Abstract 4388: Weighted gene co-expression network analysis identified cell cycle signaling pathway associated hub genes correlated with progression and prognosis of multiple myeloma

2020 ◽  
Author(s):  
Olayinka O. Adebayo ◽  
Tiara Griffen ◽  
Corey Young ◽  
Eric Dammer ◽  
James W. Lillard
Keyword(s):  
Cell Cycle ◽  
Multiple Myeloma ◽  
Network Analysis ◽  
Signaling Pathway ◽  
Hub Genes ◽  
Cell Cycle Signaling

scholarly journals Integrated Bioinformatics Analysis of Master Regulators in Anaplastic Thyroid Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Zongfu Pan ◽  
Lu Li ◽  
Qilu Fang ◽  
Yangyang Qian ◽  
Yiwen Zhang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Thyroid Carcinoma ◽  
Signaling Pathway ◽  
Regulatory Network ◽  
Anaplastic Thyroid Carcinoma ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Hub Genes ◽  
Normal Thyroid ◽  
Master Regulators

Anaplastic thyroid carcinoma (ATC) is one of the most aggressive and rapidly lethal tumors. However, limited advances have been made to prolong the survival and to reduce the mortality over the last decades. Therefore, identifying the master regulators underlying ATC progression is desperately needed. In our present study, three datasets including GSE33630, GSE29265, and GSE65144 were retrieved from Gene Expression Omnibus with a total of 32 ATC samples and 78 normal thyroid tissues. A total of 1804 consistently changed differentially expressed genes (DEGs) were identified from three datasets. KEGG pathways enrichment suggested that upregulated DEGs were mainly enriched in ECM-receptor interaction, cell cycle, PI3K-Akt signaling pathway, focal adhesion, and p53 signaling pathway. Furthermore, key gene modules in PPI network were identified by Cytoscape plugin MCODE and they were mainly associated with DNA replication, cell cycle process, collagen fibril organization, and regulation of leukocyte migration. Additionally, TOP2A, CDK1, CCNB1, VEGFA, BIRC5, MAPK1, CCNA2, MAD2L1, CDC20, and BUB1 were identified as hub genes of the PPI network. Interestingly, module analysis showed that 8 out of 10 hub genes participated in Module 1 network and more than 70% genes of Module 2 consisted of collagen family members. Notably, transcription factors (TFs) regulatory network analysis indicated that E2F7, FOXM1, and NFYB were master regulators of Module 1, while CREB3L1 was the master regulator of Module 2. Experimental validation showed that CREB3L1, E2F7, and FOXM1 were significantly upregulated in ATC tissue and cell line when compared with normal thyroid group. In conclusion, the TFs regulatory network provided a more detail molecular mechanism underlying ATC occurrence and progression. TFs including E2F7, FOXM1, CREB3L1, and NFYB were likely to be master regulators of ATC progression, suggesting their potential role as molecular therapeutic targets in ATC treatment.

scholarly journals The HiNF-P/p220NPAT Cell Cycle Signaling Pathway Controls Nonhistone Target Genes

2007 ◽  
Vol 67 (21) ◽  
pp. 10334-10342 ◽  
Author(s):  
Ricardo Medina ◽  
Margaretha van der Deen ◽  
Angela Miele-Chamberland ◽  
Rong-Lin Xie ◽  
Andre J. van Wijnen ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Signaling Pathway ◽  
Target Genes ◽  
Cell Cycle Signaling

scholarly journals A Noncanonical Role for the CKI-RB-E2F Cell-Cycle Signaling Pathway in Plant Effector-Triggered Immunity

2014 ◽  
Vol 16 (6) ◽  
pp. 787-794 ◽  
Author(s):  
Shui Wang ◽  
Yangnan Gu ◽  
Sophia G. Zebell ◽  
Lisa K. Anderson ◽  
Wei Wang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Signaling Pathway ◽  
Effector Triggered Immunity ◽  
Cell Cycle Signaling

scholarly journals Identification of Hub Genes and Potential ceRNA Networks of Diabetic Nephropathy by Weighted Gene Co-Expression Network Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Guoqing Li ◽  
Jun Zhang ◽  
Dechen Liu ◽  
Qiong Wei ◽  
Hui Wang ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Network Analysis ◽  
Disease Progression ◽  
Signaling Pathway ◽  
Microvascular Complications ◽  
Pearson Correlation ◽  
Mapk Signaling ◽  
Diabetic Patients ◽  
Hub Genes ◽  
Regulatory Pathways

