scholarly journals A network view of microRNA and gene interactions in different pathological stages of colon cancer

2019 ◽  
Vol 12 (S7) ◽  
Author(s):  
Jia Wen ◽  
Benika Hall ◽  
Xinghua Shi
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Gene Interactions ◽  
New Strategy ◽  
Pathological Stages

Abstract Background Colon cancer is one of the common cancers in human. Although the number of annual cases has decreased drastically, prognostic screening and translational methods can be improved. Hence, it is critical to understand the molecular mechanisms of disease progression and prognosis. Results In this study, we develop a new strategy for integrating microRNA and gene expression profiles together with clinical information toward understanding the regulation of colon cancer. Particularly, we use this approach to identify microRNA and gene expression networks that are specific to certain pathological stages. To demonstrate the application of our method, we apply this approach to identify microRNA and gene interactions that are specific to pathological stages of colon cancer in The Cancer Genome Atlas (TCGA) datasets. Conclusions Our results show that there are significant differences in network connections between miRNAs and genes in different pathological stages of colon cancer. These findings point to a hypothesis that these networks signify different roles of microRNA and gene regulation in the pathogenesis and tumorigenesis of colon cancer.

scholarly journals Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach

2022 ◽  
Vol 2022 ◽  
pp. 1-17
Author(s):  
Md. Rakibul Islam ◽  
Lway Faisal Abdulrazak ◽  
Mohammad Khursheed Alam ◽  
Bikash Kumar Paul ◽  
Kawsar Ahmed ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
New Treatments

Background. Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB. Methods. A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣ log   fold   change ∣ > 1 and P < 0.05 . The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network. Results. Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.

A prognostic model constructed by CTHRC1 and LRFN4 in Stomach adenocarcinoma by Bioinformatics Analysis

2020 ◽  
Author(s):  
Songling Han ◽  
Wei Zhu ◽  
Qijie Guan ◽  
Zhuoheng Zhong ◽  
Ruoke Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prognostic Model ◽  
Cox Regression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Cancer Genome Atlas ◽  
Stomach Adenocarcinoma

Abstract Background Stomach adenocarcinoma (STAD) is the most common histological type of stomach cancer, which causes a considerable number of deaths worldwide. This study specifically aimed to identify potential biomarkers and reveal the underlying molecular mechanisms. Methods Gene expression profiles microarray data were downloaded from the Gene Expression Omnibus (GEO) database. The ‘limma’ R package was used to screen the differentially expressed genes (DEGs) between STAD and matched normal tissues. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for function enrichment analyses of DEGs. The data of STAD cases with both RNA sequencing and clinical information of The Cancer Genome Atlas (TCGA) were obtained from Genomic Data Commons (GDC) data portal. Survival curves were analyzed by the Kaplan-Meier method, univariate Cox regression analysis and multivariate Cox regression were performed using ‘survival’ package. CIBERSORT algorithm used approach to characterize the 22 human immune cell composition. Gene expression profiles microarray data and clinical information were downloaded from GEO database to validate prognostic model. Results Three public datasets including 90 STAD patients and 43 healthy controls were used and 44 genes were differentially expressed in all three datasets. These genes were primarily implicated in biological processes including cell adhesion, wound healing and extracellular matrix organization. Seven out of 44 genes showed significant survival differences based on their expression differences. CTHRC1 and LRFN4 were eventually used to constructed risk score and prognostic model by univariate Cox regression and stepwise multivariate Cox regression in The Cancer Genome Atlas (TCGA)-STAD dataset. The group having high risk scores and the group having low risk scores had significant differences in the infiltration level of multiple immune cells including CD4 memory resting T cells, M2 macrophages, memory B cells, resting dendritic cells, eosinophils, and gamma delta T cells. Multivariate Cox regression analyses indicated that the risk score was an independent predictor after adjusting for age, sex, and tumor stage. At last, the model was verified and evaluated by another independent dataset and showed a good classification effect. Conclusions The present study constructed the prognostic model by expression of CTHRC1 and LRFN4 for the first time via comprehensive bioinformatics analysis, which may provide clinical guidance and potential therapeutic targets for STAD.

scholarly journals Modulation of the Immune Response by Deferasirox in Myelodysplastic Syndrome Patients

2021 ◽  
Vol 14 (1) ◽  
pp. 41
Author(s):  
Hana Votavova ◽  
Zuzana Urbanova ◽  
David Kundrat ◽  
Michaela Dostalova Merkerova ◽  
Martin Vostry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Blood Cell ◽  
Myelodysplastic Syndrome ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Adaptive Immune Response ◽  
Gene Expression Profiles ◽  
Iron Chelator ◽  
Multiple Cancer

