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Published online by Cambridge University Press: 11 September 2020
Breast cancer is the most commonly diagnosed malignancy among women and accounts for about 25% of all new cancer cases and 13% of all cancer deaths in Canadian women. It is a highly heterogeneous disease, encompassing multiple tumour entities, each characterised by distinct morphology, behaviour and clinical implications. Moreover, different breast tumour subtypes have different risk factors, clinical presentation, histopathological features, outcome and response to systemic therapies. Therefore, any strategies capable of the stratification of breast cancer by clinically relevant subtypes are an important requirement for personalised and targeted treatment. Therefore, in the advancement towards the concept of precision medicine that takes individual patient variability into account, several investigators have focused on the identification of effective clinical breast cancer biomarkers that interrogate key aberrant pathways potentially targetable with molecular targeted or immunological therapies.
This paper reports on a review of 11 current clinical and emerging biomarkers used in screening for early detection and diagnosis, to stratify patients by disease subtype, to identify patients’ risk for metastatic disease and subsequent relapse, to monitor patient response to specific treatment and to provide clinicians the possibility of prospectively identifying groups of patients who will benefit from a particular treatment.
The future holds promising for the use of effective clinical breast cancer biomarkers for early detection and personalised patient-specific targeted treatment and increased patient survival. Breast cancer biomarkers can potentially assist in early-staged, non-invasive, sensitive and specific breast cancer detection and screening, provide clinically useful information for identification of patients with a greater likelihood of benefiting from the specific treatment, offer a better understanding of the metastatic process in cancer patients, predict disease and for patients with the established disease can assist define the nature of the disease, monitor the success of treatment and guide the clinical management of the disease.