Integrated Transcriptomic Analysis of Necrosis-related Gene in Diffuse Gliomas

2019 ◽  
Vol 80 (04) ◽  
pp. 240-249
Author(s):  
Jiajia Wang ◽  
Jie Ma
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Prognostic Index ◽  
Gene Expression Profiles ◽  
Risk Groups ◽  
Low Risk ◽  
Differentially Expressed ◽  
Low Grade

Glioblastoma multiforme (GBM), an aggressive brain tumor, is characterized histologically by the presence of a necrotic center surrounded by so-called pseudopalisading cells. Pseudopalisading necrosis has long been used as a prognostic feature. However, the underlying molecular mechanism regulating the progression of GBMs remains unclear. We hypothesized that the gene expression profiles of individual cancers, specifically necrosis-related genes, would provide objective information that would allow for the creation of a prognostic index. Gene expression profiles of necrotic and nonnecrotic areas were obtained from the Ivy Glioblastoma Atlas Project (IVY GAP) database to explore the differentially expressed genes.A robust signature of seven genes was identified as a predictor for glioblastoma and low-grade glioma (GBM/LGG) in patients from The Cancer Genome Atlas (TCGA) cohort. This set of genes was able to stratify GBM/LGG and GBM patients into high-risk and low-risk groups in the training set as well as the validation set. The TCGA, Repository for Molecular Brain Neoplasia Data (Rembrandt), and GSE16011 databases were then used to validate the expression level of these seven genes in GBMs and LGGs. Finally, the differentially expressed genes (DEGs) in the high-risk and low-risk groups were subjected to gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes pathway, and gene set enrichment analyses, and they revealed that these DEGs were associated with immune and inflammatory responses. In conclusion, our study identified a novel seven-gene signature that may guide the prognostic prediction and development of therapeutic applications.

scholarly journals Genomewide Expression Profile Analysis of the Candida glabrata Pdr1 Regulon

2010 ◽  
Vol 10 (3) ◽  
pp. 373-383 ◽  
Author(s):  
Kelly E. Caudle ◽  
Katherine S. Barker ◽  
Nathan P. Wiederhold ◽  
Lijing Xu ◽  
Ramin Homayouni ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Candida Glabrata ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Resistant Isolate ◽  
Content Type ◽  
Activating Mutations ◽  
Zinc Cluster

ABSTRACTThe ABC transportersCandida glabrataCdr1 (CgCdr1), CgPdh1, and CgSnq2 are known to mediate azole resistance in the pathogenic fungusC. glabrata. Activating mutations inCgPDR1, a zinc cluster transcription factor, result in constitutive upregulation of these ABC transporter genes but to various degrees. We examined the genomewide gene expression profiles of two matched azole-susceptible and -resistantC. glabrataclinical isolate pairs. Of the differentially expressed genes identified in the gene expression profiles for these two matched pairs, there were 28 genes commonly upregulated withCgCDR1in both isolate sets includingYOR1,LCB5,RTA1,POG1,HFD1, and several members of theFLOgene family of flocculation genes. We then sequencedCgPDR1from each susceptible and resistant isolate and found two novel activating mutations that conferred increased resistance when they were expressed in a common background strain in whichCgPDR1had been disrupted. Microarray analysis comparing these reengineered strains to their respective parent strains identified a set of commonly differentially expressed genes, includingCgCDR1,YOR1, andYIM1, as well as genes uniquely regulated by specific mutations. Our results demonstrate that while CgPdr1 activates a broad repertoire of genes, specific activating mutations result in the activation of discrete subsets of this repertoire.

Changes in Gene Expression Profiles in Patients with 5q- Syndrome Caused by Lenalidomide Treatment

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 5023-5023
Author(s):  
Monika Belickova ◽  
Jaroslav Cermak ◽  
Jitka Vesela ◽  
Eliska Cechova ◽  
Zuzana Zemanova ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Conflicts Of Interest ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Aurora A ◽  
Genes Expression ◽  
Marrow Stroma ◽  
Cell Niche

