scholarly journals CYP1B1-AS1 Is a Novel Biomarker in Glioblastoma by Comprehensive Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Tao Ye ◽  
Lan-lan Li ◽  
Xue-mei Peng ◽  
Qin Li
Keyword(s):  
Mutual Effect ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Molecular Biomarker ◽  
Kaplan Meier ◽  
Cancer Types ◽  
Signal Path ◽  
Tumor Types ◽  
Spearman’S Correlation

Objective. Growing evidence shows that enhancer RNAs (eRNAs) are pivotal for tumor progression. In this research, our team aimed to identify the survival-related eRNAs and further explore their potential function in glioblastoma (GBM). Methods. RNA-sequencing data in 31 tumor types were acquired from TCGA datasets. The survival-related eRNAs were identified by the use of Kaplan-Meier survival analyses and Spearman’s correlation analyses. KEGG pathway enrichment analysis was completed to investigate the underlying signal paths of the critical eRNA. Pancancer assays were applied to explore the association between CYP1B1-AS1 and CYP1B1. Results. We identified 74 survival-related eRNAs and focused on CYP1B1-AS1 which displayed the greatest cor value. CYP1B1 was identified as a regulatory target of CYP1B1-AS1. KEGG analyses suggested that CYP1B1-AS1 might play an essential role through CK-CKR mutual effect, complement and coagulation cascades, TNF signal path, and JAK-STAT signal path. The pancancer verification outcomes revealed that CYP1B1-AS1 was related to survival in 4 cancers, i.e., LIHC, KIRP, KICH, and KIRC. Association was discovered between CYP1B1-AS1 and the targeted gene, CYP1B1, in 29 cancer types. Conclusion. The outcomes herein provided the first evidence that overexpression of CYP1B1-AS1 might be a potential molecular biomarker for predicting the prognosis of patients with GBM.

scholarly journals Blood Transcriptome Profiling Reveals Diet-Induced Changes in Metabolic Pathway Gene Expression

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 938-938
Author(s):  
Jaapna Dhillon ◽  
Jose Godoy-Lugo ◽  
Rudy Ortiz
Keyword(s):  
Gene Expression ◽  
Young Adults ◽  
Signal Transduction Pathway ◽  
Enrichment Analysis ◽  
Immunoglobulin Superfamily ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
P Values ◽  
Pathway Gene ◽  
Blood Transcriptome

Abstract Objectives This study explored the effects of diet-induced (almonds vs. crackers) changes on blood transcriptome profiles of young adults. Methods Young adults (age: 18–22 years) were randomly assigned to consume either almonds (2 oz./d, n = 13) or an isocaloric control snack of graham crackers (325 kcal/d, n = 10) daily for 4 weeks. Blood samples were collected at baseline and 4 weeks after intervention. Total leukocyte RNA was extracted and sequenced. Gene expression profiling was carried out using a 3′ Tag-RNA-Seq protocol. Barcoded sequencing libraries were prepared using the QuantSeq FWD kit for multiplexed sequencing. Data were preprocessed, STAR aligned, and count tables generated using the QuantSeq FWD-UMI pipeline. Differential expression (DE) analysis was conducted on the time x diet model using the limma-voom packages in R. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the DE p-values was conducted using the Wilcoxon rank-sum test in R. P-values were adjusted for false discovery rate correction (FDR). Results Out of 13,018 filtered genes, 69 were differentially expressed (FDR < 0.1). Glutamic-oxaloacetic transaminase 2 (GOT2), diacylglycerol kinase alpha (DGKA), and glutaryl-CoA dehydrogenase (GCDH) genes were upregulated with almond consumption. GOT2 plays a role in amino acid metabolism and the urea and tricarboxylic acid cycles, DGKA is involved in lipid metabolism, and GCDH is involved in lysine degradation and tryptophan metabolism. Cracker consumption resulted in greater upregulation of TGF-beta activated kinase 1 gene (MAP3K7) binding protein 3 (TAB3) gene which is involved in the NF-kappaB signal transduction pathway and a greater downregulation in the immunoglobulin superfamily member 8 (IGSF8) gene. Enrichment analyses indicate gene annotations to 341 KEGG pathways. Thermogeneic and ribosomal pathways were significantly enriched (FDR < 0.1). Pathways related to oxidative phosphorylation, sphingolipid signaling, and tryptophan, propanoate, and starch and sucrose metabolism were also differentially enriched (P < 0.05, FDR < 0.3). Conclusions These findings indicate that diet (almond vs cracker) potentially alters metabolism through changes in gene transcription. The implications of these findings and associations with health and disease outcomes need to be investigated further. Funding Sources NIH

