Summarizing RNA-Seq Data or Differentially Expressed Genes Using Gene Set, Network, or Pathway Analysis

Author(s):  
Enrica Calura ◽  
Paolo Martini
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Bochi Zhu ◽  
Xijing Mao ◽  
Yuhong Man

Objectives. Glioblastoma (GBM) is a malignant brain tumor which is the most common and aggressive type of central nervous system cancer, with high morbidity and mortality. Despite lots of systematic studies on the molecular mechanism of glioblastoma, the pathogenesis is still unclear, and effective therapies are relatively rare with surgical resection as the frequently therapeutic intervention. Identification of fundamental molecules and gene networks associated with initiation is critical in glioblastoma drug discovery. In this study, an approach for the prediction of potential drug was developed based on perturbation-induced gene expression signatures. Methods. We first collected RNA-seq data of 12 pairs of glioblastoma samples and adjacent normal samples from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by DESeq2, and coexpression networks were analyzed with weighted gene correlation network analysis (WGCNA). Furthermore, key driver genes were detected based on the differentially expressed genes and potential chemotherapeutic drugs and targeted drugs were found by correlating the gene expression profiles with drug perturbation database. Finally, RNA-seq data of glioblastoma from The Cancer Genome Atlas (TCGA) dataset was collected as an independent validation dataset to verify our findings. Results. We identified 1771 significantly DEGs with 446 upregulated genes and 1325 downregulated genes. A total of 24 key drivers were found in the upregulated gene set, and 81 key drivers were found in the downregulated gene set. We screened the Crowd Extracted Expression of Differential Signatures (CREEDS) database to identify drug perturbations that could reverse the key factors of glioblastoma, and a total of 354 drugs were obtained with p value < 10-10. Finally, 7 drugs that could turn down the expression of upregulated factors and 3 drugs that could reverse the expression of downregulated key factors were selected as potential glioblastoma drugs. In addition, similar results were obtained through the analysis of TCGA as independent dataset. Conclusions. In this study, we provided a framework of workflow for potential therapeutic drug discovery and predicted 10 potential drugs for glioblastoma therapy.


Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 467 ◽  
Author(s):  
Lilibeth Lanceta ◽  
Conor O'Neill ◽  
Nadiia Lypova ◽  
Xiahong Li ◽  
Eric Rouchka ◽  
...  

Acquired resistance to cyclin-dependent kinases 4 and 6 (CDK4/6) inhibition in estrogen receptor-positive (ER+) breast cancer remains a significant clinical challenge. Efforts to uncover the mechanisms underlying resistance are needed to establish clinically actionable targets effective against resistant tumors. In this study, we sought to identify differentially expressed genes (DEGs) associated with acquired resistance to palbociclib in ER+ breast cancer. We performed next-generation transcriptomic RNA sequencing (RNA-seq) and pathway analysis in ER+ MCF7 palbociclib-sensitive (MCF7/pS) and MCF7 palbociclib-resistant (MCF7/pR) cells. We identified 2183 up-regulated and 1548 down-regulated transcripts in MCF7/pR compared to MCF7/pS cells. Functional analysis of the DEGs using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database identified several pathways associated with breast cancer, including ‘cell cycle’, ‘DNA replication’, ‘DNA repair’ and ‘autophagy’. Additionally, Ingenuity Pathway Analysis (IPA) revealed that resistance to palbociclib is closely associated with deregulation of several key canonical and metabolic pathways. Further studies are needed to determine the utility of these DEGs and pathways as therapeutics targets against ER+ palbociclib-resistant breast cancer.


2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Lucia Seale ◽  
Vedbar Khadka ◽  
Mark Menor ◽  
Alexandru Sasuclark ◽  
Kyrillos Guirguis ◽  
...  

