A comparative study of topology-based pathway enrichment analysis methods

Ma, Jing; Shojaie, Ali; Michailidis, George

doi:10.1186/s12859-019-3146-1

Cited by 68 publications

(58 citation statements)

References 49 publications

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“…The first enzyme, β-gal, hydrolyses fluoresceindi-β-galactopyranoside (FGP) into fluorescein and galactose; in the absence of glucose, GOx can oxidize galactose and produce hydrogen peroxide (H 2 O 2 ), [72] which is used by HRP to oxidize Amplex Red (AR) into resorufin. This cascade performed by well-known enzymes allows accurate identification of which phenomena are due to diffusion; [73][74][75] additionally, the choice of FGP instead of the canonical lactose allows two reactions to be followed fluorometrically, and to infer the behavior of the middle one that does not produce fluorescent species, thus providing a deeper insight as to how enzyme activities were affected by the three-step cascade in confined spaces. Moreover, we kept the focus on maintaining the relative enzymatic concentrations constant for highlighting the versatility of our system in providing the many possible physical segregation and combinations for studying a multi-step cascade reaction.…”

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confidence: 99%

Combinatorial Strategy for Studying Biochemical Pathways in Double Emulsion Templated Cell‐Sized Compartments

et al. 2020

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optimize these pathways and thus to guarantee their maximum chance of survival, cells produce enzymes at precise and constant rates. [4] However, because of cellular complexity, determination of optimal enzyme levels is still unclear, in particular because specific enzymatic functions are strongly interconnected with their cascade effects. [5] A smart manner to study the behavior of enzymes, when involved in complex reactions, consists of taking advantage of synthetic micrometer-sized compartments shaped into spherical architectural bodies. [6-8] Though these idealized models favor even partitioning of membrane proteins and simplify diffusion gradients, similarly to cells, they provide the desired membrane selectivity and permeability. [9,10] Single specific functions have been presented by combining enzymes (the catalytic compounds) with synthetic supramolecular assemblies, either intrinsically semipermeable, such as lipid-coated porous silica particles, [11] protein cages, [12] layer-by-layer capsules, [13-15] and polydopamine capsules, [16,17] or rendered permeable by the insertion of biopores/membrane proteins (acting as "gates" for the passage of molecules), as in lipid-based [7,18,19] or polymer-based [8,20-22] giant unilamellar vesicles (GUVs). At present, GUVs formed with amphiphilic block copolymers are particularly appealing because they provide enhanced structural membrane properties compared to lipids, since they possess compartments with higher chemical versatility, controlled permeability, robustness, and stability. [23] Nevertheless, common approaches to form polymer GUVs by self-assembly, as electroformation [24] and film-rehydration, [25] rely on the statistical process of encapsulation of biomolecules with a probability of finding the designed amount of one type of enzyme inside the compartments ranging from 12-57%. In the context of elementary biochemical pathways where at least two enzymes are present, this scenario is even more unsatisfactory, with co-encapsulation of two enzymes inside one compartment as low as 10-22%. [26,27] These shortcomings are worsened by the fact that these probabilities have a large uncertainty induced by specific properties of enzymes (e.g., solubility and stability). To date, scientists have struggled to work with stateof-the-art average values for number/mass of enzymes that are vastly non-representative (limited by a small sample size) Cells rely upon producing enzymes at precise rates and stoichiometry for maximizing functionalities. The reasons for this optimal control are unknown, primarily because of the interconnectivity of the enzymatic cascade effects within multi-step pathways. Here, an elegant strategy for studying such behavior, by controlling segregation/combination of enzymes/ metabolites in synthetic cell-sized compartments, while preserving vital cellular elements is presented. Therefore, compartments shaped into polymer GUVs are developed, producing via high-precision double-emulsion microfluidics that enable: i) tight control over the absolute and...

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confidence: 99%

Combinatorial Strategy for Studying Biochemical Pathways in Double Emulsion Templated Cell‐Sized Compartments

et al. 2020

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“…All studies were Phase I biomarker discovery studies. Of the 30 included studies, 18 were from Asia and the Far East [8,9,[11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26], seven from Europe [27][28][29][30][31][32][33], three from North America [34][35][36], and two from the Middle East [37,38]. ASCC tumour sites identified were the head and neck (n = 17), oesophageal (n = 8), and lung (n = 5).…”

Section: Resultsmentioning

confidence: 99%

“…Data preprocessing included name check against the Human Metabolome Database (HMDB), data checks, and missing values. Parameters used to analyse this data were the hypergeometric test for overrepresentation analysis and the relativebetweenness centrality test for pathway topology analysis based on the KEGG pathway library [18][19][20]. Normalisation was performed using the weighted means of identified metabolite that were increased/decreased in squamous cell carcinoma (SCC) in each sample type.…”

