Emerging Biomarkers Inform Therapy Choice in HR+ Breast Cancer

Targeted Therapies in OncologySeptember 2022
Volume 11
Issue 12
Pages: 93

Clinicians use their knowledge of emerging subtypes and biomarkers, which provide a hint at possible outcomes, to select therapy from among the ever-increasing treatment armamentarium.

Debu Tripathy, MD

Debu Tripathy, MD

For years, breast cancers’ hormone receptor (HR) and HER2 statuses, as determined by immunohistochemical staining, have guided clinicians in choosing the most appropriate therapies. Clinicians use their knowledge of emerging subtypes and biomarkers, which provide a hint at possible outcomes, to select therapy from among the ever-increasing treatment armamentarium.

These biomarkers can be prognostic, predictive, or a combination of both.1 Prognostic markers assess the underlying biology of the cancer and are used to indicate how the patient will fare regardless of treatment, if treatment is needed at all. Predictive markers indicate how the patient will respond to a particular therapy, which can help determine which treatment to give. Predictive markers are often associated with sensitivity or resistance to particular drugs and may be—but are not necessarily—the target of the drug in question. Increasingly, such predictive markers can be detected in circulating tumor DNA to avoid the logistical challenges, invasive nature, and sampling errors inherent in repetitive tissue biopsies. They can then be harnessed to get the correct treatments to patients who will benefit from them, while sparing those who would not benefit the adverse effects, stress, and expense of unnecessary treatments.

According to Debu Tripathy, MD, professor of medicine and chair of the Department of Breast Medical Oncology, Division of Cancer Medicine, at The University of Texas MD Anderson Cancer Center in Houston, Texas, personalized medicine is not on the horizon—it is here. “Right now, genomic screening is very important in patients as soon as they [receive a diagnosis of] advanced metastatic cancer because there are already targeted therapies that can be used as their first treatment. If patients want to be included in clinical trials, genomic screening allows their therapeutic options to grow even more [because] if they harbor certain mutations, they may be eligible to get drugs that target that mutation but have not yet been approved. The field is changing so quickly; we continue to discover new mutations and develop new drugs that target them. One day, genomic screening will be used to monitor the patient’s response to treatment.”

Current Biomarkers for HR+ Breast Cancers

Approximately 80% of breast tumors are classifi ed as HR-positive (HR+) because they express the estrogen receptor (ER),2 so they respond to selective ER modulators such as tamoxifen (Soltamox), raloxifene (Evista), and toremifene (Fareston), as well as aromatase inhibitors. Somatic mutations in ESR1 are associated with acquired resistance to these drugs, with ESR1 mutations found in approximately 20% of patients with metastatic ER+ breast cancer.3 They are associated with poorer outcomes than in patients with ESR1 wild-type disease.2 Acquired resistance to aromatase inhibitors is considered inevitable in patients with metastatic cancers. Newer drugs that can thwart this acquired resistance are in clinical trials, such as the HDAC inhibitor entinostat and selective ER degraders (SERDs).2,4 These drugs induce expression of ESR1 so the tumors become sensitive to endocrine therapy again.

Approximately 15% to 20% of breast cancers are HER2+, and patients with this cancer have a poorer prognosis than those with HER2-negative (HER2–) cancers. HER2 is targeted by the monoclonal antibodies trastuzumab (Herceptin) and pertuzumab (Perjeta) and the small molecule inhibitor lapatinib (Tykerb). It is thus a predictive as well as a diagnostic biomarker, indicating sensitivity to these drugs.

The presence of somatic mutations in other genes regulating cell growth can tell clinicians if a tumor harboring them will be resistant or susceptible to the next generation of chemotherapies, which were developed in response to the development of acquired resistance to hormone-based treatments. For example, tumors with amplification of FGFR1 or loss of PTEN or Rb1 are predictive for resistance to CDK4/6 inhibitors such as palbociclib (Ibrance), abemaciclib (Verzenio), and ribociclib (Kisqali), which slow cell growth.5,6 Results of a study showed that among patients with ER+ advanced breast cancer who developed resistance to CDK4/6 inhibition, some acquired Rb1 loss and others acquired PTEN loss.6 This is important because, in the metastatic setting, such CDK4/6 inhibitors combined with endocrine therapy represent the current gold standard of care.

