ORCID Profile
0000-0003-0287-8899
Current Organisation
Royal College of Surgeons in Ireland
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Publisher: Frontiers Media SA
Date: 26-02-2019
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.C.6530519.V1
Abstract: AbstractPurpose: Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers. Experimental Design: Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment. Results: Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal i EPHA2 /i expression is associated with REG resistance. Conclusions: Subtype classification systems represent canonical “ i termini a quo /i ” (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors. /
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22480721.V1
Abstract: Supplementary Figures S1 - S8 and Table S1. Fig S1: Analysis of copy number burden in a PDX population trial of REG treated mCRC PDXs. Fig S2: Effect of REG on microvessel density and proliferation according to CNA cluster. Fig S3 - S6: BCL-2 family profiling of mCRC PDX models via quantitative Western blotting. Fig S7: RPPA protein scores indicating proteins' association with the PDX models' response to REG. Fig S8: Western blot validation of differential EPHA2 protein expression between REG post- and pre-treatment progressor and non-progressor PDX models. Table S1: List of antibodies and dilution factors used against desired targets in RPPA analysis.
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.22480721
Abstract: Supplementary Figures S1 - S8 and Table S1. Fig S1: Analysis of copy number burden in a PDX population trial of REG treated mCRC PDXs. Fig S2: Effect of REG on microvessel density and proliferation according to CNA cluster. Fig S3 - S6: BCL-2 family profiling of mCRC PDX models via quantitative Western blotting. Fig S7: RPPA protein scores indicating proteins' association with the PDX models' response to REG. Fig S8: Western blot validation of differential EPHA2 protein expression between REG post- and pre-treatment progressor and non-progressor PDX models. Table S1: List of antibodies and dilution factors used against desired targets in RPPA analysis.
Publisher: Springer Science and Business Media LLC
Date: 10-12-2015
DOI: 10.1038/BJC.2015.420
Publisher: Wiley
Date: 2020
DOI: 10.1111/IMJ.14692
Publisher: Elsevier BV
Date: 04-2013
DOI: 10.1016/J.BIOMATERIALS.2012.12.032
Abstract: The biodegradable polymer medium chain length polyhydroxyalkanoate (mclPHA), produced by Pseudomonas putida CA-3, was depolymerised and the predominant monomer (R)-3-hydroxydecanoic acid (R10) purified. R10 was conjugated to a d-peptide DP18 and its derivatives. All peptides conjugated with R10 exhibited greater anti-cancer activity compared to the unconjugated peptides. Unconjugated and conjugated peptides were cytocidal for cancer cells. Conjugation of R10 to peptides was essential for enhanced anti-proliferation activity, as unconjugated mixes did not result in enhancement of anti-cancer activity. The conjugation of R10 resulted in more rapid uptake of peptides into HeLa and MiaPaCa cells compared to unconjugated peptide. Both unconjugated and R10 conjugated peptides localized to the mitochondria of HeLa and MiaPaCa cells and induced apoptosis. Peptide conjugated with a terminally hydroxylated decanoic acid (ω-hydroxydecanoic acid) exhibited 3.3 and 6.3 fold higher IC(50) values compared to R10 conjugated peptide indicating a role for the position of the hydroxyl moiety in enhancement of anti-cancer activity. Conjugation of decanoic acid (C10) to peptides resulted in similar or higher IC(50) values compared to R10 conjugates but C10 conjugates did not exhibit any cancer selectivity. Combination studies showed that R10DP18L exhibited synergy with cisplatin, gemcitabine, and taxotere with IC(50) values in the nanomolar range.
Publisher: American Association for Cancer Research (AACR)
Date: 23-08-2021
DOI: 10.1158/1078-0432.CCR-21-0818
Abstract: Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers. Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment. Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal EPHA2 expression is associated with REG resistance. Subtype classification systems represent canonical “termini a quo” (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors.
