cfDNA, Genetic Assays Inform Important Treatment Decisions in Breast Cancer

April 14, 2021
Hayley Virgil
Hayley Virgil

Senior Editor, OncLive®
Hayley Virgil heads OncLive's feature article efforts and specializes in social issues and equality in oncology. Prior to joining the company in early 2020, she worked as an editor in numerous industries, including media, marketing, hospitality, and computer science, and freelanced in subjects such as history, culture, and the natural sciences.

Genetic assays such as those utilized in the phase 3 TAILORx, MINDACT, and RxPONDER trials are helping to provide valuable insight to inform treatment decisions in patients with breast cancer.

Genetic assays such as those utilized in the phase 3 TAILORx (NCT00310180), MINDACT (NCT00433589), and RxPONDER (NCT01272037) trials are helping to provide valuable insight to inform treatment decisions in patients with breast cancer, according to Kevin Kalinsky, MD, MS, who added that pairing these assays with novel markers such as cell-free DNA (cfNDA) could potentially provide more information so that this could become a composite risk.

“cfDNA may give us some additional information in terms of prognosis and prediction, but I think one of the questions is, can [it] be used as a composite? Can [it] be used together [with these assays], especially in patients who are early on in their disease process?” Kalinsky questioned. “One of the unique things about cfDNA is you may be able to detect [whether] a patient is escaping dormancy [or whether] you should change interventions to decrease the likelihood of late recurrence.”

In an interview with OncLive® during an Institutional Perspectives in Cancer webinar on Breast Cancer, Kalinsky, the director of the Glenn Family Breast Center and Breast Medical Oncology at Winship Cancer Institute and acting associate professor in the Department of Hematology and Medical Oncology at Emory University School of Medicine, discussed the different assays utilized in breast cancer, their utility in informing clinical decisions, as well as the potential role of cfDNA.

OncLive®: Based on the data that read out from the TAILORx, MINDACT, and RxPONDER studies, how is the relationship between recurrence score, clinical risk, and menopausal status being reconciled with the benefit of adjuvant chemotherapy?

Kalinsky: The results of RxPONDER really helped offer some clarity on how we should be thinking about our patients with hormone receptor (HR)–positive and HER2-negative breast cancer with 1 to 3 positive lymph nodes. The reason that this study was reported early, with about 50% of events, is that we saw a differential effect based upon menopausal status. [For] patients who are postmenopausal, we really did not see any subgroup of patients who seemed to benefit from the addition of chemotherapy. This is opposed to patients who are premenopausal, where we saw an improvement in invasive disease-free survival, as well as overall survival in those who received chemotherapy followed by endocrine therapy compared to endocrine therapy alone.

We've seen data from TAILORx that also showed in patients who have HR-positive, HER2-negative, node-negative [disease] that when you dichotomize them based upon age, those who are less than 50 [years of age and] have a recurrence score of 16 to 25 may benefit from the addition of chemotherapy, as opposed to those who are over the age of 50 years. There seems to be this difference based upon age and menopausal status. [Additionally], data from TAILORx [demonstrated] that clinical risk is important. We saw these data at the 2020 San AntonioBreast Cancer Symposium [SABCS], as well. There is a new calculation tool where providers can go online and put in the information, including factors such as age, size, and grade, and they can [calculate] individualized risk based on the incorporation of the recurrence score. That helps you determine whether there is a benefit from chemotherapy in patients who have node-negative disease.

The MINDACT trial was a bit different in that it was using a 70-gene assay. We saw this discordance between those patients who were either clinically low risk or high risk and who had a discordant genomic risk. Updated data [presented] at SABCS really demonstrated that those patients who were clinically low risk did quite well. We saw some updated data at other prior meetings where for these patients with HR-positive, HER2-negative disease, genomic assays [can] help us determine whether there is a benefit for utilization of chemotherapy.

The other thing that's important to note is that studies are starting to be designed to look at cfDNA, and having an intervention based upon the presence or absence of cfDNA. That is where the field is going—[going beyond this] pretreatment, diagnostic sample to help us determine [whether] chemotherapy [should be used]. One of the questions [that] the new frontier is going is [try to answer is] whether we can utilize these liquid assays to help us not only determine prognostic risk, but also potential benefit from chemotherapy and see whether we have clearance of cfDNA in, for instance, minimal residual disease. We do have some important updates from these trials, but we'll see how future trials will help to inform treatment decisions, as well.

Do you believe that cfDNA could replace these assays some day?

I don't necessarily believe that cfDNA would replace the tumor-based genomic assays. [However], these could potentially in the future, be utilized in concert and then maybe help provide more information so that this could become a composite risk.

What are your thoughts on the data from the 21-Gene Recurrence Score and Clinical-Pathological Features [RSClin] that read out at SABCS?

The data were presented at SABCS by Joseph A. Sparano, MD, of Albert Einstein College of Medicine, as well as published in the Journal of Clinical Oncology, and demonstrated the potential utility of RSClin, which is now something that's available on the Genomic Health website. [Investigators] developed these data, including data from TAILORx, and then they validated the prognostic data from this dataset and showed that there was good association between modeling for prognosis based upon this model.

We've also seen that this model can be helpful for the potential prediction of chemotherapy risk, and then individualizing what that risk is. [This involves] incorporation of the recurrence score, grade, tumor size, and age. When you use the recurrence score by itself, it may give you [information that tells you], OK, if you take hormonal therapy for 5 years, your risk is X% at 9 years or so.' RSClin is incorporating all those features and coming up with an individualized risk at 10 years. It can be very helpful for informing systemic therapeutics when we're talking with patients.

Would you say that's the superior assay at this point or does each have its own merits?

The assays are different. They are looking at different [factors], have different signatures, and we don't have studies that have compared all of them with each other. We do have some data which compared different assays like recurrence score and breast cancer index. There were some differences in terms of late recurrence, and also some data that had demonstrated the inherent differences in terms of estrogen or proliferation signaling that help determine the risk that is identified with that assay. However, what I would generally say is that the assays are not the same. When you're talking with the patient, think about using 1 assay, and then stick with that assay to help determine next steps.

Are any other studies ongoing that you would like to highlight?

Some studies are in design and some are about to initiate accrual. For instance, our colleague, Lajos Pusztai, MD, DPhil, from Yale Cancer Center, is leading the DARE study that is being run through a consortium that is looking at patients with HR-positive, HER2-negative disease where cfDNA is detected. [Patients are] randomized to have an intervention—in this particular case, fulvestrant [Faslodex] plus palbociclib [Ibrance]—to see whether they do better in a randomized study. We are at the genesis of these studies. We'll see what the ultimate utility of cfDNA is in this particular study.