Gene Expression Meta-Analysis Reveals Interferon-Induced Genes Associated With SARS Infection in Lungs

BackgroundSevere Acute Respiratory Syndrome (SARS) corona virus (CoV) infections are a serious public health threat because of their pandemic-causing potential. This work is the first to analyze mRNA expression data from SARS infections through meta-analysis of gene signatures, possibly identifying therapeutic targets associated with major SARS infections.MethodsThis work defines 37 gene signatures representing SARS-CoV, Middle East Respiratory Syndrome (MERS)-CoV, and SARS-CoV2 infections in human lung cultures and/or mouse lung cultures or samples and compares them through Gene Set Enrichment Analysis (GSEA). To do this, positive and negative infectious clone SARS (icSARS) gene panels are defined from GSEA-identified leading-edge genes between two icSARS-CoV derived signatures, both from human cultures. GSEA then is used to assess enrichment and identify leading-edge icSARS panel genes between icSARS gene panels and 27 other SARS-CoV gene signatures. The meta-analysis is expanded to include five MERS-CoV and three SARS-CoV2 gene signatures. Genes associated with SARS infection are predicted by examining the intersecting membership of GSEA-identified leading-edges across gene signatures.ResultsSignificant enrichment (GSEA p<0.001) is observed between two icSARS-CoV derived signatures, and those leading-edge genes defined the positive (233 genes) and negative (114 genes) icSARS panels. Non-random significant enrichment (null distribution p<0.001) is observed between icSARS panels and all verification icSARSvsmock signatures derived from human cultures, from which 51 over- and 22 under-expressed genes are shared across leading-edges with 10 over-expressed genes already associated with icSARS infection. For the icSARSvsmock mouse signature, significant, non-random significant enrichment held for only the positive icSARS panel, from which nine genes are shared with icSARS infection in human cultures. Considering other SARS strains, significant, non-random enrichment (p<0.05) is observed across signatures derived from other SARS strains for the positive icSARS panel. Five positive icSARS panel genes, CXCL10, OAS3, OASL, IFIT3, and XAF1, are found across mice and human signatures regardless of SARS strains.ConclusionThe GSEA-based meta-analysis approach used here identifies genes with and without reported associations with SARS-CoV infections, highlighting this approach’s predictability and usefulness in identifying genes that have potential as therapeutic targets to preclude or overcome SARS infections.

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Gene Expression Meta-Analysis Identifies Molecular Changes Associated with SARS-CoV Infection in Lungs

10.1101/2020.11.14.382697 ◽

2020 ◽

Author(s):

Amber Park ◽

Laura K. Harris

Keyword(s):

Gene Expression ◽

Meta Analysis ◽

Infectious Clone ◽

Null Distribution ◽

Leading Edge ◽

Gene Set Enrichment Analysis ◽

Mouse Lung ◽

Gene Signatures ◽

Significant Enrichment ◽

Leading Edges

AbstractBackgroundSevere Acute Respiratory Syndrome (SARS) corona virus (SARS-CoV) infections are a serious public health threat because of their pandemic-causing potential. This work uses mRNA expression data to predict genes associated with SARS-CoV infection through an innovative meta-analysis examining gene signatures (i.e., gene lists ranked by differential gene expression between SARS and mock infection).MethodsThis work defines 29 gene signatures representing SARS infection across seven strains with established mutations that vary virulence (infectious clone SARS (icSARS), Urbani, MA15, ΔORF6, BAT-SRBD, ΔNSP16, and ExoNI) and host (human lung cultures and/or mouse lung samples) and examines them through Gene Set Enrichment Analysis (GSEA). To do this, first positive and negative icSARS gene panels were defined from GSEA-identified leading-edge genes between 500 genes from positive or negative tails of the GSE47960-derived icSARSvsmock signature and the GSE47961-derived icSARSvsmock signature, both from human cultures. GSEA then was used to assess enrichment and identify leading-edge icSARS panel genes in the other 27 signatures. Genes associated with SARS-CoV infection are predicted by examining membership in GSEA-identified leading-edges across signatures.ResultsSignificant enrichment (GSEA p<0.001) was observed between GSE47960-derived and GSE47961-derived signatures, and those leading-edges defined the positive (233 genes) and negative (114 genes) icSARS panels. Non-random (null distribution p<0.001) significant enrichment (p<0.001) was observed between icSARS panels and all verification icSARSvsmock signatures derived from human cultures, from which 51 over- and 22 under-expressed genes were shared across leading-edges with 10 over-expressed genes already being associated with icSARS infection. For the icSARSvsmock mouse signature, significant, non-random enrichment (both p<0.001) held for only the positive icSARS panel, from which nine genes were shared with icSARS infection in human cultures. Considering other SARS strains, significant (p<0.01), non-random (p<0.002) enrichment was observed across signatures derived from other SARS strains for the positive icSARS panel. Five positive icSARS panel genes, CXCL10, OAS3, OASL, IFIT3, and XAF1, were found in mice and human signatures.ConclusionThe GSEA-based meta-analysis approach used here identified genes with and without reported associations with SARS-CoV infections, highlighting this approach’s predictability and usefulness in identifying genes that have potential as therapeutic targets to preclude or overcome SARS infections.

