CEBPE expression is an independent prognostic factor for acute myeloid leukemia

A large-scale cancer-specific protein-DNA interaction network

Cancer development and progression are generally associated with gene dysregulation, often resulting from changes in the transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network, as well as an extensive promoter clone resource for future studies. Highly connected TFs bind to promoters of genes associated with either good or poor cancer prognosis, suggesting that strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene-targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activators or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF ESR1 in DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study broadens our knowledge of the TFs involved in cancer gene regulation and provides a valuable resource for future studies and therapeutics.

Comprehensive Analysis of CCAAT/Enhancer Binding Protein Family in Ovarian Cancer

Background

Ovarian cancer has brought serious threats to female health. CCAAT/enhancer binding proteins (C/EBPs) are key transcription factors involved in ovarian cancer. Therefore, comprehensive profiling C/EBPs in ovarian cancer is needed.

Methods

A comprehensive analysis concerning C/EBPs in ovarian cancer was performed. Firstly, detailed expression of C/EBP family members was integrally retrieved and then confirmed using immunohistochemistry. The regulatory effects and transcription regulatory functions of C/EBPs were studied by using regulatory network analysis and enrichment analysis. Using survival analysis, receiver operating characteristic curve analysis, and target-disease association analysis, the predictive prognostic value of C/EBPs on survival and drug responsiveness was systematically evaluated. The effects of C/EBPs on tumor immune infiltration were also assessed.

Results

Ovarian cancer tissues expressed increased CEBPA, CEBPB, and CEBPG but decreased CEBPD when compared with normal control tissues. The overall alteration frequency of C/EBPs in ovarian cancer was approaching 30%. C/EBP family members formed a reciprocal regulatory network involving carcinogenesis and had pivotal transcription regulatory functions. C/EBPs could affect survival of ovarian cancer and correlated with poor survival outcomes (OS: HR = 1.40, P = .0053 and PFS: HR = 1.41, P = .0036). Besides, expression of CEBPA, CEBPB, CEBPD, and CEBPE could predict platinum and taxane responsiveness of ovarian cancer. C/EBPs also affected immune infiltration of ovarian cancer.

Conclusions

C/EBPs were closely involved in ovarian cancer and exerted multiple biological functions. C/EBPs could be exploited as prognostic and predictive biomarkers in ovarian cancer.

A large-scale cancer-specific protein-DNA interaction network

Cancer development and progression are generally associated with dysregulation of gene expression, often resulting from changes in transcription factor (TF) sequence or expression. Identifying key TFs involved in cancer gene regulation provides a framework for potential new therapeutics. This study presents a large-scale cancer gene TF-DNA interaction network as well as an extensive promoter clone resource for future studies. Most highly connected TFs do not show a preference for binding to promoters of genes associated with either good or poor cancer prognosis, suggesting that emerging strategies aimed at shifting gene expression balance between these two prognostic groups may be inherently complex. However, we identified potential for oncogene targeted therapeutics, with half of the tested oncogenes being potentially repressed by influencing specific activator or bifunctional TFs. Finally, we investigate the role of intrinsically disordered regions within the key cancer-related TF estrogen receptor ɑ (ESR1) on DNA binding and transcriptional activity, and found that these regions can have complex trade-offs in TF function. Altogether, our study not only broadens our knowledge of TFs involved in the cancer gene regulatory network but also provides a valuable resource for future studies, laying a foundation for potential therapeutic strategies targeting TFs in cancer.

Synchronous Breast and Cervical Carcinoma: A Genetic Point of View

Breast carcinoma is the most common cancer of women in Malaysia. The most common sites of metastasis are the lung, liver, bone and brain. A 45-year-old lady was diagnosed with left invasive breast carcinoma stage IV (T4cN1M1) with axillary lymph nodes and lung metastasis. She was noted to have a cervical mass through imaging, and biopsy showed CIN III. Post chemotherapy, the patient underwent left simple mastectomy with examination under anaesthesia of the cervix, cystoscopy and staging. The cervical histopathological examination (HPE) showed squamous cell carcinoma, and clinical staging was 2A. The breast tissue HPE showed invasive carcinoma with triple receptors positivity. The patient was given tamoxifen and put on concurrent chemoradiotherapy (CCRT) for the cervical cancer. The management of each pathology of this patient involved a multi-disciplinary team that included surgeons, oncologists, gynaecologists, pathologists and radiologists. Due to the complexity of the case with two concurrent cancers, the gene expression profiles may help predict the patient's clinical outcome.

