scholarly journals TMEA: A Thermodynamically Motivated Framework for Functional Characterization of Biological Responses to System Acclimation

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 1030
Author(s):  
Kevin Schneider ◽  
Benedikt Venn ◽  
Timo Mühlhaus

The objective of gene set enrichment analysis (GSEA) in modern biological studies is to identify functional profiles in huge sets of biomolecules generated by high-throughput measurements of genes, transcripts, metabolites, and proteins. GSEA is based on a two-stage process using classical statistical analysis to score the input data and subsequent testing for overrepresentation of the enrichment score within a given functional coherent set. However, enrichment scores computed by different methods are merely statistically motivated and often elusive to direct biological interpretation. Here, we propose a novel approach, called Thermodynamically Motivated Enrichment Analysis (TMEA), to account for the energy investment in biological relevant processes. Therefore, TMEA is based on surprisal analysis, which offers a thermodynamic-free energy-based representation of the biological steady state and of the biological change. The contribution of each biomolecule underlying the changes in free energy is used in a Monte Carlo resampling procedure resulting in a functional characterization directly coupled to the thermodynamic characterization of biological responses to system perturbations. To illustrate the utility of our method on real experimental data, we benchmark our approach on plant acclimation to high light and compare the performance of TMEA with the most frequently used method for GSEA.

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11273
Author(s):  
Lei Yang ◽  
Weilong Yin ◽  
Xuechen Liu ◽  
Fangcun Li ◽  
Li Ma ◽  
...  

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.


2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 302-302
Author(s):  
Namrata Vijayvergia ◽  
Suraj Peri ◽  
Karthik Devarajan ◽  
Jianming Pei ◽  
Yulan Gong ◽  
...  

302 Background: NETs lack mutations in the “classical” signaling pathways but share mutations in regulators of gene expression (Jiao; 2011). We compared gene expression in PD & WD NETs to identify novel targets and biomarkers of differentiation. Methods: High quality RNA, extracted from paraffin blocks of deidentified NETs under an IRB-approved protocol, was profiled using a 770 gene panel (nCounter PanCancer pathway, Nanostring Technologies). The resulting data was used to identify the differentially expressed genes between PD and WD NETs using limma software (Ritchie; 2015). Gene Set Enrichment Analysis (Subramanian; 2005) identified differential pathway enrichment by calculating a Normalized Enrichment Score (NES). Results: Analysis of 16 PD and 23 WD NET samples identified 154 genes as extreme outliers ( > 2 fold up/downregulation between the subtypes). Compared to WD NETS, drug targets of interest overexpressed in PD NETs were histone lysine methyltransferase EZH2, and a cell cycle regulator CHEK1 (6.5x and 8.1x, respectively, p < 0.001). In contrast, serine/threonine protein kinase PAK 3 was upregulated in WD (10.6x, p < 0.001). These and other biomarkers will be further validated by immunolabeling of tissue sections. We also found differential enrichment of canonical pathways in PD versus WD NETs (table). Conclusions: Extreme outlier transcripts identified in PD & WD NETs support investigation of inhibitors of EZH2 (e.g. EPZ6438) and CHEK1 (e.g. LY2606368) in PD and PAK3(e.g. FRAX597) in WD NETs. Genes involved in cell cycle regulation and DNA repair in PD NETs and calcium / G protein coupled receptor signaling in WD NET account for biological differences between the 2 molecular subtypes and warrant future investigation as classifiers for NETs. Our findings provide mechanistic insights into the biology of NET and targets for therapy with direct clinical implications.[Table: see text]


2018 ◽  
Author(s):  
Juhani Aakko ◽  
Sami Pietilä ◽  
Tomi Suomi ◽  
Mehrad Mahmoudian ◽  
Raine Toivonen ◽  
...  

AbstractMetaproteomics is an emerging research area which aims to reveal the functionality of microbial communities – unlike the increasingly popular metagenomics providing insights only on the functional potential. So far, the common approach in metaproteomics has been data-dependent acquisition mass spectrometry (DDA). However, DDA is known to have limited reproducibility and dynamic range with samples of complex microbial composition. To overcome these limitations, we introduce here a novel approach utilizing data-independent acquisition (DIA) mass spectrometry, which has not been applied in metaproteomics of complex samples before. For robust analysis of the data, we introduce an open-source software package diatools, which is freely available at Docker Hub and runs on various operating systems. Our highly reproducible results on laboratory-assembled microbial mixtures and human fecal samples support the utility of our approach for functional characterization of complex microbiota. Hence, the approach is expected to dramatically improve our understanding on the role of microbiota in health and disease.


