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1.
PLoS One ; 19(2): e0289561, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38324544

RESUMO

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) has a five-year survival rate of less than 5%. Absence of symptoms at primary tumor stages, as well as high aggressiveness of the tumor can lead to high mortality in cancer patients. Most patients are recognized at the advanced or metastatic stage without surgical symptom, because of the lack of reliable early diagnostic biomarkers. The objective of this work was to identify potential cancer biomarkers by integrating transcriptome data. METHODS: Several transcriptomic datasets comprising of 11 microarrays were retrieved from the GEO database. After pre-processing, a meta-analysis was applied to identify differentially expressed genes (DEGs) between tumor and nontumor samples for datasets. Next, co-expression analysis, functional enrichment and survival analyses were used to determine the functional properties of DEGs and identify potential prognostic biomarkers. In addition, some regulatory factors involved in PDAC including transcription factors (TFs), protein kinases (PKs), and miRNAs were identified. RESULTS: After applying meta-analysis, 1074 DEGs including 539 down- and 535 up-regulated genes were identified. Pathway enrichment analyzes using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that DEGs were significantly enriched in the HIF-1 signaling pathway and focal adhesion. The results also showed that some of the DEGs were assigned to TFs that belonged to 23 conserved families. Sixty-four PKs were identified among the DEGs that showed the CAMK family was the most abundant group. Moreover, investigation of corresponding upstream regions of DEGs identified 11 conserved sequence motifs. Furthermore, weighted gene co-expression network analysis (WGCNA) identified 8 modules, more of them were significantly enriched in Ras signaling, p53 signaling, MAPK signaling pathways. In addition, several hubs in modules were identified, including EMP1, EVL, ELP5, DEF8, MTERF4, GLUP1, CAPN1, IGF1R, HSD17B14, TOM1L2 and RAB11FIP3. According to survival analysis, it was identified that the expression levels of two genes, EMP1 and RAB11FIP3 are related to prognosis. CONCLUSION: We identified several genes critical for PDAC based on meta-analysis and system biology approach. These genes may serve as potential targets for the treatment and prognosis of PDAC.


Assuntos
Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Humanos , Transcriptoma , Redes Reguladoras de Genes , Carcinoma Ductal Pancreático/genética , Perfilação da Expressão Gênica/métodos , Biomarcadores Tumorais/metabolismo , Biologia Computacional/métodos , Regulação Neoplásica da Expressão Gênica , 17-Hidroxiesteroide Desidrogenases/genética
2.
Sci Rep ; 14(1): 2782, 2024 02 02.
Artigo em Inglês | MEDLINE | ID: mdl-38307969

RESUMO

Bladder cancer (BC) is a crisis to human health. It is necessary to understand the molecular mechanisms of the development and progression of BC to determine treatment options. Publicly available expression data were obtained from TCGA and GEO databases to spot differentially expressed genes (DEGs) between cancer and normal bladder tissues. Weighted co-expression networks were constructed, and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Associations in hub genes, immune infiltration, and immune therapy were evaluated separately. Protein-protein interaction (PPI) networks for the genes identified in the normal and tumor groups were launched. 3461 DEGs in the TCGA dataset and 1069 DEGs in the GSE dataset were identified, including 87 overlapping genes between cancer and normal bladder groups. Hub genes in the tumor group were mainly enriched for cell proliferation, while hub genes in the normal group were related to the synthesis and secretion of neurotransmitters. Based on survival analysis, CDH19, RELN, PLP1, and TRIB3 were considerably associated with prognosis (P < 0.05). CDH19, RELN, PLP1, and TRIB3 may play important roles in the development of BC and are potential biomarkers in therapy and prognosis.


Assuntos
Neoplasias da Bexiga Urinária , Bexiga Urinária , Humanos , Bexiga Urinária/metabolismo , Redes Reguladoras de Genes , Perfilação da Expressão Gênica , Neoplasias da Bexiga Urinária/genética , Neoplasias da Bexiga Urinária/metabolismo , Processos Neoplásicos , Biologia Computacional , Regulação Neoplásica da Expressão Gênica
3.
BMC Med Genomics ; 17(1): 50, 2024 Feb 12.
Artigo em Inglês | MEDLINE | ID: mdl-38347610

