Transcriptional Regulatory Relationships Research Articles

Computational analysis of circadian-rhythm dysregulated genes exhibiting undifferential expression in Oryza sativa

ABSTRACT Differential expression(DE) analysis identifies genes with differential expressions in a phenotype, but it cannot detect coordinated regulations of a gene from its transcription factors(TFs). This study selected rice diurnal rhythmic samples to train a transcriptional regulatory relationship model, which was used to predict the expression levels of target genes based on those of TFs in the other samples. The difference between the predicted and real expression levels of a target gene in a sample was defined as this gene’s model-based quantitative transcription regulation alternation (mqTrans) value. This study paid special attention to those genes with significant changes in their mqTrans values but without differential expression patterns, which were called dark biomarkers of rice circadian rhythm. The investigation revealed three dark biomarkers that were otherwise ignored by the conventional biomarker studies due to the undifferential expressions. One detected dark biomarker Os11g0135400 was crucial for rice circadian changes, but they were not on the list of published genes that were differentially expressed in circadian rhythm changes. This study captured important circadian rhythmic biomarkers ignored by traditional biological and computational methods. The proposed mqTrans analysis and the detected dark biomarkers contributed complementary information to the understanding of the rice circadian rhythmic mechanism.

Genome-wide identification and transcription factor regulation of monolignol biosynthetic genes in Ginkgo biloba L.

BackgroundGinkgo biloba L. is a widely cultivated Mesozoic relict gymnosperm, and the wood is resource-rich. As a main component of plant cell walls, lignin serves for plant water transport and mechanical support, as well as directly defining the properties of wood-based products. The lignin biosynthesis pathway in gymnosperms is simpler than that in angiosperms, but has been poorly studied due to the lack of model plants. ResultsIn the present study, we systematically identified a total of 157 monolignol biosynthetic genes from 10 families in G. biloba, including 12 Gb4CLs, 34 GbC3Hs, 7 GbC4Hs, 34 GbCADs, 8 GbCCoAOMTs, 19 GbCCRs, 13 GbCOMTs, 14 GbCSEs, 11 GbHCTs and 5 GbPALs. The chromosome localization, gene structure, gene promoter and other analyses were also conducted. We established a regulatory network between the identified monolignol biosynthetic genes and TFs generated by TGMI algorithm using 133 public RNA-seq datasets of various G. biloba tissues. We then examined 2 gene pairs from the network of their regulatory relationship via yeast one-hybrid and dual-luciferase reporter assay, and the results were positive confirming interactions existing between the GbMYB-025 protein and GbCAD31 promoter, GbERF-174 protein and GbCSE13 promoter in vivo. ConclusionsOur results provided a new effective approach to find transcriptional regulatory relationships and established an important foundation for molecular mechanisms and genetic regulation of monolignol biosynthesis in G. biloba.

Abstract 4883: NFE2L3 regulates the expression of BHLHE40 in triple-negative breast cancer

Abstract Introduction: Breast Cancer (BrCA) is one of the most common cancers, causing mortality in women worldwide. Among the subtypes of breast cancer, triple-negative breast cancer (TNBC) is the most aggressive due to the absence of three major receptors: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER-2). Treatment options for TNBC are limited because of the lack of these molecular targets. We hypothesized that the identification and characterization of novel transcriptional regulatory relationships in TNBC will provide etiologic insights, enhance therapeutic outcomes, and improve patient survival. Overexpression of NFE2L3 in BrCA has inhibited cell proliferation and metastasis while overexpression of BHLHE40 has produced an inverse effect. This study aims to characterize the relationship between NFE2L3 and BHLHE40 in TNBC cells. Methods: Patient data from the two groups of our focus from the Cancer Genome Atlas BrCA RNAseq gene expression dataset were examined: triple-positive breast cancer (TPBC) and TNBC. Differentially expressed genes (DEGs) between these groups were identified using DESeq2. Pathways over-represented among the DEGs were determined using enrichR. For their impact on biological interactions, those DEGs were mapped to curate protein-protein interactions - the STRING database. Additionally, DEGs were superposed on two network inference algorithm-generated transcriptional regulatory networks (TRNs). Virtual Inference of protein activity by Enriched Regulon analysis was applied to the generated TRN to identify master regulators driving gene expression differences between TPBC and TNBC. Of the master regulators observed, the activity of NFE2L3 was explored in TNBC cells. The TRNs indicate that NFE2L3 regulates the expression of BHLHE40. This regulatory relationship was explored in TNBC cells by RNA interference, qRT-PCR, immunoblotting, and co-immunoprecipitation assays to investigate NFE2L3 and BHLHE40 gene and protein expression and interaction. Results: Among 12,000 DEGs (5% FDR), over-represented pathways included “mitotic signaling” and “G1/S transition”. Master regulators with higher expression in TNBC included NFE2L3, HMGA1, TP53, FOXC1, and SOX9; those with lower expression included FOXA1, BHLHE40, AR, XBP1, and ESR1. On silencing the cells of NFE2L3 and performing qRTPCR analysis, the expression of BHLHE40 was decreased in the TNBC cells. The protein-protein interaction between NFE2L3 and BHLHE40 was also validated. Conclusion: DEGs up-regulated in TNBC participate in cell cycle signaling. And there is a novel transcriptional regulatory relationship between NFE2L3 and BHLHE40 in TNBC cells. Citation Format: Shail Rakesh Modi, Terrick Andey, George Acquaah-Mensah. NFE2L3 regulates the expression of BHLHE40 in triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4883.