Mutations in PIK3CA are prognostic biomarkers associated with improved survival in patients with early-stage HR+/HER2– breast cancer. A pooled analysis showed a hazard ratio of 1.67, which suggests that PIK3CA mutation was an independent negative prognostic factor in breast cancer (95% CI, 1.15-2.43; P = .007).7 These are the most common genomic alterations in breast cancer; up to 40% of patients with ER+ breast cancer also have activating PIK3CA mutations. It also is one of the biomarkers most commonly screened for, because there are approved drugs that target it. The presence of PIK3CA mutations in metastatic cancer are used to predict a sensitivity to PI3 kinase inhibitors such as alpelisib (Piqray), taselisib, and copanlisib (Aliqopa), as only patients with these mutations respond to these therapies. Alterations in the PI3K/AKT/PTEN pathway likewise lead to uncontrolled cell growth and are associated with sensitivity to AKT inhibitors.

Tumors with mutations in genes responsible for DNA damage repair, including BRCA1/2, TP53, and RAD51c are sensitive to PARP inhibitors such as olaparib (Lynparza), rucaparib (Rubraca), niraparib (Zejula), and talazoparib (Talzenna).8 In breast ancer specifi cally, 2 PARP inhibitors approved for patients with metastatic breast cancer who are germline BRCA mutation carriers have demonstrated significant survival benefits.9

Since these approvals, recommendations for genetic testing among patients with breast cancer have changed.9 Consensus guidelines from the American Society of Breast Surgeons recommend that genetic testing be made available to all patients with a history of breast cancer.10 The National Comprehensive Cancer Network (NCCN) recommends genetic testing and counseling for patients with high familial/ genetic risk of developing breast cancer.11

The Breast Cancer Index (BCI) is a genomic assay to assess disease recurrence.12 It analyzes the activity of 11 genes to help predict the risk of early-stage HR+/HER2– breast cancer recurring 5 to 10 years after diagnosis. It is currently the only test recognized by the NCCN to predict if patients might benefit from more than 5 years of endocrine therapy. It starts with the traditional histologic breast cancer subtypes, then overlays the genomic biomarker data on top of those. The American Society of Clinical Oncology recommends that the BCI be offered to postmenopausal patients with 0 to 3 positive nodes after 5 years of endocrine therapy and no evidence of recurrence to see if they should continue treatment. There is currently not enough clinical evidence to support its utility in patients who have 4 or more nodes. It may not be as reliable in patients with other health conditions, and patients may have to pay for it themselves, which doctors should consider before recommending it.

Future Biomarkers for HR+ Breast Cancer

Studies are ongoing to identify more biomarkers and continue to validate and hone those already in use. The I-SPY2 neoadjuvant platform trial (NCT01042379) is an ongoing, multicenter trial that is collating gene expression data, protein phosphorylation data (phosphoproteins tend to have greater predictive specificity than expression-based biomarkers), and clinical response data in almost 1000 patients with early-stage breast cancer who were treated with 10 different novel drug regimens (plus paclitaxel).13 It takes a different approach than BCI, which appends genomic tests onto traditional breast cancer subtypes. Instead, I-SPY2 investigators’ goal is to rapidly identify new treatments and the subsets of patients who will best respond to them.

Kevin Kalinsky, MD, MS

Kevin Kalinsky, MD, MS

To that end, the investigators are refi ning breast cancer subtypes with new biomarkers to further refi ne treatment guidance and selection. Investigators found that incorporating immune and DNA repair defi ciency (DRD) phenotypes into the standard HR/HER2 matrix could improve pathologic complete response rates by as much as 15% or more in patients who are HR+. They settled on including these parameters because drugs that target them are already available. Their schema resulted in 5 response-predictive subtypes (HER2–/Immune–/DRD–, HER2–/Immune+, HER2–/Immune–/DRD+, HER2+/BluePrint [BP]-HER2_or_Basal, and HER2+/BP-Luminal) instead of the original 4 according to tumor receptors (HR–/HER2+, HR+/HER2+, HR+/HER2–, and triple negative) (FIGURE 1 and 213).