RESUMO

BACKGROUND: We aimed to investigate the involvement of long non-coding RNA (lncRNA) in bacterial and viral meningitis in children. METHODS: The peripheral blood of five bacterial meningitis patients, five viral meningitis samples, and five healthy individuals were collected for RNA sequencing. Then, the differentially expressed lncRNA and mRNA were detected in bacterial meningitis vs. controls, viral meningitis vs. healthy samples, and bacterial vs. viral meningitis patients. Besides, co-expression and the competing endogenous RNA (ceRNA) networks were constructed. Receiver operating characteristic curve (ROC) analysis was performed. RESULTS: Compared with the control group, 2 lncRNAs and 32 mRNAs were identified in bacterial meningitis patients, and 115 lncRNAs and 54 mRNAs were detected in viral meningitis. Compared with bacterial meningitis, 165 lncRNAs and 765 mRNAs were identified in viral meningitis. 2 lncRNAs and 31 mRNAs were specific to bacterial meningitis, and 115 lncRNAs and 53 mRNAs were specific to viral meningitis. The function enrichment results indicated that these mRNAs were involved in innate immune response, inflammatory response, and immune system process. A total of 8 and 1401 co-expression relationships were respectively found in bacterial and viral meningitis groups. The ceRNA networks contained 1 lncRNA-mRNA pair and 4 miRNA-mRNA pairs in viral meningitis group. GPR68 and KIF5C, identified in bacterial meningitis co-expression analysis, had an area under the curve (AUC) of 1.00, while the AUC of OR52K2 and CCR5 is 0.883 and 0.698, respectively. CONCLUSIONS: Our research is the first to profile the lncRNAs in bacterial and viral meningitis in children and may provide new insight into understanding meningitis regulatory mechanisms.


Assuntos
Meningites Bacterianas , Meningite Viral , MicroRNAs , RNA Longo não Codificante , Criança , Humanos , RNA Longo não Codificante/metabolismo , Redes Reguladoras de Genes , MicroRNAs/genética , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Análise de Sequência de RNA , Meningites Bacterianas/genética , Meningite Viral/genética , Receptores Acoplados a Proteínas G/genética , Cinesinas/genética
4.
Clin Interv Aging ; 19: 203-217, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38352274

RESUMO

Background: Recent studies have put forward the viewpoint of "bone immunology", which holds that the immune system and immune factors play an important regulatory role in the occurrence and development of osteoporosis. This study was intended to identify genetic characteristics of differentially expressed immune-related mRNA and lncRNA in patients combined with osteoporosis and vertebral fracture. Methods: The peripheral blood samples were obtained from 3 groups of subjects: healthy control (HC), osteoporosis patients without vertebral fracture (OWF), and osteoporosis patients combined with vertebral fracture (OVF). The data were integrated to obtain differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs). Subsequently, the protein-protein interaction (PPI) networks were constructed. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses were performed. Cytoscape-cytoHubba plug-in was used to identify key DEmRNAs. Furthermore, lncRNA-miRNA-mRNA, mRNA-lncRNA co-expression and transcription factors (TFs) networks were constructed. In addition, real-time PCR verification was performed. Results: Totally of 3378 lncRNA-mRNA pairs were obtained, and the lncRNA co-expressed mRNA was mainly enriched in immune-related pathways, especially in GO-biological process (GO-BP) analysis. A total of 8 hub immune-related DEmRNAs were obtained, including IL18R1, IL18RAP, SLC11A1, CSF2RA, CCR3, IL1R2, PGLYRP1, and IL1R1. The TFs network showed that 8 hub immune-related DEmRNAs had interacting TFs. The co-expression network showed that 7 hub immune-related DEmRNAs (IL18R1, IL18RAP, SLC11A1, CSF2RA, IL-1R2, PGLYRP1, and IL1R1) had lncRNA-mRNA co-expression relationship. In addition, the lncRNA-miRNA-mRNA network includes 32 miRNAs, 7 hub immune-related mRNAs (IL18R1, IL18RAP, CSF2RA, CCR3, IL1R2, PGLYRP1, and IL1R1), and 11 lncRNAs. Conclusion: Our study provides a novel and in-depth identification of co-expressed mRNAs and lncRNAs in patients combined with osteoporosis and vertebral fracture at a molecular level. This may provide new candidate biomarkers for the diagnosis of patients with high-risk fractures in the future.


Assuntos
MicroRNAs , Osteoporose , RNA Longo não Codificante , Fraturas da Coluna Vertebral , Humanos , RNA Longo não Codificante/genética , RNA Longo não Codificante/metabolismo , Transcriptoma , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Redes Reguladoras de Genes , MicroRNAs/genética , MicroRNAs/metabolismo , Osteoporose/genética
5.
Medicine (Baltimore) ; 103(5): e35859, 2024 Feb 02.
Artigo em Inglês | MEDLINE | ID: mdl-38306545

RESUMO

This study aimed to determine the potential mechanisms through which long noncoding (Lnc) RNA cancer susceptibility candidate 15 (CASC15) affects hepatocellular carcinoma (HCC). We retrieved HCC RNA-seq and clinical information from the UCSC Xena database. The differential expression (DE) of CASC15 was detected. Overall survival was analyzed using Kaplan-Meier (K-M) curves. Molecular function and signaling pathways affected by CASC15 were determined using Gene Set Enrichment Analysis. Associations between CASC15 and the HCC microenvironment were investigated using immuno-infiltration assays. A differential CASC15-miRNA-mRNA network and HCC-specific CASC15-miRNA-mRNA ceRNA network were constructed. The overexpression of CASC15 in HCC tissues was associated with histological grade, clinical stage, pathological T stage, poor survival, more complex immune cell components, and 12 immune checkpoints. We identified 27 DE miRNAs and 270 DE mRNAs in the differential CASC15-miRNA-mRNA network, and 10 key genes that were enriched in 12 cancer-related signaling pathways. Extraction of the HCC-specific CASC15-miRNA-mRNA network revealed that IGF1R, MET, and KRAS were associated with HCC progression and occurrence. Our bioinformatic findings confirmed that CASC15 is a promising prognostic biomarker for HCC, and elevated levels in HCC are associated with the tumor microenvironment. We also constructed a disease-specific CASC15-miRNA-mRNA regulatory ceRNA network that provides a new perspective for the precise indexing of patients with elevated levels of CASC15.


Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , MicroRNAs , RNA Longo não Codificante , Humanos , Carcinoma Hepatocelular/patologia , MicroRNAs/genética , MicroRNAs/metabolismo , RNA Longo não Codificante/genética , RNA Longo não Codificante/metabolismo , Neoplasias Hepáticas/patologia , RNA Mensageiro/metabolismo , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Microambiente Tumoral/genética
6.
Medicine (Baltimore) ; 103(5): e37056, 2024 Feb 02.
Artigo em Inglês | MEDLINE | ID: mdl-38306561

RESUMO

Colorectal cancer is a cancer that arises from the abnormal growth of cells in the colon or rectum. Osteosarcoma (OS) is a common primary bone tumor with high degree of malignancy. The configuration files for colorectal cancer dataset GSE142279 and OS datasets GSE197158 and GSE206448 were downloaded from Gene Expression Omnibus database using the platforms GPL20795, GPL20301, and GPL24676. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. Construction and analysis of protein-protein interactions (PPI) network. Functional enrichment analysis, gene set enrichment analysis (GSEA) were performed. A heat map of gene expression was drawn. The Comparative Toxicogenomics Database (CTD) was used to find the diseases most associated with the core genes. TargetScan was used to screen miRNAs regulating DEGs. According to the Gene Ontology (GO) analysis, DEGs are mainly enriched in acetylcholine binding receptor activity involved in Wnt signaling pathway, cell polarity pathway, PI3K-Akt signaling pathway, receptor regulator activity, cytokine-cytokine receptor interaction, transcriptional misregulation in cancer, and inflammation-mediated regulation of tryptophan transport. In the Metascape enrichment analysis, GO enrichment items related to the regulation of Wnt signaling pathway, regulation of muscle system process, and regulation of actin filament-based movement. Eight core genes (CUX1, NES, BCL11B, PAX6, EMX1, MCOLN2, TRPA1, TRPC4) were identified. CTD showed that 4 genes (CUX1, EMX1, TRPA1, BCL11B) were associated with colorectal neoplasms, colorectal tumors, colonic diseases, multiple myeloma, OS, and inflammation. PAX6, TRPA1, BCL11B, MCOLN2, CUX1, and EMX1 are highly expressed in colorectal cancer and OS, and the higher the expression level, the worse the prognosis.


Assuntos
Neoplasias Ósseas , Neoplasias Colorretais , Proteínas de Homeodomínio , Osteossarcoma , Fator de Transcrição PAX6 , Humanos , Fosfatidilinositol 3-Quinases/metabolismo , Perfilação da Expressão Gênica , Fatores de Transcrição/genética , Osteossarcoma/patologia , Neoplasias Ósseas/patologia , Neoplasias Colorretais/genética , Inflamação/genética , Proteínas Supressoras de Tumor/genética , Biologia Computacional , Redes Reguladoras de Genes , Regulação Neoplásica da Expressão Gênica , Canal de Cátion TRPA1/genética , Proteínas Repressoras/metabolismo
7.
Int J Mol Sci ; 25(3)2024 Jan 25.
Artigo em Inglês | MEDLINE | ID: mdl-38338756

RESUMO

The Single-cell Assay for Transposase-Accessible Chromatin with high throughput sequencing (scATAC-seq) has gained increasing popularity in recent years, allowing for chromatin accessibility to be deciphered and gene regulatory networks (GRNs) to be inferred at single-cell resolution. This cutting-edge technology now enables the genome-wide profiling of chromatin accessibility at the cellular level and the capturing of cell-type-specific cis-regulatory elements (CREs) that are masked by cellular heterogeneity in bulk assays. Additionally, it can also facilitate the identification of rare and new cell types based on differences in chromatin accessibility and the charting of cellular developmental trajectories within lineage-related cell clusters. Due to technical challenges and limitations, the data generated from scATAC-seq exhibit unique features, often characterized by high sparsity and noise, even within the same cell type. To address these challenges, various bioinformatic tools have been developed. Furthermore, the application of scATAC-seq in plant science is still in its infancy, with most research focusing on root tissues and model plant species. In this review, we provide an overview of recent progress in scATAC-seq and its application across various fields. We first conduct scATAC-seq in plant science. Next, we highlight the current challenges of scATAC-seq in plant science and major strategies for cell type annotation. Finally, we outline several future directions to exploit scATAC-seq technologies to address critical challenges in plant science, ranging from plant ENCODE(The Encyclopedia of DNA Elements) project construction to GRN inference, to deepen our understanding of the roles of CREs in plant biology.