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Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples

EBioMedicine ◽

10.1016/j.ebiom.2021.103525 ◽

2021 ◽

Vol 70 ◽

pp. 103525

Author(s):

Abhijith Biji ◽

Oyahida Khatun ◽

Shachee Swaraj ◽

Rohan Narayan ◽

Raju S. Rajmani ◽

...

Keyword(s):

Prognostic Markers ◽

Meta Analysis ◽

Therapeutic Targets ◽

Omics Data

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Key pathways involved in prostate cancer based on gene set enrichment analysis and meta analysis

Genetics and Molecular Research ◽

10.4238/2011.december.14.10 ◽

2011 ◽

Vol 10 (4) ◽

pp. 3856-3887 ◽

Cited By ~ 11

Author(s):

Q.Y. Ning ◽

J.Z. Wu ◽

N. Zang ◽

J. Liang ◽

Y.L. Hu ◽

...

Keyword(s):

Prostate Cancer ◽

Meta Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Gene Set ◽

Key Pathways

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COL6A2/3 can serve as potential therapeutic targets and prognostic biomarkers for clear cell renal cell carcinoma

10.21203/rs.3.rs-119445/v1 ◽

2020 ◽

Author(s):

Wingkeung Yiu ◽

Can-Xuan Li ◽

Jie Chen

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Mrna Expression ◽

Renal Cell ◽

Clear Cell ◽

Therapeutic Targets ◽

Gene Set Enrichment Analysis ◽

Prognostic Biomarkers ◽

Cell Renal Cell Carcinoma ◽

Tumorigenesis And Progression

Abstract Background: Growing evidence has shown that the type VI collagen alpha chain (COL6A) family involved in the tumorigenesis and progression of diverse malignancies; however, its biological roles and potential mechanisms in clear cell renal cell carcinoma (ccRCC) remain unknown. The study was designed to explore the potential mechanisms and functions of COL6As in ccRCC.Methods: ONCOMINE and GEPIA databases were used to compare the transcriptional expression data of COL6As in ccRCC samples and normal renal samples. UALCAN database was utilized to determine the association between clinicopathological features and COL6As expression. Kaplan–Meier method was employed to determine the prognostic value of COL6As mRNA expression in ccRCC. CBioPortal database was used to investigate the genetic alterations of COL6As in ccRCC. Co-expression analyses, functional enrichment analyses, and gene set enrichment analysis (GSEA) were utilized to explore the potential action mechanisms of COL6As in ccRCC. Finally, we estimated the relationship between COL6As expression with immune cell infiltrates.Results: Upregulated transcriptional COL6A2/COL6A3 expression was observed in ccRCC specimens by comparison with noncancerous renal specimens. Patients with increased COL6A2/COL6A3 mRNA expression have a poor clinical outcome and unfavorable prognosis. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and GSEA analyses showed that COL6A2/COL6A3 might promote the tumorigenesis and progression of ccRCC by involving in several cancer-related pathways, such as axon guidance, focal adhesion, ECM receptor interaction. Besides, we found that COL6A2/COL6A3 expression was significantly associated with immune infiltration levels in ccRCC.Conclusions: COL6A2 and COL6A3 could act as candidate prognostic biomarkers and therapeutic targets in ccRCC. However, further experimental work was required to validate the conclusions.

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Norepinephrine exposure restrains endometrial decidualization in early pregnancy

Journal of Endocrinology ◽

10.1530/joe-20-0479 ◽

2021 ◽

Author(s):

Jiju Wang ◽

Yuhui Tang ◽

Songcun Wang ◽

Liyuan Cui ◽

Da-Jin Li ◽

...