scholarly journals Identification of Potential Prognostic Competing Triplets in High-Grade Serous Ovarian Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jian Zhao ◽  
Xiaofeng Song ◽  
Tianyi Xu ◽  
Qichang Yang ◽  
Jingjing Liu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
P53 Signaling ◽  
Oocyte Meiosis ◽  
The Difference ◽  
Division Cell ◽  
The Impact

Increasing lncRNA-associated competing triplets were found to play important roles in cancers. With the accumulation of high-throughput sequencing data in public databases, the size of available tumor samples is becoming larger and larger, which introduces new challenges to identify competing triplets. Here, we developed a novel method, called LncMiM, to detect the lncRNA–miRNA–mRNA competing triplets in ovarian cancer with tumor samples from the TCGA database. In LncMiM, non-linear correlation analysis is used to cover the problem of weak correlations between miRNA–target pairs, which is mainly due to the difference in the magnitude of the expression level. In addition, besides the miRNA, the impact of lncRNA and mRNA on the interactions in triplets is also considered to improve the identification sensitivity of LncMiM without reducing its accuracy. By using LncMiM, a total of 847 lncRNA-associated competing triplets were found. All the competing triplets form a miRNA–lncRNA pair centered regulatory network, in which ZFAS1, SNHG29, GAS5, AC112491.1, and AC099850.4 are the top five lncRNAs with most connections. The results of biological process and KEGG pathway enrichment analysis indicates that the competing triplets are mainly associated with cell division, cell proliferation, cell cycle, oocyte meiosis, oxidative phosphorylation, ribosome, and p53 signaling pathway. Through survival analysis, 107 potential prognostic biomarkers are found in the competing triplets, including FGD5-AS1, HCP5, HMGN4, TACC3, and so on. LncMiM is available at https://github.com/xiaofengsong/LncMiM.

scholarly journals Expression Profiles of tRNA-Derived Small RNAs and Their Potential Roles in Primary Nasopharyngeal Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Zhaoyi Lu ◽  
Kai Su ◽  
Xiaomin Wang ◽  
Mingjie Zhang ◽  
Shiyin Ma ◽  
...  
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Small Rnas ◽  
Target Genes ◽  
Expression Profiles ◽  
Target Prediction ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Diagnostic Efficiency ◽  
Sequencing Data ◽  
Qrt Pcr

Introduction: tRNA-derived small RNAs (tsRNAs), a class of small non-coding RNAs, are divided into two categories: tRNA-related fragments (tRFs) and tRNA halves (tiRNAs). Abnormal expression of tsRNAs has been found in diverse cancers, which indicates that further understanding of the function of tsRNAs will help identify new biomarkers and potential therapeutic targets. Until now, the underlying roles of tsRNAs in primary nasopharyngeal carcinoma (NPC) are still unknown.Methods: tRF and tiRNA sequencing was performed on four pairs of NPC tissues and healthy controls. Thirty pairs of NPC samples were used for quantitative real-time polymerase chain reaction (qRT-PCR) verification, and the ROC analysis was used to evaluate the diagnostic efficiency initially. Target prediction and bioinformatics analysis of validated tRFs and tiRNAs were conducted to explore the mechanisms of tsRNAs in NPC’s pathogenesis.Results: A total of 158 differentially expressed tRFs and tiRNAs were identified, of which 88 are upregulated and 70 are downregulated in NPC. Three validated tRFs in the results of qRT-PCR were consistent with the sequencing data: two upregulations (tRF-1:28-Val-CAC-2 and tRF-1:24-Ser-CGA-1-M3) and one downregulation (tRF-55:76-Arg-ACG-1-M2). The GO and KEGG pathway enrichment analysis showed that the potential target genes of validated tRFs are widely enriched in cancer pathways. The related modules may play an essential role in the pathogenesis of NPC.Conclusions: The tsRNAs may become a novel class of biological diagnostic indicators and possible targets for NPC.

scholarly journals A molecular portrait of microsatellite instability across multiple cancers