Assuntos
Cromatina , Transposases , Cromatina/genética , Transposases/genética , Transposases/metabolismo , Sequenciamento de Nucleotídeos em Larga Escala , DNA , Redes Reguladoras de Genes , Análise de Célula Única
8.
Int J Mol Sci ; 25(3)2024 Feb 05.
Artigo em Inglês | MEDLINE | ID: mdl-38339216

RESUMO

Climate change is expected to intensify the occurrence of abiotic stress in plants, such as hypoxia and salt stresses, leading to the production of reactive oxygen species (ROS), which need to be effectively managed by various oxido-reductases encoded by the so-called ROS gene network. Here, we studied six oxido-reductases families in three Brassicaceae species, Arabidopsis thaliana as well as Nasturtium officinale and Eutrema salsugineum, which are adapted to hypoxia and salt stress, respectively. Using available and new genomic data, we performed a phylogenomic analysis and compared RNA-seq data to study genomic and transcriptomic adaptations. This comprehensive approach allowed for the gaining of insights into the impact of the adaptation to saline or hypoxia conditions on genome organization (gene gains and losses) and transcriptional regulation. Notably, the comparison of the N. officinale and E. salsugineum genomes to that of A. thaliana highlighted changes in the distribution of ohnologs and homologs, particularly affecting class III peroxidase genes (CIII Prxs). These changes were specific to each gene, to gene families subjected to duplication events and to each species, suggesting distinct evolutionary responses. The analysis of transcriptomic data has allowed for the identification of genes related to stress responses in A. thaliana, and, conversely, to adaptation in N. officinale and E. salsugineum.


Assuntos
Arabidopsis , Brassicaceae , Brassicaceae/genética , Arabidopsis/genética , Espécies Reativas de Oxigênio , Redes Reguladoras de Genes , Oxirredutases/genética , Hipóxia , Regulação da Expressão Gênica de Plantas , Estresse Fisiológico
9.
Brief Bioinform ; 25(2)2024 Jan 22.
Artigo em Inglês | MEDLINE | ID: mdl-38340090

RESUMO

MOTIVATION: Genome-wide association studies (GWAS) have enabled large-scale analysis of the role of genetic variants in human disease. Despite impressive methodological advances, subsequent clinical interpretation and application remains challenging when GWAS suffer from a lack of statistical power. In recent years, however, the use of information diffusion algorithms with molecular networks has led to fruitful insights on disease genes. RESULTS: We present an overview of the design choices and pitfalls that prove crucial in the application of network propagation methods to GWAS summary statistics. We highlight general trends from the literature, and present benchmark experiments to expand on these insights selecting as case study three diseases and five molecular networks. We verify that the use of gene-level scores based on GWAS P-values offers advantages over the selection of a set of 'seed' disease genes not weighted by the associated P-values if the GWAS summary statistics are of sufficient quality. Beyond that, the size and the density of the networks prove to be important factors for consideration. Finally, we explore several ensemble methods and show that combining multiple networks may improve the network propagation approach.


Assuntos
Estudo de Associação Genômica Ampla , Polimorfismo de Nucleotídeo Único , Humanos , Estudo de Associação Genômica Ampla/métodos , Algoritmos , Redes Reguladoras de Genes , Predisposição Genética para Doença
10.
Genome Med ; 16(1): 30, 2024 Feb 12.
Artigo em Inglês | MEDLINE | ID: mdl-38347596

RESUMO

BACKGROUND: Biological processes are controlled by groups of genes acting in concert. Investigating gene-gene interactions within different cell types can help researchers understand the regulatory mechanisms behind human complex diseases, such as tumors. METHODS: We collected extensive single-cell RNA-seq data from tumors, involving 563 patients with 44 different tumor types. Through our analysis, we identified various cell types in tumors and created an atlas of different immune cell subsets across different tumor types. Using the SCINET method, we reconstructed interactome networks specific to different cell types. Diverse functional data was then integrated to gain biological insights into the networks, including somatic mutation patterns and gene functional annotation. Additionally, genes with prognostic relevance within the networks were also identified. We also examined cell-cell communications to investigate how gene interactions modulate cell-cell interactions. RESULTS: We developed a data portal called CellNetdb for researchers to study cell-type-specific interactome networks. Our findings indicate that these networks can be used to identify genes with topological specificity in different cell types. We also found that prognostic genes can deconvolved into cell types through analyzing network connectivity. Additionally, we identified commonalities and differences in cell-type-specific networks across different tumor types. Our results suggest that these networks can be used to prioritize risk genes. CONCLUSIONS: This study presented CellNetdb, a comprehensive repository featuring an atlas of cell-type-specific interactome networks across 44 human tumor types. The findings underscore the utility of these networks in delineating the intricacies of tumor microenvironments and advancing the understanding of molecular mechanisms underpinning human tumors.


