DiSWOP: a novel measure for cell-level protein network analysis in localized proteomics image data

Kovacheva, Violeta N.; Khan, Asifullah; Khan, Michael; Epstein, D. B. A.; Rajpoot, Nasir M.

doi:10.1093/bioinformatics/btt676

Cited by 9 publications

(9 citation statements)

References 21 publications

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“…Kovacheva et al [ 36 ] introduced the DiSWOP framework for analysing multiplex IF data, such as the one simulated by the model described above. The approach analyses cell phenotypes in normal and cancerous colon tissue imaged using the TIS microscope [ 34 ].…”

Section: Resultsmentioning

confidence: 99%

Subcellular protein expression models for microsatellite instability in colorectal adenocarcinoma tissue images

Kovacheva

Rajpoot

2016

BMC Bioinformatics

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BackgroundNew bioimaging techniques capable of visualising the co-location of numerous proteins within individual cells have been proposed to study tumour heterogeneity of neighbouring cells within the same tissue specimen. These techniques have highlighted the need to better understand the interplay between proteins in terms of their colocalisation.ResultsWe recently proposed a cellular-level model of the healthy and cancerous colonic crypt microenvironments. Here, we extend the model to include detailed models of protein expression to generate synthetic multiplex fluorescence data. As a first step, we present models for various cell organelles learned from real immunofluorescence data from the Human Protein Atlas. Comparison between the distribution of various features obtained from the real and synthetic organelles has shown very good agreement. This has included both features that have been used as part of the model input and ones that have not been explicitly considered. We then develop models for six proteins which are important colorectal cancer biomarkers and are associated with microsatellite instability, namely MLH1, PMS2, MSH2, MSH6, P53 and PTEN. The protein models include their complex expression patterns and which cell phenotypes express them. The models have been validated by comparing distributions of real and synthesised parameters and by application of frameworks for analysing multiplex immunofluorescence image data.ConclusionsThe six proteins have been chosen as a case study to illustrate how the model can be used to generate synthetic multiplex immunofluorescence data. Further proteins could be included within the model in a similar manner to enable the study of a larger set of proteins of interest and their interactions. To the best of our knowledge, this is the first model for expression of multiple proteins in anatomically intact tissue, rather than within cells in culture.

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Section: Resultsmentioning

confidence: 99%

Subcellular protein expression models for microsatellite instability in colorectal adenocarcinoma tissue images

Kovacheva

Rajpoot

2016

BMC Bioinformatics

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“…η ( L v , L u ) = c (c is a constant) if L v ≠ L u , otherwise 0. This algorithm is also applied to cell segmentation in colon fluorescence images [278], where it further eliminates small candidates or merges adjacent regions to constrain subsequent cell phenotype analysis on only distinguishable nuclei.…”

Section: Nucleus and Cell Segmentation Methodsmentioning

confidence: 99%

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

Xing

Yang

2016

IEEE Rev. Biomed. Eng.

430

220

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Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to inter-observer variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literatures. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast (DIC), fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

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“…2 ). Cyclical imaging has been applied to address a variety of biological problems [ 21 – 54 ], and mathematics/informatics approaches to ICM data have been published 19 , 20 , 52 , 55 – 57 . Several editorials 58 , 59 and a research highlight 60 have featured toponome research.…”

Section: Icroscopic M Ethod Fmentioning

confidence: 99%

Advances in toponomics drug discovery: Imaging cycler microscopy correctly predicts a therapy method of amyotrophic lateral sclerosis

Schubert

2015

Cytometry Pt A

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An imaging cycler microscope (ICM) is a fully automated (epi)fluorescence microscope which overcomes the spectral resolution limit resulting in parameter-and dimensionunlimited fluorescence imaging. This enables the spatial resolution of large molecular systems with their emergent topological properties (toponome) in morphologically intact cells and tissues displaying thousands of multi protein assemblies at a time. The resulting combinatorial geometry of these systems has been shown to be key for invivo/in-situ detection of lead proteins controlling protein network topology and (dys)-function: If lead proteins are blocked or downregulated the corresponding disease protein network disassembles. Here, correct therapeutic predictions are exemplified for ALS. ICM drug target studies have discovered an 18-dimensional cell surface molecular system in ALS-PBMC with a lead drug target protein, whose therapeutic downregulation is now reported to show statistically significant effect with stop of disease progression in one third of the ALS patients. Together, this clinical and the earlier experimental validations of the ICM approach indicate that ICM readily discovers in vivo robustness nodes of disease with lead proteins controlling them. Breaking in vivo robustness nodes using drugs against their lead proteins is likely to overcome current high drug attrition rates. V C 2015 The Author. Published by Wiley Periodicals, Inc, on behalf of ISAC.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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DiSWOP: a novel measure for cell-level protein network analysis in localized proteomics image data

Abstract: http://www2.warwick.ac.uk/fac/sci/dcs/research/combi/research/bic/diswop.

Cited by 9 publications

References 21 publications

Subcellular protein expression models for microsatellite instability in colorectal adenocarcinoma tissue images

Subcellular protein expression models for microsatellite instability in colorectal adenocarcinoma tissue images

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

Advances in toponomics drug discovery: Imaging cycler microscopy correctly predicts a therapy method of amyotrophic lateral sclerosis

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