Supervisor View Full Details 2nd

• cancer/oncology

• Surgery

• Other

Breast Cancer

Our programme of research is focused on uncovering networks involved in mediating resistance in ER-positive breast cancer, and in doing so identify markers to predict endocrine sensitivity and importantly develop new therapeutic targets.
Our approach is to focus on transcriptional networks, harnessing data from high throughput experimental methods including RNAseq, Methylseq, ChIPseq, molecular studies and translational studies. We are capitalising on our established strengths in translational research, in particular making use of cultures derived from patient tumours, PDX models and clinical datasets. This allows us to model the mechanism(s) of resistance and define new predictive markers and therapeutic targets.

- Vareslija D, McBryan J, Fagan A, Redmond AM, Hao Y, Sims AH, Turnbull A, Dixon JM, Ó Gaora P, Hudson L, Purcell S, Hill AD, Young LS. Adaptation to AI Therapy in Breast Cancer Can Induce Dynamic Alterations in ER Activity. Clin Cancer Res. 2016 1;22(11):2765-77
- McBryan J, Fagan A, McCartan D, Bane FT, VareSlija D, Cocchiglia S, Byrne C, Bolger J, McIlroy M, Hudson L, Tibbitts P, Gaora PÓ, Hill AD, Young LS. Transcriptomic Profiling of Sequential Tumors from Breast Cancer Patients Provides a Global View of Metastatic Expression Changes. Clin Cancer Res. 2015 1;21(23):5371-9.

'Alterations in molecular heterogeneity during endocrine treatment in ER-positive breast cancer'

Endocrine therapies, both tamoxifen and aromatase inhibitors (AIs), successfully treat ER positive breast cancer. A small but significant number of patients however will acquire resistance and develop disease recurrence.

The importance of tumour molecular heterogeneity in determining response to targeted therapy is now firmly established. Furthermore, the ability of a subset of breast tumors to alter their molecular profile between primary and recurrent tumours is the subject of intense investigation by our group (Vareslija D et al. J Natl Cancer Inst. 2019 Apr 1;111(4):388-398; McBryan et al., Clin Cancer Res, 2015;21(23):5371-9). This tumour adaptability is controlled, at least in part, through transcription factors responding to the therapeutic environment.

Despite concentrated efforts to discover robust biomarkers of endocrine sensitivity, no clinical assay to monitor real-time patient response to endocrine treatment has been developed. Understanding how tumours adapt to endocrine therapy has the potential to uncover new biomarkers of drug sensitivity and novel therapeutic targets to detect and treat endocrine resistant metastatic disease. Assessment can only be truly identified through longitudinal transcriptomic analyses.

In this study exome, RNA and Methyl sequencing will be performed in breast cancer patient tissue and PDX models sequentially over the period of treatment to determine the altering genetic landscape in ER-positive tumours under therapeutic pressure. This work will identify the emergence of acquired resistance to endocrine therapy in breast cancer.
Our approach is to focus on transcriptional networks, harnessing data from high throughput experimental methods including RNAseq, Methylseq, ChIPseq, molecular studies and translational studies. We are capitalising on our established strengths in translational research, in particular making use of cultures derived from patient tumours, PDX models and clinical datasets. This allows us to model the mechanism(s) of resistance and define new predictive markers and therapeutic targets