A Transfer-Learning-Based Deep Convolutional Neural Network for Predicting Leukemia-Related Phosphorylation Sites from Protein Primary Sequences

As one of the most important post-translational modifications (PTMs), phosphorylation refers to the binding of a phosphate group with amino acid residues like Ser (S), Thr (T) and Tyr (Y) thus resulting in diverse functions at the molecular level. Abnormal phosphorylation has been proved to be closely related with human diseases. To our knowledge, no research has been reported describing specific disease-associated phosphorylation sites prediction which is of great significance for comprehensive understanding of disease mechanism. In this work, focusing on three types of leukemia, we aim to develop a reliable leukemia-related phosphorylation site prediction models by combing deep convolutional neural network (CNN) with transfer-learning. CNN could automatically discover complex representations of phosphorylation patterns from the raw sequences, and hence it provides a powerful tool for improvement of leukemia-related phosphorylation site prediction. With the largest dataset of myelogenous leukemia, the optimal models for S/T/Y phosphorylation sites give the AUC values of 0.8784, 0.8328 and 0.7716 respectively. When transferred learning on the small size datasets, the models for T-cell and lymphoid leukemia also give the promising performance by common sharing the optimal parameters. Compared with other five machine-learning methods, our CNN models reveal the superior performance. Finally, the leukemia-related pathogenesis analysis and distribution analysis on phosphorylated proteins along with K-means clustering analysis and position-specific conversation profiles on the phosphorylation site all indicate the strong practical feasibility of our easy-to-use CNN models.

Transcription factor MEF2D is required for the maintenance of MLL-rearranged acute myeloid leukemia

MEF2D is highly expressed in MLL-rearranged AML and required for leukemia development in vitro and in vivo.

MEF2D suppresses CEBPE-mediated myeloid differentiation in AML.

Acute myeloid leukemia (AML) with MLL-rearrangement (MLL-r) comprises ∼10% of all AML cases and portends poor outcomes. Much remains uncovered on how MLL-r AML drives leukemia development while preventing cells from normal myeloid differentiation. Here, we identified that transcription factor MEF2D is a super-enhancer-associated, highly expressed gene in MLL-r AML. Knockout of MEF2D profoundly impaired leukemia growth, induced myeloid differentiation, and delayed oncogenic progression in vivo. Mechanistically, MEF2D loss led to robust activation of a CEBPE-centered myeloid differentiation program in AML cells. Chromatin profiling revealed that MEF2D binds to and suppresses the chromatin accessibility of CEBPE cis-regulatory regions. In human acute leukemia samples, MEF2D expression showed a strong negative correlation with the expression of CEBPE. Depletion of CEBPE partially rescued the cell growth defect and myeloid cell differentiation induced by the loss of MEF2D. Lastly, we show that MEF2D is positively regulated by HOXA9, and downregulation of MEF2D is an important mechanism for DOT1L inhibitor-induced antileukemia effects. Collectively, our findings suggest that MEF2D plays a critical role in human MLL-r AML and uncover the MEF2D-CEBPE axis as a crucial transcriptional mechanism regulating leukemia cell self-renewal and differentiation block.

CEBPG promotes acute myeloid leukemia progression by enhancing EIF4EBP1

Background

Acute myeloid leukemia (AML) is a myeloid neoplasm accounts for 7.6% of hematopoietic malignancies. AML is a complex disease, and understanding its pathophysiology is contributing to the improvement in the treatment and prognosis of AML. In this study, we assessed the expression profile and molecular functions of CCAAT enhancer binding protein gamma (CEBPG), a gene implicated in myeloid differentiation and AML progression.

Methods

shRNA mediated gene interference was used to down-regulate the expression of CEBPG in AML cell lines, and knockdown efficiency was detected by RT-qPCR and western blotting. The effect of knockdown on the growth of AML cell lines was evaluated by CCK-8. Western blotting was used to detect PARP cleavage, and flow cytometry were used to determine the effect of knockdown on apoptosis of AML cells. Genes and pathways affected by knockdown of CEBPG were identified by gene expression analysis using RNA-seq. One of the genes affected by knockdown of CEBPG was Eukaryotic translation initiation factor 4E binding protein 1 (EIF4EBP1), a known repressor of translation. Knockdown of EIF4EBP1 was used to assess its potential role in AML progression downstream of CEBPG.