Abstract Abstract 5023 A direct effects of lenalidomide on gene expression in 5q- patients was studied using HumanRef-8 v2 Expression BeadChips (Illumina). Expression profiles of 6 patients (before treatment and at the time of the first erytroid response) and 6 healthy controls were investigated from CD14+ monocytes of peripheral blood. Differentially expressed genes were identified by Significance Analysis of Microarrays (SAM). Simultaneously, selected genes (TNF, JUN, IL1) were monitored in the course of treatment using Real-Time PCR with Taqman Gene Expression Assays. A comparison of gene expression levels before and during lenalidomide treatment revealed 97 differentially expressed genes (FC >2; p<0.05) related to following biological processes: immune response (16 genes), inflammatory response (11 genes), response to bacteria (8 genes), anti-apoptosis (7 genes), regulation of MAP kinase activity (5 genes), oxygen transport (4 genes), and regulation of cell proliferation (11 genes). An overexpression of a number of cytokines (e.g. TNF, IL8, IL1B, CCL3L, CXCL2, and TNFAIP3) was detected in patients before treatment, after lenalidomide administration expression of the majority of the up-regulated cytokine genes decreased to the control baseline level. Detected overproduction of the cytokines in 5q- syndrome may lead to an increased apoptosis of hematopoietic progenitor cells and together with excessive oxidative stress may contribute to the damage the hematopoietic niche. In the same manner, untreated patients showed suppressed expression of two genes (CXCR4, CRTAP) which play an important role in the stem cell niche. After treatment, we detected increased expression of these genes. Both the observations might explain favorable effects of lenalidomide on the bone marrow stroma defect seen in 5q- syndrome. On the other hand, a substantial increase of the ARPC1B gene (an activator and a substrate of Aurora A) expression was detected after lenalidomide treatment. Since overexpression of Aurora A leads to polyploidy and chromosomal instability, ARPC1B might play a role in the disease progression observed in some patients treated with lenalidomide. To conclude, described changes in genes expression may contribute to identification of the pathways affected by lenalidomide and to the explanation of some effects of this drug that have not been fully understood yet. Supported by grants NS/9634 MZCR, UHKT2005 00023736, MSM0021620808 and COST EUGESMA Disclosures: No relevant conflicts of interest to declare.

Association Between Gene Expression Profiles and Commonly Mutated Genes In The Hematopoietic Stem Cells Of Patients With Myelodysplastic Syndromes

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2779-2779 ◽  
Author(s):  
Andrea Pellagatti ◽  
Moritz Gerstung ◽  
Elli Papaemmanuil ◽  
Luca Malcovati ◽  
Aristoteles Giagounidis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Gene Expression Data ◽  
Expression Profiles ◽  
Gene Mutations ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Expression Data ◽  
Common Gene ◽  
Mutational Status

Abstract A particular profile of gene expression can reflect an underlying molecular abnormality in malignancy. Distinct gene expression profiles and deregulated gene pathways can be driven by specific gene mutations and may shed light on the biology of the disease and lead to the identification of new therapeutic targets. We selected 143 cases from our large-scale gene expression profiling (GEP) dataset on bone marrow CD34+ cells from patients with myelodysplastic syndromes (MDS), for which matching genotyping data were obtained using next-generation sequencing of a comprehensive list of 111 genes involved in myeloid malignancies (including the spliceosomal genes SF3B1, SRSF2, U2AF1 and ZRSR2, as well as TET2, ASXL1and many other). The GEP data were then correlated with the mutational status to identify significantly differentially expressed genes associated with each of the most common gene mutations found in MDS. The expression levels of the mutated genes analyzed were generally lower in patients carrying a mutation than in patients wild-type for that gene (e.g. SF3B1, ASXL1 and TP53), with the exception of RUNX1 for which patients carrying a mutation showed higher expression levels than patients without mutation. Principal components analysis showed that the main directions of gene expression changes (principal components) tend to coincide with some of the common gene mutations, including SF3B1, SRSF2 and TP53. SF3B1 and STAG2 were the mutated genes showing the highest number of associated significantly differentially expressed genes, including ABCB7 as differentially expressed in association with SF3B1 mutation and SULT2A1 in association with STAG2 mutation. We found distinct differentially expressed genes associated with the four most common splicing gene mutations (SF3B1, SRSF2, U2AF1 and ZRSR2) in MDS, suggesting that different phenotypes associated with these mutations may be driven by different effects on gene expression and that the target gene may be different. We have also evaluated the prognostic impact of the GEP data in comparison with that of the genotype data and importantly we have found a larger contribution of gene expression data in predicting progression free survival compared to mutation-based multivariate survival models. In summary, this analysis correlating gene expression data with genotype data has revealed that the mutational status shapes the gene expression landscape. We have identified deregulated genes associated with the most common gene mutations in MDS and found that the prognostic power of gene expression data is greater than the prognostic power provided by mutation data. AP and MG contributed equally to this work. JB and PJC are co-senior authors. Disclosures: No relevant conflicts of interest to declare.