Identification of hub genes and transcription factors in patients with primary gout complicated with atherosclerosis

Evidence shows that primary gout is prone to develop to atherosclerosis, but the mechanism of its occurrence is still not fully clarified. The aim of this study was to explore the molecular mechanism of the occurrence of this complication in gout. The gene expression profiles of primary gout and atherosclerosis were downloaded from the gene expression omnibus database. Overlapping differentially expressed genes (DEGs) between gout and atherosclerosis were identified. The biological roles of common DEGs were explored through enrichment analyses. Hub genes were identified using protein–protein interaction networks. The immune infiltrations of 28 types of immune cells in gout and control samples from GSE160170 were evaluated by the ssGSEA method. Transcription factors (TFs) were predicted using Transcriptional Regulatory Relationships Unraveled by Sentence Based Text Mining (TRRUST) database. A total of 168 overlapping DEGs were identified. Functional enrichment analyses indicated that DEGs were mostly enriched in chemokine signaling pathway, regulation of actin cytoskeleton, and TNF signaling pathway. CytoScape demonstrated 11 hub genes and two gene cluster modules. The immune infiltration analysis showed that the expression of DEGs in gout was significantly upregulated in activated CD4 T cells, gamma delta T cells, T follicular helper cell, CD56dim natural killer cells, and eosinophil. TRRUST predicted one TF, RUNX family transcription factor 1. Our study explored the pathogenesis of gout with atherosclerosis and discovered the immune infiltration of gout. These results may guide future experimental research and clinical transformation.

Identification of Senescence-Related Biomarkers and Regulatory Networks in Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) is a severe neurological disorder with substantial societal implications. Cellular senescence plays a critical role in ICH pathogenesis. This study aims to identify senescence-related biomarkers in ICH for diagnostic and therapeutic purposes. Raw data from GSE24265 in Gene Expression Omnibus was downloaded. Senescence-related genes were acquired from CellAge. Differential gene analysis was done between patients with ICH and controls. The intersection of ICH differentially expressed genes and senescence-related genes for senescence-related ICH genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Protein-protein interaction network was constructed through the Search Tool for the Retrieval of Interacting Genes. Single sample gene set enrichment analysis was done for immune cell infiltration and function evaluation in control and ICH groups. miRWalk2.0 database was used for microRNA predictions targeting ICH biomarkers. Transcriptional regulatory relationships unraveled by sentence-based text mining database was employed to predict transcription factors regulating identified biomarkers. Thirteen senescence-related ICH genes were identified. They were primarily enriched in the positive regulation of angiogenesis and the Advanced Glycation End Product -Receptor for AGE signaling pathway in diabetic complications. Validation in the GSE149317 data set and receiver operating characteristic analysis highlighted Caveolin 1, C-X-C Motif Chemokine Ligand 1, ETS proto-oncogene 1, transcription factor, and Serpin Family E Member 1 as potential ICH biomarkers. Single sample gene set enrichment analysis revealed increased Type 2 T helper cell 2_cells, Treg cells, and immune functions like Antigen-presenting cells_co_stimulation in patients with ICH. Fourteen microRNA, including has-miR-6728-3p, were predicted to regulate these biomarkers. transcription factors such as PPARG, RARA, HMGA1, and NFKB1 were identified as potential regulators of the ICH biomarkers. Caveolin 1, C-X-C Motif Chemokine Ligand 1, ETS proto-oncogene 1, transcription factor, and Serpin Family E Member 1 may serve as valuable biomarkers in ICH. Targeting these genes could contribute to ICH prevention and treatment.