Assuntos
Neoplasias , Humanos , Neoplasias/genética , Redes Reguladoras de Genes , Microambiente Tumoral/genética
11.
BMC Bioinformatics ; 25(1): 53, 2024 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-38302900

RESUMO

BACKGROUND: Non-coding RNAs represent a large part of the human transcriptome and have been shown to play an important role in disease such as cancer. However, their biological functions are still incompletely understood. Among non-coding RNAs, circular RNAs (circRNAs) have recently been identified for their microRNA (miRNA) sponge function which allows them to modulate the expression of miRNA target genes by taking on the role of competitive endogenous RNAs (ce-circRNAs). Today, most computational tools are not adapted to the search for ce-circRNAs or have not been developed for the search for ce-circRNAs from user's transcriptomic data. RESULTS: In this study, we present Cirscan (CIRcular RNA Sponge CANdidates), an interactive Shiny application that automatically infers circRNA-miRNA-mRNA networks from human multi-level transcript expression data from two biological conditions (e.g. tumor versus normal conditions in the case of cancer study) in order to identify on a large scale, potential sponge mechanisms active in a specific condition. Cirscan ranks each circRNA-miRNA-mRNA subnetwork according to a sponge score that integrates multiple criteria based on interaction reliability and expression level. Finally, the top ranked sponge mechanisms can be visualized as networks and an enrichment analysis is performed to help its biological interpretation. We showed on two real case studies that Cirscan is capable of retrieving sponge mechanisms previously described, as well as identifying potential novel circRNA sponge candidates. CONCLUSIONS: Cirscan can be considered as a companion tool for biologists, facilitating their ability to prioritize sponge mechanisms for experimental validations and identifying potential therapeutic targets. Cirscan is implemented in R, released under the license GPL-3 and accessible on GitLab ( https://gitlab.com/geobioinfo/cirscan_Rshiny ). The scripts used in this paper are also provided on Gitlab ( https://gitlab.com/geobioinfo/cirscan_paper ).


Assuntos
MicroRNAs , Neoplasias , Humanos , MicroRNAs/genética , MicroRNAs/metabolismo , RNA Circular/genética , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Reprodutibilidade dos Testes , Redes Reguladoras de Genes
12.
BMC Genomics ; 25(1): 158, 2024 Feb 08.
Artigo em Inglês | MEDLINE | ID: mdl-38331736

RESUMO

BACKGROUND: Studies have confirmed that Infectious bovine rhinotracheitis virus (IBRV) infection induces mitochondrial damage. MicroRNAs (miRNAs) are a class of noncoding RNA molecules, which are involved in various biological processes and pathological changes associated with mitochondrial damage. It is currently unclear whether miRNAs participate in IBRV-induced mitochondrial damage in Madin-Darby bovine kidney (MDBK) cells. RESULTS: In the present study, we used high-throughput sequencing technology, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to screen for mitochondria-related miRNAs and messenger RNAs (mRNAs). In total, 279 differentially expressed miRNAs and 832 differentially expressed mRNAs were identified in 6 hours (IBRV1) versus 24 hours (IBRV2) after IBRV infection in MDBK cells. GO and KEGG enrichment analysis revealed that 42 differentially expressed mRNAs and 348 target genes of differentially expressed miRNAs were correlated with mitochondrial damage, and the miRNA-mitochondria-related target genes regulatory network was constructed to elucidate their potential regulatory relationships. Among the 10 differentially expressed miRNAs, 8 showed expression patterns consistent with the high-throughput sequencing results. Functional validation results showed that overexpression of miR-10a and miR-182 aggravated mitochondrial damage, while inhibition of miR-10a and miR-182 alleviated mitochondrial damage. CONCLUSIONS: This study not only revealed the expression changes of miRNAs and mRNAs in IBRV-infected MDBK cells, but also revealed possible biological regulatory relationship between them. MiR-10a and miR-182 may have the potential to be developed as biomarkers for the diagnosis and treatment of IBRV. Together, Together, these data and analyses provide additional insights into the roles of miRNA and mRNA in IBRV-induced mitochondria damage.


Assuntos
Herpesvirus Bovino 1 , MicroRNAs , Animais , Bovinos , MicroRNAs/genética , MicroRNAs/metabolismo , Herpesvirus Bovino 1/genética , Células Epiteliais/metabolismo , Rim/metabolismo , Redes Reguladoras de Genes , RNA Mensageiro/genética , Perfilação da Expressão Gênica
13.
OMICS ; 28(2): 90-101, 2024 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-38320250