A prospective study to evaluate the role of gene expression profiles (GEP) in predicting clinical outcome of patients (pts) receiving preoperative chemotherapy for oesophagogastric (OG) cancer

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 4501-4501
Author(s):  
S. Rao ◽  
D. Cunningham ◽  
M. Benson ◽  
R. Te Poele ◽  
L. Welsh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Outcome ◽  
Differentially Expressed Genes ◽  
Preoperative Chemotherapy ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Control Measures ◽  
Differentially Expressed ◽  
Outcome Group

4501 Background: Whilst preoperative chemotherapy has demonstrated survival benefit for pts with potentially resectable OG cancer it is not possible to predict the benefit for an individual pt. This study was designed to prospectively correlate GEP with clinical outcome. Methods: Eligible pts were deemed to have resectable disease after staging CT, EUS, and laparoscopy as indicated & following discussion at the multidisciplinary team meeting. All pts received neoadjuvant platinum & fluoropyrimidine based chemotherapy & clinical data were entered prospectively onto a study specific database. GEP were produced from total RNA isolated from snap frozen pre treatment tumour biopsies obtained at baseline endoscopy. Labelled cDNA was hybridised versus a universal human reference using an in house c DNA array of 22,000 clones. Results: Of the pts with adequate follow up accrued between 2002–2005, 35 met the quality control measures for the arrays. Median age=66 yrs (47–83); male=32, female=3; tumour subsites: oesophagus=23, oesophago-gastric junction (OGJ)=12; adenocarcinoma=35; T stage: T 2=3, T3=30, T4=2; N stage: N0=12, N1=23; performance status 0=7, 1=28. Median follow up=938 days. Median overall survival (OS) = 570 days. Prognostic groups were designated according to the median OS (days) of the group: good > median and poor < median. Supervised hierarchical clustering of normalised data revealed significantly differentially expressed genes based on OS (p<0.01) with 2 distinct clusters: a poor outcome group: N= 17 (2yr OS 17.6%) [95% CI: 4.3–38.3], a good outcome group: N=18 (2 yr OS 55%) [95% CI: 30.5–74.8]. Of the differentially expressed genes, those involved in receptor tyrosine kinase signalling & cell growth were amongst the most significantly affected pathways. Conclusions: This novel technique using GEP in tumour biopsies has successfully identified groups of tumours with distinct gene expression profiles that correlate with survival. The approach warrants further validation in a larger cohort. It could facilitate the development of tailored treatment according to individual tumour biology in OG cancer. No significant financial relationships to disclose.

An empirical Bayes method for robust variance estimation in detecting DEGs using microarray data

2017 ◽  
Vol 15 (05) ◽  
pp. 1750020 ◽  
Author(s):  
Na You ◽  
Xueqin Wang
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Multiple Testing ◽  
Empirical Bayes ◽  
Variance Estimation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Link Function ◽  
Multiple Testing Procedure

The microarray technology is widely used to identify the differentially expressed genes due to its high throughput capability. The number of replicated microarray chips in each group is usually not abundant. It is an efficient way to borrow information across different genes to improve the parameter estimation which suffers from the limited sample size. In this paper, we use a hierarchical model to describe the dispersion of gene expression profiles and model the variance through the gene expression level via a link function. A heuristic algorithm is proposed to estimate the hyper-parameters and link function. The differentially expressed genes are identified using a multiple testing procedure. Compared to SAM and LIMMA, our proposed method shows a significant superiority in term of detection power as the false discovery rate being controlled.

scholarly journals Gene expression profiles of progressive pancreatic endocrine tumours and their liver metastases reveal potential novel markers and therapeutic targets