Results

We explored the ChIP-Seq data of AML cell lines and non-AML hematopoietic cells, and found CEBPG was activated through its distal enhancer in AML cell lines. Using the public transcriptomic dataset, the Cancer Cell Line Encyclopedia (CCLE) and western blotting, we also found CEBPG was overexpressed in AML. Moreover, we observed that CEBPG promotes AML cell proliferation by activating EIF4EBP1, thus contributing to the progression of AML. These findings indicate that CEBPG could act as a potential therapeutic target for AML patients.

Conclusion

In summary, we systematically explored the molecular characteristics of CEBPG in AML and identified CEBPG as a potential therapeutic target for AML patients. Our findings provide novel insights into the pathophysiology of AML and indicate a key role for CEBPG in promoting AML progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02305-z.

ACE2 protein expression within isogenic cell lines is heterogeneous and associated with distinct transcriptomes

The membrane protein angiotensin-converting enzyme 2 (ACE2) is a physiologic regulator of the renin-angiotensin system and the cellular receptor for the SARS-CoV-2 virus. Prior studies of ACE2 expression have primarily focused on mRNA abundance, with investigation at the protein level limited by uncertain specificity of commercial ACE2 antibodies. Here, we report our development of a sensitive and specific flow cytometry-based assay for cellular ACE2 protein abundance. Application of this approach to multiple cell lines revealed an unexpected degree of cellular heterogeneity, with detectable ACE2 protein in only a subset of cells in each isogenic population. This heterogeneity was mediated at the mRNA level by transcripts predominantly initiated from the ACE2 proximal promoter. ACE2 expression was heritable but not fixed over multiple generations of daughter cells, with gradual drift toward the original heterogeneous background. RNA-seq profiling identified distinct transcriptomes of ACE2-expressing relative cells to non-expressing cells, with enrichment in functionally related genes and transcription factor target sets. Our findings provide a validated approach for the specific detection of ACE2 protein at the surface of single cells, support an epigenetic mechanism of ACE2 gene regulation, and identify specific pathways associated with ACE2 expression in HuH7 cells.

ACE2 protein expression within isogenic cell lines is heterogeneous and associated with distinct transcriptomes

The membrane protein angiotensin-converting enzyme 2 (ACE2) is a physiologic regulator of the renin-angiotensin system and the cellular receptor for the SARS-CoV-2 virus. Prior studies of ACE2 expression have primarily focused on mRNA abundance, with investigation at the protein level limited by uncertain specificity of commercial ACE2 antibodies. Here, we report our development of a sensitive and specific flow cytometry-based assay for cellular ACE2 protein abundance. Application of this approach to multiple cell lines revealed an unexpected degree of cellular heterogeneity, with detectable ACE2 protein in only a subset of cells in each isogenic population. This heterogeneity was mediated at the mRNA level by transcripts predominantly initiated from the ACE2 proximal promoter. ACE2 expression was heritable but not fixed over multiple generations of daughter cells, with gradual drift toward the original heterogeneous background. RNA-seq profiling identified distinct transcriptomes of ACE2-expressing relative cells to non-expressing cells, with enrichment in functionally related genes and transcription factor target sets. Our findings provide a validated approach for the specific detection of ACE2 protein at the surface of single cells, support an epigenetic mechanism ACE2 gene regulation, and identify specific pathways associated with ACE2 expression in HuH7 cells.

UHRF1 predicts poor prognosis by triggering cell cycle in lung adenocarcinoma

Accumulating evidence suggests that ubiquitin‐like with plant homeodomain and ring finger domains 1 (UHRF1) is overexpressed in non‐small cell lung cancer (NSCLC); however, the expression and function of UHRF1 in the subtype of NSCLC are still unclear. Here, we investigate the expression and prognosis traits of UHRF1 in large NSCLC cohorts and explore the molecular characters during UHRF1 up‐regulation. We find that UHRF1 is predominantly overexpressed in lung squamous cell carcinoma (SCC). Surprisingly, the up‐regulated UHRF1 is only associated with the overall survival of lung adenocarcinoma (ADC) and knockdown of UHRF1 dramatically attenuates ADC tumorigenesis. Mechanically, we identify a hub gene that includes a total of 55 UHRF1‐related genes, which are tightly associated with cell cycle pathway and yield to the poor clinical outcome in ADC patients. What's more, we observe knockdown of UHRF1 only affects ADC cells cycle and induces cell apoptosis. These results suggest that up‐regulated UHRF1 only contributes to lung ADC survival by triggering cell cycle pathway, and it may be a prognostic biomarker for lung ADC patients.

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.