Gene Set Enrichement Analysis beim kolorektalen Karzinom mit hepatischer oder peritonealer Metastasierung

2019 ◽  
Author(s):  
F Bösch ◽  
V Jurinovic ◽  
M Schoenberg ◽  
E Pretzsch ◽  
C Lampert ◽  
...  
Keyword(s):  
2019 ◽  
Vol 16 (5) ◽  
pp. 392-401
Author(s):  
Shengli Zhang ◽  
Zekun Tong ◽  
Haoyu Yin ◽  
Yifan Feng

Background: Finding the pathogenic gene is very important for understanding the pathogenesis of the disease, locating effective drug targets and improving the clinical level of medical treatment. However, the existing methods for finding the pathogenic genes still have limitations, for instance the computational complexity is high, and the combination of multiple genes and pathways has not been considered to search for highly related pathogenic genes and so on. Methods: We propose a pathogenic genes selection model of genetic disease based on Network Motifs Slicing Feedback (NMSF). We find a point set which makes the conductivity of the motif minimum then use it to substitute for the original gene pathway network. Based on the NMSF, we propose a new pathogenic genes selection model to expand pathogenic gene set. Results: According to the gene set we have obtained, selection of key genes will be more accurate and convincing. Finally, we use our model to screen the pathogenic genes and key pathways of liver cancer and lung cancer, and compare the results with the existing methods. Conclusion: The main contribution is to provide a method called NMSF which simplifies the gene pathway network to make the selection of pathogenic gene simple and feasible. The fact shows our result has a wide coverage and high accuracy and our model has good expeditiousness and robustness.


2018 ◽  
Vol 21 (2) ◽  
pp. 74-83
Author(s):  
Tzu-Hung Hsiao ◽  
Yu-Chiao Chiu ◽  
Yu-Heng Chen ◽  
Yu-Ching Hsu ◽  
Hung-I Harry Chen ◽  
...  

Aim and Objective: The number of anticancer drugs available currently is limited, and some of them have low treatment response rates. Moreover, developing a new drug for cancer therapy is labor intensive and sometimes cost prohibitive. Therefore, “repositioning” of known cancer treatment compounds can speed up the development time and potentially increase the response rate of cancer therapy. This study proposes a systems biology method for identifying new compound candidates for cancer treatment in two separate procedures. Materials and Methods: First, a “gene set–compound” network was constructed by conducting gene set enrichment analysis on the expression profile of responses to a compound. Second, survival analyses were applied to gene expression profiles derived from four breast cancer patient cohorts to identify gene sets that are associated with cancer survival. A “cancer–functional gene set– compound” network was constructed, and candidate anticancer compounds were identified. Through the use of breast cancer as an example, 162 breast cancer survival-associated gene sets and 172 putative compounds were obtained. Results: We demonstrated how to utilize the clinical relevance of previous studies through gene sets and then connect it to candidate compounds by using gene expression data from the Connectivity Map. Specifically, we chose a gene set derived from a stem cell study to demonstrate its association with breast cancer prognosis and discussed six new compounds that can increase the expression of the gene set after the treatment. Conclusion: Our method can effectively identify compounds with a potential to be “repositioned” for cancer treatment according to their active mechanisms and their association with patients’ survival time.


2020 ◽  
Vol 15 ◽  
Author(s):  
Chen-An Tsai ◽  
James J. Chen

Background: Gene set enrichment analyses (GSEA) provide a useful and powerful approach to identify differentially expressed gene sets with prior biological knowledge. Several GSEA algorithms have been proposed to perform enrichment analyses on groups of genes. However, many of these algorithms have focused on identification of differentially expressed gene sets in a given phenotype. Objective: In this paper, we propose a gene set analytic framework, Gene Set Correlation Analysis (GSCoA), that simultaneously measures within and between gene sets variation to identify sets of genes enriched for differential expression and highly co-related pathways. Methods: We apply co-inertia analysis to the comparisons of cross-gene sets in gene expression data to measure the costructure of expression profiles in pairs of gene sets. Co-inertia analysis (CIA) is one multivariate method to identify trends or co-relationships in multiple datasets, which contain the same samples. The objective of CIA is to seek ordinations (dimension reduction diagrams) of two gene sets such that the square covariance between the projections of the gene sets on successive axes is maximized. Simulation studies illustrate that CIA offers superior performance in identifying corelationships between gene sets in all simulation settings when compared to correlation-based gene set methods. Result and Conclusion: We also combine between-gene set CIA and GSEA to discover the relationships between gene sets significantly associated with phenotypes. In addition, we provide a graphical technique for visualizing and simultaneously exploring the associations of between and within gene sets and their interaction and network. We then demonstrate integration of within and between gene sets variation using CIA and GSEA, applied to the p53 gene expression data using the c2 curated gene sets. Ultimately, the GSCoA approach provides an attractive tool for identification and visualization of novel associations between pairs of gene sets by integrating co-relationships between gene sets into gene set analysis.


Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 120
Author(s):  
Yiyun Sun ◽  
Dandan Xu ◽  
Chundong Zhang ◽  
Yitao Wang ◽  
Lian Zhang ◽  
...  

We previously demonstrated that proline-rich protein 11 (PRR11) and spindle and kinetochore associated 2 (SKA2) constituted a head-to-head gene pair driven by a prototypical bidirectional promoter. This gene pair synergistically promoted the development of non-small cell lung cancer. However, the signaling pathways leading to the ectopic expression of this gene pair remains obscure. In the present study, we first analyzed the lung squamous cell carcinoma (LSCC) relevant RNA sequencing data from The Cancer Genome Atlas (TCGA) database using the correlation analysis of gene expression and gene set enrichment analysis (GSEA), which revealed that the PRR11-SKA2 correlated gene list highly resembled the Hedgehog (Hh) pathway activation-related gene set. Subsequently, GLI1/2 inhibitor GANT-61 or GLI1/2-siRNA inhibited the Hh pathway of LSCC cells, concomitantly decreasing the expression levels of PRR11 and SKA2. Furthermore, the mRNA expression profile of LSCC cells treated with GANT-61 was detected using RNA sequencing, displaying 397 differentially expressed genes (203 upregulated genes and 194 downregulated genes). Out of them, one gene set, including BIRC5, NCAPG, CCNB2, and BUB1, was involved in cell division and interacted with both PRR11 and SKA2. These genes were verified as the downregulated genes via RT-PCR and their high expression significantly correlated with the shorter overall survival of LSCC patients. Taken together, our results indicate that GLI1/2 mediates the expression of the PRR11-SKA2-centric gene set that serves as an unfavorable prognostic indicator for LSCC patients, potentializing new combinatorial diagnostic and therapeutic strategies in LSCC.


Diversity ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 81
Author(s):  
Jakub Sawicki ◽  
Katarzyna Krawczyk ◽  
Monika Ślipiko ◽  
Monika Szczecińska

The leafy liverwort Nowellia curvifolia is a widespread Holarctic species belonging to the family Cephaloziaceae. It is made up of a newly sequenced, assembled and annotated organellar genomes of two European specimens, which revealed the structure typical for liverworts, but also provided new insights into its microevolution. The plastome of N. curvifolia is the second smallest among photosynthetic liverworts, with the shortest known inverted repeats. Moreover, it is the smallest liverwort genome with a complete gene set, since two smaller genomes of Aneura mirabilis and Cololejeunea lanciloba are missing six and four protein-coding genes respectively. The reduction of plastome size in leafy liverworts seems to be mainly impacted by deletion within specific region between psbA and psbD genes. The comparative intraspecific analysis revealed single SNPs difference among European individuals and a low number of 35 mutations differentiating European and North American specimens. However, the genetic resources of Asian specimen enabled to identify 1335 SNPs in plastic protein-coding genes suggesting an advanced cryptic speciation within N. curvifolia or the presence of undescribed morphospecies in Asia. Newly sequenced mitogenomes from European specimens revealed identical gene content and structure to previously published and low intercontinental differentiation limited to one substitution and three indels. The RNA-seq based RNA editing analysis revealed 17 and 127 edited sites in plastome and mitogenome respectively including one non-canonical editing event in plastid chiL gene. The U to C editing is common in non-seed plants, but in liverwort plastome is reported for the first time.


Author(s):  
Mari K. Halle ◽  
Marte Sødal ◽  
David Forsse ◽  
Hilde Engerud ◽  
Kathrine Woie ◽  
...  

