Using AML cell lines with induced IFNG phenotypes to produce prognostic index scores for stratification of AML patients

Courtney, M, 2024. Using AML cell lines with induced IFNG phenotypes to produce prognostic index scores for stratification of AML patients. PhD, Nottingham Trent University.

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Abstract

Acute myeloid leukaemia (AML) is a haematological malignancy which inhibits the production and maturation of functional immune cells. Patients are treated with induction chemotherapy and haematopoietic stem cell transplant (HSCT). HSCT replaces the patients defunct immune system using donor stem cells. Therefore, disruption via immune suppression is detrimental to patient prognosis. At present, AML patient’s prognosis is predicted using cytogenetic abnormalities and genetic mutations, however, 50-70% of AML patients are labelled as ‘intermediate’ risk. This group displays variation in response to frontline chemotherapy and HSCT, indicating a need for improved stratification to assign patients tailored treatments. Prognostic indicators (PI) are crucial in guiding therapeutic decisions and improving outcomes for AML patients. This work focuses on generating prognostic index scores based on methylation modulated IFNG driven immune evasion in AML.

PI scores were generated using AML cell lines (Kasumi-1 and KG-1) subjected to treatment with IFNG, and demethylation agent 5AzaC. Pairwise linear regression identified significant treatment-induced transcriptomic changes and a shortlist of candidate transcripts associated with IFNG signalling and demethylation was created. PI scores were computed using normalised transcription data from IFNG, 5AzaC and IFNG5AzaC treated cell lines and β-values generated using cox proportional hazards forward selection model. The study employed the TCGA patient dataset for discovery and BeatAML, HOVON, German-AML, and CN-AML for validation. PI score performance was compared to established prognostic methods.

All PI scores split adult patients in the European LeukemiaNet cytogenetic risk category into subgroups with good and poor survival in the TCGA dataset, with the 5AzaC and IFNG PI scores association with OS validated in the CN-AML (intermediate risk group) data set (n = 242). Comparing the area under the curve (AUC) for PI scores (5AzaC PI AUC = 0.599, IFNG PI AUC = 0.637, and IFNG5AzaC PI AUC = 0.657), with established prognostic scores revealed comparable performance to LSC17 score (AUC=0.65) and the ELN cytogenetic risk categories (AUC=0.66). However, they were outperformed by other established scores. The study demonstrated the potential of cell line-derived PI scores to predict AML patient survival.

Item Type: Thesis
Creators: Courtney, M.
Contributors:
Name
Role
NTU ID
ORCID
Rutella, S.
Thesis supervisor
JVG3RUTELS
Pockley, G.
Thesis supervisor
AAS3POCKLA
Vadakekolathu, J.
Thesis supervisor
BIO3VADAKJ
Date: July 2024
Rights: The copyright in this work is held by the author. You may copy up to 5% of this work for private study, or personal, non-commercial research. Any re-use of the information contained within this document should be fully referenced, quoting the author, title, university, degree level and pagination. Queries or requests for any other use, or if a more substantial copy is required, should be directed to the author.
Divisions: Schools > School of Science and Technology
Record created by: Melissa Cornwell
Date Added: 27 Sep 2024 10:20
Last Modified: 27 Sep 2024 10:20
URI: https://irep.ntu.ac.uk/id/eprint/52314

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