1, CPNE8, PLXNC1, SLC40A1, and SPINK2 that are associated with AML survival. K-M illustrated that the high expression of the nine-prognostic genes is associated with poor prognosis in AML. ROC further provided high diagnostic efficacy of the prognostic genes. ANOVA also validated the difference in gene expression profiles of the nine genes between the survival groups, and highlighted four prognostic genes to provide novel insight into risk subcategories poor and intermediate-poor, as well as good and intermediate-good that displayed similar expression patterns. Conclusion: Prognostic genes can provide more accurate risk stratification in AML. CD109, CPNE3, DDIT4, and INPP4B provided novel targets for better intermediate-risk stratification. This could enhance treatment strategies for this group, which constitutes the majority of adult AML patients.

A ferroptosis-related prognostic model with excellent clinical performance based on the exploration of the mechanism of oral squamous cell carcinoma progression

As a hot topic today, ferroptosis is closely involved in the progression and treatment of cancer. Accordingly, we built a prognostic model around ferroptosis to predict the overall survival of OSCC patients. We used up to 6 datasets from 3 different databases to ensure the credibility of the model. Then, through differentially expressed, Univariate Cox, and Lasso regression analyses, a model composed of nine prognostic-related differently expressed ferroptosis-related genes (CISD2, DDIT4, CA9, ALOX15, ATG5, BECN1, BNIP3, PRDX5 and MAP1LC3A) were constructed. Moreover, Kaplan-Meier curves, Receiver Operating Characteristic curves and principal component analysis used to verify the model's predictive ability showed the model's superiority. To deeply understand the mechanism of ferroptosis affecting the occurrence, development and prognosis of OSCC, we performed enrichment analysis in different risk groups identified by the model. The results showed that numerous TP53-related, immune-related and ferroptosis-related functions and pathways were enriched. Further immune microenvironment analysis and mutation analysis have once again revealed the correlation between risk score and immunity and TP53 mutation. Finally, the correlation between risk score and OSCC clinical treatment, as well as Nomogram show the brilliant clinical application prospects of the prognostic model.

Distinct noncoding RNAs and RNA binding proteins associated with high-risk pediatric and adult acute myeloid leukemias detected by regulatory network analysis

BACKGROUND

Acute myeloid leukemia (AML) is a heterogeneous disease in both children and adults. Although it is well-known that adult and pediatric AMLs are genetically distinct diseases, the driver genes for high-risk pediatric and adult AMLs are still not fully understood. Particularly, the interactions between RNA binding proteins (RBPs) and noncoding RNAs (ncRNAs) for high-risk AMLs have not been explored.

AIM

To identify RBPs and noncoding RNAs (ncRNAs) that are the master regulators of high-risk AML.

METHODS

In this manuscript, we identify over 400 upregulated genes in high-risk adult and pediatric AMLs respectively with the expression profiles of TCGA and TARGET cohorts. There are less than 5% genes commonly upregulated in both cohorts, highlighting the genetic differences in adult and childhood AMLs. A novel distance correlation test is proposed for gene regulatory network construction. We build RBP-based regulatory networks with upregulated genes in high-risk adult and pediatric AMLs, separately.

RESULTS

We discover that three RBPs, three snoRNAs, and two circRNAs function together and regulate over 100 upregulated RNA targets in adult AML, whereas two RBPs are associated with 17 long noncoding RNAs (lncRNAs), and all together regulate over 90 upregulated RNA targets in pediatric AML. Of which, two RBPs, MLLT3 and RBPMS, and their circRNA targets, PTK2 and NRIP1, are associated with the overall survival (OS) in adult AML (p ≤ 0.01), whereas two different RBPs, MSI2 and DNMT3B, and 13 (out of 17) associated lncRNAs are prognostically significant in pediatric AML.

CONCLUSIONS

Both RBPs and ncRNAs are known to be the major regulators of transcriptional processes. The RBP-ncRNA pairs identified from the regulatory networks will allow better understanding of molecular mechanisms underlying high-risk adult and pediatric AMLs, and assist in the development of novel RBPs and ncRNAs based therapeutic strategies.

Longitudinal single-cell transcriptomics reveals distinct patterns of recurrence in acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is a heterogeneous and aggressive blood cancer that results from diverse genetic aberrations in the hematopoietic stem or progenitor cells (HSPCs) leading to the expansion of blasts in the hematopoietic system. The heterogeneity and evolution of cancer blasts can render therapeutic interventions ineffective in a yet poorly understood patient-specific manner. In this study, we investigated the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs at genetic and transcriptional levels, and unveiled the underlying pathways and genes contributing to recurrence.

