scholarly journals 12 Survival-related differentially expressed genes based on the TARGET-osteosarcoma database

2021 ◽  
pp. 153537022110074
Author(s):  
Emel Rothzerg ◽  
Jiake Xu ◽  
David Wood ◽  
Sulev Kõks
Keyword(s):  
Differentially Expressed Genes ◽  
Clinical Information ◽  
Differentially Expressed ◽  
P Value ◽  
Sequencing Data ◽  
Gene Expressions ◽  
Expression Of Genes ◽  
Kaplan Meier ◽  
And Gender ◽  
Upregulated Genes

The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) project aims to determine molecular changes that drive childhood cancers, including osteosarcoma. The main purpose of the program is to use the open-source database to develop novel, effective, and less toxic therapies. We downloaded TARGET-OS RNA-Sequencing data through R studio and merged the mRNA expression of genes with clinical information (vital status, survival time and gender). Further, we analyzed differential gene expressions between dead and alive patients based on TARGET-OS project. By this study, we found 5758 differentially expressed genes between deceased and alive patients with a false discovery rate below 0.05; 4469 genes were upregulated in deceased patients compared to alive, whereas 1289 genes were downregulated. The survival-related genes were obtained using Kaplan–Meier survival analysis and Cox univariate regression (KM < 0.05 and Cox P-value < 0.05). Out of 5758 differentially expressed genes, only 217 have been associated with overall survival. Eight survival-related downregulated genes ( ERCC4, CLUAP1, CTNNBIP1, GCA, RAB40C, SIRPA, USP11, and TCN2) and four survival-related upregulated genes ( MUC1, COL13A1, JAG2 and KAZALD1) were selected for further analysis as potential independent prognostic candidate genes. This study may help to discover novel prognostic markers and potential therapeutic targets for osteosarcoma.

scholarly journals Transcriptomics Analysis of Lens from Patients with Posterior Subcapsular Congenital Cataract

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1904
Author(s):  
Xiaolei Lin ◽  
Hongzhe Li ◽  
Tianke Yang ◽  
Xin Liu ◽  
Fan Fan ◽  
...  
Keyword(s):  
Epithelial Cells ◽  
Differentially Expressed Genes ◽  
Congenital Cataract ◽  
Fold Change ◽  
Differentially Expressed ◽  
P Value ◽  
Sequencing Analysis ◽  
Log2 Fold Change ◽  
Upregulated Genes ◽  
Cataract Patients

To gain insight into the aetiology of posterior subcapsular congenital cataract from the perspective of transcriptional changes, we conducted an mRNA sequencing analysis of the lenses in posterior subcapsular congenital cataract patients and in normal children. There were 1,533 differentially expressed genes from 19,072 genes in the lens epithelial cells of the posterior subcapsular congenital cataract patients compared to in the normal controls at a cut-off criteria of |log2 fold change| of >1 and a p-value of <0.05, including 847 downregulated genes and 686 upregulated genes. To further narrow down the DEGs, we utilised the stricter criteria of |log2 fold change| of >1 and an FDR value of <0.05, and we identified 551 DEGs, including 97 upregulated genes and 454 downregulated genes. This study also identified 1,263 differentially expressed genes of the 18,755 genes in lens cortex and nuclear fibres, including 646 downregulated genes and 617 upregulated genes. The downregulated genes in epithelial cells were significantly enriched in the structural constituent of lenses, lens development and lens fibre cell differentiation. After filtering the DEGs using the databases iSyTE and Cat-Map, several high-priority candidate genes related to posterior subcapsular congenital cataract such as GRIFIN, HTRA1 and DAPL1 were identified. The findings of our study may provide a deeper understanding of the mechanisms of posterior subcapsular congenital cataract and help in the prevention and treatment of this disease.

scholarly journals Genes related to maintenance of autophagy and successful aging

2018 ◽  
Vol 76 (12) ◽  
pp. 831-839
Author(s):  
Carolina Fioroto Chaves ◽  
Diego Robles Mazzotti ◽  
Maysa Seabra Cendoroglo ◽  
Luiz Roberto Ramos ◽  
Sergio Tufik ◽  
...  
Keyword(s):  
Cell Survival ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
Peripheral Blood ◽  
Successful Aging ◽  
Oldest Old ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Expression Of Genes ◽  
Transcriptional Process