Abstract B049: Pancreatic beta cell stress pathways drive pancreatic ductal adenocarcinoma development in obesity

Abstract Epidemiologic studies have shown that obesity is a risk factor for more than a dozen cancers, including pancreatic ductal adenocarcinoma (PDAC). As PDAC is one of the leading causes of cancer-related death and obesity rates are rapidly increasing worldwide, it is imperative that we understand the mechanisms by which obesity promotes PDAC progression. To address this gap in knowledge, our lab combined a well-established genetic model for obesity (O: Lepob/ob) with a Kras-driven pancreatic cancer model (KC: Pdx1-Cre; KrasLSL-G12D/+) that mimics human PDAC progression. Resultant KCO mice had a drastic increase in tumor development compared to their lean counterparts, whereas induced weight loss intercepted tumor progression, showing that the tumor-promoting effects of obesity can be reversed. Bulk RNA sequencing of tumors from these mice revealed aberrantly increased expression of multiple peptide hormones expressed in insulin-producing beta (b) cells of pancreatic islets, including cholecystokinin (CCK) and amylin (Iapp). Strikingly, transgenic expression of CCK and Iapp in b-cells was sufficient to promote Kras-driven pancreatic tumorigenesis in non-obese mice. Single-cell RNA sequencing of b cells showed a trajectory of changes in gene expression with increasing obesity from wildtype to high-fat diet-fed to Lepob/ob mice. Further in silico analysis combining archetypal (AANet) with pseudotime (TrajectoryNet) methods demonstrated that b cells misexpressing hormones (CCK and Iapp) arose from a specific subtype of preexisting b cells, specifically virgin b cells, a rare, immature, regenerative population. Preliminary in vivo lineage tracing analyses in MIP-CreERT;LSL-TdTomato;Lepob/ob mice support these findings. Finally, we investigated the transcriptional networks that lead to aberrant CCK and Iapp expression in b cells. By combining Grainger causality analysis with known gene-gene relationships in the Transcriptional Regulatory Relationship Unraveled by Sentence-based Text mining (TRRUST) v2 database, we discovered a stress-induced mitogen-activated protein kinase (MAPK8)-cJun pathway that promotes pro-tumorigenic hormone expression in b cells. These combined experimental and computational methods nominate novel b cell targets to subvert the development of PDAC, an exocrine tumor. Citation Format: Cathy C. Garcia, Aarthi Venkat, Alex Tong, Sherry Agabiti, Lauren Lawres, Rebecca Cardone, Richard Kibbey, Smita Krishnaswamy, Mandar D Muzumdar. Pancreatic beta cell stress pathways drive pancreatic ductal adenocarcinoma development in obesity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B049.

Uncovering the pathogenesis of obesity complicated with papillary thyroid carcinoma via bioinformatics and experimental validation.

This study aimed to investigate the common molecular mechanism between obesity and papillary thyroid cancer (PTC), the most common pathological type of thyroid cancer. In this study, we obtained gene expression datasets for obesity (GSE151839) and PTC (GSE33630) from the Gene Expression Omnibus (GEO). We used the Perl program and R software to identify differentially expressed genes (DEGs) and common genes, perform GO function and KEGG pathway enrichment analysis, construct a protein-protein interaction (PPI) network, identify hub genes, and perform transcription factors (TFs) analysis. After undergoing validation in external datasets and in vitro experiments, common targets for both diseases were ultimately identified. A total of 23 genes that were differentially expressed (DEGs) between obesity and papillary thyroid carcinoma (PTC) were identified in our study. Among these DEGs, 17 genes were up-regulated while 6 genes were down-regulated. Then the top ten key genes were identified from the PPI network using cytoHubba and MCODE plug-in. Further evidence from external datasets revealed that MMP9, MNDA, TNC, and CHIT1 were identified as hub genes for both diseases. The study utilized Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRRUST) to perform an enrichment analysis of TFs. This analysis identified ELF4 and STAT3 as common TFs for both diseases. Additionally, in vitro experiments were conducted to further analyze the clinical significance and biological functions of these TFs. The identification and investigation of hub genes and their corresponding TFs that regulate abnormalities in obesity and PTC can enhance our comprehension of the underlying connection between these two diseases, thus leading to the development of novel diagnostic approaches.

Exploring the potential relationship between frozen shoulder and Dupuytren's disease through bioinformatics analysis and machine learning.