16α[18F]fl uoro-17β-estradiol (FES)-PET is an imaging technique used to measure how much estrogen binds to the ERs present in the tumors.14 H igher F ES-PET u ptake i s a positive prognostic marker and a predictive biomarker that indicates sensitivity to SERDs. It is promising but has thus far only been assessed in clinical trials, including an ongoing phase 2 study (NCT02398773).2,14

Many of the new drugs in development target mechanisms of action beyond HR and HER2. In order to harness them effectively, more studies such as this are required to make sure that all of the patients who will benefit from a given drug will get it and avoids added adverse events and expense for patients who are not likely to benefit.

As Kevin Kalinsky, MD, MS, associate professor in the Department of Hematology and Medical Oncology at Emory University School of Medicine in Atlanta, Georgia, said: “Research is ongoing to identify more agents that successfully target mutations, and even in cases where we already have therapeutics, research is ongoing to improve the targeting to focus only on that mutation to minimize off-target and adverse effects.”


1. Weigel MT, Dowsett M. Current and emerging biomarkers in breast cancer: prognosis and prediction. Endocr Relat Cancer. 2010;17(4):R245-R262. doi:10.1677/ERC-10-0136

2. Freelander A, Brown LJ, Parker A, et al. Molecular biomarkers for contemporary therapies in hormone receptor-positive breast cancer. Genes (Basel). 2021;12(2):285. doi:10.3390/genes12020285

3. Jeselsohn R, Buchwalter G, De Angelis C, Brown M, Schiff R. ESR1 mutations—a mechanism for acquired endocrine resistance in breast cancer. Nat Rev Clin Oncol. 2015;12(10):573-583. doi:10.1038/nrclinonc.2015.117

4. Schick J, Ritchie RP, Restini C. Breast cancer therapeutics and biomarkers: past, present, and future approaches. Breast Cancer (Auckl). 2021;15:1178223421995854. doi:10.1177/1178223421995854

5. Asghar US, Kanani R, Roylance R, Mittnacht S. Systematic review of molecular biomarkers predictive of resistance to CDK4/6 inhibition in metastatic breast cancer. JCO Precis Oncol. 2022;6:e2100002. doi:10.1200/PO.21.00002

6. Costa C, Wang Y, Ly A, et al. PTEN loss mediates clinical cross-resistance to CDK4/6 and PI3Kα inhibitors in breast cancer. Cancer Discov. 2020;10(1):72-85. doi:10.1158/2159-8290.CD-18-0830

7. Sobhani N, Roviello G, Corona SP, et al. The prognostic value of PI3K mutational status in breast cancer: a meta-analysis. J Cell Biochem. 2018;119(6):4287-4292. doi:10.1002/jcb.26687

8. Li H, Liu ZY, Wu N, et al. PARP inhibitor resistance: the underlying mechanisms and clinical implications. Mol Cancer. 2020;19(1):107. doi:10.1186/s12943-020-01227-0

9. Tung N, Garber JE. PARP inhibition in breast cancer: progress made and future hopes. NPJ Breast Cancer. 2022;8(1):47. doi:10.1038/s41523-022-00411-3

10. Manahan ER, Kuerer HM, Sebastian M, et al. Consensus guidelines on genetic testing for hereditary breast cancer from the American Society of Breast Surgeons. Ann Surg Oncol. 2019;26(10):3025-3031. doi:10.1245/s10434-019-07549-8

11. Daly MB, Pal T, Berry MP, et al. Genetic/familial high-risk assessment: breast, ovarian, and pancreatic, version 2.2021, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Net. 2021;19(1):77-102. doi:10.6004/jnccn.2021.0001

12. Andre F, Ismaila N, Allison KH, et al. Biomarkers for adjuvant endocrine and chemotherapy in early-stage breast cancer: ASCO guideline update [published correction appears in J Clin Oncol. 2022;40(22):2514]. J Clin Oncol. 2022;40(16):1816-1837. doi:10.1200/JCO.22.00069

13. Wolf DM, Yau C, Wulfkuhle J, et al. Redefining breast cancer subtypes to guide treatment prioritization and maximize response: predictive biomarkers across 10 cancer therapies. Cancer Cell. 2022;40(6):609-623.e6. doi:10.1016/j.ccell.2022.05.005

14. Kurland BF, Peterson LM, Lee JH, et al. Estrogen receptor binding (18f-FES PET) and glycolytic activity (18F-FDG PET) predict progression-free survival on endocrine therapy in patients with ER+ breast cancer. Clin Cancer Res. 2017;23(2):407-415. doi:10.1158/1078-0432.CCR-16-0362

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