Keyword(s):

Stromal Cells ◽

Adrenergic Receptor ◽

Enrichment Analysis ◽

Normal Pregnancy ◽

Receptor Expression ◽

Gene Set Enrichment Analysis ◽

Endometrial Stromal Cells ◽

Significant Enrichment

Previous studies have focused on the role of norepinephrine on arrhythmias, generalized anxiety disorder, and cancer. This study aimed to investigate the effect of norepinephrine on endometrial decidualization. Artificial decidualization and norepinephrine-treated mice were established in vivo. In vitro, human endometrial stromal cells were treated with MPA and cAMP to induce decidualization. Decidual markers and important signaling molecules during decidualization were detected using quantitative real-time polymerase chain reaction and Western blot. RNA sequencing was performed to determine related signaling pathways. Exposure of excess norepinephrine significantly restricted the induced expression of decidualized markers Dtprp, BMP2, WNT4, and Hand2 in mice. In vitro, 10 µM norepinephrine markedly downregulated the expressions of prolactin, IGFBP1, and PLZF, which are the specifical markers of decidual stromal cells during decidualization. The gene set enrichment analysis showed that a significant enrichment in neuroactive ligand–receptor interactions of norepinephrine treatment group. The α1b-adrenergic receptor expression was upregulated by norepinephrine. Interestingly, norepinephrine did not inhibit the expression of IGFBP1 in endometrial stromal cells after silencing α1b-adrenergic receptor, while significantly suppressed the induced decidualization with overexpression of α1b-adrenergic receptor. When α1b-adrenergic receptor was activated, endometrial p-PKC was significantly increased under post-treatment with norepinephrine in vivo and in vitro. In addition, norepinephrine treatment inhibited embryo and fetal development using a normal pregnancy model. Therefore, norepinephrine exposure inhibited endometrial decidualization through the activation of the PKC signaling pathway by upregulating α1b-adrenergic receptor. Our study could explain some female reproductive problems due to stress and provide some novel strategies for this disorder.

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Identification of 10 Gene Signatures as Prognostic Biomarkers for Peritoneal Metastatic Gastric Cancer

10.21203/rs.3.rs-1093123/v1 ◽

2021 ◽

Author(s):

Junliang Li ◽

Lingfang Zhang ◽

Tiankang Guo

Keyword(s):

Gastric Cancer ◽

Clustering Algorithm ◽

Transforming Growth Factor ◽

Cox Regression ◽

Risk Groups ◽

Metastatic Gastric Cancer ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

Cox Regression Analysis ◽

Gene Signatures

Abstract Background. Peritoneal metastatic gastric cancer (PMGC) is very common, and usually, the prognosis is poor. There is currently an absence of accurate methods for the early diagnosis and prediction of peritoneal metastasis (PM). This highlights the need to develop strategies to identify the risk of PMGC. Methods. We performed a comprehensive discovery of biomarkers to predict PM by analyzing profiling datasets from GSE62254. The prognostic PM-related genes were obtained using the univariate Cox regression analysis, followed by a least absolute shrinkage and selection operator regression (LASSO) to establish a risk score model. The gene set enrichment analysis (GSEA) was used to determine the pathway enrichment in both the high- and low-risk groups. The 1-, 3-, and 5-year overall survival (OS) rates and area under the receiver operating characteristic curve (ROC) were used to compare the predictive accuracy-based risk stratification. In addition, an unsupervised clustering algorithm was applied to divide patients into subgroups according to the PM-related genes. Results. We identified 10 genes (MMP12, TAC1, TSPYL5, PPP1R14A, TMSB15B, NPY1R, PCDH9, EPM2AIP1, TIG7, and DYNC1I1) for PMGC diagnosis. The OS rates between the high- and low-risk groups at 1-, 3-, and 5-years were significantly different in the training and validation sets. The AUCs at 1-, 3-, and 5-years in the training set were 0.71, 0.74, and 0.73, respectively. In the validation set, the AUCs at 1-, 3-, and 5-years were 0.68, 0.66, and 0.69, respectively. The 10 gene signatures were correlated with immune cell infiltration in both the high- and low-risk groups. In addition, based on the GSEA, several significant pathways were enriched in the high-risk PMGC group, such as the Wnt and transforming growth factor beta (TGF-β) signaling pathway and leukocyte transendothelial migration pathway. Furthermore, unsupervised cluster analysis showed that the model could distinguish the level of risk among patients with PMGC. Conclusions. Overall, 10 gene signatures were identified for PMGC risk prediction. These may be valuable in making clinical decisions to improve treatment outcomes in patients with PMGC.

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Prognostic value of biglycan in gastric cancer

10.21203/rs.3.rs-103093/v1 ◽

2020 ◽

Author(s):

Sizhe Hu ◽

Peipei Li ◽

Chenying Wang ◽

Xiyong Liu

Keyword(s):