Frozen shoulder (FS) and Dupuytren's disease (DD) are two closely related diseases, but the mechanism of their interaction is unknown. Our study sought to elucidate the molecular mechanism of these two diseases through shared gene and protein interactions. GSE75152 and GSE140731 data were downloaded from the Gene Expression Omnibus (GEO) database, and shared genes between FS and DD were selected by using R packages. Then, we used Cytoscape software and the STRING database to produce a protein-protein interaction (PPI) network. Important interaction networks and hub genes were selected through MCODE and cytoHubba algorithms. To explore the potential mechanisms of the development of the two diseases, the hub genes were further enriched by GO and KEGG analyses. We predicted the transcription factors (TFs) of hub genes with Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRRUST). Moreover, we identified candidate genes for FS with DD with cytoHubba and machine learning algorithms. Finally, we analyzed the role of immunocyte infiltration in FS and constructed the relationship between candidate genes and immunocytes in FS. We identified a total of 321 shared genes. The results of GO and KEGG enrichment of shared genes showed that extracellular matrix and collagen fibril tissue play a certain role in the occurrence and development of disease. According to the importance of genes, we constructed the key PPI network of shared genes and the top 15 hub genes for FS with DD. Then, we predicted that five TFs are related to the hub genes and are highly expressed in the FS group. Machine learning results show that the candidate genes POSTN and COL11A1 may be key for FS with DD. Finally, immune cell infiltration revealed the disorder of immunocytes in FS patients, and expression of candidate genes can affect immunocyte infiltration. We identified a PPI network, 15 hub genes, and two immune-related candidate genes (POSTN and COL11A1) using bioinformatics analysis and machine learning algorithms. These genes have the potential to serve as diagnostic genes for FS in DD patients. Furthermore, our study reveals disorder of immunocytes in FS.

Bioinformatics-Based Analysis of Circadian Rhythm Regulation Mechanisms in Alzheimer's Disease.

There is a close association between Alzheimer's disease (AD) and circadian rhythms, and neuroinflammatory-related pathways are associated with both interactions. To reveal the relationship between circadian rhythm (CR) and AD at the level of genes, pathways, and molecular functions through bioinformatics. We analyzed the differential genes between AD and control groups in GSE122063 and found the important gene modules; obtained CR-related genes from GeenCard database; used Venn 2.1 database to obtain the intersection of genes of AD important modules with CR-related genes; and used STRING database and Cytoscape 3.7.1 to construct the gene protein-protein interaction network. The MCODE plugin was used to screen pivotal genes and analyze their differential expression. We trranslated with www.DeepL.com/Translator (free version) to obtain transcriptional regulatory relationships from the TRRUST database and construct a hub gene-transcription factor relationship network. A total of 42 common genes were screened from AD and CR genes, mainly involving signaling pathways such as neuroactive ligand-receptor interactions. A total of 10 pivotal genes were screened from the common genes of CR and AD, which were statistically significant in the comparison of AD and control groups (p < 0.001), and ROC analysis showed that all these pivotal genes had good diagnostic significance. A total of 36 TFs of pivotal genes were obtained. We identified AD- and CR-related signaling pathways and 10 hub genes and found strong associations between these related genes and biological processes such as inflammation.

Loss of Nudt15 thiopurine detoxification increases direct DNA damage in hematopoietic stem cells

Thiopurines, such as 6-mercaptopurine (6-MP), are widely used as cytotoxic agents and immunosuppressants for leukemia and autoimmune or inflammatory diseases. A nonsynonymous single nucleotide polymorphism (p.Arg139Cys; R139C) of the nucleoside diphosphate-linked moiety X-type motif 15 (NUDT15) gene causes the loss of thiopurine detoxification, inducing myelosuppression. To understand such hematotoxicity, we investigate the effects of NUDT15 R139C on hematopoietic stem cells (HSCs) upon thiopurine administration. Using previously established Nudt15R138C knock-in mice, which mimic myelosuppression in NUDT15R139C homozygous or heterozygous patients following thiopurine administration, we investigated the numerical changes of HSCs and hematopoietic progenitor cells following 6-MP administration using in vivo flowcytometry and ex vivo HSC expansion. Genes differentially expressed between Nudt15+/+ HSCs and Nudt15R138C/R138C HSCs were identified using RNA-sequencing before the emergence of 6-MP-induced HSC-damage. Gene Ontology (GO) and Transcriptional Regulatory Relationships Unraveled by Sentence-based Text Mining (TRRUST) analyses were performed to elucidate the molecular effects of 6-MP on HSCs. In Nudt15R138C/R138C mice, 6-MP induced exhaustion of HSCs faster than that of multipotent progenitors and as fast as that of myeloid-committed progenitors. Ex vivo-expanded Nudt15R138C/R138C HSCs were dose- and time-dependently damaged by 6-MP. GO analysis identified the DNA damage response and cell cycle process as the most strongly influenced processes in Nudt15R138C/R138C HSCs. TRRUST analysis revealed that the Trp53-regulated transcriptional regulatory network is influenced prior to HSC exhaustion in Nudt15R138C/R138C HSCs. The loss of NUDT15 thiopurine detoxification enhances thiopurine-mediated DNA damage via the Trp53 networks in HSCs. Therefore, caution is required in long-term thiopurine use in patients with NUDT15 R139C in view of its adverse effects on HSCs in the form of DNA damage.

