Abstract
Wāhine Māori are significantly affected by non-communicable diseases like breast and gynaecological cancers yet remain underrepresented in translational research that informs personalised treatment strategies. The enduring impacts of colonisation have created systemic barriers to equitable cancer care for many Māori communities, resulting in disparities in treatment access and outcomes. As personalised approaches to cancer care become more routine globally, it is crucial that Māori are represented in the genomic data underpinning these strategies. This will help ensure the benefits of personalised medicine extend to Māori and prevent the perpetuation of further inequities in cancer outcomes. Therefore, this thesis used modern genomic and personalised medicine tools, specifically single cell RNA sequencing and tissue-derived tumour organoid models, to investigate intra- and intertumoral heterogeneity, and responses to standard-of-care chemotherapies, in a cohort of wāhine Māori.
Kaupapa Māori principles were used to establish tikanga-Māori guided frameworks. These were developed using the foundational work of other Māori scholars, building on these frameworks through collaborations with local iwi Ngāti Toa Rangatira, clinical and research partners, other Māori researchers from across Aotearoa New Zealand and collaborators from the Broad Institute of MIT and Harvard in Cambridge, USA. These frameworks prioritised participant wellbeing, minimised potential risks, and applied mana-enhancing, strengths-based approaches to data use and tissue handling. Tikanga principles such as manaakitanga, mana, whakapapa and tika, guided the ethical use of live tissue models, advanced sequencing tools, and Māori genomic data.
These frameworks were then applied in Chapters 4 and 5, which used single nucleus RNA sequencing and RNAscope (for breast cancer samples) to explore the intra- and inter-tumoral heterogeneity of breast and ovarian cancer in a wāhine Māori cohort. Participant-specific epithelial cell populations were identified that differed in inferred phenotype, predicted function, and cell-cell communication. Tumour microenviroanment components, including fibroblasts, macrophages and lymphocytes, also varied across individuals. These analyses highlighted the relevance of small subpopulations on tumour development, and the importance of analysing tumours at an individualised level within the context of personalised medicine.
Chapter 6 focused on treatment responses to standard of care chemotherapies using three-dimensional tumour models in an ‘N of 1’ approach, aligning with the participant-specific heterogeneity observed in earlier chapters. Spheroid models were assessed to optimise sequencing protocols for low-cell number samples and to evaluate treatment responses. While these models showed improved spatial organisation and cellular interactions compared to traditional two-dimensional cultures, they failed to fully capture in vivo tumour heterogeneity, and no significant differences in treatment response were observed between monoculture and fibroblast spheroid cocultures.
Participant-derived tumour organoid models of gynaecological cancers were then developed to investigate a more biologically relevant model for assessing treatment responses. These tumour organoids retained the characteristics of the parental tumour, displaying distinct morphologies and subtype-specific treatment responses to paclitaxel and carboplatin. Pathway analyses revealed distinct, individualised responses that reflected tumour subtype and molecular context, highlighting the utility of tumour organoid models in personalised treatment responses.
Together, these findings suggest the need to reframe and shift away from one-size-fits-all approaches to cancer treatment towards more personalised strategies, particularly for communities who already face inequities in treatment outcomes. Extensive intra- and intertumoral heterogeneity observed in this work has important implications for both tumour progression and treatment response. Accurate and representative genomic data are essential to ensure Māori are equitably included in personalised medicine pathways. Furthermore, culturally responsive science must be integrated with modern biomedical tools to advance equity for wāhine Māori with breast and ovarian cancer, in ways that are mana-enhancing and honour the principles and commitment to Te Tiriti o Waitangi.