Endocrinology ◽  
2012 ◽  
Vol 153 (8) ◽  
pp. 3679-3691 ◽  
Author(s):  
Yunguang Tong ◽  
Yun Zheng ◽  
Jin Zhou ◽  
Nelson M. Oyesiku ◽  
H. Phillip Koeffler ◽  
...  

Although prolactinomas can be effectively treated with dopamine agonists, about 20% of patients develop dopamine resistance or tumor recurrence after surgery, indicating a need for better understanding of underlying disease mechanisms. Although estrogen-induced rat prolactinomas have been widely used to investigate the development of this tumor, the extent that the model recapitulates features of human prolactinomas is unclear. To prioritize candidate genes and gene sets regulating human and rat prolactinomas, microarray results derived from human prolactinomas and pituitaries of estrogen-treated ACI rats were integrated and analyzed. A total of 4545 differentially expressed pituitary genes were identified in estrogen-treated ACI rats [false discovery rate (FDR) &lt; 0.01]. By comparing pituitary microarray results derived from estrogen-treated Brown Norway rats (a strain not sensitive to estrogen), 4073 genes were shown specific to estrogen-treated ACI rats. Human prolactinomas exhibited 1177 differentially expressed genes (FDR &lt; 0.05). Combining microarray data derived from human prolactinoma and pituitaries of estrogen-treated ACI rat, 145 concordantly expressed genes, including E2F1, Myc, Igf1, and CEBPD, were identified. Gene set enrichment analysis revealed that 278 curated pathways and 59 gene sets of transcription factors were enriched (FDR &lt; 25%) in estrogen-treated ACI rats, suggesting a critical role for Myc, E2F1, CEBPD, and Sp1 in this rat prolactinoma. Similarly increased Myc, E2F1, and Sp1 expression was validated using real-time PCR and Western blot in estrogen-treated Fischer rat pituitary glands. In summary, characterization of individual genes and gene sets in human and in estrogen-induced rat prolactinomas validates the model and provides insights into genomic changes associated with this commonly encountered pituitary tumor.


2021 ◽  
Author(s):  
Nicol Mecozzi ◽  
Arianna Nenci ◽  
Olga Vera ◽  
Aimee Falzone ◽  
Gina M DeNicola ◽  
...  

Circular RNAs (circRNAs) are a class of non-coding RNAs that feature a covalently closed ring structure formed through backsplicing. circRNAs are broadly expressed and contribute to biological processes through a variety of functions. Standard gain-of-function and loss-of-function approaches to study gene functions have significant limitations when studying circRNAs. Overexpression studies in particular suffer from the lack of efficient genetic tools. While mammalian expression plasmids enable transient overexpression of circRNAs in cultured cells, most cell biological studies require long-term ectopic expression. Here we report the development and characterization of genetic tools enabling stable circRNA overexpression in vitro and in vivo. We demonstrated that circRNA expression constructs can be delivered to cultured cells via transposons, whereas lentiviral vectors have limited utility for the delivery of circRNA constructs. We further showed that circRNA transposons can be supplied to mouse livers via hydrodynamic tail vein injection, resulting in ectopic circRNA expression in a hepatocellular carcinoma mouse model. Furthermore, we generated genetically engineered mice harboring circRNA expression constructs. We demonstrate that this approach enables constitutive, global circRNA overexpression as well as inducible circRNA expression directed specifically to melanocytes in a melanoma mouse model. Overall, these tools expand the genetic toolkit available for the functional characterization of circRNAs of interest.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 4572-4572
Author(s):  
Mark Farha ◽  
Randy Vince ◽  
Srinivas Nallandhighal ◽  
Judith Stangl-Kremser ◽  
Steven Goldenthal ◽  
...  

