Identification of ITPR1 as a hub gene of Group 3 Medulloblastoma and coregulated genes with potential prognostic values

Abstract The Group 3 Medulloblastoma ( Grp3-MB ) is an aggressive molecular subtype with a high incidence of metastasis and deaths. In this study, were used an RNA sequencing data ( RNA-Seq ) from a Brazinian cohort of MBs to identify hub genes associated with the metastatic risk. Data validation were performed by using multiple large datasets from MBs (GSE85217, GSE37418, EGAS00001001953). DESeq2 package in R software was used to identify the differentially expressed genes ( DEGs ) in our RNA-Seq data. The DEGs data were accessed to construct the modules/graphs of coexpression and to identify hub genes through Cytoscape platform. The co-regulated genes were enriched by the Kyoto Encyclopedia of Genes and Genomes ( KEGG ) pathway and the Protein-protein interaction ( PPI ) network was visualized by Cytoscape. The Kaplan–Meier plotter and ROC curves were used to validate the diagnostic and prognostic values of specific biomarkers identified through this model. We identified that Inositol 1,4,5-triphosphate receptor type 1 ( ITPR1 ) as a downregulated hub gene, with a high diagnostic accuracy to Grp3-MBs and associated with tumor metastasis. In addition, we identified genes significantly correlated with ITPR1 that were associated with metastasis in Grp3-MB ( ATP1A2 , MTTL7A and RGL1) , and worst overall survival in MBs ( ANTXR1 and RGL1 ). Our findings suggest that the ITPR1 hub gene is potentially involved in the metastatic process for Grp3-MB. Our data also provide evidence of targets that may serve as prognostic predictors and/or regulators for the metastatic process that maybe explored for further research of individualized therapy to Grp3-MBs.

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Hyaluronan-mediated motility receptor expression functions as a prognostic biomarker in uterine carcinosarcoma based on bioinformatics analysis

Journal of International Medical Research ◽

10.1177/03000605211021043 ◽

2021 ◽

Vol 49 (6) ◽

pp. 030006052110210

Author(s):

Hui Sun ◽

Li Ma ◽

Jie Chen

Keyword(s):

Interaction Network ◽

Maximal Clique ◽

Receptor Expression ◽

The Cancer Genome Atlas ◽

Uterine Carcinosarcoma ◽

Sequencing Data ◽

Hub Genes ◽

Protein Protein Interaction ◽

Normal Tissues ◽

Potential Biomarker

Objective Uterine carcinosarcoma (UCS) is a rare, aggressive tumour with a high metastasis rate and poor prognosis. This study aimed to explore potential key genes associated with the prognosis of UCS. Methods Transcriptional expression data were downloaded from the Gene Expression Profiling Interactive Analysis database and differentially expressed genes (DEGs) were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses using Metascape. A protein–protein interaction network was constructed using the STRING website and Cytoscape software, and the top 30 genes obtained through the Maximal Clique Centrality algorithm were selected as hub genes. These hub genes were validated by clinicopathological and sequencing data for 56 patients with UCS from The Cancer Genome Atlas database. Results A total of 1894 DEGs were identified, and the top 30 genes were considered as hub genes. Hyaluronan-mediated motility receptor (HMMR) expression was significantly higher in UCS tissues compared with normal tissues, and elevated expression of HMMR was identified as an independent prognostic factor for shorter survival in patients with UCS. Conclusions These results suggest that HMMR may be a potential biomarker for predicting the prognosis of patients with UCS.