Section: Metabolite Analysismentioning

confidence: 99%

Metabolic Biomarkers of Squamous Cell Carcinoma of the Aerodigestive Tract: A Systematic Review and Quality Assessment

Goh

Antonowicz

Boshier

et al. 2020

Oxidative Medicine and Cellular Longevity

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Introduction. Aerodigestive squamous cell carcinomas (ASCC) constitute a major source of global cancer deaths. Patients typically present with advanced, incurable disease, so new means of detecting early disease are a research priority. Metabolite quantitation is amenable to point-of-care analysis and can be performed in ASCC surrogates such as breath and saliva. The purpose of this systematic review is to summarise progress of ASCC metabolomic studies, with an emphasis on the critical appraisal of methodological quality and reporting. Method. A systematic online literature search was performed to identify studies reporting metabolic biomarkers of ASCC. This review was conducted in accordance with the recommendations of the Cochrane Library and MOOSE guidelines. Results. Thirty studies comprising 2117 patients were included in the review. All publications represented phase-I biomarker discovery studies, and none validated their findings in an independent cohort. There was heterogeneity in study design and methodological and reporting quality. Sensitivities and specificities were higher in oesophageal and head and neck squamous cell carcinomas compared to those in lung squamous cell carcinoma. The metabolic phenotypes of these cancers were similar, as was the kinetics of metabolite groups when comparing blood, tissue, and breath/saliva concentrations. Deregulation of amino acid metabolism was the most frequently reported theme. Conclusion. Metabolite analysis has shown promising diagnostic performance, especially for oesophageal and head and neck ASCC subtypes, which are phenotypically similar. However, shortcomings in study design have led to inconsistencies between studies. To support future studies and ultimately clinical adoption, these limitations are discussed.

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“…For each pathway, the geometric mean of all rankings across different mean changes is taken as the final measure of relative performance. Spreadsheets with disaggregated empirical powers for each pathway, across all the experimental settings, are provided in [32].…”

Section: Ranking Empirical Powersmentioning

confidence: 99%

“…Detailed results for all parameter settings in Excel spreadsheets, together with datasets and R code for reproducing the results of this study can be found in [32].…”

Section: Availability Of Data and Materialsmentioning

confidence: 99%

A Comparative Study of Topology-based Pathway Enrichment Analysis Methods

Shojaie

Michailidis

2019

Preprint

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Background: Pathway enrichment analysis is extensively used in the analysis of Omics data for gaining biological insights into the functional roles of pre-defined subsets of genes, proteins and metabolites. A large number of methods have been proposed in the literature for this task. The vast majority of these methods use as input expression levels of the biomolecules under study together with their membership in pathways of interest. The latest generation of pathway enrichment methods also leverages information on the topology of the underlying pathways, which as evidence from their evaluation reveals, lead to improved sensitivity and specificity. Nevertheless, a systematic empirical comparison of such methods is still lacking, making selection of the most suitable method for a specific experimental setting challenging. This comparative study of nine network-based methods for pathway enrichment analysis aims to provide a systematic evaluation of their performance based on three real data sets with different number of features (genes/metabolites) and number of samples. Results:The findings highlight both methodological and empirical differences across the nine methods. In particular, certain methods assess pathway enrichment due to differences both across expression levels and in the strength of the interconnectedness of the members of the pathway, while others only leverage differential expression levels. In the more challenging setting involving a metabolomics data set, the results show that methods that utilize both pieces of information (with NetGSA being a prototypical one) exhibit superior statistical power in detecting pathway enrichment. Conclusion:The analysis reveals that a number of methods perform equally well when testing large size pathways, which is the case with genomic data. On the other hand, NetGSA that takes into consideration both differential expression of the biomolecules in the pathway, as well as changes in the topology exhibits a superior performance when testing small size pathways, which is usually the case for metabolomics data.

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A comparative study of topology-based pathway enrichment analysis methods

Cited by 68 publications

References 49 publications

Combinatorial Strategy for Studying Biochemical Pathways in Double Emulsion Templated Cell‐Sized Compartments

Combinatorial Strategy for Studying Biochemical Pathways in Double Emulsion Templated Cell‐Sized Compartments

Metabolic Biomarkers of Squamous Cell Carcinoma of the Aerodigestive Tract: A Systematic Review and Quality Assessment

A Comparative Study of Topology-based Pathway Enrichment Analysis Methods

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