Abstract Background Advanced cervical cancer carries a particularly poor prognosis, and few treatment options exist. Identification of effective molecular markers is vital to improve the individualisation of treatment. We investigated transcriptional data from cervical carcinomas related to patient survival and recurrence to identify potential molecular drivers for aggressive disease. Methods Primary tumour RNA-sequencing profiles from 20 patients with recurrence and 53 patients with cured disease were compared. Protein levels and prognostic impact for selected markers were identified by immunohistochemistry in a population-based patient cohort. Results Comparison of tumours relative to recurrence status revealed 121 differentially expressed genes. From this gene set, a 10-gene signature with high prognostic significance (p = 0.001) was identified and validated in an independent patient cohort (p = 0.004). Protein levels of two signature genes, HLA-DQB1 (n = 389) and LIMCH1 (LIM and calponin homology domain 1) (n = 410), were independent predictors of survival (hazard ratio 2.50, p = 0.007 for HLA-DQB1 and 3.19, p = 0.007 for LIMCH1) when adjusting for established prognostic markers. HLA-DQB1 protein expression associated with programmed death ligand 1 positivity (p < 0.001). In gene set enrichment analyses, HLA-DQB1high tumours associated with immune activation and response to interferon-γ (IFN-γ). Conclusions This study revealed a 10-gene signature with high prognostic power in cervical cancer. HLA-DQB1 and LIMCH1 are potential biomarkers guiding cervical cancer treatment.


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.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yi Chen ◽  
Fons. J. Verbeek ◽  
Katherine Wolstencroft

Abstract Background The hallmarks of cancer provide a highly cited and well-used conceptual framework for describing the processes involved in cancer cell development and tumourigenesis. However, methods for translating these high-level concepts into data-level associations between hallmarks and genes (for high throughput analysis), vary widely between studies. The examination of different strategies to associate and map cancer hallmarks reveals significant differences, but also consensus. Results Here we present the results of a comparative analysis of cancer hallmark mapping strategies, based on Gene Ontology and biological pathway annotation, from different studies. By analysing the semantic similarity between annotations, and the resulting gene set overlap, we identify emerging consensus knowledge. In addition, we analyse the differences between hallmark and gene set associations using Weighted Gene Co-expression Network Analysis and enrichment analysis. Conclusions Reaching a community-wide consensus on how to identify cancer hallmark activity from research data would enable more systematic data integration and comparison between studies. These results highlight the current state of the consensus and offer a starting point for further convergence. In addition, we show how a lack of consensus can lead to large differences in the biological interpretation of downstream analyses and discuss the challenges of annotating changing and accumulating biological data, using intermediate knowledge resources that are also changing over time.


2019 ◽  
Vol 8 (10) ◽  
pp. 1580 ◽  
Author(s):  
Kyoung Min Moon ◽  
Kyueng-Whan Min ◽  
Mi-Hye Kim ◽  
Dong-Hoon Kim ◽  
Byoung Kwan Son ◽  
...  

Ninety percent of patients with scrub typhus (SC) with vasculitis-like syndrome recover after mild symptoms; however, 10% can suffer serious complications, such as acute respiratory failure (ARF) and admission to the intensive care unit (ICU). Predictors for the progression of SC have not yet been established, and conventional scoring systems for ICU patients are insufficient to predict severity. We aimed to identify simple and robust indicators to predict aggressive behaviors of SC. We evaluated 91 patients with SC and 81 non-SC patients who were admitted to the ICU, and 32 cases from the public functional genomics data repository for gene expression analysis. We analyzed the relationships between several predictors and clinicopathological characteristics in patients with SC. We performed gene set enrichment analysis (GSEA) to identify SC-specific gene sets. The acid-base imbalance (ABI), measured 24 h before serious complications, was higher in patients with SC than in non-SC patients. A high ABI was associated with an increased incidence of ARF, leading to mechanical ventilation and worse survival. GSEA revealed that SC correlated to gene sets reflecting inflammation/apoptotic response and airway inflammation. ABI can be used to indicate ARF in patients with SC and assist with early detection.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jovana Maksimovic ◽  
Alicia Oshlack ◽  
Belinda Phipson

AbstractDNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.


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