Diabetic nephropathy (DN) is one of the most common microvascular complications in diabetic patients, and is the main cause of end-stage renal disease. The exact molecular mechanism of DN is not fully understood. The aim of this study was to identify novel biomarkers and mechanisms for DN disease progression by weighted gene co-expression network analysis (WGCNA). From the GSE142153 dataset based on the peripheral blood monouclear cells (PBMC) of DN, we identified 234 genes through WGCNA and differential expression analysis. Gene Ontology (GO) annotations mainly included inflammatory response, leukocyte cell-cell adhesion, and positive regulation of proteolysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways mostly included IL-17 signaling pathway, MAPK signaling pathway, and PPAR signaling pathway in DN. A total of four hub genes (IL6, CXCL8, MMP9 and ATF3) were identified by cytoscape, and the relative expression levels of hub genes were also confirmed by RT-qPCR. ROC curve analysis determined that the expression of the four genes could distinguish DN from controls (the area under the curve is all greater than 0.8), and Pearson correlation coefficient analysis suggested that the expression of the four genes was related to estimated glomerular filtration rate (eGFR) of DN. Finally, through database prediction and literature screening, we constructed lncRNA-miRNA-mRNA network. We propose that NEAT1/XIST/KCNQ1T1-let-7b-5p-IL6, NEAT1/XIST-miR-93-5p-CXCL8 and NEAT1/XIST/KCNQ1T1-miR-27a-3p/miR-16-5p-ATF3 might be potential RNA regulatory pathways to regulate the disease progression of early DN. In conclusion, we identified four hub genes, namely, IL6, CXCL8, MMP9, and ATF3, as markers for early diagnosis of DN, and provided insight into the mechanisms of disease development in DN at the transcriptome level.

scholarly journals Diallyl thiosulfinate enhanced the anti-cancer activity of dexamethasone in the side population cells of multiple myeloma by promoting miR-127-3p and deactivating the PI3K/AKT signaling pathway

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenfeng He ◽  
Yonghui Fu ◽  
Yongliang Zheng ◽  
Xiaoping Wang ◽  
Bin Liu ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Multiple Myeloma ◽  
Cell Proliferation ◽  
Cell Cycle Arrest ◽  
Signaling Pathway ◽  
Cell Lines ◽  
Colony Formation ◽  
Side Population ◽  
Mtor Signaling Pathway ◽  
Cycle Arrest

Abstract Background Side population (SP) cells, which have similar features to those of cancer stem cells, show resistance to dexamethasone (Dex) treatment. Thus, new drugs that can be used in combination with Dex to reduce the population of SP cells in multiple myeloma (MM) are required. Diallyl thiosulfinate (DATS, allicin), a natural organosulfur compound derived from garlic, has been shown to inhibit the proliferation of SP cells in MM cell lines. Therefore, we investigated the effect of a combination of DATS and Dex (DAT + Dex) on MM SP cells. Methods SP cells were sorted from MM RPMI-8226 and NCI-H929 cell lines using Hoechst 33342-labeled fluorescence-activated cell sorting. The growth of SP cells was evaluated using the cell counting kit-8 assay. Cell cycle and apoptosis assays were conducted using a BD Calibur flow cytometer. miRNA expression was measured using quantitative reverse transcription-polymerase chain reaction. Phosphoinositide 3-kinase (PI3K), phosphorylated AKT (p-AKT), AKT, p-mechanistic target of rapamycin (mTOR), and mTOR levels were measured using western blot analysis. Results Our results showed that the combination of DATS+Dex inhibited sphere formation, colony formation, and proliferation of MM SP cells by inducing apoptosis and cell cycle arrest in the G1/S phase. In addition, the combination of DATS+Dex promoted miR-127-3p expression and inhibited PI3K, p-AKT, and p-mTOR expression in SP cells. Knockdown of miR-127-3p expression weakened the effect of DATS+Dex on cell proliferation, colony formation, apoptosis, and cell cycle of MM SP cells. Additionally, knockdown of miR-127-3p activated the PI3K/AKT/mTOR signaling pathway in MM SP cells cotreated with DATS+Dex. Conclusion We demonstrated that cotreatment with DATS+Dex reduced cell proliferation, promoted apoptosis, and caused cell cycle arrest of MM SP cells by promoting miR-127-3p expression and deactivating the PI3K/AKT/mTOR signaling pathway.

scholarly journals Exploration and validation of hub genes and pathways in the progression of hypoplastic left heart syndrome via weighted gene co-expression network analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xuelan Liu ◽  
Honglei Shang ◽  
Bin Li ◽  
Liyun Zhao ◽  
Ying Hua ◽  
...  
Keyword(s):  
Network Analysis ◽  
Signaling Pathway ◽  
Hypoplastic Left Heart Syndrome ◽  
Left Heart ◽  
Hypoplastic Left Heart ◽  
Hub Genes ◽  
Molecular Abnormalities ◽  
Black Module ◽  
Left Heart Syndrome ◽  
Key Pathways

