While several biomarkers have been identified in patients with breast cancer, including ESR1 and PIK3CA mutations, not all of these are driver mutations that can be effectively targeted with treatment.
Francisco J. Esteva, MD, PhD
The challenge of precision medicine in metastatic breast cancer is to develop well-tolerated therapies based on key actionable, accessible, and validated biomarkers, said Francisco J. Esteva, MD, PhD.
While several biomarkers have been identified in patients with breast cancer, including ESR1 and PIK3CA mutations, not all of these are driver mutations that can be effectively targeted with treatment, he told an audience at the 16th Annual International Congress on the Future of Breast Cancer East, hosted by the Physicians’ Education Resource®, LLC (PER®). Esteva, professor of medicine, associate director of clinical investigation, and director of the Breast Medical Oncology Program, Laura and Isaac Perlmutter Cancer Center, New York University Langone Cancer, was there to explain the current understanding of the molecular landscape of metastatic breast cancer.
“We need to find the biomarkers that have a possibility to respond to treatment, monitor response, or understand treatment resistance,” he said.
The estrogen receptor, progesterone receptor, HER2, and activating BRCA mutations, which he noted are especially important to identity in the use of PARP inhibitors, are the essential biomarkers in the treatment of patients with breast cancer are at present. Clinical trials have also identified promising biomarkers in AKT1, PIK3CA, PTEN, ESR1, FGFR1 amplification, and more. However, there is difficulty in proving their clinical utility.
“Once we find a mutation, it is not always a driver mutation,” he said.
Esteva noted that the number of mutations in primary breast cancer tumors can vary widely. In an analysis of common mutations in patients with primary breast cancer, the Cancer Genome Atlas Network found that somatic non-silent PIK3CA mutations were commonly seen in luminal tumors, specifically the luminal A subtype (45%), which had the highest degree of significantly mutated genes, the luminal B subtype (29%), and in HER2-enriched tumors (39%).1 TP53 mutations were seen in 37% of cases, including 80% in basal-like tumors. Only 30% of cases showed a single driver mutation alone.
Researchers observed only a handful of frequent mutations metastatic breast cancer tumors compared with early breast cancer tumors: ESR1, FSIP2, AGRN, FRAS1, IGFN1, EDC4, OSBPL3, and PALB2.2 The ESR1 mutation was noted in approximately 30% of the metastatic breast cancer tumors, Esteva pointed out. The researchers determined ESR1 to be a driver mutation as well as a metastatic gene.
Lefebvre et al also found that patients with metastatic breast cancer and a somatic mutation in 1 of the 8 genes had a worse prognosis. Patients without driver mutations had a longer overall survival than those with driver mutations.
In an analysis of 4 studies involving endocrine therapy in patients with hormone receptor (HR)—positive advanced or metastatic breast cancer, researchers found ESR1 mutations in approximately 30% of patients.3 In the FERGI trial, 37.3% of patients harbored an ESR1 mutation, 39.1% in the SOFEA trial, 25.3% in the PALOMA-3 trial, and 28.8% in the BOLERO-2 trial.
As observed in these 4 studies, ESR1 mutations are prognostic and predictive biomarkers of resistance to aromatase inhibitors in patients with metastatic disease, but they can also be helpful in guiding treatment of endocrine-based therapies.
In results from the SOFEA trial, patients with ESR1 mutations demonstrated improved progression-free survival (PFS) rates with fulvestrant (Faslodex) when compared with exemestane (Aromasin) (HR, 0.52; 95% CI, 0.30-0.92; P = .02). Patients with wild-type ESR1 had similar PFS rates with either treatment (HR, 1.07; 95% CI, 0.68-1.67; P = .77).4
Results from PALOMA-3 showed that the addition of palbociclib (Ibrance) to fulvestrant improved PFS over fulvestrant monotherapy among patients with both ESR1-mutant (HR, 0.43; 95% CI, 0.25 to 0.74; P = .002) and ESR1 wild-type (HR, 0.49; 95% CI, 0.35 to 0.70; P <.001).
Researchers investigated the pan-PI3K inhibitor buparlisib in combination with fulvestrant in the phase III BELLE-3 trial compared with fulvestrant alone in patients with HR-positive locally advanced or metastatic breast cancer following progression on or after an mTOR inhibitor.5 Esteva said that the addition of buparlisib led to a small improvement with a PFS rate, 3.9 versus 1.8 months for placebo plus fulvestrant, representing a 33% reduction in the risk of progression or death (HR, 0.67; 95% CI, 0.53-0.84; P <.001).
Researchers performed tissue testing on 321 patients and detected PIK3CA-mutated tumors in 34%. The median PFS with the buparlisib combination in this patient population was 4.7 versus 1.4 months with fulvestrant alone (HR, 0.39; 95% CI, 0.23-0.65; P <.001). Patients with PIK3CA wild-type tumor derived less benefit from the combination; median PFS was 2.8 versus 2.7 months for buparlisib and placebo, respectively (HR, 0.83; 95% CI, 0.60-1.14; P = .117).
Median PFS with buparlisib was 4.2 months versus 1.6 months with fulvestrant plus placebo (HR, 0.46; 95% CI, 0.29-0.73; P <.001) in patients with PIK3CA-positive tumors detected by ctDNA analysis (n = 348; 39%). In the wild-type group, PFS with the PI3K inhibitor was 3.9 versus 2.7 months with placebo (HR, 0.73; 95% CI, 0.53-1.00; P = .026).
However, researchers observed a greater toxicity profile with the combination. Instead, Esteva suggested moving toward the higher specificity and bioactivity seen with the more tolerable PI3K-alpha inhibitors.
“If [the benefit of PI3K inhibitors in patients with PIK3CA mutations] is confirmed, particularly with the more tolerable PI3K-alpha selective inhibitors, this may be an area of research to select these patients,” he said.
To improve upon the discovery of biomarkers to aid in guiding precision medicine for patients with breast cancer in the future, Esteva recommended looking to pathway activation and dependency, multiple genomic alterations, and functional studies to find more actionable and accessible biomarkers.