4572 Background: Metastatic clear cell renal cell carcinoma (ccRCC) has a 5-year survival of 12%, but the number of approved immune checkpoint blockade (ICB) agents is growing, necessitating the need to better identify responders. The composition and role of the tumor immune microenvironment (TIME) has yet to be comprehensively characterized in ccRCC. Here, we leveraged a genomic data driven approach to characterize TIME subtypes in ccRCC. Methods: Whole transcriptome data from patients with local and metastatic disease in the Cancer Genome Atlas KIRC (TCGA-KIRC) project was utilized (n = 537). CIBERSORT was used for immune cell deconvolution, and unsupervised hierarchical clustering divided the cohort based on similar immune profiles. Progression free (PFS) and overall (OS) survival of each cluster was analyzed, and Gene Set Enrichment analysis was performed among clusters. The tumor immune dysfunction and exclusion (TIDE) tool, which uses a genomic signature validated on immunotherapy treated melanoma patients to model tumor immune evasion, was then used to predict response to ICB in the TCGA-KIRC clusters. Results: There was a distinct M0hi cluster identified which demonstrated a higher proportion of patients with stage III/IV disease, decreased PFS and OS (Table). Additionally, the M0hi cluster was characterized by lower PD-L1 expression (ANOVA, p = 0.0045) and an enrichment of epithelial to mesenchymal transition (EMT) hallmark genes [Enrichment Score = 0.64, p = 0.001]. The M0hi cluster also showed a higher degree of T-Cell Exclusion (ANOVA, p = 2.2x10-16), predominance of Cancer Associated Fibroblasts (CAFs; ANOVA, p = 2.2x10-16) and Myeloid Derived Suppressor Cells (MDSCs; ANOVA, p = 4.1x10-10). The M0hi cluster had the lowest predicted response to immunotherapy using the TIDE tool (Table). Conclusions: Comprehensive characterization of the TCGA-KIRC cohort led to identification of a distinct cluster of ccRCC defined molecularly by decreased PD-L1 and increased EMT gene expression and cellularly by enrichment of M0 macrophages, CAFs, MDSCs, and an exclusion of T Cells. Patients within this cluster exhibited aggressive disease and poor predicted response to ICB. These findings warrant further validation to identify appropriate therapeutic approaches for this ccRCC subgroup.[Table: see text]


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 3448-3448
Author(s):  
Harumi Kato ◽  
Kazuhito Yamamoto ◽  
Kennosuke Karube ◽  
Miyuki Katayama ◽  
Shinobu Tsuzuki ◽  
...  

Abstract Abstract 3448 Age-related EBV-associated B-cell lymphoproliferative disorder (AR-EBLPD) is classified as a subtype of diffuse large cell lymphoma (DLBCL) according to the WHO classification. However, molecular genetic characterization of AR-EBLPD remains largely unknown. We studied expression profiles of 5 AR-EBLPD and 8 EB-negative DLBCL samples using the Agilent 44K human oligonucleotide microarray. Total RNA was extracted from fresh-frozen tumor samples. Each microarray slide was converted into datasets using the Agilent Micro Array Scanner and Feature extractions. Data was standardized with Z-scores. Differences in mRNA expression levels between two sample groups were calculated using a two-sided t-test. A total of 1973 probes showed a p-value less than 0.05 with less than a 25% false discovery rate (FDR). These probes included 1688 genes. The number of probes showing high expression in AR-EBLPD and EB-negative DLBCL was 804 (693 genes) and 1169 (995 genes), respectively. First, we selected the top 300 differentially expressed genes. Genes highly expressed in AR-EBLPD included IL6, TNFAIP3, HOPX, and SLAMF1. IL6 is known as a gene encoding a cytokine which functions in inflammation and the maturation of B lymphocytes, and TNFAIP3 is known as a negative regulatory gene of the NF-kB pathway. HOPX and SLAMF1 are reported as genes related to lymphocyte function or the immune system (Schwartzberg et al. Nature immunology 2009, Hawiger et al. Nature immunology 2011). For better characterization, we next performed Gene Ontology Analysis using the WEB-based GEne SeT AnaLysis Toolkit and found that categories of external stimulus and inflammatory responses were enriched in AR-EBLPD. The Kyoto Encyclopedia of Genes and Genomes (KEGG)-signaling analyses showed that pathways of the NOD-like receptor (p-value =1.30e-06), JAK-STAT (p-value =9.01e-06), and Toll-like receptor (p-value =0.0002) were characteristic of AR-EBLPD. These results implied that inflammation would be prominent in AR-EBLPD cases. For validation, we next performed Gene Set Enrichment Analysis (GSEA) using all the database of KEGG pathways (186 gene sets). Dominant gene sets in AR-EBLPD included the cytokine-cytokine receptor interaction [Normalized Enrichment Score (NES) =2.66, p-value<0.001], NOD-like receptor pathway (NES =2.26, p-value<0.001), TOLL-like receptor pathway (NES =2.14, p-value<0.001), and JAK-STAT pathway (NES =1.79, p-value<0.001). Since all the pathways were related to the NF-kB pathway, inflammatory responses were suggested to activate the NF-kB pathway or vice versa. For confirmation, we finally performed GSEA using gene sets of the NF-kB pathway, which were obtained from a gene set reported by an NIH group (Puente et al. Nature 2011) and 30 gene sets in the GSEA database, and found that the gene sets of the NF-kB pathway were enriched in AR-EBLPD (Figure 1). Our results suggested that the inflammatory and immune-related genes were enriched in AR-EBLPD and that activation of the genes may be associated with NF-kB activation. Aberrant immune and inflammatory responses could define the clinical presentations of AR-EBLPD cases. (Figure 1) Gene Set Enrichment Analysis of 5 AR-EBLPD and 8 EB-negative DLBCL samples. The NF-kB signature reported from an NIH group (Puente et al. Nature 2011) was enriched in AR-EBLPD [Normalized Enrichment Score (NES) =2.20, p-value<0.001]. Disclosures: No relevant conflicts of interest to declare.