ABSTRACT Considering aging as a phenomenon in which there is a decline in essential processes for cell survival, we investigated the autophagic and proteasome pathways in three different groups: young, older and oldest old male adults. The expression profile of autophagic pathway-related genes was carried out in peripheral blood, and the proteasome quantification was performed in plasma. No significant changes were found in plasma proteasome concentrations or in correlations between proteasome concentrations and ages. However, some autophagy- and/or apoptosis-related genes were differentially expressed. In addition, the network and enrichment analysis showed an interaction between four of the five differentially expressed genes and an association of these genes with the transcriptional process. Considering that the oldest old individuals maintained both the expression of genes linked to the autophagic machinery, and the proteasome levels, when compared with the older group, we concluded that these factors could be considered crucial for successful aging.

scholarly journals Efficiency Analysis of Competing Tests for Finding Differentially Expressed Genes in Lung Adenocarcinoma

2008 ◽  
Vol 6 ◽  
pp. CIN.S791 ◽  
Author(s):  
Rick Jordan ◽  
Satish Patel ◽  
Hai Hu ◽  
James Lyons-Weiler
Keyword(s):  
Lung Adenocarcinoma ◽  
Differentially Expressed Genes ◽  
Efficiency Analysis ◽  
Differentially Expressed ◽  
Classification Error ◽  
Sample Classification ◽  
Expression Of Genes ◽  
Using Data ◽  
Intuitive Method ◽  
Transformation Methods

In this study, we introduce and use Efficiency Analysis to compare differences in the apparent internal and external consistency of competing normalization methods and tests for identifying differentially expressed genes. Using publicly available data, two lung adenocarcinoma datasets were analyzed using caGEDA ( http://www.bioinformatics2.pitt.edu/GE2/GEDA.html ) to measure the degree of differential expression of genes existing between two populations. The datasets were randomly split into at least two subsets, each analyzed for differentially expressed genes between the two sample groups, and the gene lists compared for overlapping genes. Efficiency Analysis is an intuitive method that compares the differences in the percentage of overlap of genes from two or more data subsets, found by the same test over a range of testing methods. Tests that yield consistent gene lists across independently analyzed splits are preferred to those that yield less consistent inferences. For example, a method that exhibits 50% overlap in the 100 top genes from two studies should be preferred to a method that exhibits 5% overlap in the top 100 genes. The same procedure was performed using all available normalization and transformation methods that are available through caGEDA. The ‘best’ test was then further evaluated using internal cross-validation to estimate generalizable sample classification errors using a Naïve Bayes classification algorithm. A novel test, termed D1 (a derivative of the J5 test) was found to be the most consistent, and to exhibit the lowest overall classification error, and highest sensitivity and specificity. The D1 test relaxes the assumption that few genes are differentially expressed. Efficiency Analysis can be misleading if the tests exhibit a bias in any particular dimension (e.g. expression intensity); we therefore explored intensity-scaled and segmented J5 tests using data in which all genes are scaled to share the same intensity distribution range. Efficiency Analysis correctly predicted the ‘best’ test and normalization method using the Beer dataset and also performed well with the Bhattacharjee dataset based on both efficiency and classification accuracy criteria.

scholarly journals Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis (TRPCA) Method

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yue Hu ◽  
Jin-Xing Liu ◽  
Ying-Lian Gao ◽  
Sheng-Jun Li ◽  
Juan Wang
Keyword(s):  
Principal Component Analysis ◽  
Differentially Expressed Genes ◽  
Principal Component ◽  
Component Analysis ◽  
Differentially Expressed ◽  
Low Rank ◽  
Cancer Gene ◽  
Sequencing Data ◽  
Robust Principal Component Analysis ◽  
The Matrix

In the big data era, sequencing technology has produced a large number of biological sequencing data. Different views of the cancer genome data provide sufficient complementary information to explore genetic activity. The identification of differentially expressed genes from multiview cancer gene data is of great importance in cancer diagnosis and treatment. In this paper, we propose a novel method for identifying differentially expressed genes based on tensor robust principal component analysis (TRPCA), which extends the matrix method to the processing of multiway data. To identify differentially expressed genes, the plan is carried out as follows. First, multiview data containing cancer gene expression data from different sources are prepared. Second, the original tensor is decomposed into a sum of a low-rank tensor and a sparse tensor using TRPCA. Third, the differentially expressed genes are considered to be sparse perturbed signals and then identified based on the sparse tensor. Fourth, the differentially expressed genes are evaluated using Gene Ontology and Gene Cards tools. The validity of the TRPCA method was tested using two sets of multiview data. The experimental results showed that our method is superior to the representative methods in efficiency and accuracy aspects.