Methods

Whole-exome sequencing was used to detect somatic mutations and large copy number variations (CNVs). Single cell RNA-seq was performed to investigate the clonal heterogeneity between Dx-Re pairs and amongst patients.

Results

scRNA-seq analysis revealed extensive expression differences between patients and Dx-Re pairs, even for those with the same -presumed- initiating events. Transcriptional differences between and within patients are associated with clonal composition and evolution, with the most striking differences in patients that gained large-scale copy number variations at relapse. These differences appear to have significant molecular implications, exemplified by a DNMT3A/FLT3-ITD patient where the leukemia switched from an AP-1 regulated clone at Dx to a mTOR signaling driven clone at Re. The two distinct AML1-ETO pairs share genes related to hematopoietic stem cell maintenance and cell migration suggesting that the Re leukemic stem cell-like (LSC-like) cells evolved from the Dx cells.

Conclusions

In summary, the single cell RNA data underpinned the tumor heterogeneity not only amongst patient blasts with similar initiating mutations but also between each Dx-Re pair. Our results suggest alternatively and currently unappreciated and unexplored mechanisms leading to therapeutic resistance and AML recurrence.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-022-01635-4.

Longitudinal single-cell transcriptomics reveals distinct patterns of recurrence in acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is a heterogeneous and aggressive blood cancer that results from diverse genetic aberrations in the hematopoietic stem or progenitor cells (HSPCs) leading to the expansion of blasts in the hematopoietic system. The heterogeneity and evolution of cancer blasts can render therapeutic interventions ineffective in a yet poorly understood patient-specific manner. In this study, we investigated the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs at genetic and transcriptional levels, and unveiled the underlying pathways and genes contributing to recurrence.

METHODS

Whole-exome sequencing was used to detect somatic mutations and large copy number variations (CNVs). Single cell RNA-seq was performed to investigate the clonal heterogeneity between Dx-Re pairs and amongst patients.

RESULTS

scRNA-seq analysis revealed extensive expression differences between patients and Dx-Re pairs, even for those with the same -presumed- initiating events. Transcriptional differences between and within patients are associated with clonal composition and evolution, with the most striking differences in patients that gained large-scale copy number variations at relapse. These differences appear to have significant molecular implications, exemplified by a DNMT3A/FLT3-ITD patient where the leukemia switched from an AP-1 regulated clone at Dx to a mTOR signaling driven clone at Re. The two distinct AML1-ETO pairs share genes related to hematopoietic stem cell maintenance and cell migration suggesting that the Re leukemic stem cell-like (LSC-like) cells evolved from the Dx cells.

CONCLUSIONS

In summary, the single cell RNA data underpinned the tumor heterogeneity not only amongst patient blasts with similar initiating mutations but also between each Dx-Re pair. Our results suggest alternatively and currently unappreciated and unexplored mechanisms leading to therapeutic resistance and AML recurrence.

Identification and Validation of Dilated Cardiomyopathy-Related Genes via Bioinformatics Analysis

Purpose

Dilated cardiomyopathy (DCM) is a type of cardiomyopathy that can easily cause heart failure and has a high mortality rate. Therefore, there is an urgent need to study the underlying mechanism of action of dilated cardiomyopathy. In the present study, we aimed to explore potential miRNA–mRNA pairs and drugs related to DCM.

Methods

The Microarray data were collected from the Gene Expression Omnibus (GEO) database. Bioinformatics analysis differentially expressed miRNAs and mRNAs in each microarray were obtained. The target genes of miRNAs were obtained from the miRWalk 2.0 database, and the intersection of these two gene sets (miRNA target genes and differentially expressed mRNAs in the microarray) was obtained. Pathway and Gene Ontology (GO) enrichment analyses were performed in the KOBAS database. Cytoscape software was used to construct the miRNA–mRNA network, and the final hub genes were obtained. Furthermore, we predicted several candidate drugs related to hub genes using DSigDB database. To confirm the abnormal expression of hub genes, qRT-PCR was performed.

Results

In total, eight differentially expressed miRNAs and 92 differentially expressed mRNAs were identified. In addition, 47 differentially expressed miRNA target genes were identified. According to the analysis results of the miRNA-mRNA network, we identified hsa-miR-551b-3p, hsa-miR-770-5p, hsa-miR-363-3p, PIK3R1, DDIT4, and CXCR4 as hub genes in DCM. Several candidate drugs, which are related to the hug genes, were identified.

Conclusion

In conclusion, in our study, we identified several hub genes that may be involved in the pathogenesis of DCM. Several drugs related to these hub genes may be used as clinical therapeutic candidates.