Deferasirox (DFX) is an oral iron chelator used to reduce iron overload (IO) caused by frequent blood cell transfusions in anemic myelodysplastic syndrome (MDS) patients. To study the molecular mechanisms by which DFX improves outcome in MDS, we analyzed the global gene expression in untreated MDS patients and those who were given DFX treatment. The gene expression profiles of bone marrow CD34+ cells were assessed by whole-genome microarrays. Initially, differentially expressed genes (DEGs) were determined between patients with normal ferritin levels and those with IO to address the effect of excessive iron on cellular pathways. These DEGs were annotated to Gene Ontology terms associated with cell cycle, apoptosis, adaptive immune response and protein folding and were enriched in cancer-related pathways. The deregulation of multiple cancer pathways in iron-overloaded patients suggests that IO is a cofactor favoring the progression of MDS. The DEGs between patients with IO and those treated with DFX were involved predominantly in biological processes related to the immune response and inflammation. These data indicate DFX modulates the immune response mainly via neutrophil-related genes. Suppression of negative regulators of blood cell differentiation essential for cell maturation and upregulation of heme metabolism observed in DFX-treated patients may contribute to the hematopoietic improvement.

scholarly journals Integrating Genetic and Transcriptomic Data to Reveal Pathogenesis and Prognostic Markers of Pancreatic Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Kaisong Bai ◽  
Tong Zhao ◽  
Yilong Li ◽  
Xinjian Li ◽  
Zhantian Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Adenocarcinoma ◽  
Somatic Mutation ◽  
Somatic Mutations ◽  
Prognostic Markers ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Genomic Variation ◽  
The Cancer Genome Atlas ◽  
Driver Genes

Pancreatic adenocarcinoma (PAAD) is one of the deadliest malignancies and mortality for PAAD have remained increasing under the conditions of substantial improvements in mortality for other major cancers. Although multiple of studies exists on PAAD, few studies have dissected the oncogenic mechanisms of PAAD based on genomic variation. In this study, we integrated somatic mutation data and gene expression profiles obtained by high-throughput sequencing to characterize the pathogenesis of PAAD. The mutation profile containing 182 samples with 25,470 somatic mutations was obtained from The Cancer Genome Atlas (TCGA). The mutation landscape was generated and somatic mutations in PAAD were found to have preference for mutation location. The combination of mutation matrix and gene expression profiles identified 31 driver genes that were closely associated with tumor cell invasion and apoptosis. Co-expression networks were constructed based on 461 genes significantly associated with driver genes and the hub gene FAM133A in the network was identified to be associated with tumor metastasis. Further, the cascade relationship of somatic mutation-Long non-coding RNA (lncRNA)-microRNA (miRNA) was constructed to reveal a new mechanism for the involvement of mutations in post-transcriptional regulation. We have also identified prognostic markers that are significantly associated with overall survival (OS) of PAAD patients and constructed a risk score model to identify patients’ survival risk. In summary, our study revealed the pathogenic mechanisms and prognostic markers of PAAD providing theoretical support for the development of precision medicine.

scholarly journals Transcriptome-wide gene expression plasticity in Stipa grandis in response to grazing intensity differences

2020 ◽  
Author(s):  
Zhenhua Dang ◽  
Yuanyuan Jia ◽  
Yunyun Tian ◽  
Jiabin Li ◽  
Yanan Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Metabolic Pathways ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Grazing Intensity ◽  
Glycolate Oxidase ◽  
Bisphosphate Carboxylase ◽  
Grazing Intensities

Organisms have evolved effective and distinct adaptive strategies to survive. Stipa grandis is one of the widespread dominant species on the typical steppe of the Inner Mongolian Plateau, and is regarded as a suitable species for studying the effects of grazing in this region. Although phenotypic (morphological and physiological) variations in S. grandis in response to long-term grazing have been identified, the molecular mechanisms underlying adaptations and plastic responses remain largely unknown. Accordingly, we performed a transcriptomic analysis to investigate changes in gene expression of S. grandis under four different grazing intensities. A total of 2,357 differentially expressed genes (DEGs) were identified among the tested grazing intensities, suggesting long-term grazing resulted in gene expression plasticity that affected diverse biological processes and metabolic pathways in S. grandis. DEGs were identified that indicated modulation of Calvin–Benson cycle and photorespiration metabolic pathways. The key gene´expression profiles encoding various proteins (e.g., Ribulose-1,5-bisphosphate carboxylase/oxygenase, fructose-1,6-bisphosphate aldolase, glycolate oxidase etc.) involved in these pathways suggest that they may synergistically respond to grazing to increase the resilience and stress tolerance of S. grandis. Our findings provide scientific clues for improving grassland use and protection, and identify important questions to address in future transcriptome studies.

scholarly journals SMC4, CCNB1 and CKS1B as potential targets and new critical biomarkers for the prognosis of human bladder cancer

2021 ◽  
Author(s):  
Hongpeng Fang ◽  
Zhansen Huang ◽  
Xianzi Zeng ◽  
Jiaming Wan ◽  
Jieying Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Transcriptional Level ◽  
Hub Genes ◽  
Kaplan Meier ◽  
High Form

