Analysis Of Differential Gene Expression Profiles Research Articles

Tumor genomic analysis for biomarker identification in a phase I trial of the Wee 1 inhibitor adavosertib (AZD1775).

3624 Background: Adavosertib, a first-in-class Wee1 kinase inhibitor, abrogates G2/M cell cycle arrest causing premature mitosis and DNA replication stress, yielding enhanced DNA damage. Here we report on potential biomarkers of response from tumor genomic analysis in patients (pts) with solid tumors treated with adavosertib. Methods: Adavosertib was administered once daily on days 1-5 and 8-12 of a 21-day cycle. RECIST 1.1 was used to evaluate clinical response. Paired tumor biopsies were obtained for RNASeq gene expression profiling (GEP) and for whole-exome sequencing (WES) to evaluate gene mutation and copy number amplification (CNA). Fold change (FC) was calculated to define gene overexpression. To identify the frequency of CNA and mRNA overexpression for the genomic biomarkers of interest, cBioPortal analysis using TCGA and MSK-IMPACT datasets was performed. Differential GEP analysis of tumor and paired normal tissue was performed using the gene expression profiling interactive analysis (GEPIA) interface (Tang et al. 2017). Results: Out of 35 pts evaluable for response, 6 (17%) had partial response (PR; 4 ovarian carcinoma [OVC], 2 endometrial carcinoma [EC]). The median duration of response was 5.2 months (range 4.0-23.1). Eighteen pts (51.4%) had stable disease. Genomic analysis of tumor biopsies was available for 9 pts; 7 of these pts were evaluable for response, and 3 had PR (2 OVC, 1 EC). WES revealed TP53 mutations in 6 pts (66.6%; 3 pts with PR, 2 with progressive disease,1 not evaluable). On WES, tumor Cyclin E1 ( CCNE1) CNA was present in 1 of 3 PR pts while tumors from all 3 PR samples showed relatively high CCNE1 expression by RNAseq (FC = 4.07). In the MSK-IMPACT 2017 dataset, CCNE1 CNA was identified in 1.8% of pts (194 of 10336); of which, OVC (10.3%) and EC (8.7%) had the highest incidence of CCNE1 CNAs. In separate tumor-specific (OVC, EC) TCGA datasets having CCNE1 overexpression and/or CNA, overlap in CCNE1 overexpression with CCNE1 CNA was 35.5% (OVC) and 25.2% (EC). Compared to normal ovarian/ endometrial tissues, GEPIA analysis revealed significantly higher CCNE1 mRNA expression in OVC (FC = 3.5) and EC (FC = 3.8). Conclusions: CCNE1alterations (overexpression and/or CNA) tend to be enriched in OVC and EC with a limited fraction showing both overexpression and CNA. Tumor genomic analysis of additional OVC and EC pts treated with adavosertib is required to determine whether CCNE1 mRNA overexpression, regardless of CCNE1 CNA, is a potential biomarker of response to this drug in these tumor types. Funded by NCI contract No. HHSN261200800001E. Clinical trial information: NCT01748825 .

Differential gene expression profile analysis of RIG-I- versus type I IFN-stimulated primary human nasal epithelial cells and protection from influenza virus replication

Abstract Nasal mucosa is a key barrier against upper airway infection including influenza. Trained innate antiviral immunity has the potential to broadly protect the host from a variety of respiratory viruses. Although exposure of cells to type I IFN confers some degree of protection, direct stimulation of innate immune sensors may induce a more effective and longer lasting antiviral immunity. In the present study we analysed the gene expression profile and functional consequence of direct activation of RIG-I by its specific ligand 5′-triphosphate RNA (3pRNA) in primary human nasal epithelial cells, and compared these effects to stimulation of other innate receptors and stimulation by type I IFN. Gene expression analysis was carried out by Lexogen QuantSeq 3′mRNA sequencing. For functional analysis, epithelial cells were exposed to H1N1 influenza virus strain A/PR/8/34. Viral replication was analysed by qPCR. Gene set enrichment analysis revealed upregulation of pathways related to antiviral immune response and type I Interferon signaling. Activation of RIG-I in epithelial cells induced a broad panel of antiviral defense mechanisms which extends beyond those stimulated by recombinant type I IFN. RIG-I-stimulated cells were completely protected from influenza viral replication, while viability of the cells was not reduced. Recombinant IFN-b resulted in lower protection against viral replication compared to 3pRNA, demonstrating that RIG-I induces additional functional antiviral activities not induced by exogenous type I IFN acting alone. Thus, our findings support the concept that stimulation of RIG in epithelial cells is a promising strategy to protect cells from viruses including emerging viral infections of the respiratory tract.