Potential genes and pathways along with immune cells infiltration in the progression of atherosclerosis identified via microarray gene expression dataset re-analysis

Vascular ◽  
2020 ◽  
Vol 28 (5) ◽  
pp. 643-654 ◽  
Author(s):  
Jing Xu ◽  
Yuejin Yang
Keyword(s):  
Differentially Expressed Genes ◽  
Immune Cells ◽  
Interaction Network ◽  
Wilcoxon Test ◽  
Differentially Expressed ◽  
P Value ◽  
The Novel ◽  
Microarray Gene Expression ◽  
Progression Of Atherosclerosis ◽  
Geo Database

Objective Atherosclerosis is a chronic inflammatory process characterized by the accumulation and formation of lipid-rich plaques within the layers of the arterial wall. Although numerous studies have reported the underlying pathogenesis, no data-based studies have been conducted to analyze the potential genes and immune cells infiltration in the different stages of atherosclerosis via bioinformatics analysis. Methods In this study, we downloaded GSE100927 and GSE28829 from NCBI-GEO database. Gene ontology and pathway enrichment were performed via the DAVID database. The protein interaction network was constructed via STRING. Enriched hub genes were analyzed by the Cytoscape software. The evaluation of the infiltrating immune cells in the dataset samples was performed by the CIBERSORT algorithm. Results We identified 114 common upregulated differentially expressed genes and 22 common downregulated differentially expressed genes. (adjust p value < 0.01 and log FC ≥ 1). A cluster of 10 genes including CYBA, SLC11A1, FCER1G, ITGAM, ITGB2, CD53, ITGAX, VAMP8, CLEC5A, and CD300A were found to be significant. Through the deconvolution algorithm CIBERSORT, we analyzed the significant alteration of immune cells infiltration in the progression of atherosclerosis with the threshold of the Wilcoxon test at p value <0.05. Conclusions These results may reveal the underlying correlations between genes and immune cells in atherosclerosis, which enable us to investigate the novel insights for the development of treatments and drugs.

scholarly journals Integrative molecular analysis of metastatic hepatocellular carcinoma

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Dongfang Wang ◽  
Yanjing Zhu ◽  
Jing Tang ◽  
Qiuyu Lian ◽  
Guijuan Luo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Differentially Expressed Genes ◽  
Primary Tumor ◽  
Integrative Analysis ◽  
Differentially Expressed ◽  
Focal Region ◽  
Differential Analysis ◽  
Gene Expressions ◽  
Molecular Alterations ◽  
Matched Primary Tumor

Abstract Background Hepatocellular carcinoma (HCC) is the major type of primary liver cancer. Intrahepatic metastasis, such as portal vein tumor thrombosis (PVTT), strongly indicates poor prognosis of HCC. But now, there are limited understandings of the molecular features and mechanisms of those metastatic HCCs. Methods To characterize the molecular alterations of the metastatic HCCs, we implemented an integrative analysis of the copy number variations (CNVs), DNA methylations and transcriptomes of matched adjacent normal, primary tumor and PVTT samples from 19 HCC patients. Results CNV analysis identified a frequently amplified focal region chr11q13.3 and a novel deletion peak chr19q13.41 containing three miRNAs. The integrative analysis with RNA-seq data suggests that CNVs and differential promoter methylations regulate distinct oncogenic processes. Then, we used individualized differential analysis to identify the differentially expressed genes between matched primary tumor and PVTT of each patient. Results show that 5 out of 19 studied patients acquire evidential progressive alterations of gene expressions (more than 1000 differentially expressed genes were identified in each patient). While, another subset of eight patients have nearly identical gene expressions between the corresponding matched primary tumor and PVTT. Twenty genes were found to be recurrently and progressively differentially expressed in multiple patients. These genes are mainly associated with focal adhesion, xenobiotics metabolism by cytochrome P450 and amino acid metabolism. For several differentially expressed genes in metabolic pathways, their expressions are significantly associated with overall survivals and vascular invasions of HCC patients. The following transwell assay experiments validate that they can regulate invasive phenotypes of HCC cells. Conclusions The metastatic HCCs with PVTTs have significant molecular alterations comparing with adjacent normal tissues. The recurrent alteration patterns are similar to several previously published general HCC cohorts, but usually with higher severity. By an individualized differential analysis strategy, the progressively differentially expressed genes between the primary tumor and PVTT were identified for each patient. A few patients aquire evidential progressive alterations of gene expressions. And, experiments show that several recurrently differentially expressed genes can strongly regulate HCC cell invasions.

