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Bhowmick R, Sarkar RR. Identification of potential microRNAs regulating metabolic plasticity and cellular phenotypes in glioblastoma. Mol Genet Genomics 2023; 298:161-181. [PMID: 36357622 DOI: 10.1007/s00438-022-01966-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 10/25/2022] [Indexed: 11/12/2022]
Abstract
MicroRNAs (miRNAs) play important role in regulating cellular metabolism, and are currently being explored in cancer. As metabolic reprogramming in cancer is a major mediator of phenotypic plasticity, understanding miRNA-regulated metabolism will provide opportunities to identify miRNA targets that can regulate oncogenic phenotypes by taking control of cellular metabolism. In the present work, we studied the effect of differentially expressed miRNAs on metabolism, and associated oncogenic phenotypes in glioblastoma (GBM) using patient-derived data. Networks of differentially expressed miRNAs and metabolic genes were created and analyzed to identify important miRNAs that regulate major metabolism in GBM. Graph network-based approaches like network diffusion, backbone extraction, and different centrality measures were used to analyze these networks for identification of potential miRNA targets. Important metabolic processes and cellular phenotypes were annotated to trace the functional responses associated with these miRNA-regulated metabolic genes and associated phenotype networks. miRNA-regulated metabolic gene subnetworks of cellular phenotypes were extracted, and important miRNAs regulating these phenotypes were identified. The most important outcome of the study is the target miRNA combinations predicted for five different oncogenic phenotypes that can be tested experimentally for miRNA-based therapeutic design in GBM. Strategies implemented in the study can be used to generate testable hypotheses in other cancer types as well, and design context-specific miRNA-based therapy for individual patient. Their usability can be further extended to other gene regulatory networks in cancer and other genetic diseases.
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Affiliation(s)
- Rupa Bhowmick
- Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune, Maharashtra, 411008, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Ram Rup Sarkar
- Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune, Maharashtra, 411008, India. .,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.
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Sultana A, Alam MS, Liu X, Sharma R, Singla RK, Gundamaraju R, Shen B. Single-cell RNA-seq analysis to identify potential biomarkers for diagnosis, and prognosis of non-small cell lung cancer by using comprehensive bioinformatics approaches. Transl Oncol 2022; 27:101571. [PMID: 36401966 PMCID: PMC9676382 DOI: 10.1016/j.tranon.2022.101571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 10/12/2022] [Accepted: 10/24/2022] [Indexed: 11/18/2022] Open
Abstract
Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and the leading cause of cancer-related deaths worldwide. Identification of gene biomarkers and their regulatory factors and signaling pathways is very essential to reveal the molecular mechanisms of NSCLC initiation and progression. Thus, the goal of this study is to identify gene biomarkers for NSCLC diagnosis and prognosis by using scRNA-seq data through bioinformatics techniques. scRNA-seq data were obtained from the GEO database to identify DEGs. A total of 158 DEGs (including 48 upregulated and 110 downregulated) were detected after gene integration. Gene Ontology enrichment and KEGG pathway analysis of DEGs were performed by FunRich software. A PPI network of DEGs was then constructed using the STRING database and visualized by Cytoscape software. We identified 12 key genes (KGs) including MS4A1, CCL5, and GZMB, by using two topological methods based on the PPI networking results. The diagnostic, expression, and prognostic potentials of the identified 12 key genes were assessed using the receiver operating characteristics (ROC) curve and a web-based tool, SurvExpress. From the regulatory network analysis, we extracted the 7 key transcription factors (TFs) (FOXC1, YY1, CEBPB, TFAP2A, SREBF2, RELA, and GATA2), and 8 key miRNAs (hsa-miR-124-3p, hsa-miR-34a-5p, hsa-miR-21-5p, hsa-miR-155-5p, hsa-miR-449a, hsa-miR-24-3p, hsa-let-7b-5p, and hsa-miR-7-5p) associated with the KGs were evaluated. Functional enrichment and pathway analysis, survival analysis, ROC analysis, and regulatory network analysis highlighted crucial roles of the key genes. Our findings might play a significant role as candidate biomarkers in NSCLC diagnosis and prognosis.