Development and Validation of a Robust Ferroptosis-Related Prognostic Signature in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer. Ferroptosis is a newly recognized process of cell death, which is different from other forms of cell death in morphology, biochemistry, and genetics, and has played a vital role in cancer biology. This study aimed to identify a ferroptosis-related gene signature associated with LUAD prognosis.

Methods

Dataset TCGA-LUAD which came from the TCGA portal was taken as the training cohort. GSE72094 and GSE68465 from the GEO database were treated as validation cohorts. Two hundred fifty-nine ferroptosis-related genes were retrieved from the FerrDb database. In the training cohort, Kaplan–Meier and univariate Cox analyses were conducted for preliminary screening of ferroptosis-related genes with potential prognostic capacity. These genes then entered into the LASSO Cox regression model, constructing a gene signature. The latter was then evaluated in the training and validation cohorts via Kaplan–Meier, Cox, and ROC analyses. In addition, the correlations between risk score and autophagy were examined by Pearson correlation coefficient. The analyses of GSEA and immune infiltrating were performed for better studying the function annotation of the gene signature and the character of each kind of immune cells played in the tumor microenvironment.

Results

A 15-gene signature was found from the training cohort and validated by Kaplan–Meier and Cox regression analyses, revealing its independent prognosis value in LUAD. Moreover, the ROC analysis was conducted, confirming a strong predictive ability that this signature owned for LUAD prognosis. One hundred fifty-one of 222 (68.01%) autophagy-related genes were discovered significantly correlated with risk scores. Analyses of GSEA and immune infiltration exhibited in detail the specific pathways that associate with the 15-gene signature and identified the crucial roles of resting mast cells and resting dendritic cells owned in the prognosis of the 15-gene signature.

Conclusion

In this present study, a novel ferroptosis-related 15-gene signature (RELA, ACSL3, YWHAE, EIF2S1, CISD1, DDIT4, RRM2, PANX1, TLR4, ARNTL, LPIN1, HERPUD1, NCOA4, PEBP1, and GLS2) was built. It could accurately predict the prognosis of LUAD and was related to resting mast cells and resting dendritic cells, which provide potential for the personalized outcome prediction and the development of new therapies in LUAD population.

Employing hypoxia characterization to predict tumour immune microenvironment, treatment sensitivity and prognosis in hepatocellular carcinoma

The hypoxic microenvironment was recognized as a major driving force of the malignant phenotype in hepatocellular carcinoma (HCC), which contributes to tumour immune microenvironment (TIM) remodeling and tumor progression. Dysregulated hypoxia-related genes (HRGs) result in treatment resistance and poor prognosis by reshaping tumor cellular activities and metabolism. Approaches to identify the relationship between hypoxia and tumor progression provided new sight for improving tumor treatment and prognosis. But, few practical tools, forecasting relationship between hypoxia, TIM, treatment sensitivity and prognosis in HCC were reported. Here, we pooled mRNA transcriptome and clinical pathology data from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), and later developed a hypoxia risk model including four HRGs (DCN, DDIT4, PRKCA and NDRG1). The high-risk group displayed poor clinical characteristics, a malignant phenotype with carcinogenesis/proliferation pathways activation (MTORC1 and E2F) and immunosuppressive TIM (decreased immune cell infiltrations and upregulated immunosuppressive cytokines). Meanwhile, activated B cells, effector memory CD8 T cells and EZH2 deregulation were associated with patient’s survival, which might be the core changes of HCC hypoxia. Finally, we validated the ability of the hypoxia risk model to predict treatment sensitivity and found high hypoxia risk patients had poor responses to HCC treatment, including surgical resection, Sorafenib, Transarterial Chemoembolization (TACE) and immunotherapy. In conclusion, based on 4 HRGs, we developed and validated a hypoxia risk model to reflect pathological features, evaluate TIM landscape, predict treatment sensitivity and compounds specific to hypoxia signatures in HCC patients.

DDIT4 mediates the proliferation-promotive effect of IL-34 in human monocytic leukemia cells

Interleukin 34 (IL-34) is a cytokine that shares the receptor with colony-stimulating factor 1 (CSF-1). IL-34 is involved in a broad range of pathologic processes including cancer. We previously demonstrated that IL-34 promoted the proliferation and colony formation of human acute monocytic leukemia (AMoL) cells. However, the mechanism has not been elucidated. Here, by analyzing the gene profiles of Molm13 and THP1 cells overexpressing IL-34 (Molm13-IL-34 and THP1-IL-34), upregulation of the DNA damage-inducible transcript 4 (DDIT4) was detected in both series. Knockdown of DDIT4 effectively inhibited the proliferation, promoted apoptosis and colony formation in Molm13-IL-34 and THP1-IL-34 cells. Our results suggest that DDIT4 mediates the proliferation-promotive effect of IL-34 whereas does not mediate the promotive effect of IL-34 on colony formation in AMoL cells.