MicroRNA-181a-5p Curbs Osteogenic Differentiation and Bone Formation Partially Through Impairing Runx1-Dependent Inhibition of AIF-1 Transcription.

Evidence has revealed the involvement of microRNAs (miRNAs) in modulating osteogenic differentiation, implying the promise of miRNA-based therapies for treating osteoporosis. This study investigated whether miR-181a-5p influences osteogenic differentiation and bone formation and aimed to establish the mechanisms in depth. Clinical serum samples were obtained from osteoporosis patients, and MC3T3-E1 cells were treated with osteogenic induction medium (OIM) to induce osteogenic differentiation. miR-181a-5p-, Runt-related transcription factor 1 (Runx1)-, and/or allograft inflammatory factor-1 (AIF-1)-associated oligonucleotides or vectors were transfected into MC3T3-E1 cells to explore their function in relation to the number of calcified nodules, alkaline phosphatase (ALP) staining and activity, expression levels of osteogenesis-related proteins, and apoptosis. Luciferase activity, RNA immunoprecipitation, and chromatin immunoprecipitation assays were employed to validate the binding relationship between miR-181a-5p and Runx1, and the transcriptional regulatory relationship between Runx1 and AIF-1. Ovariectomy (OVX)-induced mice were injected with a miR-181a-5p antagonist for in vivo verification. miR-181a-5p was highly expressed in the serum of osteoporosis patients. OIM treatment decreased miR-181a-5p and AIF-1 expression, but promoted Runx1 expression in MC3T-E1 cells. Meanwhile, upregulated miR-181a-5p suppressed OIM-induced increases in calcified nodules, ALP content, and osteogenesis-related protein expression. Mechanically, miR-181a-5p targeted Runx1, which acted as a transcription factor to negatively modulate AIF-1 expression. Downregulated Runx1 suppressed the miR-181a-5p inhibitor-mediated promotion of osteogenic differentiation, and downregulated AIF-1 reversed the miR-181a-5p mimic-induced inhibition of osteogenic differentiation. Tail vein injection of a miR-181a-5p antagonist induced bone formation in OVX-induced osteoporotic mice. In conclusion, miR-181a-5p affects osteogenic differentiation and bone formation partially via the modulation of the Runx1/AIF-1 axis.

VDR Regulates BNP Promoting Neurite Growth and Survival of Cochlear Spiral Ganglion Neurons through cGMP-PKG Signaling Pathway

Spiral ganglion neurons (SGNs) are important for hearing, and their peripheral and central processes connect sensory cells of the Corti organ to the central nervous system. The resulting network forms a point-to-point auditory conduction. As a cardiac hormone, brain natriuretic peptide (BNP) binds to natriuretic peptide receptor type A leading to diuresis, vasodilatation, inhibition of renin and aldosterone production, and cardiac and vascular myocyte growth. This study primarily aimed to explore the expression and function of BNP in the rat's inner ear and elucidate its regulatory mechanism. We determined the expression and function of BNP and found that the vitamin D receptor (VDR) could upregulate the expression of BNP and enhance its function. In SGNs of the rat inner ear, BNP promotes neuron survival and prolongs neurite length through the cGMP-PKG signaling pathway, which could be regulated by VDR and provide a novel approach for neuronal regeneration therapy. To the best of our knowledge, this is the first study to report this potential transcriptional regulatory relationship and will act as a reference for research on neuronal regeneration therapy for SGNs injury.

Single-cell analyses of axolotl telencephalon organization, neurogenesis, and regeneration.

Salamanders are tetrapod models to study brain organization and regeneration; however, the identity and evolutionary conservation of brain cell types are largely unknown. We delineated the cell populations in the axolotl telencephalon during homeostasis and regeneration using single-cell genomic profiling. We identified glutamatergic neurons with similarities to amniote neurons of hippocampus, dorsal and lateral cortex, and conserved γ-aminobutyric acid-releasing (GABAergic) neuron classes. We inferred transcriptional dynamics and gene regulatory relationships of postembryonic, region-specific neurogenesis and unraveled conserved differentiation signatures. After brain injury, ependymoglia activate an injury-specific state before reestablishing lost neuron populations and axonal connections. Together, our analyses yield insights into the organization, evolution, and regeneration of a tetrapod nervous system.