scholarly journals Transcriptome profiling of posterior kidney of brown trout, Salmo trutta, during proliferative kidney disease

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Arun Sudhagar ◽  
Reinhard Ertl ◽  
Gokhlesh Kumar ◽  
Mansour El-Matbouli
Keyword(s):  
Immune System ◽  
Kidney Disease ◽  
Differentially Expressed Genes ◽  
Brown Trout ◽  
Salmo Trutta ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Proliferative Kidney Disease ◽  
Immune System Process ◽  
Upregulated Genes

Abstract Background Tetracapsuloides bryosalmonae is a myxozoan parasite which causes economically important and emerging proliferative kidney disease (PKD) in salmonids. Brown trout, Salmo trutta is a native fish species of Europe, which acts as asymptomatic carriers for T. bryosalmonae. There is only limited information on the molecular mechanism involved in the kidney of brown trout during T. bryosalmonae development. We employed RNA sequencing (RNA-seq) to investigate the global transcriptome changes in the posterior kidney of brown trout during T. bryosalmonae development. Methods Brown trout were exposed to the spores of T. bryosalmonae and posterior kidneys were collected from both exposed and unexposed control fish. cDNA libraries were prepared from the posterior kidney and sequenced. Bioinformatics analysis was performed using standard pipeline of quality control, reference mapping, differential expression analysis, gene ontology, and pathway analysis. Quantitative real time PCR was performed to validate the transcriptional regulation of differentially expressed genes, and their correlation with RNA-seq data was statistically analyzed. Results Transcriptome analysis identified 1169 differentially expressed genes in the posterior kidney of brown trout, out of which 864 genes (74%) were upregulated and 305 genes (26%) were downregulated. The upregulated genes were associated with the regulation of immune system process, vesicle-mediated transport, leucocyte activation, and transport, whereas the downregulated genes were associated with endopeptidase regulatory activity, phosphatidylcholine biosynthetic process, connective tissue development, and collagen catabolic process. Conclusion To our knowledge, this is the first RNA-seq based transcriptome study performed in the posterior kidney of brown trout during active T. bryosalmonae development. Most of the upregulated genes were associated with the immune system process, whereas the downregulated genes were associated with other metabolic functions. The findings of this study provide insights on the immune responses mounted by the brown trout on the developing parasite, and the host molecular machineries modulated by the parasite for its successful multiplication and release.

scholarly journals Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

2020 ◽  
Vol 9 (2) ◽  
pp. LMT30
Author(s):  
Chuanli Ren ◽  
Weixiu Sun ◽  
Xu Lian ◽  
Chongxu Han
Keyword(s):  
Lung Adenocarcinoma ◽  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Kaplan Meier ◽  
Key Genes ◽  
Core Genes

Aim: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). Materials & methods: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID. Results: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD. Conclusion: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

scholarly journals Bayesian Mixture Model Analysis for Detecting Differentially Expressed Genes

2008 ◽  
Vol 2008 ◽  
pp. 1-12 ◽  
Author(s):  
Zhenyu Jia ◽  
Shizhong Xu
Keyword(s):  
Mixture Model ◽  
Differentially Expressed Genes ◽  
Differential Expression Analysis ◽  
Differentially Expressed ◽  
Control Treatment ◽  
Microarray Gene Expression ◽  
Bayesian Mixture Model ◽  
Bayesian Mixture ◽  
Truncated Normal ◽  
Upregulated Genes