2016 ◽  
Author(s):  
Isidro Cortes-Ciriano ◽  
Sejoon Lee ◽  
Woong-Yang Park ◽  
Tae-Min Kim ◽  
Peter J. Park
Keyword(s):  
Microsatellite Instability ◽  
High Sensitivity ◽  
Tumor Type ◽  
Sequencing Data ◽  
Molecular Fingerprints ◽  
Dna Mismatch ◽  
Oncogenic Pathways ◽  
Cancer Types ◽  
Tumor Types ◽  
Pan Cancer

ABSTRACTMicrosatellite instability (MSI) refers to the hypermutability of the cancer genome due to impaired DNA mismatch repair. Although MSI has been studied for decades, the large amount of sequencing data now available allows us to examine the molecular fingerprints of MSI in greater detail. Here, we analyze ~8000 exome and ~1000 whole-genome pairs across 23 cancer types. Our pan-cancer analysis reveals that the prevalence of MSI events is highly variable within and across tumor types including some in which MSI is not typically examined. We also identify genes in DNA repair and oncogenic pathways recurrently subject to MSI and uncover non-coding loci that frequently display MSI events. Finally, we propose an exomebased predictive model for the MSI phenotype that achieves high sensitivity and specificity. These results advance our understanding of the genomic drivers and consequences of MSI, and a comprehensive catalog of tumor-type specific MSI loci we have generated enables efficient panel-based MSI testing to identify patients who are likely to benefit from immunotherapy.

scholarly journals Mining TCGA database for gene expression in ovarian serous cystadenocarcinoma microenvironment

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11375
Author(s):  
Youzheng Xu ◽  
Yixin Xu ◽  
Chun Wang ◽  
Baoguo Xia ◽  
Qingling Mu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Strong Predictor ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Poor Overall Survival ◽  
Protein Protein Interaction ◽  
Serous Cystadenocarcinoma ◽  
Kaplan Meier ◽  
Limma Package

Background Ovarian cancer is one of the leading causes of female deaths worldwide. Ovarian serous cystadenocarcinoma occupies about 90% of it. Effective and accurate biomarkers for diagnosis, outcome prediction and personalized treatment are needed urgently Methods Gene expression profile for OSC patients was obtained from the TCGA database. The ESTIMATE algorithm was used to calculate immune scores and stromal scores of expression data of ovarian serous cystadenocarcinoma samples. Survival results between high and low groups of immune and stromal score were compared and differentially expressed genes (DEGs) were screened out by limma package. The Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the protein-protein interaction (PPI) network analysis were performed with the g:Profiler database, the Cytoscape and Search Tool for the Retrieval of Interacting Genes (STRING-DB). Survival results between high and low immune and stromal score groups were compared. Kaplan-Meier plots based on TCGA follow up information were generated to evaluate patients’ overall survival. Results Eighty-six upregulated DEGs and one downregulated DEG were identified. Three modules, which included 49 nodes were chosen as important networks. Seven DEGs (VSIG4, TGFBI, DCN, F13A1, ALOX5AP, GPX3, SFRP4) were considered to be correlated with poor overall survival. Conclusion Seven DEGs (VSIG4, TGFBI, DCN, F13A1, ALOX5AP, GPX3, SFRP4) were correlated with poor overall survival in our study. This new set of genes can become strong predictor of survival, individually or combined. Further investigation of these genes is needed to validate the conclusion to provide novel understanding of tumor microenvironment with ovarian serous cystadenocarcinoma prognosis and treatment.

scholarly journals Construction and comprehensive analysis of a ceRNA network to reveal potential prognostic biomarkers for lung adenocarcinoma

2021 ◽  
Author(s):  
Lei Gao ◽  
Ling Zhang
Keyword(s):  
Lung Adenocarcinoma ◽  
Drug Targets ◽  
Enrichment Analysis ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Functional Roles ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Underlying Mechanisms ◽  
Patient Prognosis