Identification of hub genes and transcription factors in patients with rheumatoid arthritis complicated with atherosclerosis

The aim of this study was to explore the overlapping key genes, pathway networks and transcription factors (TFs) related to the pathogenesis of rheumatoid arthritis (RA) and atherosclerosis. The gene expression profiles of RA and atherosclerosis were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between RA and atherosclerosis were identified. The biological roles of common DEGs were explored through enrichment analysis. Hub genes were identified using protein–protein interaction networks. TFs were predicted using Transcriptional Regulatory Relationships Unraveled by Sentence Based Text Mining (TRRUST) database. The hub genes and TFs were validated with other datasets. The networks between TFs and hub genes were constructed by CytoScape software. A total of 131 DEGs (all upregulated) were identified. Functional enrichment analyses indicated that DEGs were mostly enriched in leukocyte migration, neutrophil activation, and phagocytosis. CytoScape demonstrated 12 hub genes and one gene cluster module. Four of the 12 hub genes (CSF1R, CD86, PTPRC, and CD53) were validated by other datasets. TRRUST predicted two TFs, including Spi-1 proto-oncogene (SPI1) and RUNX family transcription factor 1(RUNX1). The expression of RUNX1 was validated with another dataset. Our study explored the common pathogenesis of RA and atherosclerosis. These results may guide future experimental research and clinical transformation.

Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network

BackgroundAlthough great efforts have been made to study the occurrence and development of glioma, the molecular mechanisms of glioma are still unclear. Single-cell sequencing technology provides a new perspective for researchers to explore the pathogens of tumors to further help make treatment and prognosis decisions for patients with tumors.MethodsIn this study, we proposed an algorithm framework to explore the molecular mechanisms of glioma by integrating single-cell gene expression profiles and gene regulatory relations. First, since there were great differences among malignant cells from different glioma samples, we analyzed the expression status of malignant cells for each sample, and then tumor consensus genes were identified by constructing and analyzing cell-specific networks. Second, to comprehensively analyze the characteristics of glioma, we integrated transcriptional regulatory relationships and consensus genes to construct a tumor-specific regulatory network. Third, we performed a hybrid clustering analysis to identify glioma cell types. Finally, candidate tumor gene biomarkers were identified based on cell types and known glioma-related genes.ResultsWe got six identified cell types using the method we proposed and for these cell types, we performed functional and biological pathway enrichment analyses. The candidate tumor gene biomarkers were analyzed through survival analysis and verified using literature from PubMed.ConclusionsThe results showed that these candidate tumor gene biomarkers were closely related to glioma and could provide clues for the diagnosis and prognosis of patients with glioma. In addition, we found that four of the candidate tumor gene biomarkers (NDUFS5, NDUFA1, NDUFA13, and NDUFB8) belong to the NADH ubiquinone oxidoreductase subunit gene family, so we inferred that this gene family may be strongly related to glioma.

Chromatin accessibility regulates chemotherapy-induced dormancy and reactivation

Cisplatin-based chemotherapy remains the standard care for non-small cell lung cancer (NSCLC) patients. Relapse after chemotherapy-induced dormancy affects the overall survival of patients. The evolution of cancer cells under chemotherapy stress is regulated by transcription factors (TFs) with binding sites initially buried deep within inaccessible chromatin. The transcription machinery and dynamic epigenetic alterations during the process of dormancy-reactivation of lung cancer cells after chemotherapy need to be investigated. Here, we investigated the chromatin accessibility of lung cancer cells after cisplatin treatment, using an assay for transposase-accessible chromatin sequencing (ATAC-seq). We observed that global chromatin accessibility was extensively improved. Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRRUST) v.2 was used to elucidate TF-target interaction during the process of dormancy and reactivation. Enhancer regions and motifs specific to key TFs including JUN, MYC, SMAD3, E2F1, SP1, CTCF, SMAD4, STAT3, NFKB1, and KLF4 were enriched in differential loci ATAC-seq peaks of dormant and reactivated cancer cells induced by chemotherapy. The findings suggest that these key TFs regulated gene expressions during the process of dormancy and reactivation of cancer cells through altering promoter accessibility of target genes. Our study helps advance understanding of how cancer cells adapt to the stress induced by chemotherapy through TF binding motif accessibility.