Abstract Objectives Selenium is a trace element critical for appropriate response to oxidative stress in cells. Once ingested, dietary selenium is mostly metabolized by the liver. Selenium is utilized to produce the amino acid selenocysteine, which can be incorporated into selenoproteins, most of them functioning in curbing reactive oxygen species. The enzyme selenocysteine lyase (Scly) decomposes selenocysteine into selenide, and its highest expression and activity occurs in the liver. Disrupting the Scly gene (Scly−/−) resulted in overweight mice with hyperlipidemia, hyperinsulinemia and glucose intolerance, phenotype traits that were aggravated by a selenium-deficient diet. In the liver, Scly−/−mice had lower hepatic selenium levels than their wild-type mice counterparts. Our objective was to identify differentially expressed genes and pathways in Scly−/- mice livers affected by dietary selenium levels. Methods Scly−/- and wild-type mice were fed diets containing 0.08 (mildly low) or 0.25 (adequate) ppm of sodium selenite. We extracted total RNA from livers with a commercial kit. High-quality RNA (RIN ≥ 7) as assessed by a BioAnalyzer was employed in RNA-sequencing. RNA-Seq data analysis was performed on Partek flow software followed by pathway analysis using Ingenuity Pathway Analysis software. Validation of results was pursued by real-time RT-qPCR using specific primer sets. Results Hepatic RNA-Seq analysis revealed 52 genes differentially regulated by Scly disruption and low dietary selenium levels, encompassing 41 pathways, including PXR/RXR activation, LPS/IL-1-mediated inhibition of RXR function, xenobiotic metabolism signaling, nicotine degradation, adipogenesis, and acyl-CoA hydrolysis. Ten differentially expressed genes were validated by real-time RT-qPCR, including Selenobp2, Eif4ebp3, Mt1, and Mt2. Conclusions We identified pathways and validated genes in the Scly−/- mouse liver that are implicated in the metabolic phenotype displayed by this model on a low selenium diet. Funding Sources This project was supported by the National Institutes of Health (NIH) grants U54MD007601 Ola Hawaii (subproject 5544), P30-CA071789–128, R01DK47320, and P20GM103466. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 530-530
Author(s):  
Paola Neri ◽  
Kathy Gratton ◽  
Li Ren ◽  
Jiri Slaby ◽  
Ines Tagoug ◽  
...  

Abstract Background Immunomodulatory (IMiDs) drugs’ cytotoxicity in MM cells is mediated through their binding to cereblon (CRBN) an adaptor protein of the Cul4a-DDB1-ROC1 ubiquitin E3 ligase complex. Loss of CRBN is clearly associated with resistance to IMiDs (Zhu et al. Blood. 2011) however this does not appear to be the sole mechanism through which MM cells may acquire resistance to this class of drugs. In addition, the acquisition of CRBN mutations within the Thalidomide binding domain (exons 10-11) have not been well studied. Similarly and while splice variants of CRBN were recently reported (Ghandi et al. Blood. 2012), no correlations has been made between the presence of these isoforms and IMiDs resistance in primary samples. Methods and Results In this study, we first validated CRBN as biomarker of clinical response to lenalidomide. At the mRNA level, using qRT-PCR (n=26, amplicons with 2 sets of primers overlapping exons 8-9 and exons 10-11) low CRBN in CD138 sorted bone plasma cells was significantly associated with shorter PFS (p=0.008) and lack of response to lenalidomide. We next compared CRBN mRNA (qRT-PCR) expression in paired samples (n=17 patients - 34 pairs) collected immediately pre-treatment and at the time of disease progression post-lenalidomide. In 10/17 (58.8%), a significant reduction (2-ΔΔCT < 0.8) in the CRBN amplicon levels was observed between the paired pre- and post-treatment samples. These data suggest that in nearly half of the patients, CRBN-independent mechanisms may be mediating resistance to IMiDs. In order to elucidate these CRBN-independent mechanisms of resistance to lenalidomide and identify potential targets that may overcome it, RNA-seq analysis was performed in 12 paired patients samples obtained sequentially from the same patient prior to lenalidomide treatment initiation and after development of resistance. Transcriptome sequence data was generated by RNA-seq performed for each sample on Ion Torrent Proton sequencer with a minimum of 70 million reads per sample. Poly(A) is captured with poly(T) magnetic beads, fragmented and copied to cDNA libraries with reverse transcriptase and primers. Filtered Fastq files are processed with TopHat-Fusion alignment against hg19 as reference genome. Cufflinks and Cuffdiff algorithms were used to detect differentially expressed transcripts and spliced isoforms. A total of 830 genes were identified as differentially expressed (p value and FDR <0.05) between the pre- and post-lenalidomide paired samples. Selected differentially expressed genes were also measured by RT-PCR analysis to confirm the validity of the RNA-seq analysis. In order to gain insight into the cellular and molecular functions of this identified gene set, we compared it to the expression of 395 gene sets curated in the Molecular Signatures Database (MSigDB), using the Gene set enrichment analysis (GSEA) algorithm. Among the most enriched gene sets in this analysis were KRAS.KIDNEY_UP.V1_UP; KRAS.LUNG_UP.V1_UP; KRAS.600.LUNG.BREAST_UP.V1_UP; RAF_UP.V1_DN; MEK_UP.V1_DN; and STK33_DN suggesting a role for the RAS-RAF-MAPK pathway in the acquired resistance to IMiDs. Other gene sets of interest included AKT_UP_MTOR_DN.V1_DN, E2F3_UP.V1_UP; EIF4E_UP and RPS14_DN.V1_DN; consistent with a role for the translational machinery activity (mTOR-4EBP1-eIF4E pathway) in IMiDs resistance. Of interest variant splice isoforms of CRBN were visualized using the Integrative Genomics Viewer (IGV) tool including isoforms lacking exon 10, which contains a portion of the IMiD-binding domain. However these CRBN splice variants are unlikely to be implicated in resistance to IMiDs since they were not enriched in the relapsed paired samples. Conclusions Study of the transcriptome of paired pre- and post-IMIDs in myeloma primary cells confirms that acquired resistance to this class of drugs is associated with the direct loss of CRBN as well as through the modulation of other CRBN-independent pathways. Disclosures: No relevant conflicts of interest to declare.


