Tierney, Ciara (2020) Proteomic Characterisation of Patient Samples Diagnosed with Haematological Malignancies. PhD thesis, National University of Ireland Maynooth.
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Abstract
Multiple myeloma (MM) is the second most commonly diagnosed lymphoid cancer
worldwide, after non-Hodgkin’s lymphoma, and is characterised by the uninhibited
proliferation of terminally differentiated B-lymphocytes. The proliferation of these
mutated plasma cells leads to the secretion of monoclonal proteins, resulting in
mutated heavy/light chain immunoglobulin formation. Characterised by serum
albumin levels, serum beta-2-microglobulin levels and hypercalcemia, renal
impairment, anaemia, bone lesions (CRAB criteria), MM is diagnosed as stage Ⅰ, Ⅱ
or Ⅲ. Even with a multitude of new, novel treatments developed for MM, although
OS has increased significantly, MM is considered an incurable disease as the vast
majority of patients go into relapse. With the use of label-free liquid chromatography
mass spectrometry, proteomic analysis was carried out on MM patient samples with
varying drug resistance. Vinculin, talin-1, filamin A and integrin β3 were identified as
having an increased abundance in drug resistance in 4 of the 6 drugs tested.
Activated RNA polymerase II transcriptional coactivator p15 118 phosphoserine and
heat shock protein 27 phosphoserine 78 were identified as having a changed
abundance between sensitive and resistant patients. Fatty acid binding protein 5 was
detected in saliva as having a significant increase in abundance throughout disease
progression of MM. Macrophage inflammatory protein 1α is predicted to play a
significant role in the development of adverse side effects, after Rsq-VD treatment,
with an observed increased abundance in all patients who developed toxicity
throughout the clinical trial. CD44 is also predicted to have potential as a biomarker
for poor outcome after Rsq-VD treatment. Multiple proteins were identified as
differentially abundant in Group 1 (favourable) to Group 3 (Adverse) in acute myeloid
leukaemia (AML), stromal derived growth factor 1 being of particular interest in this
study. Overall this work shows proteomic techniques can be used to identify potential
biomarkers for haematological malignancies.
Item Type: | Thesis (PhD) |
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Keywords: | Proteomic Characterisation; Patient Samples; Haematological Malignancies; |
Academic Unit: | Faculty of Science and Engineering > Biology |
Item ID: | 16834 |
Depositing User: | IR eTheses |
Date Deposited: | 10 Jan 2023 15:16 |
URI: | https://mural.maynoothuniversity.ie/id/eprint/16834 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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