Comparative transcriptome profiling of healthy and diseased Chowghat Green Dwarf coconut palms from root (wilt) disease hot spots

Understanding the molecular basis of host-pathogen interactions is imperative for devising disease management strategies. The root (wilt) disease is the foremost debilitating disease threatening coconut production in India. To explore the molecular mechanisms involved in compatible and incompatible interactions, global transcriptome profiling of leaves of healthy and diseased Chowghat Green Dwarf (CGD) palms was conducted. RNA-Seq analysis generated more than 190 million 100 bp reads from both healthy and diseased samples. Assembled transcriptome yielded 59,282 transcripts with a median length of 987 bp. BLASTX annotation of transcriptome resulted in 39,665 transcripts getting annotated from Uniprot and date palm proteome database. Differential gene expression profiling analysis revealed 2718 transcripts to be up- or down- regulated in the diseased palms in comparison to healthy control at a fold change of 2 and above with a p value <=0.05. The differentially expressed transcripts could be categorized into pathways which included cell wall biogenesis, primary and secondary metabolism, plant-pathogen interaction, cellular transport, hormone biosynthesis and signaling. Validation by quantitative real time PCR (RT-qPCR) of a set of arbitrarily selected genes, both up-regulated and down-regulated, established a comparable pattern as observed by RNA-Seq analysis. Overall, the resources generated in this study provide an in-depth analysis and new insights into the interaction of coconut palms with the root (wilt) disease pathogen.

Differential gene expression profiling analysis in Pleurotus ostreatus during interspecific antagonistic interactions with Dichomitus squalens and Trametes versicolor

This study provided analysis of differentially expressed genes (DEGs) in Pleurotus ostreatus under the interaction with Dichomitus squalens and Trametes versicolor, which is valuable for exploration on the fungal defence system against stressful condition caused by interspecific antagonistic interaction. Our result showed significant upregulation of abundant defence-related genes encoding laccase, manganese peroxidase, aldo–keto reductase, and glutathione S-transferase, which all play important roles in oxidative stress-resistant response. Importantly, Lacc2 and Lacc10 were found to be dominantly induced laccase genes in P. ostreatus under interspecific interaction. Meanwhile, a large number of carbohydrate metabolism-related and energy production-related genes involved in nutrient and territory competition were also enhanced. These genes were annotated as glycoside hydrolase, citrate synthase, malate dehydrogenase, succinate dehydrogenase, succinyl-CoA synthetase, NADH dehydrogenase, cytochrome c reductase/oxidase, and ATP synthase. Also, 12 DEGs were selected for validation by quantitative real-time PCR (qRT-PCR), all these genes showed consistent expression between the result of qRT-PCR and RNA-seq.

De novo Transcriptome Analysis of Miscanthus lutarioriparius Identifies Candidate Genes in Rhizome Development.

