Browsing by Author "Livesey, Michelle"

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    Investigation of distinct gene expression profile patterns that can improve the classification of intermediate-risk prognosis in AML patients
    (Frontiers Media, 2023) Eshibona, Nasr; Livesey, Michelle; Christoffels, Alan
    Acute myeloid leukemia (AML) is a heterogeneous type of blood cancer that generally affects the elderly. AML patients are categorized with favorable-, intermediate-, and adverse-risks based on an individual’s genomic features and chromosomal abnormalities. Despite the risk stratification, the progression and outcome of the disease remain highly variable. To facilitate and improve the risk stratification of AML patients, the study focused on gene expression profiling of AML patients within various risk categories. Therefore, the study aims to establish gene signatures that can predict the prognosis of AML patients and find correlations in gene expression profile patterns that are associated with risk groups. Microarray data were obtained from Gene Expression Omnibus (GSE6891). The patients were stratified into four subgroups based on risk and overall survival. Limma was applied to screen for differentially expressed genes (DEGs) between short survival (SS) and long survival (LS). DEGs strongly related to general survival were discovered using Cox regression and LASSO analysis. To assess the model’s accuracy, Kaplan-Meier (K-M) and receiver operating characteristic (ROC) were used.
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    Persistence of ancestral khoesan mitochondrial patterns incontemporary South African populations
    (Annals of Human Genetics, 2025) D’Amato, Maria Eugenia; Ristow, Peter; Livesey, Michelle
    introduction southern africa has been inhabited by hunter-gatherers for at least 20,000 years and has received diverse immigration flows in the last 2000 years. the original inhabitants have interacted with the pastoralist migrants from eastern africa (∼2000 ybp), followed by the southern bantu migration arriving some 1000 ybp, and more recently with the european and asian settlers after the 17th century. many of the original khoekhoe and san inhabitants have either become extinct or have disappeared through admixture in south africa (sa), in a sex-biased manner involving khoesan women. methods in this study, we generated mitochondrial dna (mtdna) control region (cr) sequences for 247 south african individuals. the sampling effort was concentrated in regions and populations with historical links to the khoesan population groups: admixed (coloured, griqua), nama (khoekhoe) and bantu in three provinces. here we evaluate the composition and extent of connectivity between population groups and regions, and to assess the distribution of haplotypes for the practical application of mtdna cr data in forensic identifications. results the analysis of the newly generated sequences revealed 142 distinct haplotypes, of which 122 were unique. haplogroup l0 was predominant (overall 71.7%). a high-frequency l0d2a haplotype dominated the pool of the admixed groups with 10%–12.5% incidence overall or per region. comparative analysis with 545 extant mtdna cr sequences from south african khoesan and admixed descendants revealed extensive population structure and high within-group haplotype sharing. conclusion the observed population and regional variations, combined with the prevalence of high-frequency haplotypes, align with patterns of matrilocality. these findings highlight the limitations of using mtdna control region analysis for forensic applications in south africa.
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    Transforming RNA-Seq gene expression to track cancer progression in the multi-stage early to advanced-stage cancer development
    (Public Library of Science, 2023) Livesey, Michelle; Rossouw, Sophia Catherine; Blignaut, Renette
    Cancer progression can be tracked by gene expression changes that occur throughout early-stage to advanced-stage cancer development. The accumulated genetic changes can be detected when gene expression levels in advanced-stage are less variable but show high variability in early-stage. Normalizing advanced-stage expression samples with earlystage and clustering of the normalized expression samples can reveal cancers with similar or different progression and provide insight into clinical and phenotypic patterns of patient samples within the same cancer.