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Affiliation(s)
- Adiba Sultana
- School of Biology and Basic Medical Sciences, Soochow University Medical College, 199 Ren'ai Road, Suzhou 215123, China; Center for Systems Biology, Soochow University, Suzhou 215006, China; Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Xinchuan Road 2222, Chengdu, Sichuan, China
| | - Md Shahin Alam
- School of Biology and Basic Medical Sciences, Soochow University Medical College, 199 Ren'ai Road, Suzhou 215123, China
| | - Xingyun Liu
- Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Xinchuan Road 2222, Chengdu, Sichuan, China
| | - Rohit Sharma
- Department of Rasa Shastra and Bhaishajya Kalpana, Faculty of Ayurveda, Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh 221005, India.
| | - Rajeev K Singla
- Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Xinchuan Road 2222, Chengdu, Sichuan, China; School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, Punjab 144411, India.
| | - Rohit Gundamaraju
- ER Stress and Mucosal Immunology Lab, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, Tasmania, TAS 7248, Australia
| | - Bairong Shen
- Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Xinchuan Road 2222, Chengdu, Sichuan, China.
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Transcription factor SNAI2 exerts pro-tumorigenic effects on glioma stem cells via PHLPP2-mediated Akt pathway. Cell Death Dis 2022; 13:516. [PMID: 35654777 PMCID: PMC9163135 DOI: 10.1038/s41419-021-04481-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 12/01/2021] [Accepted: 12/17/2021] [Indexed: 01/21/2023]
Abstract
The current study aimed to investigate the effects associated with SNAI2 on the proliferation of glioma stem cells (GSCs) to elucidate its underlying molecular mechanism in the development of glioma. The expression of Snail family transcriptional repressor 2 (SNAI2) in glioma tissues was initially predicted via bioinformatics analysis and subsequently confirmed by reverse transcription quantitative polymerase chain reaction (RT-qPCR), which revealed that SNAI2 was highly expressed in glioma tissues as well as GSCs, with an inverse correlation with overall glioma patient survival detected. Loss- and gain- of-function assays were performed to determine the roles of SNAI2 and pleckstrin homology domain and leucine rich repeat protein phosphatase 2 (PHLPP2) on GSC viability, proliferation and apoptosis. Data were obtained indicating that SNAI2 promoted the proliferation of GSCs, while overexpressed PHLPP2 brought about a contrasting trend. As detected by chromatin immunoprecipitation, RT-qPCR and agarose gel electrophoresis, SNAI2 bound to the promoter region of PHLPP2 and repressed the transcription of PHLPP2 while SNAI2 was found to inhibit PHLPP2 resulting in activation of the Akt pathway. Finally, the roles of SNAI2 and PHLPP2 were verified in glioma growth in nude mice xenografted with tumor. Taken together, the key findings of the present study suggest that SNAI2 may promote the proliferation of GSCs through activation of the Akt pathway by downregulating PHLPP2.
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Bendahou MA, Ibrahimi A, Boutarbouch M. Bioinformatics Analysis of Differentially Expressed Genes and miRNAs in Low-Grade Gliomas. Cancer Inform 2020; 19:1176935120969692. [PMID: 33223819 PMCID: PMC7649870 DOI: 10.1177/1176935120969692] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 10/01/2020] [Indexed: 12/28/2022] Open
Abstract
Low-grade glioma is the most common type of primary intracranial tumor. In the last 3 years, new observations of molecular precursors in adults with gliomas have led to a modification in the histopathologic classification of these brain tumors. Among the biomarkers that have been highlighted, we have the micro RNAs (miRNAs) which play a crucial role in the regulation of gene expression and the long noncoding RNAs (lncRNAs) controlling various cellular and metabolic pathways. In our study, large-scale data on sequenced RNA and miRNAs from 516 patients were obtained from the Cancer Genome Atlas database by the TCGAbiolinks package. We identified the differential expression of miRNAs and genes using the Limma package and then we used the ClusterProfiler package for annotations of the biological pathways of the expressed genes, the survival package to estimate the survival analysis, and the GDCRNATools package to determine miRNAs-genes and miRNAs-lncRNAs interactions. We obtained a significant correlation between the miRNAs identified and the overall survival of the patients (log-rank P < .05) and we have theoretically proposed a novel network of miRNAs involved in low-grade gliomas, specifically astrocytomas and oligodendrogliomas, which combine both genes and lncRNAs.