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MicroRNA expression analysis for identification of biomarkers in inflammatory bowel disease subtypes

10.21203/rs.3.rs-27227/v1 ◽

2020 ◽

Author(s):

Manisha Mandal ◽

Shyamapada Mandal

Keyword(s):

Ribosome Biogenesis ◽

Target Genes ◽

Proteasomal Degradation ◽

Differentially Expressed ◽

Hub Genes ◽

Hub Gene ◽

Protein Protein Interaction ◽

Bowel Diseases ◽

Inflammatory Bowel ◽

Protein Protein Interaction Networks

Abstract The potential biomarkers in inflammatory bowel diseases (IBDs) were analyzed from GSE53867 dataset. Differentially expressed microRNAs (DEMs)-genes and protein-protein interaction networks were constructed, and hub genes selected using Cytoscape. Differentially expressed genes were analyzed for GO and Reactome-pathway. Seven DEMs were upregulated in Crohn's disease (CD), 4 downregulated in ulcerative colitis (UC), 8 upregulated and 2 downregulated in IBD. A 620, 2377, and 1821 target-genes were in CD, UC, and IBD, respectively. SOCS3, upregulated by miR-650, was hub gene in CD, induced by cytokines, through NFKB-signalling pathway to mediate ubiquitin-proteasomal degradation. CIRH1A, downregulated by miR-16, was hub gene of UC, acted by impairing ribosome-biogenesis. SKP2 and ASB1, up- and downregulated, by miR-142 and miR-665, respectively, were hub genes of IBD, induced cytokines through activation of TLR- and TNF-signalling pathways to mediate ubiquitin-proteasomal degradation. SOCS3, CIRH1A, SKP2 and ASB1 genes might serve as valuable biomarkers to differentiate CD, UC and IBD.

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Depicting the Core Transcriptome Modulating Multiple Abiotic Stresses Responses in Sesame (Sesamum indicum L.)

International Journal of Molecular Sciences ◽

10.3390/ijms20163930 ◽

2019 ◽

Vol 20 (16) ◽

pp. 3930 ◽

Cited By ~ 16

Author(s):

Komivi Dossa ◽

Marie A. Mmadi ◽

Rong Zhou ◽

Tianyuan Zhang ◽

Ruqi Su ◽

...

Keyword(s):

Abiotic Stresses ◽

Meta Analysis ◽

Plant Responses ◽

Proof Of Concept ◽

Rna Seq ◽

Wild Type ◽

Salt Treatment ◽

Hub Genes ◽

Hub Gene ◽

The Core

Sesame is a source of a healthy vegetable oil, attracting a growing interest worldwide. Abiotic stresses have devastating effects on sesame yield; hence, studies have been performed to understand sesame molecular responses to abiotic stresses, but the core abiotic stress-responsive genes (CARG) that the plant reuses in response to an array of environmental stresses are unknown. We performed a meta-analysis of 72 RNA-Seq datasets from drought, waterlogging, salt and osmotic stresses and identified 543 genes constantly and differentially expressed in response to all stresses, representing the sesame CARG. Weighted gene co-expression network analysis of the CARG revealed three functional modules controlled by key transcription factors. Except for salt stress, the modules were positively correlated with the abiotic stresses. Network topology of the modules showed several hub genes predicted to play prominent functions. As proof of concept, we generated over-expressing Arabidopsis lines with hub and non-hub genes. Transgenic plants performed better under drought, waterlogging, and osmotic stresses than the wild-type plants but did not tolerate the salt treatment. As expected, the hub gene was significantly more potent than the non-hub gene. Overall, we discovered several novel candidate genes, which will fuel investigations on plant responses to multiple abiotic stresses.

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Comparative Transcriptome Analysis Reveals the Potential Cardiovascular Protective Targets of the Thyroid Hormone Metabolite 3-Iodothyronamine (3-T1AM)

BioMed Research International ◽

10.1155/2020/1302453 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Zhou Haiyan ◽

Hu Bailong ◽

Zhang Bei ◽

Wang Yiming ◽

Liu Xingde

Keyword(s):