RESUMO

Ovarian cancer is a major cause of cancer deaths among women. Early diagnosis and precision/personalized medicine are essential to reduce mortality and morbidity of ovarian cancer, as with new molecular targets to accelerate drug discovery. We report here an integrated systems biology and machine learning (ML) approach based on the differential coexpression analysis to identify candidate systems biomarkers (i.e., gene modules) for serous ovarian cancer. Accordingly, four independent transcriptome datasets were statistically analyzed independently and common differentially expressed genes (DEGs) were identified. Using these DEGs, coexpressed gene pairs were unraveled. Subsequently, differential coexpression networks between the coexpressed gene pairs were reconstructed so as to identify the differentially coexpressed gene modules. Based on the established criteria, "SOV-module" was identified as being significant, consisting of 19 genes. Using independent datasets, the diagnostic capacity of the SOV-module was evaluated using principal component analysis (PCA) and ML techniques. PCA showed a sensitivity and specificity of 96.7% and 100%, respectively, and ML analysis showed an accuracy of up to 100% in distinguishing phenotypes in the present study sample. The prognostic capacity of the SOV-module was evaluated using survival and ML analyses. We found that the SOV-module's performance for prognostics was significant (p-value = 1.36 × 10-4) with an accuracy of 63% in discriminating between survival and death using ML techniques. In summary, the reported genomic systems biomarker candidate offers promise for personalized medicine in diagnosis and prognosis of serous ovarian cancer and warrants further experimental and translational clinical studies.


Assuntos
Perfilação da Expressão Gênica , Neoplasias Ovarianas , Humanos , Feminino , Perfilação da Expressão Gênica/métodos , Medicina de Precisão , Neoplasias Ovarianas/diagnóstico , Neoplasias Ovarianas/genética , Redes Reguladoras de Genes , Biologia de Sistemas , Biomarcadores Tumorais/genética , Regulação Neoplásica da Expressão Gênica
14.
Immunity ; 57(2): 287-302.e12, 2024 Feb 13.
Artigo em Inglês | MEDLINE | ID: mdl-38354704

RESUMO

The interaction of the tumor necrosis factor receptor (TNFR) family member CD27 on naive CD8+ T (Tn) cells with homotrimeric CD70 on antigen-presenting cells (APCs) is necessary for T cell memory fate determination. Here, we examined CD27 signaling during Tn cell activation and differentiation. In conjunction with T cell receptor (TCR) stimulation, ligation of CD27 by a synthetic trimeric CD70 ligand triggered CD27 internalization and degradation, suggesting active regulation of this signaling axis. Internalized CD27 recruited the signaling adaptor TRAF2 and the phosphatase SHP-1, thereby modulating TCR and CD28 signals. CD27-mediated modulation of TCR signals promoted transcription factor circuits that induced memory rather than effector associated gene programs, which are induced by CD28 costimulation. CD27-costimulated chimeric antigen receptor (CAR)-engineered T cells exhibited improved tumor control compared with CD28-costimulated CAR-T cells. Thus, CD27 signaling during Tn cell activation promotes memory properties with relevance to T cell immunotherapy.


Assuntos
Antígenos CD28 , Redes Reguladoras de Genes , Fator 2 Associado a Receptor de TNF/genética , Fator 2 Associado a Receptor de TNF/metabolismo , Antígenos CD28/metabolismo , Transdução de Sinais , Ativação Linfocitária , Receptores de Antígenos de Linfócitos T/metabolismo , Membro 7 da Superfamília de Receptores de Fatores de Necrose Tumoral/genética , Membro 7 da Superfamília de Receptores de Fatores de Necrose Tumoral/metabolismo , Ligante CD27/genética , Ligante CD27/metabolismo , Linfócitos T CD8-Positivos
15.
Artigo em Inglês | MEDLINE | ID: mdl-38348310

RESUMO

Purpose: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide, characterized by intense lung infiltrations of immune cells (macrophages and monocytes). While existing studies have highlighted the crucial role of the competitive endogenous RNA (ceRNA) regulatory network in COPD development, the complexity and characteristics of the ceRNA network in monocytes remain unexplored. Methods: We downloaded messenger RNA (mRNA), microRNA (miRNA), and long noncoding RNA (lncRNA) microarray data from GSE146560, GSE102915, and GSE71220 in the Gene Expression Omnibus (GEO) database. This data was used to identify differentially expressed mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and lncRNAs (DElncRNAs). Predicted miRNAs that bind to DElncRNAs were intersected with DEmiRNAs, forming a set of intersecting miRNAs. This set was then used to predict potential binding mRNAs, intersected with DEmRNAs, and underwent functional enrichment analysis using R software and the STRING database. The resulting triple regulatory network and hub genes were constructed using Cytoscape. Comparative Toxicomics Database (CTD) was utilized for disease correlation predictions, and ROC curve analysis assessed diagnostic accuracy. Results: Our study identified 5 lncRNAs, 4 miRNAs, and 149 mRNAs as differentially expressed. A lncRNA-miRNA-mRNA regulatory network was constructed, and hub genes were selected through hub analysis. Enrichment analysis highlighted terms related to cell movement and gene expression regulation. We established a LINC00482-has-miR-6088-PRRC2B ceRNA network with diagnostic relevance for COPD. ROC analysis demonstrated the diagnostic value of these genes. Moreover, a positive correlation between LINC00482 and PRRC2B expression was observed in COPD PBMCs. The CTD database indicated their involvement in inflammatory responses. Conclusion: In summary, our study not only identified pivotal hub genes in peripheral blood mononuclear cells (PBMCs) of COPD but also constructed a ceRNA regulatory network. This contributes to understanding the pathophysiological processes of COPD through bioinformatics analysis, expanding our knowledge of COPD, and providing a foundation for potential diagnostic and therapeutic targets for COPD.