Control-treatment design is widely used in microarray gene expression experiments. The purpose of such a design is to detect genes that express differentially between the control and the treatment. Many statistical procedures have been developed to detect differentially expressed genes, but all have pros and cons and room is still open for improvement. In this study, we propose a Bayesian mixture model approach to classifying genes into one of three clusters, corresponding to clusters of downregulated, neutral, and upregulated genes, respectively. The Bayesian method is implemented via the Markov chain Monte Carlo (MCMC) algorithm. The cluster means of down- and upregulated genes are sampled from truncated normal distributions whereas the cluster mean of the neutral genes is set to zero. Using simulated data as well as data from a real microarray experiment, we demonstrate that the new method outperforms all methods commonly used in differential expression analysis.

Gene Expression Profiling of Hyperdiploid Multiple Reveal Complex Gene Dosage Effects and an mRNA Translation/Protein Synthesis Signature.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 1538-1538
Author(s):  
Wee-Joo Chng ◽  
Scott Van Wier ◽  
Gregory Ahmann ◽  
Tammy Price-Troska ◽  
Kim Henderson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Differentially Expressed Genes ◽  
Gene Dosage ◽  
Gene Copy Number ◽  
Mrna Translation ◽  
Differentially Expressed ◽  
Gene Copy ◽  
Gene Dosage Effect ◽  
Expression Of Genes

Abstract Hyperdiploid MM (H-MM), characterized by recurrent trisomies constitute about 50% of MM, yet very little is known about its pathogenesis and oncogenic mechanisms. Studies in leukemia and solid tumors have shown gene dosage effect of aneuploidy on gene expression. To determine the possible gene dosage effect and deregulated cellular program in H-MM we undertook a gene expression study of CD138-enriched plasma-cell RNA from 53 hyperdiploid and 37 non-hyperdiploid MM (NH-MM) patients using the Affymetrix U133A chip (Affymetrix, Santa Clara, CA). Gene expression data was analyzed using GeneSpring 7 (Agilent Technologies, Palo Alto, CA). Genes differentially expressed between H-MM and NH-MM were obtained by t-test (p&lt;0.01). The majority of the differentially expressed genes (57%) were under-expressed in H-MM. Genes located on the commonly trisomic chromosomes were mostly (but not always) over-expressed in H-MM and constitute 76% of over-expressed genes. Chromosome 1 contained the most differentially expressed genes (17%) followed by chromosome 12 (9%), and 19 (8%). To examine the relationship of gene copy number to gene expression, we examined the expression of genes on chromosomes 9 and 15 in subjects with 2 copies (15 normal control and 20 NH-MM) and 3 copies (12 H-MM) of each chromosome as detected by interphase FISH. We then derived a ratio of the mean expression of each gene on these chromosomes between patients with 3 copies and 2 copies of the chromosome. If a simple relationship exists between gene expression and gene copy number, one would expect the ratio of expression of most genes on these two chromosomes to be about 1.5 in H-MM compared to NH-MM. However, many genes have ratios either higher than 2 or lower than 0.5. Furthermore, when the heterogeneity of cells with underlying trisomies is taken into consideration by correcting the ratio for the number of cells with trisomies, the actual ratio is always lower than the expected ratio. When the expression of genes on a chromosome was compressed to a median value, this value was always higher in the trisomic chromosomes for H-MM compared to NH-MM. The data suggests that although gene dosage influence gene expression, the relationship is complex and some genes are more gene dosage dependent than others. Amongst the differentially expressed genes with known function, 33% are involved in mRNA translation/protein synthesis. Of note, 37 of the top 100 differentially expressed genes are involved in these processes. In particular, 60 ribosomal protein (RP) genes are significantly (p&lt;0.05) upregulated in H-MM. This signature in H-MM is not associated with increase proliferation as measured by PCLI. This predominant signature suggests that deregulated protein synthesis may be important for the biology of H-MM. Many of these RPs are involved in the synthesis of product of oncogenic pathways (e.g. MYC, NF-KB pathways) and may mediate the growth and survival of tumor cells. It is therefore possible that these tumor cells may be sensitive to the disruption of mRNA translation/protein synthesis. Targeting the mTOR pathway with rapamycin may therefore be useful for treatment of H-MM.

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