Gastric Cancer ◽

Transcription Factors ◽

Poor Prognosis ◽

Prognostic Significance ◽

Bioinformatic Analysis ◽

Gene Set Enrichment Analysis ◽

High Expression ◽

Mrna Levels ◽

Gene Signatures ◽

Kaplan Meier

Abstract Background: BGN (biglycan) is a family member of small leucine-rich repeat proteoglycans. High expression of BGN might enhance the invasion and metastasis in some types of tumors. Here, the prognostic significance of BGN was evaluated in gastric cancer.Material and Methods: Two independent Gene Expression Omnibus (GEO) gastric cancer microarray datasets( n= 64, n=432) were collected for this study. Kaplan-Meier analysis was applied to evaluate if BGN impacts the outcomes of gastric cancer. The gene set enrichment analysis (GSEA) was used to explore BGN and cancer-related gene signatures. Bioinformatic analysis predicted the putative transcription factors of BGN.Results: For gastric cancer, the mRNA expression level of BGN in tumor tissues was significantly higher than that in normal tissues. Kaplan-Meier analysis showed that higher expression of BGN mRNA was significantly associated with more reduced recurrence-free survival (RFS). GSEA results suggested that BGN significantly enriched metastasis and poor prognosis gene signatures, revealing that BGN might be associated with cell proliferation, poor differentiation, high invasiveness of gastric cancer. Meanwhile, the putative transcription factors, including AR, E2F1, and TCF4, weres predicted by bioinformatic analysis and also significantly correlated with expression of BGN in mRNA levels. Conclusion: High expression of BGN mRNA was significantly related to poor prognosis, which suggested BGN was a potential prognostic biomarker and therapeutic target of gastric cancer.

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An analytical and experimental investigation of aerofoil–turbulence interaction noise for plates with spanwise-varying leading edges

Journal of Fluid Mechanics ◽

10.1017/jfm.2019.78 ◽

2019 ◽

Vol 865 ◽

pp. 137-168 ◽

Cited By ~ 12

Author(s):

Lorna J. Ayton ◽

Paruchuri Chaitanya

Keyword(s):

Noise Reduction ◽

Analytic Solution ◽

Piecewise Linear ◽

Separation Of Variables ◽

Leading Edge ◽

Test Case ◽

Far Field ◽

Mean Flow ◽

Flat Plates ◽

Leading Edges

This paper presents an analytic solution for gust–aerofoil interaction noise for flat plates with spanwise-varying periodic leading edges in uniform mean flow. The solution is obtained by solving the linear inviscid equations via separation of variables and the Wiener–Hopf technique, and is suitable for calculating the far-field noise generated by any leading edge with a single-valued piecewise linear periodic spanwise geometry. Acoustic results for homogeneous isotropic turbulent flow are calculated by integrating the single-gust solution over a wavenumber spectrum. The far-sound pressure level is calculated for five test-case geometries; sawtooth serration, slitted $v$-root, slitted $u$-root, chopped peak and square wave, and compared to experimental measurements. Good agreement is seen over a range of frequencies and tip-to-root ratios (varying the sharpness of the serration). The analytic solution is then used to calculate the propagating pressure along the leading edge of the serration for fixed spanwise wavenumbers, i.e. only the contribution to the surface pressure which propagates to the far field. Using these results, two primary mechanisms for noise reduction are discussed; tip and root interference, and a redistribution of energy from cuton modes to cutoff modes. A secondary noise-reduction mechanism due to nonlinear features is also discussed and seen to be particularly important for leading edges with very narrow slits.

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The Effect of Variable Chord Length on Transonic Axial Rotor Performance

Journal of Turbomachinery ◽

10.1115/1.1459734 ◽

2002 ◽

Vol 124 (3) ◽

pp. 351-357 ◽

Cited By ~ 8

Author(s):

William B. Roberts ◽

Albert Armin ◽

George Kassaseya ◽

Kenneth L. Suder ◽

Scott A. Thorp ◽

...

Keyword(s):

Leading Edge ◽

Aerodynamic Performance ◽

Chord Length ◽

Rotor Blades ◽

Civil Aviation ◽

Turbofan Engines ◽

Transonic Compressor ◽

Compressor Rotor ◽

Significant Difference ◽

Leading Edges

Aircraft fan and compressor blade leading edges suffer from atmospheric particulate erosion that reduces aerodynamic performance. Recontouring the blade leading edge region can restore blade performance. This process typically results in blades of varying chord length. The question therefore arises as to whether performance of refurbished fans and compressors could be further improved if blades of varying chord length are installed into the disk in a certain order. To investigate this issue the aerodynamic performance of a transonic compressor rotor operating with blades of varying chord length was measured in back-to-back compressor test rig entries. One half of the rotor blades were the full nominal chord length while the remaining half of the blades were cut back at the leading edge to 95% of chord length and recontoured. The rotor aerodynamic performance was measured at 100, 80, and 60% of design speed for three blade installation configurations: nominal-chord blades in half of the disk and short-chord blades in half of the disk; four alternating quadrants of nominal-chord and short-chord blades; nominal-chord and short-chord blades alternating around the disk. No significant difference in performance was found between configurations, indicating that blade chord variation is not important to aerodynamic performance above the stall chord limit if leading edges have the same shape. The stall chord limit for most civil aviation turbofan engines is between 94–96% of nominal (new) blade chord.

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