LncRNA-MIAT promotes neural cell autophagy and apoptosis in ischemic stroke by up-regulating REDD1

BACKGROUND

Ischemic stroke (IS) accounts for 80% of stroke incidence, which has an impact on the life quality of patients. Long non-coding RNA (LncRNA), a class of non-coding transcripts greater than 200 nucleotidesin length, has been extensively studied in cerebrovascular diseases. Myocardial infarction associated transcript (MIAT) is highly expressed in nervous system. Therefore this study aims to explore the role of LncRNA MIAT in IS and to clarify its underlying mechanism, providing therapeutic value for the treatment of IS.

METHODS

The neurological function of rats was evaluated by neurological deficit score. Triphenyltetrazolium chloride (TTC) staining was used to detect infarct area in brain tissues. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to examine the expression of MIAT. Western blotting was used to detect the expressions of REDD1, p-mTOR, autophagy-related proteins LC3 and p62, and apoptotic-related proteins Bax, cleaved-caspase3, Bcl-2. Flow cytometry was applied to examine neuronal cell apoptosis. RNA pull-down and RIP assay was used to verify the binding of MIAT and REDD1. The level of REDD1 ubiquitination was detected by ubiquitination and Co-immunoprecipitation (Co-IP) assay.

RESULTS

The expressions of MIAT and REDD1 were increased in IS rats and oxygen-glucose deprivation/reoxygenation (OGD/R)-induced PC12 cell injury. After interference with si-MIAT, the results of flow cytometry showed that the rate of apoptosis was reduced. Western blotting results showed that the expression of LC3II/LC3I, Bax, and cleaved-caspase3 was decreased, while the expression of p-mTOR, p62, and Bcl-2 was increased. RNA pull-down and RIP assay found the binding relationship between MIAT and REDD1, and interference with si-MIAT down-regulated the expression of REDD1. The level of REDD1 ubiquitination was increased and the expression of REDD1 was decreased after interference with si-MIAT in PC12 cells. Co-IP results showed that interference with si-MIAT enhanced the binding ability of CUL4A-DDB1 and REDD1.

CONCLUSION

Altogether, MIAT promotes autophagy and apoptosis of neural cells and aggravates IS by up-regulating the expression of REDD1.

Prognostic Value of MicroRNA-20b in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a highly heterogeneous disease that requires fine-grained risk stratification for the best prognosis of patients. As a class of small non-coding RNAs with important biological functions, microRNAs play a crucial role in the pathogenesis of AML. To assess the prognostic impact of miR-20b on AML in the presence of other clinical and molecular factors, we screened 90 AML patients receiving chemotherapy only and 74 also undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) from the Cancer Genome Atlas (TCGA) database. In the chemotherapy-only group, high miR-20b expression subgroup had shorter event-free survival (EFS) and overall survival (OS, both P < 0.001); whereas, there were no significant differences in EFS and OS between high and low expression subgroups in the allo-HSCT group. Then we divided all patients into high and low expression groups based on median miR-20b expression level. In the high expression group, patients treated with allo-HSCT had longer EFS and OS than those with chemotherapy alone (both P < 0.01); however, there were no significant differences in EFS and OS between different treatment subgroups in the low expression group. Further analysis showed that miR-20b was negatively correlated with genes in “ribosome,” “myeloid leukocyte mediated immunity,” and “DNA replication” signaling pathways. ORAI2, the gene with the strongest correlation with miR-20b, also had significant prognostic value in patients undergoing chemotherapy but not in the allo-HSCT group. In conclusion, our findings suggest that high miR-20b expression is a poor prognostic indicator for AML, but allo-HSCT may override its prognostic impact.

Development and validation of a hypoxia-related gene pair signature to predict overall survival in head and neck squamous cell carcinoma

OBJECTIVE

Head and neck squamous cell carcinoma (HNSCC) are a highly aggressive tumor with an extremely poor prognosis. Thus, we aimed to develop and validate a robust prognostic signature that can estimate the prognosis for HNSCC.

METHODS

Data on gene expressions and clinical were downloaded from TCGA and GEO database. To develop the best prognosis signature, a LASSO Cox Regression model was employed. Time-dependent receiver-operating characteristic (ROC) was used to determine the best cut-off value. Patients were divided into high-risk and low-risk hypoxia groups according to cut-off value. Survival differences were evaluated by log-rank test, while multivariate analysis was performed by a Cox proportional hazards model.