Abstract Background More and more studies have proven that circular RNAs (circRNAs) play vital roles in cancer development via sponging miRNAs. However, the expression pattern of competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD) remains largely unclear. The current study explored functional roles and the regulatory mechanisms of circRNA as ceRNAs in LUAD and their potential impact on LUAD patient prognosis. Methods In this study, we systematically screened differential expression circRNAs (DEcircRNAs), miRNAs (DEmiRNAs) and mRNAs (DEGs) associated with LUAD. Then, DEcircRNAs, DEmiRNAs and DEGs were selected to construct a circRNA–miRNA–mRNA prognosis-related regulatory network based on interaction information from the ENCORI database. Subsequently, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the genes in the network to predict the potential underlying mechanisms and functions of circRNAs in LUAD. In addition, Kaplan–Meier survival analysis was performed to evaluate clinical outcomes of LUAD patients, and drug sensitivity analysis was used to screen potential biomarkers for drug treatment of patients with LUAD. Results As a result, ten circRNAs were aberrantly expressed in LUAD tissues. The ceRNA network was built, which included 3 DEcircRNAs, 6 DEmiRNAs and 157 DEGs. The DEGs in the ceRNA network of hsa_circ_0049271 enriched in biological processes of cell proliferation and the Jak-STAT signaling pathway. We also detected 7 mRNAs in the ceRNA network of hsa_circ_0049271 that were significantly associated with the overall survival of LUAD patients (P < 0.05). Importantly, four genes (PDGFB, CCND2, CTF1, IL7R) identified were strongly associated with STAT3 activation and drugs sensitivity in GDSC. Conclusions In summary, a ceRNA network was successfully constructed, which including one circRNA, two miRNAs, and seven mRNAs. Seven mRNAs (PDGFB, TNFRSF19, CCND2, CTF1, IL11RA, IL7R and MAOA) were remarkably associated with the prognosis of LUAD patients. Among seven mRNA species, four genes (PDGFB, CCND2, CTF1, and IL7R) could be considered as drug targets in LUAD. Our research will provide new insights into the prognosis-related ceRNA network in LUAD.

scholarly journals Comparative Analysis between Wild and Cultivated Cucumbers Reveals Transcriptional Changes during Domestication Process

Plants ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 63
Author(s):  
Eslam M. Abdel-Salam ◽  
Mohammad Faisal ◽  
Abdulrahman A. Alatar ◽  
Quaiser Saquib ◽  
Hend A. Alwathnani
Keyword(s):  
Genetic Research ◽  
Enrichment Analysis ◽  
Preliminary Evidence ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Secondary Products ◽  
Cucumis Sativus L ◽  
Transcriptional Changes ◽  
Domestication Process

The cultivated cucumber (Cucumis sativus L.) was reported to have been developed from a wild cucumber (Cucumis hystrix Chakrav.), nevertheless, these two organisms exhibit noteworthy differences. For example, the wild cucumber is known for its high resistance to different biotic and abiotic stresses. Moreover, the leaves and fruits of the wild cucumber have a bitter taste compared to the cultivated cucumber. These differences could be attributed mainly to the differences in gene expression levels. In the present investigation, we analyzed the RNA-sequencing data to show the differentially expressed genes (DEGs) between the wild and cultivated cucumbers. The identified DEGs were further utilized for Gene Ontology (GO) and pathway enrichment analysis and for identification of transcription factors and regulators. In the results, several enriched GO terms in the biological process, cellular component, and molecular functions categories were identified and various enriched pathways, especially the biosynthesis pathways of secondary products were recognized. Plant-specific transcription factor families were differentially expressed between the wild and cultivated cucumbers. The results obtained provide preliminary evidence for the transcriptional differences between the wild and cultivated cucumbers which developed during the domestication process as a result of natural and/or artificial selection, and they formulate the basis for future genetic research and improvement of the cultivated cucumber.

scholarly journals Identification of prognostic factors for intrahepatic cholangiocarcinoma based on long non-coding RNAs-associated ceRNA network

2020 ◽  
Author(s):  
Zhichen Kang ◽  
Lixin Guo ◽  
Zhuo Zhu ◽  
Rongfeng Qu
Keyword(s):  
Prognostic Factors ◽  
Intrahepatic Cholangiocarcinoma ◽  
Messenger Rna ◽  
Transcriptome Sequencing ◽  
Tumor Biology ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Cerna Network ◽  
Non Coding Rnas