2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Suzana Makpol ◽  
Azalina Zainuddin ◽  
Kien Hui Chua ◽  
Yasmin Anum Mohd Yusof ◽  
Wan Zurinah Wan Ngah

The effect ofγ-tocotrienol, a vitamin E isomer, in modulating gene expression in cellular aging of human diploid fibroblasts was studied. Senescent cells at passage 30 were incubated with 70 μM ofγ-tocotrienol for 24 h. Gene expression patterns were evaluated using Sentrix HumanRef-8 Expression BeadChip from Illumina, analysed using GeneSpring GX10 software, and validated using quantitative RT-PCR. A total of 100 genes were differentially expressed (P<0.001) by at least 1.5 fold in response toγ-tocotrienol treatment. Amongst the genes wereIRAK3, SelS, HSPA5, HERPUD1, DNAJB9, SEPR1, C18orf55, ARF4, RINT1, NXT1, CADPS2, COG6, andGLRX5. Significant gene list was further analysed by Gene Set Enrichment Analysis (GSEA), and the Normalized Enrichment Score (NES) showed that biological processes such as inflammation, protein transport, apoptosis, and cell redox homeostasis were modulated in senescent fibroblasts treated withγ-tocotrienol. These findings revealed thatγ-tocotrienol may prevent cellular aging of human diploid fibroblasts by modulating gene expression.


2018 ◽  
Author(s):  
Rani K. Powers ◽  
Andrew Goodspeed ◽  
Harrison Pielke-Lombardo ◽  
Aik-Choon Tan ◽  
James C. Costello

AbstractMotivationGene Set Enrichment Analysis (GSEA) is routinely used to analyze and interpret coordinate changes in transcriptomics experiments. For an experiment where less than seven samples per condition are compared, GSEA employs a competitive null hypothesis to test significance. A gene set enrichment score is tested against a null distribution of enrichment scores generated from permuted gene sets, where genes are randomly selected from the input experiment. Looking across a variety of biological conditions, however, genes are not randomly distributed with many showing consistent patterns of up- or down-regulation. As a result, common patterns of positively and negatively enriched gene sets are observed across experiments. Placing a single experiment into the context of a relevant set of background experiments allows us to identify both the common and experiment-specific patterns of gene set enrichment.ResultsWe compiled a compendium of 442 small molecule transcriptomic experiments and used GSEA to characterize common patterns of positively and negatively enriched gene sets. To identify experiment-specific gene set enrichment, we developed the GSEA-InContext method that accounts for gene expression patterns within a user-defined background set of experiments to identify statistically significantly enriched gene sets. We evaluated GSEA-InContext on experiments using small molecules with known targets and show that it successfully prioritizes gene sets that are specific to each experiment, thus providing valuable insights that complement standard GSEA analysis.Availability and ImplementationGSEA-InContext is implemented in Python. Code, the background expression compendium, and results are available at: https://github.com/CostelloLab/GSEA-InContext


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