2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A646-A647
Author(s):  
Max Meneveau ◽  
Pankaj Kumar ◽  
Kevin Lynch ◽  
Karlyn Pollack ◽  
Craig Slingluff

BackgroundVaccines are a promising therapeutic for patients with advanced cancer, but achieving robust T-cell responses remains a challenge. Melanoma-associated antigen-A3 (MAGE-A3) in combination with adjuvant AS15 (a formulation of Toll-Like-Receptor (TLR)-4 and 9 agonists and a saponin), induced systemic CD4+ T-cell responses in 50% of patients when given subcutaneously/intradermally. Little is known about the transcriptional landscape of the vaccine-site microenvironment (VSME) of patients with systemic T-cell responses versus those without. We hypothesized that patients with systemic T-cell responses to vaccination would exhibit increased immune activation in the VSME, higher dendritic cell (DC) activation/maturation, TLR-pathway activation, and enhanced Th1 signatures.MethodsBiopsies of the VSME were obtained from participants on the Mel55 clinical trial (NCT01425749) who were immunized with MAGE-A3/AS15. Biopsies were taken 8 days after immunization. T-cell response to MAGE-A3 was assessed in PBMC after in-vitro stimulation with recMAGE-A3, by IFNγ ELISPOT assay. Gene expression was assessed by RNAseq using DESeq2. Comparisons were made between immune-responders (IR), non-responders (NR), and normal skin controls. FDR p<0.01 was considered significant.ResultsFour IR, four NR, and three controls were evaluated. The 500 most variable genes were used for principal component analysis (PCA). Two IR samples were identified as outliers on PCA and excluded from further analysis. There were 882 differentially expressed genes (DEGs) in the IR group vs the NR group (figure 1A). Unsupervised clustering of the top 500 DEGs revealed clustering according to the experimental groups (figure 1B). Of the 10 most highly upregulated DEGs, 9 were immune-related (figure 1C). Gene-set enrichment analysis revealed that immune-related pathways were highly enriched in IRs vs NRs (figure 1D). CD4 and CD8 expression did not differ between IR and NR (figure 2A), though both were higher in IR compared to control. Markers of DC activation/maturation were higher in IR vs NR (figure 2B), as were several Th1 associated genes (figure 2C). Interestingly, markers of exhaustion were higher in IR v NR (figure 2D). Expression of numerous TLR-pathway genes was higher in IR vs NR, including MYD88, but not TICAM1 (figure 2E).Abstract 611 Figure 1Gene expression profiling of vaccine site samples from patients immunized with MAGE-A3/AS15. (A) Volcano plots showing the distribution of differentially expressed genes (DEGs) between immune responders (IR) and non-responders (NR), IR and control, and NR and control. (B) Heatmap of the top 500 most differentially expressed genes demonstrating hierarchical clustering of sequenced samples according to IR, NR, and control. (C) Table showing the 10 most highly up and down-regulated genes in IR compared to NR. 9 of the top 10 most highly up-regulated genes are related to the immune response. (D) Enrichment plots from a gene set enrichment analysis highlighting the upregulation of immune related pathways in IR compared to NR. Gene set enrichment data was generated from the Reactome gene set database and included all expressed genes. Significance was set at FDR p <0.01Abstract 611 Figure 2Expression of T-cell markers in IR vs NR vs Control samples in the vaccine site microenvironment (VSME). (A) T-cell markers showing similar expression in IR vs NR but higher expression in IR vs control. (B) Markers of dendritic cell activation and maturation in the VSME which are higher in IR vs control but not IR vs NR. (B) Transcription factors and genes associated with Th1/Th2 responses within the VSME. (D) Genes associated with T-cell exhaustion at the VSME. (E) Expression of TLR pathway genes in the VSME. Expression data is provided in terms of normalized counts. Bars demonstrate median and interquartile range. N=9. IR = immune responder, NR = non-responder, TLR = Toll-like Receptor. * = <0.01, ** < 0.001, *** <0.0001, **** < 0.00001ConclusionsThese findings suggest a unique immune-transcriptional landscape in the VSME is associated with circulating T-cell responses to immunization, with differences in DC activation/maturation, Th1 response, and TLR signaling. Thus, immunologic changes in the VSME are useful predictors of systemic immune response, and host factors that modulate immune-related signaling at the vaccine site may have concordant systemic effects on promoting or limiting immune responses to vaccines.Trial RegistrationSamples for this work were collected from patients enrolled on the Mel55 clinical trial NCT01425749.Ethics ApprovalThis work was completed after approval from the UVA institutional review board IRB-HSR# 15398.