The Impacts of Transcriptional Regulatory Mechanism and Protein Interaction Relationship between RUNX1 and KLF4 on the Biological Functions of t (8;21) Leukemia Cells

Our previous study has reported that sodium phenylbutyrate (PB), one of the HDAC inhibitors, could induce t (8;21) leukemia cells to undergo differentiation and apoptosis. However, genes that promote differentiation and apoptosis in this process are not fully identified. Identification of these genes and elucidation of their interaction relationships are essential to develop novel therapy strategies for t (8;21) leukemia.In this study, we found that the expressions of RUNX1, KLF4 and P57 at both mRNA and protein level were significantly up-regulated in Kasumi-1 cells after PB treatment. Bioinformatics analysis further demonstrated that there might be some transcriptional regulatory mechanism and protein interaction relationship among these three genes.For the study of transcriptional regulatory mechanism, a KLF4 promoter/enhancer reporter plasmid containing RUNX1 binding sites and a P57 promoter/enhancer reporter plasmid containing KLF4 binding sites were constructed. Luciferase assay showed that RUNX1 exhibited strong transcriptional activation effect on KLF4 promoter/enhancer reporter plasmid in a dose-dependent manner, while RUNX1-ETO showed slight effect. KLF4 exhibited dose-dependent transcriptional activation effect on P57 promoter /enhancer reporter plasmid. These transcriptional regulatory relationships were further confirmed by Western blot assay. Transient expression of exogenous RUNX1 up-regulated the expression of KLF4 and P57 in 293T cells and Kasumi-1 cells, while RUNX1-ETO had no effect.In the study of protein interaction relationship, co-immunoprecipitation (CO-IP) and immunofluorescence confocal imaging showed that RUNX1 interacted with KLF4 and co-localized with it in nucleus, and Runt homology domain (RHD) was responsible for this interaction. RUNX1-ETO competed with RUNX1 for binding to KLF4 in a dose-dependent manner through RHD and the ETO domains. PB has no effect on the interactions between RUNX1/RUNX1-ETO with KLF4. To further investigate the effects of RUNX1 and RUNX1-ETO on KLF4-dependent transactivation of target genes, a luciferase reporting plasmid containing KLF4 binding sites was constructed. Luciferase assay was then performed and showed that RUNX1 could coactivate KLF4 target genes while RUNX1-ETO had little effect.Finally,RUNX1, KLF4 and P57 were overexpressed in Kasumi-1 cells by a pCDH lentivirus system, and their biological functions were investigated by MTS assay and flow cytometry. Overexpression of either of the three genes could inhibit cell proliferation, block cell cycle and induce apoptosis of t (8;21) leukemia cells. Moreover, in vivo experiment demonstrated that overexpression of KLF4 and P57 in mouse bone marrow leukemic cells could reduce the incidence of leukemia development in recipient mice.In conclusion, we reported “RUNX1-KLF4-P57” as a novel signaling pathway in t (8;21) leukemia cells in this study. RUNX1 transactivated KLF4 and then P57 in leukemia cells to inhibit cell proliferation, block cell cycle and induce cell apoptosis, while oncoprotein RUNX1-ETO had little effect. Moreover, RUNX1 interacted with KLF4 and coactivated its target genes, which could be blocked by the competed binding of RUNX1-ETO with KLF4. Our study revealed the regulatory relationship between RUNX1 and KLF4 and the impacts of RUNX1-ETO on this relationship, which helps to elucidate the mechanism of t (8;21) leukemogenensis. DisclosuresNo relevant conflicts of interest to declare.

Identification of potential diagnostic biomarkers in MMPs for pancreatic carcinoma.

Pancreatic cancer (PC) is a malignant tumor which ranks fourth in cancer-related death. However, the specificity and sensitivity of traditional biomarkers such as carbohydrate antigen 19-9 no longer meet the clinical requirements.Tools as ONCOMINE and Gene Expression Profiling Interactive Analysis (GEPIA) were used to analyze the differential expression of matrix metalloproteinases (MMPs) in PC and adjacent tissues. For further analysis, we adopted database for annotation, visualization and integrated discovery (DAVID 6.8), transcriptional regulatory relationships unraveled by sentence-based text (TRRUST) and other tools. We also identified drugs targeted the selected MMPs.Eight MMPs (MMP1, MMP2, MMP7, MMP9, MMP11, MMP12, MMP14, and MMP28) were differentially expressed in PC and adjacent tissue. MMP1 (P = .0189), MMP7 (P = .000216), MMP11 (P = .0209), MMP14 (P = .00611) were correlated with the pathological stages of PC. Patients with higher expression of MMP1 (P = .0011), MMP2 (P = .011), MMP7 (P = .0081), MMP9 (P = .046), MMP11 (P = .0019), MMP12 (P = .0011), MMP14 (P = .0011), and MMP28 (P = 6.3e-06) showed poor prognosis. Ten transcription factors were associated with the up-regulation of selected MMPs. Marimastat (DB00786) was found to target selected MMPs.Our research revealed that selected MMPs played an important role in the early diagnosis and prognosis of PC.

