Updates in the treatment of HR+HER2- breast cancer.

PURPOSE OF REVIEW: Breast cancer (BC) is the most common cancer among women in the United States and the second leading cause of cancer death. BC research, diagnostics, drug development, and expansion of therapies for novel indications advances so rapidly that BC treatment standards change month-by-month. Herein we discuss notable advancements in the past year for hormone receptor positive (HR+) HER2 negative (HER2-) BC. RECENT FINDINGS: Radiolabeled estradiol imaging and circulating tumor DNA (ctDNA) have changed our approach to metastatic BC (mBC) detection. Amongst an abundance of therapy options, treatment de-escalation to avoid toxicities is a priority. Promising results with CDK4/6 inhibitors in the curative setting have been demonstrated even as we await final data for use in the metastatic setting. Several novel endocrine therapies are expected to gain FDA-approval in the near future. Antibody-drug conjugates have expanded from other mBC types to HR+HER2- mBC. The PROMISE trial helped define disease recurrence outcomes for premenopausal women seeking pregnancy. SUMMARY: The diagnostic and treatment landscape for HR+HER2- BC continues to rapidly evolve on multiple fronts.

Selection of appropriate biomarkers to monitor effectiveness of ovarian function suppression in pre-menopausal patients with ER+ breast cancer.

Use of gonadotropin-releasing hormone (GnRH) agonists has been widely adopted to provide reversible ovarian function suppression for pre-menopausal breast cancer patients who are also receiving aromatase inhibitor or tamoxifen therapy based on results of 25 randomized trials representing almost 15,000 women demonstrating a survival benefit with this approach. Past clinical trials designed to establish the efficacy of GnRH agonists have monitored testosterone in the prostate cancer setting and estradiol in the breast cancer setting. We explore the merits of various biomarkers including estradiol, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) and their utility for informing GnRH agonist treatment decisions in breast cancer. Estradiol remains our biomarker of choice in ensuring adequate ovarian function suppression with GnRH agonist therapy among pre-menopausal women with breast cancer. We recommend future trials to continue to focus on estradiol levels as the primary endpoint, as they have in the past.

Quantitative Predictors of Response to Neoadjuvant Chemotherapy on Dynamic Contrast-enhanced 3T Breast MRI.

OBJECTIVE: To assess whether changes in quantitative parameters on breast MRI better predict pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer than change in volume. METHODS: This IRB-approved retrospective study included women with newly diagnosed breast cancer who underwent 3T MRI before and during NAC from January 2013 to December 2019 and underwent surgery at our institution. Clinical data such as age, histologic diagnosis and grade, biomarker status, clinical stage, maximum index cancer dimension and volume, and surgical pathology (presence or absence of in-breast pCR) were collected. Quantitative parameters were calculated using software. Correlations between clinical features and MRI quantitative measures in pCR and non-pCR groups were assessed using univariate and multivariate logistic regression. RESULTS: A total of 182 women with a mean age of 52 years (range, 26-79 years) and 187 cancers were included. Approximately 45% (85/182) of women had pCR at surgery. Stepwise multivariate regression analysis showed statistical significance for changes in quantitative parameters (increase in time to peak and decreases in peak enhancement, wash out, and Kep [efflux rate constant]) for predicting pCR. These variables in combination predicted pCR with 81.2% accuracy and an area under the curve (AUC) of 0.878. The AUCs of change in index cancer volume and maximum dimension were 0.767 and 0.613, respectively. CONCLUSION: Absolute changes in quantitative MRI parameters between pre-NAC MRI and intra-NAC MRI could help predict pCR with excellent accuracy, which was greater than changes in index cancer volume and maximum dimension.