Unveiling the Potential of Liquid Biopsy in HER2-Positive Breast Cancer Management

SIMPLE SUMMARY: Breast cancer (BC) is the most prevailing cancer in women worldwide. Amongst the different BC subtypes, human epidermal growth factor receptor 2 (HER2)-positive tumours are characterised by an overexpression of the HER2 membrane receptor. Nowadays, HER2-status assessment relies on immunohistochemical methodologies in the tumour tissue, which could be complemented by novel methodologies to improve the clinical management of these patients. In this regard, liquid biopsy is an easy, rapid, and minimally invasive tool to obtain circulating tumour components from body fluids. Herein, by reviewing the published studies, we aim to decipher the clinical validity of liquid biopsy in both early and metastatic HER2-positive BC. ABSTRACT: Invasive breast cancer (BC) is the most common cancer in women with a slightly increasing yearly incidence. BC immunohistochemical characterisation is a crucial tool to define the intrinsic nature of each tumour and personalise BC patients’ clinical management. In this regard, the characterisation of human epidermal growth factor receptor 2 (HER2) status guides physicians to treat with therapies tailored to this membrane receptor. Standardly, a tumour solid biopsy is therefore required, which is an invasive procedure and has difficulties to provide the complete molecular picture of the tumour. To complement these standard-of-care approaches, liquid biopsy is a validated methodology to obtain circulating tumour components such as circulating tumour DNA (ctDNA) and circulating tumour cells (CTCs) from body fluids in an easy-to-perform minimal-invasive manner. However, its clinical validity in cancer is still to be demonstrated. This review focusses on the utilisation of both ctDNA and CTCs in early and metastatic HER2-positive BC tumours. We discuss recently published studies deciphering the capacity of liquid biopsy to determine the response to neoadjuvant and adjuvant therapies as well as to predict patients’ outcomes.