Amanda Kathleen Miles

Publications (2)5.55 Total impact

• Article: Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.

  Baharak Vafadar-Isfahani, Graham Ball, Clare Coveney, Christophe Lemetre, David Boocock, Lennart Minthon, Oskar Hansson, Amanda Kathleen Miles, Sabina M Janciauskiene, Donald Warden, A David Smith, Gordon Wilcock, Noor Kalsheker, Robert Rees, Balwir Matharoo-Ball, Kevin Morgan
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  ABSTRACT: We have used proteomic fingerprinting to investigate diagnosis of Alzheimer's disease (AD). Samples of lumbar cerebrospinal fluid (CSF) from clinically-diagnosed AD cases (n = 33), age-matched controls (n = 20), and mild cognitive impairment (MCI) patients (n = 10) were used to obtain proteomic profiles, followed by bioinformatic analysis that generated a set of potential biomarkers in CSF samples that could discriminate AD cases from controls. The identity of the biomarker ions was determined using mass spectroscopy. The panel of seven peptide biomarker ions was able to discriminate AD patients from controls with a median accuracy of 95% (sensitivity 85%, specificity 97%). When this model was applied to an independent blind dataset from MCI patients, the intensity of signals was intermediate between the control and AD patients implying that these markers could potentially predict patients with early neurodegenerative disease. The panel were identified, in order of predictive ability, as SPARC-like 1 protein, fibrinogen alpha chain precursor, amyloid-β, apolipoprotein E precursor, serum albumin precursor, keratin type I cytoskeletal 9, and tetranectin. The 7 ion ANN model was further validated using an independent cohort of samples, where the model was able to classify AD cases from controls with median accuracy of 84.5% (sensitivity 93.3%, specificity 75.7%). Validation by immunoassay was performed on the top three identified markers using the discovery samples and an independent sample cohort which was from postmortem confirmed AD patients (n = 17).
  Journal of Alzheimer's disease: JAD 11/2011; 28(3):625-36. · 3.74 Impact Factor
• Article: Serum biomarkers which correlate with failure to respond to immunotherapy and tumor progression in a murine colorectal cancer model.

  Baharak Vafadar-Isfahani, Stephanie Anne-Sophie Laversin, Murrium Ahmad, Graham Ball, Clare Coveney, Christophe Lemetre, Amanda Kathleen Miles, Gerhard van Schalkwyk, Robert Rees, Balwir Matharoo-Ball
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  ABSTRACT: To advance our understanding of mechanisms involved in tumor progression/regression, a CT26 colorectal mouse model treated intra-tumorally with DISC-herpes simplex virus as immunotherapy was used in the discovery and validation phases to investigate and ultimately identify biomarkers correlating with the failure to respond to immunotherapy. For the discovery phase, serum protein/peptide profiles of a retrospective sample collection (total n=70) were analyzed using MALDI-TOF-MS combined with artificial neural networks. Following identification of the key predictive peptides using ESI-MS/MS, validation of the identified proteins was carried out on serum and tissues collected in an independent sample set (total n=60). Artificial neural network analysis resulted in four discriminatory peaks with an accuracy of 86%, sensitivity of 90% and specificity of 81% between the progressor/regressor groups. Three of the identified discriminatory markers were upregulated and demonstrated a positive correlation with tumor progression following DISC-herpes simplex virus therapy. Immunovalidation studies corroborated the MALDI-TOF-MS findings. Immunohistochemistry revealed that serum amyloid A-1 and serum amyloid P produced in the liver localized intracellularly in CT26 tumor tissue. MALDI-TOF-MS and BI analysis of the serum proteome of tumor-bearer mice undergoing immunotherapy, identified biomarkers associating with "failure to respond" and biological arrays confirmed these findings.
  PROTEOMICS - CLINICAL APPLICATIONS 09/2010; 4(8-9):682-96. · 1.81 Impact Factor