2006 ◽  
Vol 13 (2) ◽  
pp. 541-558 ◽  
Author(s):  
G Capurso ◽  
S Lattimore ◽  
T Crnogorac-Jurcevic ◽  
F Panzuto ◽  
M Milione ◽  
...  
Keyword(s):  
Gene Expression ◽  
Liver Metastases ◽  
Cell Lines ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Therapeutic Targets ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Striking Similarity ◽  
Metastatic Lesions

The intrinsic nature of tumour behaviour (stable vs progressive) and the presence of liver metastases are key factors in determining the outcome of patients with a pancreatic endocrine tumour (PET). Previous expression profile analyses of PETs were limited to non-homogeneous groups or to primary lesions only. The aim of this study was to investigate the gene expression profiles of a more uniform series of sporadic, non-functioning (NF) PETs with progressive disease and, for the first time, their liver metastases, on the Affymetrix human genome U133A and B GeneChip set. Thirteen NF PET samples (eight primaries and five liver metastases) from ten patients with progressive, metastatic disease, three cell lines (BON, QGP and CM) and four purified islet samples were analysed. The same samples were employed for confirmation of candidate gene expression by means of quantitative RT-PCR, while a further 37 PET and 15 carcinoid samples were analysed by immunohistochemistry. Analysis of genes differentially expressed between islets and primaries and metastases revealed 667 up- and 223 down-regulated genes, most of which have not previously been observed in PETs, and whose gene ontology molecular function has been detailed. Overexpression of bridging integrator 1 (BIN1) and protein Z dependent protease inhibitor (SERPINA10) which may represent useful biomarkers, and of lymphocyte specific protein tyrosine kinase (LCK) and bone marrow stromal cell antigen (BST2) which could be used as therapeutic targets, has been validated. When primary tumours were compared with metastatic lesions, no significantly differentially expressed genes were found, in accord with cluster analysis which revealed a striking similarity between primary and metastatic lesions, with the cell lines clustering separately. We have provided a comprehensive list of differentially expressed genes in a uniform set of aggressive NF PETs. A number of dysregulated genes deserve further in-depth study as potentially promising candidates for new diagnostic and treatment strategies. The analysis of liver metastases revealed a previously unknown high level of similarity with the primary lesions.

RNA-seq analysis of non-muscular invasive bladder cancer to reveal different gene expression profiles between smoking and non-smoking patients.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 478-478
Author(s):  
Zhichao Fu ◽  
Shenghua Liu ◽  
Jianfei Wang ◽  
Ning He ◽  
Yadong Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Tumor Progression ◽  
Urothelial Carcinoma ◽  
Differentially Expressed Genes ◽  
Poor Prognosis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Rna Seq

478 Background: Bladder cancer is the ninth most common malignancy in the world, approximately 75% of patients are diagnosed with non-muscle invasive bladder cancer (NMIBC). Smoking has been established to be a carcinogenic risk factor of bladder cancer. Nevertheless, the detailed relationship between smoking and progression of NMIBC are poorly understood. In this study, we revealed high expressed genes in smoking patients were significantly related to tumor progression in NMIBC patients. Methods: A total of 54 NMIBC patients including 19 never smokers and 35 smokers (current smokers and previous smokers) were enrolled in this study.The gene expression profiles were obtained by RNA-seq and the differentially expressed genes between smoking and non-smoking patients were identified using DESeq2 .The further analysis of the association between genes expression and patient survival in NMIBC cohorts(Jakob et al., 2016)and IMvigor 210 cohorts(Jonathan et al., 2016)by Kaplan-Meier survival estimate. Results: We identified 46 differentially expressed genes (p<0.05) in smoking and non-somking NMIBC patients. IDO1 and KRT14 gene, which related to bladder cancer progression and poor prognosis, was identified significantly higher expressed in somking group compared with non-smoking and they have a logFC of 2.6,3.9 with FDR 1.83E-5,3.40E-5 respectively. The expression of other genes, including KRT6A, CASP14, SERPINA1, MYO3A and IL20RB, were significantly higher in smoking patients compared to non-somking. Notably, survival data analysis from 476 NMIBC cohorts showed that IL20RB had a significant relationship with poor PFS(p = 0.021) and in the Mvigor 210 Cohort including 310 advanced or metastatic urothelial carcinoma patients treated with atezolizumab, we found that the high expression of IL20RB was significantly related to poor OS(p = 0.002). Conclusions: We identified 14 genes related to tumor progression were significantly higher in smoking NMIBC patients than in non-smoking. Among these genes, the expression of IL20RB was related to the poor prognosis of NMIBC, and it may correlates with reduced clinical benefit of immunotherapeutic in patients with urothelial carcinoma.