HIGHLIGHT De novo transcriptome profiling of five tissues reveals candidate genes putatively involved in rhizome development in M. lutarioriparius.Miscanthus lutarioriparius is a promising lignocellulosic feedstock for second-generation bioethanol production. However, the genomic resource for this species is relatively limited thus hampers our understanding of the molecular mechanisms underlying many important biological processes. In this study, we performed the first de novo transcriptome analysis of five tissues (leaf, stem, root, lateral bud and rhizome bud) of M. lutarioriparius with an emphasis to identify putative genes involved in rhizome development. Approximately 66 gigabase (GB) paired-end clean reads were obtained and assembled into 169,064 unigenes with an average length of 759 bp. Among these unigenes, 103,899 (61.5%) were annotated in seven public protein databases. Differential gene expression profiling analysis revealed that 4,609, 3,188, 1,679, 1,218, and 1,077 genes were predominantly expressed in root, leaf, stem, lateral bud, and rhizome bud, respectively. Their expression patterns were further classified into 12 distinct clusters. Pathway enrichment analysis revealed that genes predominantly expressed in rhizome bud were mainly involved in primary metabolism and hormone signaling and transduction pathways. Noteworthy, 19 transcription factors (TFs) and 16 hormone signaling pathway-related genes were identified to be predominantly expressed in rhizome bud compared with the other tissues, suggesting putative roles in rhizome formation and development. In addition, a predictive regulatory network was constructed between four TFs and six auxin and abscisic acid (ABA) -related genes. Furthermore, the expression of 24 rhizome-specific genes was further validated by quantitative real-time RT-PCR (qRT-PCR) analysis. Taken together, this study provide a global portrait of gene expression across five different tissues and reveal preliminary insights into rhizome growth and development. The data presented will contribute to our understanding of the molecular mechanisms underlying rhizome development in M. lutarioriparius and remarkably enrich the genomic resources of Miscanthus.

Differential gene expression profiling analysis in workers occupationally exposed to benzene

Benzene is an important industrial chemical and an environmental contaminant, but the pathogenesis of hematotoxicity induced by chronic occupational benzene exposure remains to be elucidated. To gain an insight into the molecular mechanisms and new biomarkers, microarray analysis was used to identify the differentially expressed mRNA critical for benzene hematotoxicity. RNA was extracted from four chronic benzene poisoning patients occupationally exposed to benzene, three benzene-exposed workers without clinical symptoms and three health controls without benzene exposure and mRNA expression profiling was performed using Gene Chip Human Gene 2.0ST Arrays. Analysis of mRNA expression profiles were conducted to identify key genes, biological processes and pathways by the series test of cluster (STC), STC-Gene Ontology analysis (STC-GO), pathway analysis and Signal-net. Principal findings: 1) 1661 differentially expressed mRNAs were identified and assigned to sixteen model profiles. 2) Profiles 14, 10, 11, 1 and 15 are the predominant expression profiles which were involved in immune response, inflammatory response, chemotaxis, defense response, anti-apoptosis and signal transduction. 3) The importance of immune response at benzene hematotoxicity is highlighted by several immune-related signaling pathways such as B/T cell receptor signaling pathway, acute myeloid leukemia, hematopoietic cell lineage and natural killer cell mediated cytotoxicity. 4) Signet analysis showed that PIK3R1, PIK3CG, PIK3R2, GNAI3, KRAS, NRAS, NFKB1, HLA-DMA, and HLA-DMB were key genes involved in benzene hematotoxicity. These genes might be new biomarkers for the prevention and early diagnosis of benzene poisoning. This is a preliminary study that paves the way to further functional study to understand the underlying regulatory mechanisms.

A dependency graph approach for the analysis of differential gene expression profiles

A central aim of differential gene expression profile analysis is to provide an interpretation of given data at the level of biological processes and pathways. However, traversing descriptive data into context is not straightforward. We present a gene-centric dependency graph approach supporting an interpretation of omics profiles at the level of affected networks. The core of our dependency graph comprises data objects encoding the functional categorization of a particular gene, its tissue-specific reference gene expression, as well as known interactions and subcellular location of assigned proteins. On the basis of these genome, transcriptome, and proteome data we compute pair-wise object (gene) dependencies and interpret them as weighted edges in a dependency graph. Mapping of omics profiles on this graph can be used to identify connectors linking features of the omics list, in turn providing the basis for identification of subgraphs and motifs characterizing the cellular state under analysis. We exemplify this approach by analyzing differential gene expression data characterizing B-cell lymphoma and demonstrate the identification of B-cell lymphoma associated subgraphs.

