Aditya Bardia, MD, MPH, FASCO, is a professor in the Department of Medicine, Division of Hematology/Oncology and director of Translational Research Integration at UCLA Health Jonsson Comprehensive Cancer Center.

With our expanding understanding of complex cancer genetics and the emergence of personalized anticancer therapeutics tailored to driver mutations, there is a need for repeated tissue biopsies throughout the course of cancer treatment. Ideally, each time a patient clinically progresses, a repeat biopsy of the tissue could provide information regarding tumor evolution, but this is not practically feasible.

Although tissue biopsies are still the gold standard for tumor diagnosis and genotyping, core biopsies are invasive and associated with discomfort, high cost, long turnaround time, and complications. More so, it has been demonstrated that metastatic clones at different sites tend to harbor mutations that are not the same as those from their primary tumors and, as such, genetically represent a distinct disease that may not respond to the same therapy that the primary tumor does. This is known as genomic heterogeneity.

Tissue biopsies also contain only a small portion of the tumor and, therefore, may not be representative of all the mutational clones present within the biopsied tumor, which poses a problem of capturing intratumor heterogeneity.

Investigators gained a better insight into genomic variability across all tumor clones present in a patient with the discovery that tumors shed fragments of their DNA into the circulation. This occurs either passively, when cancer cells undergo necrosis or apoptosis, either spontaneously or as a response to therapy, or actively during hematogenous spreading. This valuable genetic information can be captured from circulating free tumor DNA (ctDNA), also referred to as a liquid biopsy, isolation of whole circulating tumor cells (CTCs), RNA, microRNAs/exosomes, and tumor-educated platelets.

Analysis of ctDNA has gained significant interest over the past decade in nearly all aspects of cancer treatment and across all tumor types. CtDNA consists of short fragments of double-stranded, short-lived (approximately 2 hours) DNA and is characterized by unique somatic mutations that are not present in normal cells, thereby allowing them to be differentiated from circulating free DNA (cfDNA) shed by noncancerous cells.

 CtDNA ranges from less than 0.1% to more than 10.0% of the total cfDNA depending on stage, tumor burden, vascularization of the tumor, biological features like apoptotic rate, and metastatic potential of the cancer cells.

Timing of blood collection in relation to exposure to therapy can also be critical because tumors tend to undergo necrosis and, therefore, shed their DNA when exposed to cytotoxic agents. Numerous techniques for detection and processing of ctDNA have been developed and can be categorized either as polymerase chain reaction tests or nextgeneration sequencing (NGS) assays.

The main differences between these 2 techniques are that those in the first group can detect mutations in only a limited number of loci, usually within a single gene, whereas NGS techniques are able to detect a large number of mutations, including gene amplifications, fusions, rearrangements, and aneuploidy.

These developments have led to several commercially available ctDNA test for detection of 

-sensitizing mutations in lung cancer. Cellsearch (Menarini Silicon Biosystems) is used to detect CTCs. These tests carry high sensitivity and specificity of nearly 99%.

The most relevant advantages of ctDNA detection over traditional tissue genotyping include as follows

Given the relatively high recurrence rates of breast cancer months to years following the curative treatment of non—stage IV cancer, significant efforts have been made to find applications of ctDNA for analyzing stored genetic material.

It is now clear that breast cancer is a heterogeneous disease, both phenotypically and genetically. Four luminal types of breast cancer have been identified based on hormonal expression; 10 subtypes, termed integrative clusters, have been classified by their distinct genetic signatures.

 Each type carries its own genetic specificities, which are likely responsible for the observed differences in sensitivity to chemotherapy and targeted treatments.

There are a number of genetic alterations, including mutations, amplifications, and translocations, detectable by ctDNA, which rises as the disease progresses. 

Y220C, Y220N, R273C, and R273H mutations have been associated with worse prognosis in basal-like triple-negative and other subtypes of breast cancer. Mutations in 

 (Y537N, Y537S, Y537C, D538G), and clones harboring 

 gene mutations have been shown to emerge in patients who develop resistance to aromatase inhibitors, implying that this could be the driver mutation in this subset of patients.

Among various mutations of the PI3K pathway, mutation of 

 (H1047R, H1047L, E545K, E542K) and loss of 

 negative regulator are the most frequently occurring inactivating mechanisms of this pathway in breast cancer. In addition, some breast cancers tend to change their hormonal status, namely gain or lose estrogen receptor (ER) or ERBB2/HER2 expression, further complicating their characterization and therapeutic selection.

Numerous studies have demonstrated dynamic changes of ctDNA in metastatic breast cancer (MBC) in various scenarios, but there is insufficient evidence that these changes always correlate with clinical outcomes. In the phase III BELLE-2 trial,

 mutation status (activating mutation in at least 1 of exons 1, 7, 9, or 20) was used as a biomarker to determine response to pan-PI3K inhibitor buparlisib and fulvestrant versus fulvestrant alone in postmenopausal women with endocrine-resistant, hormone receptor—positive, and HER2-negative MBC that had previously progressed on an aromatase inhibitor.

The findings demonstrated that patients with a 

 mutation benefited from the addition of buparlisib, suggesting that the 

mutation is both targetable and a likely driver mutation.

The BELLE-3 trial compared patients whose disease had relapsed on or after endocrine and mTOR inhibitor therapy. Patients were randomized to receive buparlisib with fulvestrant versus placebo plus fulvestrant. This study also showed prolonged progression-free survival (PFS) on the PI3K inhibitor in patients with a 

 mutation, but unfortunately buparlisib was also associated with a significant toxicity profile.

 mutations were analyzed in the blood specimens of participants in the phase III PALOMA-3 trial; levels of ctDNA were measured on days 1 and 15 following exposure to the CDK4/6 inhibitor palbociclib with and without fulvestrant in MBC and at progression. It was shown that patients randomized to the palbociclib arm were more likely to have early suppression of

 mutation levels (on day 15), which was predictive of PFS. Analysis of the dynamics of 

 mutations in the same study population showed less of a predictive power on long-term outcomes. More so, the analysis showed that the baseline levels of ctDNA were not predictive of PFS and that the ctDNA level suppression under treatment pressure was the key predictor.

Postanalysis of the SoFEA study results showed that patients with advanced MBC whose tumors harbored an 

 mutation had better PFS with fulvestrant compared with exemestane, whereas those with a wild-type 

 gene had similar outcomes on either drug.

 These results show that ctDNA can also be used for screening patients with MBC who may benefit from targeted treatments or to determine candidacy for clinical trials. For example, the phase I trial of elacestrant (RAD1901), a selective ER degrader, studied 

mutation dynamics in ctDNA in patients with heavily pretreated ER-positive MBC. The study demonstrated multiple responses to elacestrant in all patients, particularly those harboring

Each of the genomic breast cancer subtypes can be viewed as a distinct disease that merits testing in different study setups. Sample sizes in many of the studies published so far tend to be not large enough to explain many of the possible genetic and mutational combinations and their prognostication. For this reason, it is of utmost importance to create large biobanks and databases, such as The Cancer Genome Atlas and the Catalogue of Somatic Mutations in Cancer, and make them available to investigators.

 Incorporating ctDNA testing into clinical trial designs also offers invaluable evidence.

In summary, we believe that ctDNA will continue to gain importance in precision oncology as we continue to uncover the role and interplay of genomic alterations that promote tumor heterogeneity. It is yet to be determined how to best use ctDNA in decision making and eventual improvement of clinical outcomes for patients with MBC.

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