Eithne Costello
University of Liverpool
CancerInternal medicinePathologyOncologyCA19-9Single-nucleotide polymorphismMolecular biologyStromal cellImmunologyPancreatitisPancreatic diseasePancreasDiseasePancreatic cancerGemcitabinePancreatic ductal adenocarcinomaCancer researchDiabetes mellitusBioinformaticsMedicineBiologyGastroenterology
225Publications
51H-index
6,162Citations
Publications 218
Newest
#1Dana K. AndersenH-Index: 21
#2Suresh T. ChariH-Index: 103
Last. Stephen J. PandolH-Index: 74
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#1Manuel Gentiluomo (UniPi: University of Pisa)H-Index: 6
#2C. Corradi (UniPi: University of Pisa)H-Index: 1
Last. Gabriele Capurso (UniSR: Vita-Salute San Raffaele University)H-Index: 56
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Although pancreatic ductal adenocarcinoma (PDAC) survival is poor, there are differences in patients' response to the treatments. Detection of predictive biomarkers explaining these differences is of the utmost importance. In a recent study two genetic markers (CD44-rs353630 and CHI3L2-rs684559) were reported to be associated with survival after PDAC resection. We attempted to replicate the associations in 1856 PDAC patients (685 resected with stage I/II) from the PANcreatic Disease ReseArch (PA...
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#1Milton Ashworth (University of Liverpool)H-Index: 1
#2Benjamin Small (University of Liverpool)
Last. Eithne Costello (University of Liverpool)H-Index: 51
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Accurate blood-borne biomarkers are sought for diagnosis, prognosis and treatment stratification. Consistent handling of blood is essential for meaningful data interpretation, however, delays during processing are occasionally unavoidable. We investigated the effects of immediately placing blood samples on ice versus room temperature for 1 h (reference protocol), and holding samples on ice versus room temperature during a 3 h delay to processing. Using Luminex multi-plex assays to assess cytokin...
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BACKGROUND: Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. METHODS: We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additio...
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#1Silvana Debernardi (QMUL: Queen Mary University of London)H-Index: 17
#2Harrison O’Brien (QMUL: Queen Mary University of London)H-Index: 1
Last. Tatjana Crnogorac-Jurcevic (QMUL: Queen Mary University of London)H-Index: 34
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Publisher Copyright: © 2020 Debernardi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
1 CitationsSource
#1Lucy OldfieldH-Index: 4
#2Rohith RaoH-Index: 1
Last. Eithne CostelloH-Index: 51
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#1Lucy OldfieldH-Index: 4
#2Rohith RaoH-Index: 1
Last. Eithne CostelloH-Index: 51
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#2Anthony EvansH-Index: 4
Last. William GreenhalfH-Index: 50
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#1Anthony EvansH-Index: 4
Last. William GreenhalfH-Index: 50
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