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Displaying Results 1 - 13 of 13 on page 1 of 1

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3D multi-agent models for protein release from PLGA spherical particles with complex inner morphologies (2008)

Barat, Ana; Ruskin, Heather J.; Crane, Martin

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Anti-angiogenic drug scheduling optimisation with application to colorectal cancer. (2018)

Sturrock, Marc; Miller, Ian S; Kang, Guiyeom; Hannis Arba'ie, N; O'Farrell, A...

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Apelin: A putative novel predictive biomarker for bevacizumab response in colorectal cancer. (2017)

Zuurbier, Linda; Rahman, Arman; Cordes, Martijn; Scheick, Jennifer; Wong, Tse J; Rusten...

Apelin: A putative novel predictive biomarker for bevacizumab response in colorectal cancer. (2017)

Zuurbier, Linda; Rahman, Arman; Cordes, Martijn; Scheick, Jennifer; Wong, Tse J; Rustenburg, François; Joseph, Jesu C; Dynoodt, Peter; Casey, Rory; Drillenburg, Paul; Gerhards, Michael; Barat, Ana; Klinger, Rut; Fender, Bozena; O'Connor, Darran P; Betge, Johannes; Ebert, Matthias P; Gaiser, Timo; Prehn, Jochen HM; Griffioen, Arjan W

Abstract:

The original article is available at http://www.oncotarget.com
Bevacizumab (bvz) is currently employed as an anti-angiogenic therapy across several cancer indications. Bvz response heterogeneity has been well documented, with only 10-15% of colorectal cancer (CRC) patients benefitting in general. For other patients, clinical efficacy is limited and side effects are significant. This reinforces the need for a robust predictive biomarker of response. To identify such a biomarker, we performed a DNA microarray-based transcriptional profiling screen with primary endothelial cells (ECs) isolated from normal and tumour colon tissues. Thirteen separate populations of tumour-associated ECs and 10 of normal ECs were isolated using fluorescence-activated cell sorting. We hypothesised that VEGF-induced genes were overexpressed in tumour ECs; these genes could relate to bvz response and serve as potential predictive biomarkers. Transcriptional profiling revealed ...

https://epubs.rcsi.ie/physiolart/120

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Colorectal tumour simulation using agent based modelling and high performance computing (2016)

Kang, Guiyeom; Márquez, Claudio; Barat, Ana; Byrne, Annette T; Prehn, Jochen HM; Sorrib...

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Copy number load predicts outcome of metastatic colorectal cancer patients receiving bevacizumab combination therapy. (2018)

Smeets, Dominiek; Miller, Ian S; O'Connor, Darran P; Das, Sudipto; Moran, Bruce; B...

Copy number load predicts outcome of metastatic colorectal cancer patients receiving bevacizumab combination therapy. (2018)

Smeets, Dominiek; Miller, Ian S; O'Connor, Darran P; Das, Sudipto; Moran, Bruce; Boeckx, Bram; Gaiser, Timo; Betge, Johannes; Barat, Ana; Klinger, Rut; van Grieken, Nicole CT; Cremolini, Chiara; Prenen, Hans; Mazzone, Massimiliano; Depreeuw, Jeroen; Bacon, Orna; Fender, Bozena; Brady, Joseph; Hennessy, Bryan T; McNamara, Deborah A

Abstract:

The original article is available at <a href="https://www.nature.com">www.nature.com</a>
Increased copy number alterations (CNAs) indicative of chromosomal instability (CIN) have been associated with poor cancer outcome. Here, we study CNAs as potential biomarkers of bevacizumab (BVZ) response in metastatic colorectal cancer (mCRC). We cluster 409 mCRCs in three subclusters characterized by different degrees of CIN. Tumors belonging to intermediate-to-high instability clusters have improved outcome following chemotherapy plus BVZ versus chemotherapy alone. In contrast, low instability tumors, which amongst others consist of POLE-mutated and microsatellite-instable tumors, derive no further benefit from BVZ. This is confirmed in 81 mCRC tumors from the phase 2 MoMa study involving BVZ. CNA clusters overlap with CRC consensus molecular subtypes (CMS); CMS2/4 xenografts correspond to intermediate-to-high instability clusters and res...

https://epubs.rcsi.ie/physiolart/152

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Integrating Colon Cancer Microarray Data: Associating Locus-Specific Methylation Groups to Gene Expression-Based Classifications (2015)

Barat, Ana; Ruskin, Heather J; Byrne, Annette T; Prehn, Jochen HM

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Probabilistic methods for drug dissolution. Part 2. Modelling a soluble binary drug delivery system dissolving in vitro. (2006)

Barat, Ana; Ruskin, Heather J.; Crane, Martin

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Probabilistic models for dissolution of ethylcellulose coated microsphere (2010)

Bezbradica, Marija; Barat, Ana; Ruskin, Heather J.; Crane, Martin

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Probabilistic models for dissolution of ethylcellulose coated microspheres (2010)

Bezbradica, Marija; Barat, Ana; Ruskin, Heather J.; Crane, Martin

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Probabilistic models for drug dissolution (2006)

Barat, Ana

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Probabilistic models for drug dissolution. Part 1. Review of Monte Carlo and stochastic cellular automata approaches. (2006)

Barat, Ana; Ruskin, Heather J.; Crane, Martin

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Quantitative multi-agent models for simulating protein release from PLGA bioerodible nano- and microspheres (2008)

Barat, Ana; Crane, Martin; Ruskin, Heather J.

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Simultaneous miRNA and mRNA transcriptome profiling of human myoblasts reveals a novel set of myogenic differentiation-associated miRNAs and their target genes (2013)

Dmitriev, Petr; Barat, Ana; Polesskaya, Anna; O’Connell, Mary J; Robert, Thomas; Dessen...

Simultaneous miRNA and mRNA transcriptome profiling of human myoblasts reveals a novel set of myogenic differentiation-associated miRNAs and their target genes (2013)

Dmitriev, Petr; Barat, Ana; Polesskaya, Anna; O’Connell, Mary J; Robert, Thomas; Dessen, Philippe; Walsh, Thomas A; Lazar, Vladimir; Turki, Ahmed; Carnac, Gilles; Laoudj-Chenivesse, Dalila; Lipinski, Marc; Vassetzky, Yegor S

Abstract:

Abstract Background miRNA profiling performed in myogenic cells and biopsies from skeletal muscles has previously identified miRNAs involved in myogenesis. Results Here, we have performed miRNA transcriptome profiling in human affinity-purified CD56+ myoblasts induced to differentiate in vitro. In total, we have identified 60 miRNAs differentially expressed during myogenic differentiation. Many were not known for being differentially expressed during myogenic differentiation. Of these, 14 (miR-23b, miR-28, miR-98, miR-103, miR-107, miR-193a, miR-210, miR-324-5p, miR-324-3p, miR-331, miR-374, miR-432, miR-502, and miR-660) were upregulated and 6 (miR-31, miR-451, miR-452, miR-565, miR-594 and miR-659) were downregulated. mRNA transcriptome profiling performed in parallel resulted in identification of 6,616 genes differentially expressed during myogenic differentiation. Conclusions This simultaneous miRNA...

http://dx.doi.org/10.1186/1471-2164-14-265

Displaying Results 1 - 13 of 13 on page 1 of 1

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