Cardiovascular Diseases ◽

Thyroid Hormone ◽

Transcriptome Analysis ◽

H9c2 Cells ◽

Comparative Transcriptome ◽

Rna Seq ◽

Hub Genes ◽

Comparative Transcriptome Analysis ◽

Protein Protein Interaction ◽

Protein Protein Interaction Networks

Background. The thyroid hormone metabolite 3-iodothyronamine (3-T1AM) is rapidly emerging as a promising compound in decreasing the heart rate and lowering the cardiac output. The aim of our study was to fully understand the molecular mechanism of 3-T1AM on cardiomyocytes and its potential targets in cardiovascular diseases. Materials and Methods. In our study, we utilized RNA-Seq to characterize the gene expression in H9C2 cells after 3-T1AM treatment. Comparative transcriptome analysis, including gene ontology, signaling pathways, disease connectivity analysis, and protein-protein interaction networks (PPI), was presented to find the critical gene function, hub genes, and related pathways. Results. A total of 1494 differently expressed genes (DEGs) were identified (192 upregulated and 1302 downregulated genes) in H9C2 cells for 3-T1AM treatment. Of these, 90 genes were associated with cardiovascular diseases. The PPI analysis indicated that 5 hub genes might be the targets of 3-T1AM. Subsequently, eight DEGs characterized using RNA-Seq were confirmed by RT-qPCR assays. Conclusions. Our study provides a comprehensive analysis of 3-T1AM on H9C2 cells and delineates a new insight into the therapeutic intervention of 3-T1AM for the cardiovascular diseases.

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Subgenome Bias and Temporal Postponement of Gene Expression Contributes to the Distinctions of Fiber Quality in Gossypium Species

Frontiers in Plant Science ◽

10.3389/fpls.2021.819679 ◽

2021 ◽

Vol 12 ◽

Author(s):

Huan Mei ◽

Bowen Qi ◽

Zegang Han ◽

Ting Zhao ◽

Menglan Guo ◽

...

Keyword(s):

Gene Expression ◽

Fiber Quality ◽

Expression Patterns ◽

Rna Seq ◽

Hub Genes ◽

Hub Gene ◽

Expression Of Genes ◽

Multiple Dimensions ◽

Cotton Species ◽

Expression Bias

As two cultivated widely allotetraploid cotton species, although Gossypium hirsutum and Gossypium barbadense evolved from the same ancestor, they differ in fiber quality; the molecular mechanism of that difference should be deeply studied. Here, we performed RNA-seq of fiber samples from four G. hirsutum and three G. barbadense cultivars to compare their gene expression patterns on multiple dimensions. We found that 15.90–37.96% of differentially expressed genes showed biased expression toward the A or D subgenome. In particular, interspecific biased expression was exhibited by a total of 330 and 486 gene pairs at 10 days post-anthesis (DPA) and 20 DPA, respectively. Moreover, 6791 genes demonstrated temporal differences in expression, including 346 genes predominantly expressed at 10 DPA in G. hirsutum (TM-1) but postponed to 20 DPA in G. barbadense (Hai7124), and 367 genes predominantly expressed at 20 DPA in TM-1 but postponed to 25 DPA in Hai7124. These postponed genes mainly participated in carbohydrate metabolism, lipid metabolism, plant hormone signal transduction, and starch and sucrose metabolism. In addition, most of the co-expression network and hub genes involved in fiber development showed asymmetric expression between TM-1 and Hai7124, like three hub genes detected at 10 DPA in TM-1 but not until 25 DPA in Hai7124. Our study provides new insights into interspecific expression bias and postponed expression of genes associated with fiber quality, which are mainly tied to asymmetric hub gene network. This work will facilitate further research aimed at understanding the mechanisms underlying cotton fiber improvement.