Publisher: MDPI AG
Date: 12-12-2019
Abstract: Glioblastoma (GBM) is the most common primary brain tumor with no available cure. As previously described, seliciclib, a first-generation cyclin-dependent kinase (CDK) inhibitor, down-regulates the anti-apoptotic protein, Mcl-1, in GBM, thereby sensitizing GBM cells to the apoptosis-inducing effects of the death receptor ligand, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). Here, we have assessed the efficacy of seliciclib when delivered in combination with the antibody against human death receptor 5, drozitumab, in clinically relevant patient-derived xenograft (PDX) models of GBM. A reduction in viability and significant levels of apoptosis were observed in vitro in human GBM neurospheres following treatment with seliciclib plus drozitumab. While the co-treatment strategy induced a similar effect in PDX models, the dosing regimen required to observe seliciclib-targeted responses in the brain, resulted in lethal toxicity in 45% of animals. Additional studies showed that the second-generation CDK inhibitor, CYC065, with improved potency in comparison to seliciclib, induced a significant decrease in the size of human GBM neurospheres in vitro and was well tolerated in vivo, upon administration at clinically relevant doses. This study highlights the continued need for robust pre-clinical assessment of promising treatment approaches using clinically relevant models.
Publisher: MDPI AG
Date: 14-10-2020
Abstract: Resistance to chemotherapy often results from dysfunctional apoptosis, however multiple proteins with overlapping functions regulate this pathway. We sought to determine whether an extensively validated, deterministic apoptosis systems model, ‘DR_MOMP’, could be used as a stratification tool for the apoptosis sensitiser and BCL-2 antagonist, ABT-199 in patient-derived xenograft (PDX) models of colorectal cancer (CRC). Through quantitative profiling of BCL-2 family proteins, we identified two PDX models which were predicted by DR_MOMP to be sufficiently sensitive to 5-fluorouracil (5-FU)-based chemotherapy (CRC0344), or less responsive to chemotherapy but sensitised by ABT-199 (CRC0076). Treatment with ABT-199 significantly improved responses of CRC0076 PDXs to 5-FU-based chemotherapy, but showed no sensitisation in CRC0344 PDXs, as predicted from systems modelling. 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) scans were performed to investigate possible early biomarkers of response. In CRC0076, a significant post-treatment decrease in mean standard uptake value was indeed evident only in the combination treatment group. Radiomic CT feature analysis of pre-treatment images in CRC0076 and CRC0344 PDXs identified features which could phenotypically discriminate between models, but were not predictive of treatment responses. Collectively our data indicate that systems modelling may identify metastatic (m)CRC patients benefitting from ABT-199, and that 18F-FDG-PET could independently support such predictions.
Publisher: Oxford University Press (OUP)
Date: 30-06-2015
Publisher: American Association for Cancer Research (AACR)
Date: 31-03-2023
DOI: 10.1158/1078-0432.C.6530519
Abstract: AbstractPurpose: Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers. Experimental Design: Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment. Results: Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal i EPHA2 /i expression is associated with REG resistance. Conclusions: Subtype classification systems represent canonical “ i termini a quo /i ” (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors. /
Publisher: Elsevier BV
Date: 06-2015
DOI: 10.1016/J.JBIOTEC.2015.02.036
Abstract: Conjugation of DP18L peptide with (R)-3-hydroxydecanoic acid, derived from the biopolymer polyhydroxyalkanoate, enhances its anti-cancer activity (O'Connor et al., 2013. Biomaterials 34, 2710-2718). However, it is unknown if other (R)-3-hydroxyalkanoic acids (R3HAs) can enhance peptide activity, if chain length affects enhancement, and what effect R3HAs have on peptide structure. Here we show that the degree of enhancement of peptide (DP18L) anti-cancer activity by R3HAs is carbon chain length dependent. In all but one ex le the R3HA conjugated peptides were more active against cancer cells than the unconjugated peptides. However, R3HAs with 9 and 10 carbons were most effective at improving DP18L activity. DP18L peptide variant DP17L, missing a hydrophobic amino acid (leucine residue 4) exhibited lower efficacy against MiaPaCa cells. Circular dichroism analysis showed DP17L had a lower alpha helix content and the conjugation of any R3HA ((R)-3-hydroxyhexanoic acid to (R)-3-hydroxydodecanoic acid) to DP17L returned the helix content back to levels of DP18L. However (R)-3-hydroxyhexanoic did not enhance the anti-cancer activity of DP17L and at least 7 carbons were needed in the R3HA to enhance activity of D17L. DP17L needs a longer chain R3HA to achieve the same activity as DP18L conjugated to an R3HA. As a first step to assess the synthetic potential of polyhydroxyalkanoate derived R3HAs, (R)-3-hydroxydecanoic acid was synthetically converted to (±)3-chlorodecanoic acid, which when conjugated to DP18L improved its antiproliferative activity against MiaPaCa cells.
Publisher: Springer Science and Business Media LLC
Date: 2021
DOI: 10.1038/S41588-020-00750-6
Abstract: Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) s les from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion s les within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Annette Byrne.