Developing leukaemic biomarkers to enable personalised CNS-directed therapy

Collings, Alexander J. (2022) Developing leukaemic biomarkers to enable personalised CNS-directed therapy. PhD thesis, University of Glasgow.

Abstract

Acute lymphoblastic leukaemia (ALL) is a cancer of the blood and the most common childhood cancer in the world today. This leukaemia is known to infiltrate the central nervous system (CNS), a sanctuary site where blasts can flourish and cause relapse. There are currently no ways to accurately predict CNS relapse, so all children receive substantial amounts of CNS-directed chemotherapy which can cause short and long-term neurotoxicity. CNS leukaemia is currently classified by CSF cytology and cell count however, evidence shows that leukaemic blasts adhere to the walls of the leptomeninges which may reduce the ability of FCM and CSF cytology to accurately determine leukaemic burden in the CNS. In order to tailor CNS therapy to a child’s individual risk of relapse, better biomarkers, capable of measuring total leukemic burden at this site are needed. This project aimed to develop sensitive biomarkers for the presence of CNS leukaemia and its response to therapy by targeting cell-independent markers in samples of cerebrospinal fluid (CSF). Biomarkers of interest include CSF metabolites, soluble proteins and cell-free DNA (cfDNA).

Semi-untargeted metabolic profiling was performed using Liquid Chromatography Mass Spectrometry (LC-MS) on a large, comprehensive cohort of diagnostic CSF samples and normal control CSF to validate a panel of metabolites that showed promise in detecting a leukaemic metabolic signature. This analysis highlighted Creatine, N4-acetylcytidine, Phenylalanine and Symmetric dimethylarginine as the most promising diagnostic biomarkers. Multivariate biomarker models were created and demonstrated a higher sensitivity and specificity in detecting a leukaemic signature when the biomarkers were used in combination. Phenylalanine also demonstrated promise as a potential prognostic biomarker, presenting with elevated levels in patients who went onto to relapse in the CNS. Luminex multiplex-immunoassays were run on a subset of diagnostic CSF samples and matched control CSF for screening and identification of soluble protein/chemokine markers capable of distinguishing CNS leukaemia. Of interest, CD27, presented with elevated levels in patient diagnostic CSF compared to the control CSF.

Several different commercial cfDNA extraction kits and technologies were tested to determine the most suitable kit for extracting cfDNA from low volumes of patient CSF. Two highly sensitive platforms, droplet digital PCR (ddPCR) and next-generation sequencing (NGS) were used to identify leukaemic cfDNA by targeting the KRAS G12D mutation and immunoglobulin heavy chain (IGH) gene rearrangements. This analysis proved that leukaemic cfDNA could be detected in the low samples of patient CSF using both platforms, providing evidence that cfDNA can be used as a highly specific biomarker for CNS leukaemia.

In conclusion, this study identified promising diagnostic, prognostic and predictive biomarkers in the CSF of CNS-ALL patients, each with their advantages and disadvantages, capable of detecting CNS leukaemia taking another step towards personalising CNS-directed therapy with the aim of reducing therapy for those at low risk of CNS recurrence and intensifying treatment for those at high risk.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Additional Information: Supported by funding from the Children’s Cancer and Leukaemia Group (CCLG) and the Little Princess Trust.
• Subjects: R Medicine > R Medicine (General); R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer)
• Colleges/Schools: College of Medical Veterinary and Life Sciences > School of Cancer Sciences
• Supervisor's Name: Halsey, Professor Christina and Thomson, Dr. Fiona
• Date of Award: 2022
• Depositing User: Theses Team
• Unique ID: glathesis:2022-83152
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 04 Oct 2022 12:23
• Last Modified: 04 Oct 2022 12:24
• Thesis DOI: 10.5525/gla.thesis.83152
• URI: https://theses.gla.ac.uk/id/eprint/83152