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Integrative analysis of ferroptosis-related genes in ulcerative colitis

Journal of International Medical Research ◽

10.1177/03000605211042975 ◽

2021 ◽

Vol 49 (9) ◽

pp. 030006052110429

Author(s):

De-jun Cui ◽

Chen Chen ◽

Wen-qiang Yuan ◽

Yun-han Yang ◽

Lu Han

Keyword(s):

Ulcerative Colitis ◽

Protein Interaction ◽

Peripheral Blood ◽

Interaction Analysis ◽

Animal Experiments ◽

Interaction Network ◽

Enrichment Analysis ◽

Hub Genes ◽

Hub Gene ◽

Protein Protein Interaction

Objective The aim of this study was to identify and validate ferroptosis-related markers in ulcerative colitis (UC) to explore new directions for UC diagnosis and treatment. Methods We screened UC chips and ferroptosis-related genes from the Gene Expression Omnibus (GEO), FerrDb, and GeneCards databases. The differentially expressed genes (DEGs) and ferroptosis-related DEGs between the UC group and normal controls were analyzed using bioinformatics methods. Enrichment analysis, protein–protein interaction analysis, and hub genes were screened. Peripheral blood chip and animal experiments were used to validate the ferroptosis-related hub genes. Finally, hub gene–transcription factor, hub gene–microRNA (miRNA), and hub gene–drug interaction networks were constructed. Results Overall, 26 ferroptosis-related DEGs were identified that were significantly enriched in energy pathways and metabolism. We identified ten ferroptosis-related hub genes from the protein–protein interaction network: IL6, PTGS2, HIF1A, CD44, MUC1, CAV1, NOS2, CXCL2, SCD, and ACSL4. In the peripheral blood chip GSE94648, CD44 and MUC1 were upregulated, which was consistent with the expression trend in GSE75214. Animal experiments showed that CD44 expression was significantly increased in the colon. Conclusions Our findings indicate that CD44 and MUC1 may be ferroptosis-related markers in UC.

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MicroRNA expression analysis for identification of biomarkers in inflammatory bowel disease subtypes

10.21203/rs.3.rs-27227/v2 ◽

2020 ◽

Author(s):

Manisha Mandal ◽

Shyamapada Mandal

Keyword(s):

Ribosome Biogenesis ◽

Target Genes ◽

Proteasomal Degradation ◽

Differentially Expressed ◽

Hub Genes ◽

Hub Gene ◽

Protein Protein Interaction ◽

Bowel Diseases ◽

Inflammatory Bowel ◽

Protein Protein Interaction Networks

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An RB-1 loss of function gene signature as a tool to predict response to neoadjuvant chemotherapy plus anti-HER2 agents: a substudy of the NeoALTTO trial (BIG 1-06)

Therapeutic Advances in Medical Oncology ◽

10.1177/1758835919891608 ◽

2019 ◽

Vol 11 ◽

pp. 175883591989160 ◽

Cited By ~ 1

Author(s):

Emanuela Risi ◽

Chiara Biagioni ◽

Matteo Benelli ◽

Ilenia Migliaccio ◽

Amelia McCartney ◽

...

Keyword(s):

Neoadjuvant Chemotherapy ◽

Molecular Subtype ◽

Predictive Biomarkers ◽

Roc Curves ◽

Complete Response ◽

Gene Signature ◽

Breast Cancers ◽

Loss Of Function ◽

Sequencing Data ◽

Response To Neoadjuvant Chemotherapy

Background: Chemotherapy added to anti-HER2 agents (H) is the treatment of choice in patients with HER2+ early breast cancer. However, HER2+ tumours are clinically and biologically heterogeneous, and treatment response varies significantly by hormone receptor (HR) status and molecular subtype. Predictive biomarkers are needed in this context. This study assessed whether an RB-1 loss of function gene signature (RBsig) is predictive of response to neoadjuvant chemotherapy in combination with trastuzumab, lapatinib or both, within the NeoALTTO trial. Methods: We collected RNA-sequencing data from pretreatment biopsies derived from the NeoALTTO trial. RBsig expression was computed retrospectively and correlated with pathological complete response (pCR) using receiver-operating characteristic (ROC) curves. The RBsig was dichotomised as High/Low in correspondence to the 25th percentile. Reported p values resulted from Fisher’s exact test. Results: Of 455 NeoALTTO patients, 244 were eligible for this substudy (HR+ n = 129; HR− n = 115). Overall, pCR rate was significantly higher in patients with RBsig High tumours than those with RBsig Low (35% versus 18% respectively; p = 0.01). The area under the ROC curve (AUC) was 0.60 (95% CI 0.52–0.67). A remarkably low pCR rate of 11% was seen in HR+/RBsig Low patients versus 28% in HR+/RBsig High. Conclusions: These results indicate RBsig may add valuable information to HER2 and HR expression, which may in turn inform treatment choices. HR+/HER2+/RBsig Low breast cancers exhibited the poorest pathological response following chemotherapy plus H. Accordingly, in such patients, endocrine therapy in combination with H and, possibly, a CDK4/6 inhibitor, may potentially prove to be a more effective treatment.