Abstract Background As a common malignant cancer of the urinary system, the precise molecular mechanisms of bladder cancer remain to be illuminated. The purpose of this study was to identify core genes with prognostic value as potential oncogenes for the diagnosis, prognosis or novel therapeutic targets of bladder cancer. Methods The gene expression profiles GSE3167 and GSE7476 were available from the Gene Expression Omnibus (GEO) database. Next, PPI network was built to filter the hub gene through the STRING database and Cytoscape software and GEPIA and Kaplan-Meier plotter were implemented. Frequency and type of hub genes and sub groups analysis were performed in cBioportal and ULCAN database. Finally,We used RT-qPCR to confirm our results. Results Totally, 251 DEGs were excavated from two datasets in our study. We only founded high expression of SMC4, TYMS, CCNB1, CKS1B, NUSAP1 and KPNA2 was associated with worse outcomes in bladder cancer patients and no matter from the type of mutation or at the transcriptional level of hub genes, the tumor showed a high form of expression. However, only the expression of SMC4,CCNB1and CKS1B remained changed between the cancer and the normal samples in our results of RT-qPCR. Conclusion In conclusion,These findings indicate that the SMC4,CCNB1 and CKS1B may serve as critical biomarkers in the development and poor prognosis.

scholarly journals Identification and Validation of a Predictive Immune-related Genes Signature for the Prognosis of Cholangiocarcinoma

2020 ◽  
Author(s):  
Rui Zhang ◽  
Chen Chen ◽  
Qi Li ◽  
Jialu Fu ◽  
Dong Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
High Risk ◽  
Risk Score ◽  
Risk Model ◽  
Predictive Accuracy ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Immune Related Genes

Abstract Background: Immune-related genes (IRGs) play a crucial role in the initiation and progression of cholangiocarcinoma (CCA). However, immune signatures have rarely been used to predict prognosis of CCA. The aim of this study was to construct a novel model for CCA to predict survival based on IRGs expression data.Methods: The gene expression profiles and clinical data of CCA patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were integrated to establish and validate prognostic IRG signatures. Differentially expressed immune-related genes were screened. Univariate and multivariate Cox analysis were performed to identify prognostic IRGs, and the risk model that predicts outcomes was constructed. Furthermore, receiver operating characteristic (ROC) and Kaplan-Meier curve were plotted to examine predictive accuracy of the model, and a nomogram was constructed based on IRGs signature, combining with other clinical characteristics. Finally, CIBERSORT was used to analyze the association of immune cells infiltration with risk score.Results: We identified that 223 IRGs were significantly dysregulated in patients with CCA, among which five IRGs (AVPR1B, CST4, TDGF1, RAET1E and IL9R) were identified as robust indicators for overall survival (OS), and a prognostic model was built based on the IRGs signature. Meanwhile, patients with high risk had worse OS in training and validation cohort, and the area under the ROC was 0.898 and 0.846, respectively. Nomogram demonstrated that immune risk score contributed much more points than other clinicopathological variables, with a C-index of 0.819 (95% CI, 0.727-0.911). Finally, we found that IRGs signature was positively correlated with the proportion of CD8+ T cells, neurophils and T gamma delta, while negatively with that of CD4+ memory resting T cells.Conclusions: We established and validated an effective five IRGs-based prediction model for CCA, which could accurately classify patients into groups with low and high risk of poor prognosis.

scholarly journals Convergent evolution of venom gland transcriptomes across Metazoa

2021 ◽  
Author(s):  
Giulia Zancolli ◽  
Maarten Reijnders ◽  
Robert Waterhouse ◽  
Marc Robinson-Rechavi
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Venom Gland ◽  
Bioactive Molecules ◽  
Specific Gene ◽  
Animal Kingdom ◽  
Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

scholarly journals Transcriptomic Modification in the Cerebral Cortex following Noninvasive Brain Stimulation: RNA-Sequencing Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Ben Holmes ◽  
Seung Ho Jung ◽  
Jing Lu ◽  
Jessica A. Wagner ◽  
Liudmilla Rubbi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cerebral Cortex ◽  
Rna Sequencing ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Current Intensity ◽  
Beneficial Effects ◽  
Group A ◽  
The Impact

Transcranial direct current stimulation (tDCS) has been shown to modulate neuroplasticity. Beneficial effects are observed in patients with psychiatric disorders and enhancement of brain performance in healthy individuals has been observed following tDCS. However, few studies have attempted to elucidate the underlying molecular mechanisms of tDCS in the brain. This study was conducted to assess the impact of tDCS on gene expression within the rat cerebral cortex. Anodal tDCS was applied at 3 different intensities followed by RNA-sequencing and analysis. In each current intensity, approximately 1,000 genes demonstrated statistically significant differences compared to the sham group. A variety of functional pathways, biological processes, and molecular categories were found to be modified by tDCS. The impact of tDCS on gene expression was dependent on current intensity. Results show that inflammatory pathways, antidepressant-related pathways (GTP signaling, calcium ion binding, and transmembrane/signal peptide pathways), and receptor signaling pathways (serotonergic, adrenergic, GABAergic, dopaminergic, and glutamate) were most affected. Of the gene expression profiles induced by tDCS, some changes were observed across multiple current intensities while other changes were unique to a single stimulation intensity. This study demonstrates that tDCS can modify the expression profile of various genes in the cerebral cortex and that these tDCS-induced alterations are dependent on the current intensity applied.

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