Abstract Background Accumulating evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in tumor biology. However, the roles of cancer long non coding RNAs (lncRNAs) in lncRNA-related ceRNA network of intrahepatic cholangiocarcinoma (ICC) remain enigmatic. The current study aims to identify prognostic factors in the lncRNA-related ceRNA network of ICC. Methods The transcriptome sequencing data of the lncRNAs, messenger RNA (mRNA) and microRNA (miR) were downloaded from SRA, and TCGA database respectively. Differentially expressed lncRNAs (DElncRNAs), DEmiRs and DEmRNAs were identified and adopted to construct lncRNA-miR-mRNA ceRNA network. ICC-associated DEmRNAs were adopted to construct the PPI network. The expression of the top 6 genes in the hub module was validated in mRNA transcriptome sequencing data and ICC-related gene expression dataset GSE45001, followed by GO and KEGG pathway enrichment analysis. The potential function of genes in hub module in the ceRNA network was finally subjected to GSEA. Results Sixty coexpression DEmRNAs were identified in the ceRNA network. The 6 top genes in the hub module consists of FOS, HGF, IGF2, FOXO1, NTF3 (downregulated), and IGF1R (upregulated) in ICC tissues compared to normal adjacent tissues, followed by the successful construction of lncRNA-miR-hub network with 86 ceRNA modules. FOS, IGF2 or IGF1R might regulate the development of ICC by targeting “N-glycan biosynthesis”, “α-linolenic acid metabolism” or “type II diabetes” pathways respectively. Conclusion These results show FOS, IGF2 and IGF1R serve as prognostic factors of ICC patients.

scholarly journals Identification and comparison of circular RNAs in preeclampsia

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11299
Author(s):  
Zepeng Ping ◽  
Ling Ai ◽  
Huaxiang Shen ◽  
Xing Zhang ◽  
Huling Jiang ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Gestational Hypertension ◽  
Interaction Analysis ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Mortality And Morbidity ◽  
Specific Syndrome

Background Preeclampsia (PE) is a pregnancy-specific syndrome, belongs to the gestational hypertension diseases category and is considered among the causes of maternal and perinatal mortality and morbidity. However, the pathogenesis of PE is still vague. Methods In the present study, the circular RNA (circRNA) expression patterns of normal pregnant women and PE patients were investigated using whole RNA sequencing. Results A total of 151 differential expressed circRNAs were identified including 121 upregulated and 30 downregulated ones. Functional and pathway enrichment analysis was conducted on the differentially expressed circRNAs using Gene Ontology and KEGG databases. The results of this analysis indicated that several crucial biological processes and pathways were enriched in PE patients. circRNA–microRNA (miRNA) interaction analysis indicated that the reported differentially expresse circRNAs may be associated with some regulatory functions through miRNAs in PE patients. Two ceRNAs networks were constructed according to the targeting relationship between circRNAs/miRNAs and miRNAs/mRNAs. One sub-network contained one upregulated circRNA, four downregulated miRNAs and five upregulated mRNAs, and another sub-network contained 10 downregulated circRNAs, 21 upregulated miRNAs and 15 downregulated mRNAs. Conclusion CircRNA expression patterns have been investigated and this analysis revealed their potential regulatory mechanisms in PE patients. We constructed the ceRNAs (competing endogenous RNA) to reveal the potential molecular roles of dysregulated circRNAs in the PE patients using RNA sequencing data. circRNA_13301 was the only one upregulated circRNA in ceRNA being targeted by four miRNAs.

scholarly journals TumorFusions: an integrative resource for reporting cancer-associated transcript fusions in 33 tumor types

2017 ◽  
Author(s):  
Xin Hu ◽  
Qianghu Wang ◽  
Floris Barthel ◽  
Ming Tang ◽  
Samirkumar Amin ◽  
...  
Keyword(s):  
The Cancer Genome Atlas ◽  
Whole Genome Sequencing Data ◽  
Fusion Genes ◽  
Sequencing Data ◽  
Structural Variations ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tumor Types ◽  
Fusion Detection ◽  
Genome Atlas

Fusion genes, particularly those involving kinases, have been demonstrated as drivers and are frequent therapeutic targets in cancer1. Here, we describe our results on detecting transcript fusions across 33 cancer types from The Cancer Genome Atlas (TCGA), totaling 9,966 cancer samples and 648 normal samples2. Preprocessing, including read alignment to both genome and transcriptome, and fusion detection were carried out using a uniform pipeline3. To validate the resultant fusions, we also called somatic structural variations for 561 cancers from whole genome sequencing data. A summary of the data used in this study is provided in Table S1. Our results can be accessed per our portal at http://www.tumorfusions.org.

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