Membrane-Bound Transcriptional Activator NTL1 from Rapeseed Positively Modulates Leaf Senescence through Targeting Genes Involved in Reactive Oxygen Species Production and Programmed Cell Death.

Leaf senescence is the last stage of leaf development and is determined by various environmental and endogenous signals. Leaf senescence can determine plant productivity and fitness. Transcription factors (TFs) with the transmembrane domain constitute a special group of regulatory proteins that can translocate from the membrane system into nuclei to exert the transcriptional function upon endogenous or exogenous stimuli. Reactive oxygen species (ROSs) play an important role in numerous processes throughout the life cycle of plants including leaf senescence. Leaf senescence is characterized by massive programmed cell death (PCD) and is a type of developmental PCD. The transcriptional regulatory relationships between membrane-bound TFs and leaf senescence remain largely uncharacterized, especially in rapeseed (Brassica napus L.), an important oil crop. Here, we show that BnaNTL1 is a membrane-bound NAC (NAM, ATAF, and CUC) TF, which is predominantly expressed in senescent leaves. Expression of BnaNTL1ΔTM, a form of BnaNTL1 devoid of the transmembrane domain, can induce serious HR-like cell death symptoms and ROS accumulation in cells. Plants overexpressing BnaNTL1ΔTM show earlier leaf senescence compared with the control, accompanied by chlorophyll degradation and electrolyte leakage. Genes involved in ROS production (RbohD), PCD (VPEs and CEP1), and leaf senescence (BFN1) are significantly induced and activated by BnaNTL1ΔTM according to the quantitative reverse transcription PCR (qRT-PCR) analysis and dual luciferase reporter (Dual-LUC) assay. Moreover, electrophoretic mobility shift assay revealed that BnaNTL1 directly bound to the NTLBS elements in promoters of RbohD, γVPE, and BFN1. In conclusion, these results demonstrate that BnaNTL1 positively modulates ROS production and HR-like cell death to induce leaf senescence.

Identification of novel transcription factor-microRNA-mRNA co-regulatory networks in pulmonary large-cell neuroendocrine carcinoma.

BackgroundLarge cell neuroendocrine carcinoma (LCNEC) of the lung is a rare neuroendocrine neoplasm. Previous studies have shown that microRNAs (miRNAs) are widely involved in tumor regulation through targeting critical genes. However, it is unclear which miRNAs play vital roles in the pathogenesis of LCNEC, and how they interact with transcription factors (TFs) to regulate cancer-related genes.MethodsTo determine the novel TF-miRNA-target gene feed-forward loop (FFL) model of LCNEC, we integrated multi-omics data from Gene Expression Omnibus (GEO), Transcriptional Regulatory Relationships Unraveled by Sentence-Based Text Mining (TRRUST), Transcriptional Regulatory Element Database (TRED), and The experimentally validated microRNA-target interactions database (miRTarBase database). First, expression profile datasets for mRNAs (GSE1037) and miRNAs (GSE19945) were downloaded from the GEO database. Overlapping differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified through integrative analysis. The target genes of the FFL were obtained from the miRTarBase database, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed on the target genes. Then, we screened for key miRNAs in the FFL and performed gene regulatory network analysis based on key miRNAs. Finally, the TF-miRNA-target gene FFLs were constructed by the hypergeometric test.ResultsA total of 343 DEGs and 60 DEMs were identified in LCNEC tissues compared to normal tissues, including 210 down-regulated and 133 up-regulated genes, and 29 down-regulated and 31 up-regulated miRNAs. Finally, the regulatory network of TF-miRNA-target gene was established. The key regulatory network modules included ETS1-miR195-CD36, TAOK1-miR7-1-3P-GRIA1, E2F3-miR195-CD36, and TEAD1-miR30A-CTHRC1.ConclusionsWe constructed the TF-miRNA-target gene regulatory network, which is helpful for understanding the complex LCNEC regulatory mechanisms.