Molecular Phenotypic Descriptors of Dupuytren’s Disease Defined Using Informatics Analysis of the Transcriptome

Dupuytren's disease (DD) is a fibroproliferative disorder of unknown etiopathogenesis, which may cause progressive, permanent contracture of digits. Previous studies provide compelling evidence that genetic alterations play an important role. Macroscopically affected areas demonstrate phenotypic differences between the two structurally distinct fibrotic elements in DD (ie, the nodule and the cord). In this study, we set out to (1) compare gene expression profiles between DD and transverse carpal fascia of control subjects (external control); (2) profile DD cords and nodules from the palm against the unaffected transverse palmar fascia (internal control); and (3) identify biologically important candidate genes from the transcriptome profiles. RNA samples from DD nodules (n = 4), cords (n = 4), and internal control (n = 4) as well as external control (n = 4) from unaffected individuals were subjected to differential gene expression profile analysis. Changes of more than 2-fold in DD groups and controls were recorded. Quantitative reverse transcriptase-polymerase chain reactions were performed to validate 16 implicated genes, which included developmental control genes, matrix metalloproteinases, and apoptotic genes. Several genes associated with DD formation were common across all 6 pairwise analyses. Genes markedly upregulated shared common expression levels across all pairwise analysis studies. Pairs involving the DD nodule arrays were notably distinguishable from all other permutations. The majority of genes dysregulated in the DD cords demonstrated an increase in fold change when compared with the DD nodule tissues. Key collagens, collagenases, metalloproteinases, and inhibitors were identified. Genes involved in cytoskeleton development and lipid metabolism were markedly dysregulated. Confirmations of these alterations were obtained in quantitative reverse transcriptase-polymerase chain reaction. These data demonstrate a gradation in expression of certain genes in DD tissue phenotypes compared with control fascia. Transcriptome profiling is predictive not only of disease but also of disease phenotype. These results indicate a number of important candidate genes associated with DD formation, which may provide clues for molecular mechanisms involved in DD pathogenesis.

Comparison of gene expression profiles between Peyronie's disease and Dupuytren's contracture

Objectives To compare the gene expression alterations in human Peyronie's disease (PD) and Dupuytren's disease (DD) to determine whether they share a common pathophysiology. Multiple mRNA expression profiles of human PD have previously shown that genes that regulate fibroblast replication, myofibroblast differentiation, collagen metabolism, tissue repair, and ossification are involved. DD, a palmar fascia fibrosis, may be associated with PD. Methods Total RNA samples from PD plaques, normal tunica albuginea, Dupuytren's nodules, and normal palmar fascia (nine samples per group) were subjected to differential gene expression profile analysis (Clontech Atlas DNA microarray) comparing PD with tunica albuginea and DD with normal palmar fascia. Changes of more than 2.0 in PD and DD compared with tunica albuginea and normal palmar fascia, respectively, were recorded. Reverse transcriptase-polymerase chain reactions were performed for some genes whose expression was altered in PD. Results Some of the gene families upregulated in both PD and DD were (a) collagen degradation: matrix metalloproteinase (MMP), with MMP2 and MMP9, and thymosins (MMP activators), with TMβ10 and TMβ4; (b) ossification: osteoblast-specific factors (OSFs) OSF-1 and OSF-2 (DD only); and (c) myofibroblast differentiation: RhoGDP dissociation inhibitor 1. The genes upregulated in PD only were decorin (an inhibitor of transforming growth factor-beta1 and a part of fibroblast replication/collagen synthesis) and early growth response protein. Reverse transcriptase-polymerase chain reaction confirmed these changes. Conclusions These data demonstrate that the pattern of alterations in the expression of certain gene families in PD and DD is similar, suggesting that they share a common pathophysiology and may be amenable to the same therapeutic regimens.