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CD86 Molecule Might Be a Novel Immune-Related Prognostic Biomarker for Patients With Bladder Cancer by Bioinformatics and Experimental Assays

Frontiers in Oncology ◽

10.3389/fonc.2021.679851 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xin Yan ◽

Guo-Wei Du ◽

Zhao Chen ◽

Tong-Zu Liu ◽

Sheng Li

Keyword(s):

Bladder Cancer ◽

Prognostic Biomarker ◽

Gene Identification ◽

Clinical Feature ◽

Hub Genes ◽

High Association ◽

Hub Gene ◽

Protein Protein Interaction ◽

Novel Target ◽

Immune Related Genes

As one of the most common malignancies in the urinary system, bladder cancer (BC) occupies a high mortality and recurrence rate. BC carries an ominous prognosis. Thus, we aimed to identify a novel immune-related prognostic biomarker and therapeutic target for immunotherapy in the present study. We first constructed a co-expression network based on immune-related genes (IRGs). Two key modules showed high association with the clinical feature interested us most were further identified. Forty-five IRGs were screened out and regarded as hub genes in the co-expression network. We further constructed a protein-protein interaction (PPI) network, and five independent methods were used for hub gene identification. Three hub genes were identified in the present study. CD86 molecule (CD86) was screened out by performing overall survival (OS) analysis. Subsequent analyses by using some bioinformatics and experimental assays confirmed that CD86 was an immune-related prognostic biomarker, which might be a novel target for immunotherapy in BC. A small molecule drug named suloctidil was also identified, which showed potential for BC treatment.

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Identification of a Six Gene Prognosis Signature for Papillary Thyroid Cancer Using Multi-Omics Methods and Bioinformatics Analysis

Frontiers in Oncology ◽

10.3389/fonc.2021.624421 ◽

2021 ◽

Vol 11 ◽

Author(s):

He Ren ◽

Xin Liu ◽

Fuxin Li ◽

Xianghui He ◽

Na Zhao

Keyword(s):

Thyroid Cancer ◽

Immune Surveillance ◽

Interaction Network ◽

Disease Recurrence ◽

Papillary Thyroid ◽

Hub Genes ◽

Hub Gene ◽

Protein Protein Interaction ◽

Tcga Dataset ◽

Microarray Datasets

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer. PTC is typically curable with an excellent survival rate; however, some patients experience disease recurrence or death. This study aimed to discover potential key genes and signaling pathways of PTC, which could provide new insights for thyroid lesions. Four GEO microarray datasets were integrated to screen for candidate genes involved in PTC progression. A total of 164 upregulated and 168 downregulated differentially expressed genes (DEGs) were screened. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes were used in pathway enrichment analyses for DEGs. A protein-protein interaction network was then built and analyzed utilizing STRING and Cytoscape, followed by the identification of 13 hub genes by cytoHubba. CDH3, CTGF, CYR61, OGN, FGF13, and CHRDL1 were selected through survival analyses. Furthermore, immune infiltration, mutations and methylation analysis indicated that these six hub genes played vital roles in immune surveillance and tumor progression. ROC and K-M plots showed that these genes had good prognostic values for PTC which was validated by TCGA dataset. Finally, GSEA for a single hub gene revealed that each candidate hub gene had close associations with PTC development. These findings provided new insights into PTC pathogenesis and identified six candidate gene prognosis signature for PTC.

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