Identification of Patients At High Risk for Recurrent Venous Thromboembolism by Whole Blood Gene Expression Analysis

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2305-2305
Author(s):  
Thomas L. Ortel ◽  
Michele Beckman ◽  
W Craig Hooper ◽  
Deborah A Lewis ◽  
Jen-Tsan A. Chi ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Whole Blood ◽  
Antiphospholipid Antibodies ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Low Risk ◽  
Risk Patients ◽  
Patient Groups ◽  
Recurrent Vte

Abstract Abstract 2305 Background. Recurrent venous thromboembolism (VTE) occurs in ∼30% of patients with spontaneous VTE after completion of a standard course of anticoagulant therapy. D-dimer levels and selected clinical parameters have been used to identify patients at low risk for recurrent VTE, who may safely discontinue antithrombotic therapy. We have used gene expression profiles to distinguish patients with a single VTE from patients with recurrent VTE. The purpose of this study was to extend this initial report and identify unique gene expression patterns from whole blood that correlate with different risk profiles for VTE recurrence. Methods. Patients with ≥1 prior VTE, with the first event occurring at age 18 years or older and >3 months from the most recent event were recruited for this study. Patients were allocated into 4 groups: (1) ‘low-risk’ patients had sustained ≥1 provoked VTE; (2) ‘moderate-risk’ patients had sustained 1 unprovoked VTE (with or without provoked VTE); (3) ‘high-risk’ patients had sustained ≥2 unprovoked VTE and had no evidence for antiphospholipid antibodies; and (4) antiphospholipid syndrome (APS) patients met established consensus criteria for APS. A similar number of individuals with no prior history of VTE were enrolled as a control population. Citrated plasma, serum and PAXgene RNA tubes were collected, processed and stored at −80°C until shipped to the CDC for analysis. Antiphospholipid testing was performed on all participants to confirm correct group distribution. Total RNA was isolated from whole blood drawn into PAXgene tubes. Following sample labeling and normalization, cRNA samples were hybridized to Illumina HT-12 Beadchips to assay whole genome gene expression with over 47,000 probes against human transcripts. Two hundred and twenty six unique samples passed initial quality control measures. Quality assessment of raw data was done using GenomeStudio. The raw data files were converted to a text file using the IlluminaExpression FileCreator in GenePattern and then log transformed, normalized and median-centered using Cluster. Both unsupervised (hierarchical clustering using Cluster) and supervised analyses (SAM) were used to identify genes that were differentially expressed between the groups. GATHER was used to help understand the biological processes and gene ontology of the gene lists generated by Cluster and SAM. Results. A total of 226 participants were enrolled into the study. Characteristics of the patient groups are summarized in the Table. Demographically, the groups were similar except that patients in the high-risk group tended to be older and were more likely male. The number of events per patient, and the proportion on anticoagulant therapy, increased with the risk group. Antiphospholipid antibodies were detected in several patients in each of the 3 non-APS VTE patient groups, but in most cases this was a single test positive; antiphospholipid antibodies were present in the majority of patients with APS, typically with more than one test positive (37 of 45 with complete testing, 82%). Preliminary analysis of the gene expression profiles using an unsupervised clustering by gene on the high-risk and low-risk groups identified multiple genes that distinguished the two groups, including 18 immune response genes identified by GATHER. These two patient groups were also distinguished by SAM analysis, and multiple genes in the MAPK signaling pathway that separated the two groups were identified by the KEGG pathways in GATHER. Additional analyses are being performed on all of the groups. Conclusions. Whole blood gene expression profiling can be used to develop profiles that distinguish patients with VTE who differ based on their risk of recurrent events. Individual genes identified in these profiles may provide biological insights into the molecular basis for recurrent VTE. Disclosures: Heit: Daiichi Sankyo: Honoraria; Ortho-McNeil Janssen: Honoraria; Covidien: Honoraria. Manco-Johnson:Octapharma AG: Consultancy; Bayer: Research Funding.

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