2018 ◽  
Vol 115 ◽  
pp. 343-352 ◽  
Author(s):  
Sanjeev Kumar Shukla ◽  
Shubhra Shukla ◽  
Rehan Khan ◽  
Anuj Ahuja ◽  
Lakshya Veer Singh ◽  
...  

2018 ◽  
Vol 314 (4) ◽  
pp. L617-L625 ◽  
Author(s):  
Arjun Mohan ◽  
Anagha Malur ◽  
Matthew McPeek ◽  
Barbara P. Barna ◽  
Lynn M. Schnapp ◽  
...  

To advance our understanding of the pathobiology of sarcoidosis, we developed a multiwall carbon nanotube (MWCNT)-based murine model that shows marked histological and inflammatory signal similarities to this disease. In this study, we compared the alveolar macrophage transcriptional signatures of our animal model with human sarcoidosis to identify overlapping molecular programs. Whole genome microarrays were used to assess gene expression of alveolar macrophages in six MWCNT-exposed and six control animals. The results were compared with the transcriptional profiles of alveolar immune cells in 15 sarcoidosis patients and 12 healthy humans. Rigorous statistical methods were used to identify differentially expressed genes. To better elucidate activated pathways, integrated network and gene set enrichment analysis (GSEA) was performed. We identified over 1,000 differentially expressed between control and MWCNT mice. Gene ontology functional analysis showed overrepresentation of processes primarily involved in immunity and inflammation in MCWNT mice. Applying GSEA to both mouse and human samples revealed upregulation of 92 gene sets in MWCNT mice and 142 gene sets in sarcoidosis patients. Commonly activated pathways in both MWCNT mice and sarcoidosis included adaptive immunity, T-cell signaling, IL-12/IL-17 signaling, and oxidative phosphorylation. Differences in gene set enrichment between MWCNT mice and sarcoidosis patients were also observed. We applied network analysis to differentially expressed genes common between the MWCNT model and sarcoidosis to identify key drivers of disease. In conclusion, an integrated network and transcriptomics approach revealed substantial functional similarities between a murine model and human sarcoidosis particularly with respect to activation of immune-specific pathways.


Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.


2019 ◽  
Vol 32 (5) ◽  
pp. 515-526 ◽  
Author(s):  
William E. Fry ◽  
Sean P. Patev ◽  
Kevin L. Myers ◽  
Kan Bao ◽  
Zhangjun Fei

Sporangia of Phytophthora infestans from pure cultures on agar plates are typically used in lab studies, whereas sporangia from leaflet lesions drive natural infections and epidemics. Multiple assays were performed to determine if sporangia from these two sources are equivalent. Sporangia from plate cultures showed much lower rates of indirect germination and produced much less disease in field and moist-chamber tests. This difference in aggressiveness was observed whether the sporangia had been previously incubated at 4°C (to induce indirect germination) or at 21°C (to prevent indirect germination). Furthermore, lesions caused by sporangia from plates produced much less sporulation. RNA-Seq analysis revealed that thousands of the >17,000 P. infestans genes with a RPKM (reads per kilobase of exon model per million mapped reads) >1 were differentially expressed in sporangia obtained from plate cultures of two independent field isolates compared with sporangia of those isolates from leaflet lesions. Among the significant differentially expressed genes (DEGs), putative RxLR effectors were overrepresented, with almost half of the 355 effectors with RPKM >1 being up- or downregulated. DEGs of both isolates include nine flagellar-associated genes, and all were down-regulated in plate sporangia. Ten elicitin genes were also detected as DEGs in both isolates, and nine (including INF1) were up-regulated in plate sporangia. These results corroborate previous observations that sporangia produced from plates and leaflets sometimes yield different experimental results and suggest hypotheses for potential mechanisms. We caution that use of plate sporangia in assays may not always produce results reflective of natural infections and epidemics.


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