PIK3CA mutation detected by liquid biopsy in patients with metastatic breast cancer

The Clinical Utility of Droplet Digital PCR for Profiling Circulating Tumor DNA in Breast Cancer Patients

Breast cancer is the most common cancer affecting women worldwide. It is a malignant and heterogeneous disease with distinct molecular subtypes, which has prognostic and predictive implications. Circulating tumor DNA (ctDNA), cell-free fragmented tumor-derived DNA in blood plasma, is an invaluable source of specific cancer-associated mutations and holds great promise for the development of minimally invasive diagnostic tests. Furthermore, serial monitoring of ctDNA over the course of systemic and targeted therapies not only allows unparalleled efficacy assessments but also enables the identification of patients who are at risk of progression or recurrence. Droplet digital PCR (ddPCR) is a powerful technique for the detection and monitoring of ctDNA. Due to its relatively high accuracy, sensitivity, reproducibility, and capacity for absolute quantification, it is increasingly used as a tool for managing cancer patients through liquid biopsies. In this review paper, we gauge the clinical utility of ddPCR as a technique for mutational profiling in breast cancer patients and focus on HER2, PIK3CA, ESR1, and TP53, which represent the most frequently mutated genes in breast cancers.

Potential utility of miRNAs for liquid biopsy in breast cancer

Breast cancer (BC) remains the most prevalent malignancy due to its incidence rate, recurrence, and metastasis in women. Conventional strategies of cancer detection– mammography and tissue biopsy lack the capacity to detect the complete cancer genomic landscape. Besides, they often give false- positive or negative results. The presence of this and other disadvantages such as invasiveness, high-cost, and side effects necessitates developing new strategies to overcome the BC burden. Liquid biopsy (LB) has been brought to the fore owing to its early detection, screening, prognosis, simplicity of the technique, and efficient monitoring. Remarkably, microRNAs (miRNAs)– gene expression regulators seem to play a major role as biomarkers detected in the samples of LB. Particularly, miR-21 and miR-155 among other possible candidates seem to serve as favorable biomarkers in the diagnosis and prognosis of BC. Hence, this review will assess the potential utility of miRNAs as biomarkers and will highlight certain promising candidates for the LB approach in the diagnosis and management of BC that may optimize the patient outcome.

Targeting PIK3CA Actionable Mutations in the Circulome: A Proof of Concept in Metastatic Breast Cancer

The study of circulating cancer-derived components (circulome) is considered the new frontier of liquid biopsy. Despite the recognized role of circulome biomarkers, their comparative molecular profiling is not yet routine. In advanced breast cancer (BC), approximately 40% of hormone-receptor-positive, HER2-negative BC cases harbor druggable PIK3CA mutations suitable for combined alpelisib/fulvestrant treatment. This pilot study investigates PIK3CA mutations in circulating tumor DNA (ctDNA), tumor cells (CTCs), and extracellular vesicles (EVs) with the aim of determining which information on molecular targetable profiling could be recollected in each of them. The in-depth molecular analysis of four BC patients demonstrated, as a proof-of-concept study, that it is possible to retrieve mutational information in the three components. Patient-specific PIK3CA mutations were found in both tissue and ctDNA and in 3/4 cases, as well as in CTCs, in the classical population (large-sized CD45−/EpCAM+/− cells), and/or in the “non-conventional” sub-population (smaller-sized CD44+/EpCAM−/CD45− cells). Consistent mutational profiles of EVs with CTCs suggest that they may have been released by CTCs. This preliminary evidence on the molecular content of the different circulating biomaterials suggests their possible function as a mirror of the intrinsic heterogeneity of BC. Moreover, this study demonstrates, through mutational assessment, the tumor origin of the different CTC sub-populations sustaining the translational value of the circulome for a more comprehensive picture of the disease.

Current and Developing Liquid Biopsy Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer and leading cause of cancer mortality among woman worldwide. The techniques of diagnosis, prognosis, and therapy monitoring of breast cancer are critical. Current diagnostic techniques are mammography and tissue biopsy; however, they have limitations. With the development of novel techniques, such as personalized medicine and genetic profiling, liquid biopsy is emerging as the less invasive tool for diagnosing and monitoring breast cancer. Liquid biopsy is performed by sampling biofluids and extracting tumor components, such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), cell-free mRNA (cfRNA) and microRNA (miRNA), proteins, and extracellular vehicles (EVs). In this review, we summarize and focus on the recent discoveries of tumor components and biomarkers applied in liquid biopsy and novel development of detection techniques, such as surface-enhanced Raman spectroscopy (SERS) and microfluidic devices.

Role of ctDNA in Breast Cancer

Breast cancer is currently classified by immunohistochemistry. However, technological advances in the detection of circulating tumor DNA (ctDNA) have made new options available for diagnosis, classification, biological knowledge, and treatment selection. Breast cancer is a heterogeneous disease and ctDNA can accurately reflect this heterogeneity, allowing us to detect, monitor, and understand the evolution of the disease. Breast cancer patients have higher levels of circulating DNA than healthy subjects, and ctDNA can be used for different objectives at different timepoints of the disease, ranging from screening and early detection to monitoring for resistance mutations in advanced disease. In early breast cancer, ctDNA clearance has been associated with higher rates of complete pathological response after neoadjuvant treatment and with fewer recurrences after radical treatments. In metastatic disease, ctDNA can help select the optimal sequencing of treatments. In the future, thanks to new bioinformatics tools, the use of ctDNA in breast cancer will become more frequent, enhancing our knowledge of the biology of tumors. Moreover, deep learning algorithms may also be able to predict breast cancer evolution or treatment sensitivity. In the coming years, continued research and the improvement of liquid biopsy techniques will be key to the implementation of ctDNA analysis in routine clinical practice.