RESULTS

A 17-HRGPs composed of 24 unique genes was constructed, which was significantly related to OS. In the TCGA and GEO datasets, patients in the high hypoxia risk group have a poor prognosis (TCGA: P < 0.001, GEO: P < 0.05). After adjusting for other clinicopathological parameters, the 17-HRGP signature was independent prognostic factors in patients with HNSCC (P < 0.05). Functional analysis revealed that mRNA binding, gene silencing by RNA, RNA binding involved in posttranscriptional gene silencing signaling pathway were enriched in the low-risk groups. For this model, C-index was 0.684, which was higher than that of many established risk models. Macrophages M0, Mast cells activated, NK cells resting, T cells CD4 memory resting, etc. were significantly higher in the high-risk group, and B cells memory, Plasma cells, T cells follicular helper, T cells gamma delta, T cells CD8, etc. were significantly higher in the low-risk group.

CONCLUSION

In summary, our study constructed a robust HRGPs signature as molecular markers for predicting the outcome of HNSCC patients.

Organophosphate ester tri-o-cresyl phosphate interacts with estrogen receptor α in MCF-7 breast cancer cells promoting cancer growth

Plastic in the ocean degrades to microplastic, thereby enhancing the leaching of incorporated plasticizers due to the increased particle surface. The uptake of microplastic-derived plasticizers by marine animals and the subsequent entry in the food chain raises concerns for adverse health effects in human beings. Frequently used plasticizers as the organophosphate ester tri-o-cresyl phosphate (TOCP) are known to affect the male reproductive system. However, the overall endocrine potential of TOCP and the underlying molecular mechanisms remain elusive as yet. In this study, we investigated the molecular effects of TOCP on estrogen receptor α (ERα)-transfected HEK-ESR1 cells and the human breast cancer cell line MCF-7. Applying virtual screening and molecular docking, we identified TOCP as potent ligand of ERα in silico. Microscale thermophoresis confirmed the binding in vitro with similar intensity as the natural ligand 17-β-estradiol. To identify the molecular mechanisms of TOCP-mediated effects, we used next-generation sequencing to analyze the gene expression pattern of TOCP-treated MCF-7 cells. RNA-sequencing revealed 22 differently expressed genes associated with ESR1 as upstream regulator: CYP1A1, SLC7A11, RUNX2, DDIT4, STC2, KLHL24, CCNG2, CEACAM5, SLC7A2, MAP1B, SLC7A5, IGF1R, CD55, FOSL2, VEGFA, and HSPA13 were upregulated and PRKCD, CCNE1, CEBPA, SFPQ, TNFAIP2, KRT19 were downregulated. The affected genes promote tumor growth by increasing angiogenesis and nutritional supply, favor invasion and metastasis, and interfere with the cell cycle. Based on the gene expression pattern, we conclude TOCP to mediate endocrine effects on MCF-7 cells by interacting with ERα.

Up-regulation of DDIT4 predicts poor prognosis in acute myeloid leukaemia

The mammalian target of rapamycin (mTOR) inhibitor, DNA damage inducible transcript 4 (DDIT4), has inducible expression in response to various cellular stresses. In multiple malignancies, studies have shown that DDIT4 participates in tumorigenesis and impacts patient survival. We aimed to study the prognostic value of DDIT4 in acute myeloid leukaemia (AML), which is currently unclear. Firstly, The Cancer Genome Atlas was screened for AML patients with complete clinical characteristics and DDIT4 expression data. A total of 155 patients were included and stratified according to the treatment modality and the median DDIT4 expression levels. High DDIT4 expressers had shorter overall survival (OS) and event‐free survival (EFS) than the low expressers among the chemotherapy‐only group (all P < .001); EFS and OS were similar in the high and low DDIT4 expressers of the allogeneic haematopoietic stem cell transplantation (allo‐HSCT) group. Furthermore, in the DDIT4^high group, patients treated with allo‐HSCT had longer EFS and OS than those who received chemotherapy alone (all P < .01). In the DDIT4^low group, OS and EFS were similar in different treatment groups. Secondly, we analysed two other cytogenetically normal AML (CN‐AML) cohorts derived from the Gene Expression Omnibus database, which confirmed that high DDIT4 expression was associated with poorer survival. Gene Ontology (GO) enrichment analysis showed that the genes related to DDIT4 expression were mainly concentrated in the acute and chronic myeloid leukaemia signalling pathways. Collectively, our study indicates that high DDIT4 expression may serve as a poor prognostic factor for AML, but its prognostic effects could be outweighed by allo‐HSCT.