Assuntos
MicroRNAs , Doença Pulmonar Obstrutiva Crônica , RNA Longo não Codificante , Humanos , Redes Reguladoras de Genes , Leucócitos Mononucleares , MicroRNAs/genética , Doença Pulmonar Obstrutiva Crônica/diagnóstico , Doença Pulmonar Obstrutiva Crônica/genética , RNA Longo não Codificante/genética , RNA Mensageiro/genética
16.
PLoS One ; 19(2): e0298447, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38359008

RESUMO

Rheumatoid arthritis (RA) and primary Sjögren's syndrome (pSS) are the most common systemic autoimmune diseases, and they are increasingly being recognized as occurring in the same patient population. These two diseases share several clinical features and laboratory parameters, but the exact mechanism of their co-pathogenesis remains unclear. The intention of this study was to investigate the common molecular mechanisms involved in RA and pSS using integrated bioinformatic analysis. RNA-seq data for RA and pSS were picked up from the Gene Expression Omnibus (GEO) database. Co-expression genes linked with RA and pSS were recognized using weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis. Then, we screened two public disease-gene interaction databases (GeneCards and Comparative Toxicogenomics Database) for common targets associated with RA and pSS. The DGIdb database was used to predict therapeutic drugs for RA and pSS. The Human microRNA Disease Database (HMDD) was used to screen out the common microRNAs associated with RA and pSS. Finally, a common miRNA-gene network was created using Cytoscape. Four hub genes (CXCL10, GZMA, ITGA4, and PSMB9) were obtained from the intersection of common genes from WGCNA, differential gene analysis and public databases. Twenty-four drugs corresponding to hub gene targets were predicted in the DGIdb database. Among the 24 drugs, five drugs had already been reported for the treatment of RA and pSS. Other drugs, such as bortezomib, carfilzomib, oprozomib, cyclosporine and zidovudine, may be ideal drugs for the future treatment of RA patients with pSS. According to the miRNA-gene network, hsa-mir-21 may play a significant role in the mechanisms shared by RA and pSS. In conclusion, we identified commom targets as potential biomarkers in RA and pSS from publicly available databases and predicted potential drugs based on the targets. A new understanding of the molecular mechanisms associated with RA and pSS is provided according to the miRNA-gene network.


Assuntos
Artrite Reumatoide , MicroRNAs , Síndrome de Sjogren , Humanos , Síndrome de Sjogren/tratamento farmacológico , Síndrome de Sjogren/genética , Artrite Reumatoide/tratamento farmacológico , Artrite Reumatoide/genética , MicroRNAs/genética , Perfilação da Expressão Gênica , Redes Reguladoras de Genes
17.
NPJ Syst Biol Appl ; 10(1): 18, 2024 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-38360881

RESUMO

A major challenge in precision oncology is to detect targetable cancer vulnerabilities in individual patients. Modeling high-throughput omics data in biological networks allows identifying key molecules and processes of tumorigenesis. Traditionally, network inference methods rely on many samples to contain sufficient information for learning, resulting in aggregate networks. However, to implement patient-tailored approaches in precision oncology, we need to interpret omics data at the level of individual patients. Several single-sample network inference methods have been developed that infer biological networks for an individual sample from bulk RNA-seq data. However, only a limited comparison of these methods has been made and many methods rely on 'normal tissue' samples as reference, which are not always available. Here, we conducted an evaluation of the single-sample network inference methods SSN, LIONESS, SWEET, iENA, CSN and SSPGI using transcriptomic profiles of lung and brain cancer cell lines from the CCLE database. The methods constructed functional gene networks with distinct network characteristics. Hub gene analyses revealed different degrees of subtype-specificity across methods. Single-sample networks were able to distinguish between tumor subtypes, as exemplified by node strength clustering, enrichment of known subtype-specific driver genes among hubs and differential node strength. We also showed that single-sample networks correlated better to other omics data from the same cell line as compared to aggregate networks. We conclude that single-sample network inference methods can reflect sample-specific biology when 'normal tissue' samples are absent and we point out peculiarities of each method.


Assuntos
Neoplasias , Humanos , Neoplasias/genética , Algoritmos , Medicina de Precisão , Redes Reguladoras de Genes/genética , Transcriptoma
18.
Medicine (Baltimore) ; 103(7): e37255, 2024 Feb 16.
Artigo em Inglês | MEDLINE | ID: mdl-38363924

