The Current and Evolving Landscape of Breast Cancer Prediction and Prognosis

Abstract

The biological behaviour of breast cancer is remarkably heterogeneous and it is essential to have tools which can provide the necessary risk stratification to plan clinical management. Breast cancer prediction and prognosis needs to be holistic, and account for multiple levels of organisation. The histological classification and grading of the tumour itself presents valuable predictive and prognostic information. Hormone receptor status remains a mainstay, but roles may emerge for assessment of the intrinsic molecular subtype, for a molecular subclassification of triple negative carcinomas, and for whole genome sequencing. The recent discovery that antibody drug conjugates are effective in patients with weak HER-2 protein expression has led to the definition of the HER-2 low group. There has been a proliferation in predictive and prognostic models, numbering over 900, but the majority are at high risk of bias and tend to perform less well when applied to populations beyond the development cohort. The Nottingham Prognostic Index is a notable exception. Of the molecular risk stratification tools currently available, Oncotype Dx is the most widely recommended and used, but the question as to which test is superior remains unanswerable with current data. There is growing interest in omics-based approaches from which a number of biomarkers are being developed. It is well established that the microenvironment of the tumour is key to the tumour’s behaviour. Some components contain and destroy the cancer, whereas others are co-opted by the tumour and aid in its progression; the current evidence is reviewed, including the current status of tumour infiltrating lymphocyte assessment and immune checkpoint inhibition in breast cancer. The use of the liquid biopsy to achieve early detection of tumours and to manage tumour evolution is receiving intense attention; approaches include circulating tumour cells and circulating tumour DNA. Specific assessment of tumour giant cells may also provide the ability to anticipate tumour evolution. The influence of the gut microbiome on breast cancer is an intriguing development which requires further intensive study. There is a paucity of biomarkers in the setting of hereditary breast cancer. The use of polygenic risk scores in this setting is an interesting development requiring further study. The greatest challenge of all is to pull from such complexity key decision nodes that are clear enough to guide treatment decisions without losing the depth and richness of the information that underlies them. Seeking and finding this balance has been and will continue to be the holy grail of all endeavours in this field.