Abstract Background Despite significant progress in surgical treatment of hypoplastic left heart syndrome (HLHS), its mortality and morbidity are still high. Little is known about the molecular abnormalities of the syndrome. In this study, we aimed to probe into hub genes and key pathways in the progression of the syndrome. Methods Differentially expressed genes (DEGs) were identified in left ventricle (LV) or right ventricle (RV) tissues between HLHS and controls using the GSE77798 dataset. Then, weighted gene co-expression network analysis (WGCNA) was performed and key modules were constructed for HLHS. Based on the genes in the key modules, protein–protein interaction networks were conducted, and hub genes and key pathways were screened. Finally, the GSE23959 dataset was used to validate hub genes between HLHS and controls. Results We identified 88 and 41 DEGs in LV and RV tissues between HLHS and controls, respectively. DEGs in LV tissues of HLHS were distinctly involved in heart development, apoptotic signaling pathway and ECM receptor interaction. DEGs in RV tissues of HLHS were mainly enriched in BMP signaling pathway, regulation of cell development and regulation of blood pressure. A total of 16 co-expression network were constructed. Among them, black module (r = 0.79 and p value = 2e−04) and pink module (r = 0.84 and p value = 4e−05) had the most significant correlation with HLHS, indicating that the two modules could be the most relevant for HLHS progression. We identified five hub genes in the black module (including Fbn1, Itga8, Itga11, Itgb5 and Thbs2), and five hub genes (including Cblb, Ccl2, Edn1, Itgb3 and Map2k1) in the pink module for HLHS. Their abnormal expression was verified in the GSE23959 dataset. Conclusions Our findings revealed hub genes and key pathways for HLHS through WGCNA, which could play key roles in the molecular mechanism of HLHS.

scholarly journals Integrative systems biology approach identified crucial genes and transcription factors associated with gallbladder cancer pathogenesis

2021 ◽  
Author(s):  
Nabanita Roy ◽  
Mrinmoy Kshattry ◽  
Susmita Mandal ◽  
Mohit Kumar Jolly ◽  
Dhruba Kumar Bhattacharyya ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Transcription Factors ◽  
Network Analysis ◽  
Gallbladder Cancer ◽  
Epithelial Mesenchymal Transition ◽  
System Level ◽  
Hub Genes ◽  
Mesenchymal Transition ◽  
Cancer Pathogenesis ◽  
Lower Incidence Rate

AbstractGallbladder cancer (GBC) has a lower incidence rate among the population relative to other cancer types but majorly contributes to the total cancer cases of the biliary tract system. GBC is distinguished from other malignancies due to its high mortality, marked geographical variation and poor prognosis. To date no systemic targeted therapy is available for GBC. The main objective of this study is to determine the molecular signatures correlated with GBC development using integrative system level approaches. We performed analysis of publicly available transcriptomic data to identify differentially regulated genes and pathways. Co-expression network analysis and differential regulatory network analysis identified hub genes and hub transcription factors (TFs) associated with GBC pathogenesis and progression. We then assessed the epithelial-mesenchymal transition (EMT) status of the hub genes using a combination of three scoring methods. The hub genes such as; CDC6, MAPK15, CCNB2, BIRC7, L3MBTL1 identified are regulators of cell cycle components which suggests that cell cycle regulatory genes are significantly linked to GBC pathogenesis and progression.

scholarly journals Transcriptomic analysis of tumor tissues and organoids reveals the crucial genes regulating the proliferation of lung adenocarcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xiao Ma ◽  
Su Yang ◽  
Hesheng Jiang ◽  
Yujie Wang ◽  
Zhen Xiang
Keyword(s):  
Network Analysis ◽  
Lung Adenocarcinoma ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Cell Lines ◽  
Cancer Biology ◽  
Transcriptomic Analysis ◽  
Hub Genes ◽  
Prognostic Analysis ◽  
Tumor Tissues

Abstract Background Accumulative evidence shows that an organoid is a more practical and reliable tool in cancer biology research. This study aimed to identify and validate crucial genes involved in non-small cell lung cancer carcinogenesis and development using the transcriptomic analysis of tumor tissues and organoids. Methods Gene set enrichment analysis (GSEA) of tumor tissues, tumor organoids, and normal tissues was performed to reveal the similar and different mechanisms involved in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) carcinogenesis and progression. Differentially expressed gene analysis, prognostic analysis, and gene co-expression network analysis were further used to identify hub genes involved in LUAD and LUSC carcinogenesis and development. Finally, LUAD cell lines and organoids were used to validate these findings. Results GSEA analysis was performed to reveal the similar mechanisms involved in LUAD and LUSC carcinogenesis and development, such as P53 signaling pathway, base mismatch repair, DNA replication, cAMP signaling pathway and PPAR pathway. However, comparing with LUSC organoids, LUAD organoids showed downregulation of immune-related pathways, inflammation-related pathways, MAPK signaling pathways, and Rap1 signaling pathways, although these pathways were downregulated in LUAD and LUSC tissues by comparing with normal lung tissues. Further gene co-expression network analysis and prognostic analysis indicated CDK1, CCNB2, and CDC25A as the hub tumor-promoting genes in LUAD but not in LUSC, which were further validated in other datasets. Using LUAD cell lines and organoid models, CDK1 and CCNB2 knockdown were found to suppress LUAD proliferation. However, CDC25A knockdown did not inhibit LUAD cell line proliferation but could effectively suppress LUAD organoid growth, indicating that an organoid could be used as an effective tool to study cancer biology in LUAD. Conclusions The results revealed CDK1, CCNB2, and CDC25A as the hub genes involved in LUAD carcinogenesis and development, which could be used as the potential biomarkers and targets for LUAD.

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