HER2 Expression in Circulating Tumour Cells Isolated from Metastatic Breast Cancer Patients Using a Size-Based Microfluidic Device.

Cláudia Lopes,Sara Abalde-Cela,Laura Muinelo-Romay,Lorena Diéguez,Patrícia Corredeira,Paulina Piairo,Liliana R Pires,Patrícia Alves,Alexandre Chícharo,Luís Costa

doi:10.3390/cancers13174446

Abstract

Simple SummaryBreast cancer is the most prevalent type of cancer worldwide. By late 2020, there were 7.8 million women alive who had been diagnosed with breast cancer during the previous 5 years. HER2 overexpression in breast cancer is associated with poor prognosis. Existing HER2-targeting therapies significantly improved patient outcomes; still, designing these personalized treatments relies on accurate and comprehensive assessment of HER2 alterations. Frequent HER2 status determination during disease monitoring can be performed using circulating tumour cells (CTCs). Using a novel microfluidic device, we isolated and enumerated CTCs from metastatic breast cancer patients and assessed their HER2 expression in a comparative study with the current gold standard technology. CTCs isolated with our microfluidic technology showed to be a valuable biomarker, and their phenotypical analysis hinted utility to discriminate patient populations, although further validation is needed.HER2 is a prognostic and predictive biomarker in breast cancer, normally assessed in tumour biopsy and used to guide treatment choices. Circulating tumour cells (CTCs) escape the primary tumour and enter the bloodstream, exhibiting great metastatic potential and representing a real-time snapshot of the tumour burden. Liquid biopsy offers the unique opportunity for low invasive sampling in cancer patients and holds the potential to provide valuable information for the clinical management of cancer patients. This study assesses the performance of the RUBYchip™, a microfluidic system for CTC capture based on cell size and deformability, and compares it with the only FDA-approved technology for CTC enumeration, CellSearch®. After optimising device performance, 30 whole blood samples from metastatic breast cancer patients were processed with both technologies. The expression of HER2 was assessed in isolated CTCs and compared to tissue biopsy. Results show that the RUBYchipTM was able to isolate CTCs with higher efficiency than CellSearch®, up to 10 times more, averaging all samples. An accurate evaluation of different CTC subpopulations, including HER2+ CTCs, was provided. Liquid biopsy through the use of the RUBYchipTM in the clinic can overcome the limitations of histological testing and evaluate HER2 status in patients in real-time, helping to tailor treatment during disease evolution.

Highlights

Breast cancer is the second most common cancer in the world and one of the leading causes of cancer-related mortality in women, with main incidence between 35 and 75 years old [1,2]
This study assesses the performance of the RUBYchipTM, a microfluidic system for Circulating tumour cells (CTCs) capture based on cell size and deformability, and compares it with the only Food and Drug Administration (FDA)-approved technology for CTC enumeration, CellSearch®
In order to assess the capture efficiency of the RUBYchipTM for the isolation of breast cancer cells with different phenotypes, human peripheral whole blood samples from healthy donors were spiked with 200 Hoechst-stained cultured cells and processed through the microfluidic chip

Summary

Introduction

Breast cancer is the second most common cancer in the world and one of the leading causes of cancer-related mortality in women, with main incidence between 35 and 75 years old [1,2]. Clinical management and technological advancements allow most primary and early-stage breast cancers to be treated, either by surgery alone or surgery and complementary therapy, achieving an overall 5-year survival rate of 90% [6]. Research efforts to improve survival rates for metastatic breast cancer (MBC) are currently focused on identifying the molecular heterogeneity of breast cancer and in classifying patients into meaningful subgroups. This classification allows to stratify patients according to prognosis and to define the best therapeutic approach for each group [1]

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