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Affiliation(s)
- Mohammed Amine Bendahou
- Medical Biotechnology Laboratory (MedBiotech), BioInova Research Center, Medical and Pharmacy School, Mohammed V University in Rabat, Morocco
| | - Azeddine Ibrahimi
- Medical Biotechnology Laboratory (MedBiotech), BioInova Research Center, Medical and Pharmacy School, Mohammed V University in Rabat, Morocco
| | - Mahjouba Boutarbouch
- Department of Neurosurgery, Hospital of Specialties, CHU Ibn Sina, Rabat, Medical and Pharmacy School, Mohammed V University in Rabat, Morocco
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Li W, Luo C, Xie X, Xiao Y, Zhao F, Cai J, Zhou X, Zeng T, Fu B, Wu Y, Xiao X, Liu S. Identification of key genes and pathways in syphilis combined with diabetes: a bioinformatics study. AMB Express 2020; 10:83. [PMID: 32342229 PMCID: PMC7186291 DOI: 10.1186/s13568-020-01009-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 04/07/2020] [Indexed: 12/29/2022] Open
Abstract
We noticed that syphilis patients seem to be more susceptible to diabetes and the lesions often involve the kidneys, but the pathogenesis is not yet completely understood. In this study, microarray analysis was performed to investigate the dysregulated expressed genes (DEGs) in rabbit model of syphilis combined with diabetes. A total of 1045 genes were identified to be significantly differentially expressed, among which 571 were up-regulated and 474 were down-regulated (≥ 2.0fold, p < 0.05). Using the database visualization and integration discovery for the Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis. The downregulated DEGs were significantly enriched for biosynthesis of antibiotics, carbon metabolism and protein digestion, while the upregulated DEGs were mainly enriched for cancer and PI3K-Akt signaling pathway. Molecular Complex Detection (MCODE) plugins were used to visualize protein–protein interaction (PPI) network of DEGs and Screening for hub genes and gene modules. ALB, FN1, CASP3, MMP9, IL8, CTGF, STAT3, IGF1, VCAM-1 and HGF were filtrated as the hub genes according to the degree of connectivity from the PPI network. To the best of our knowledge, this study is the first to comprehensively identify the expression patterns of dysregulated genes in syphilis combined with diabetes, providing a basis for revealing the underlying pathogenesis of syphilis combined with diabetes and exploring the goals of therapeutic intervention.
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Zhang C, Wang F, Gao Z, Zhang P, Gao J, Wu X. Regulation of Hippo Signaling by Mechanical Signals and the Cytoskeleton. DNA Cell Biol 2020; 39:159-166. [PMID: 31821009 DOI: 10.1089/dna.2019.5087] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Affiliation(s)
- Cong Zhang
- Department of Spine Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
- Surgery Research Center, School of Medicine, Southeast University, Nanjing, China
- State Education Ministry Laboratory of Developmental Genes and Human Diseases, Southeast University, Nanjing, China
| | - Feng Wang
- Department of Spine Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zengxin Gao
- Department of Spine Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
- Department of Orthopedics, Nanjing Lishui People’s Hospital, Nanjing, China
- Department of Orthopedics, Zhongda Hospital, Lishui Branch, Southeast University, Nanjing, China
| | - Pei Zhang
- Department of Spine Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Jiawei Gao
- Surgery Research Center, School of Medicine, Southeast University, Nanjing, China
- State Education Ministry Laboratory of Developmental Genes and Human Diseases, Southeast University, Nanjing, China
| | - Xiaotao Wu
- Department of Spine Surgery, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
- Surgery Research Center, School of Medicine, Southeast University, Nanjing, China
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