RESUMO

Sepsis is a syndrome characterized by a systemic inflammatory response due to the invasion of pathogenic microorganisms. The relationship between Lipocalin-2 (LCN2), elastase, neutrophil expressed (ELANE) and sepsis remains unclear. The sepsis datasets GSE137340 and GSE154918 profiles were downloaded from gene expression omnibus generated from GPL10558. Batch normalization, differentially expressed Genes (DEGs) screening, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, Gene Set Enrichment Analysis (GSEA), immune infiltration analysis, construction and analysis of protein-protein interaction (PPI) networks, Comparative Toxicogenomics Database (CTD) analysis were performed. Gene expression heatmaps were generated. TargetScan was used to screen miRNAs of DEGs. 328 DEGs were identified. According to Gene Ontology (GO), in the Biological Process analysis, they were mainly enriched in immune response, apoptosis, inflammatory response, and immune response regulation signaling pathways. In cellular component analysis, they were mainly enriched in vesicles, cytoplasmic vesicles, and secretory granules. In Molecular Function analysis, they were mainly concentrated in hemoglobin binding, Toll-like receptor binding, immunoglobulin binding, and RAGE receptor binding. In Kyoto Encyclopedia of Genes and Genomes (KEGG), they were mainly enriched in NOD-like receptor signaling pathway, Toll-like receptor signaling pathway, TNF signaling pathway, P53 signaling pathway, and legionellosis. Seventeen modules were generated. The PPI network identified 4 core genes (MPO, ELANE, CTSG, LCN2). Gene expression heatmaps revealed that core genes (MPO, ELANE, CTSG, LCN2) were highly expressed in sepsis samples. CTD analysis found that MPO, ELANE, CTSG and LCN2 were associated with sepsis, peritonitis, meningitis, pneumonia, infection, and inflammation. LCN2 and ELANE are highly expressed in sepsis and may serve as molecular targets.


Assuntos
Mapas de Interação de Proteínas , Sepse , Humanos , Lipocalina-2/genética , Mapas de Interação de Proteínas/genética , Perfilação da Expressão Gênica , Sepse/genética , Receptores Toll-Like , Biologia Computacional , Redes Reguladoras de Genes
19.
J Chem Phys ; 160(7)2024 Feb 21.
Artigo em Inglês | MEDLINE | ID: mdl-38364008

RESUMO

In this study, we obtain an exact time-dependent solution of the chemical master equation (CME) of an extension of the two-state telegraph model describing bursty or non-bursty protein expression in the presence of positive or negative autoregulation. Using the method of spectral decomposition, we show that the eigenfunctions of the generating function solution of the CME are Heun functions, while the eigenvalues can be determined by solving a continued fraction equation. Our solution generalizes and corrects a previous time-dependent solution for the CME of a gene circuit describing non-bursty protein expression in the presence of negative autoregulation [Ramos et al., Phys. Rev. E 83, 062902 (2011)]. In particular, we clarify that the eigenvalues are generally not real as previously claimed. We also investigate the relationship between different types of dynamic behavior and the type of feedback, the protein burst size, and the gene switching rate.


Assuntos
Redes Reguladoras de Genes , Proteínas , Processos Estocásticos , Proteínas/genética , Proteínas/metabolismo , Expressão Gênica
20.
Integr Biol (Camb) ; 162024 Jan 23.
Artigo em Inglês | MEDLINE | ID: mdl-38366952

RESUMO

Diabetes is a rising global metabolic disorder and leads to long-term consequences. As a multifactorial disease, the gene-associated mechanisms are important to know. This study applied a bioinformatics approach to explore the molecular underpinning of type 2 diabetes mellitus through differential gene expression analysis. We used microarray datasets GSE16415 and GSE29226 to identify differentially expressed genes between type 2 diabetes and normal samples using R software. Following that, using the STRING database, the protein-protein interaction network was constructed and further analyzed by Cytoscape software. The EnrichR database was used for Gene Ontology and pathway enrichment analysis to explore key pathways and functional annotations of hub genes. We also used miRTarBase and TargetScan databases to predict miRNAs targeting hub genes. We identified 21 hub genes in type 2 diabetes, some showing more significant changes in the PPI network. Our results revealed that GLUL, SLC32A1, PC, MAPK10, MAPT, and POSTN genes are more important in the PPI network and can be experimentally investigated as therapeutic targets. Hsa-miR-492 and hsa-miR-16-5p are suggested for diagnosis and prognosis by targeting GLUL, SLC32A1, PC, MAPK10, and MAPT genes involved in the insulin signaling pathway. Insight: Type 2 diabetes, as a rising global and multifactorial disorder, is important to know the gene-associated mechanisms. In an integrative bioinformatics analysis, we integrated different finding datasets to put together and find valuable diagnostic and prognostic hub genes and miRNAs. In contrast, genes, RNAs, and enzymes interact systematically in pathways. Using multiple databases and software, we identified differential expression between hub genes of diabetes and normal samples. We explored different protein-protein interaction networks, gene ontology, key pathway analysis, and predicted miRNAs that target hub genes. This study reported 21 significant hub genes and some miRNAs in the insulin signaling pathway for innovative and potential diagnostic and therapeutic purposes.


Assuntos
Diabetes Mellitus Tipo 2 , Insulinas , MicroRNAs , Humanos , MicroRNAs/genética , MicroRNAs/metabolismo , Diabetes Mellitus Tipo 2/genética , Perfilação da Expressão Gênica/métodos , Redes Reguladoras de Genes , Insulinas/genética , Biologia Computacional/métodos
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