The recent arrival of CDK4/6 inhibitor agents, with an approximate doubling of progression-free survival (PFS) associated with their use in hormone receptor-positive, HER2-negative advanced breast cancer (BC), has radically changed the approach to managing this disease. However, resistance to CDK4/6 inhibitors is considered a near-inevitability in most patients. Mechanisms of resistance to these agents are multifactorial, and research in this field is still evolving. Biomarkers with the ability to identify early resistance, or to predict the likelihood of successful treatment using CDK4/6 inhibitors are yet to be identified, and represent an area of unmet clinical need. Here we present selected mechanisms of resistance to CDK4/6 inhibitors, largely focussing on roles of Rb, cyclin E1, and the PIK3CA pathway, with discussion of associated biomarkers which have been investigated and applied in recent pre-clinical and clinical studies. These biological drivers may furthermore influence clinical treatment strategies adopted beyond CDK4/6 resistance.

No abstract

NCT02549430.

Purpose Detecting signals of micrometastatic disease in patients with early breast cancer (EBC) could improve risk stratification and allow better tailoring of adjuvant therapies. We previously showed that postoperative serum metabolomic profiles were predictive of relapse in a single-center cohort of estrogen receptor (ER)–negative EBC patients. Here, we investigated this further using preoperative serum samples from ER-positive, pre-menopausal women with EBC who were enrolled in an international phase III trial. Experimental Design Proton nuclear magnetic resonance (NMR) spectroscopy of 590 EBC samples (319 with relapse or ≥6 years clinical follow-up) and 109 metastatic breast cancer (MBC) samples was performed. A Random Forest (RF) classification model was built using a training set of 85 EBC and all MBC samples. The model was then applied to a test set of 234 EBC samples, and a risk of recurrence score was generated on the basis of the likelihood of the sample being misclassified as metastatic. Results In the training set, the RF model separated EBC from MBC with a discrimination accuracy of 84.9%. In the test set, the RF recurrence risk score correlated with relapse, with an AUC of 0.747 in ROC analysis. Accuracy was maximized at 71.3% (sensitivity, 70.8%; specificity, 71.4%). The model performed independently of age, tumor size, grade, HER2 status and nodal status, and also of Adjuvant! Online risk of relapse score. Conclusions In a multicenter group of EBC patients, we developed a model based on preoperative serum metabolomic profiles that was prognostic for disease recurrence, independent of traditional clinicopathologic risk factors.

Randomized clinical trials demonstrated that CDK4/6 inhibitors are highly effective in patients with hormone receptor-positive (HR+), HER2-negative (HER2-) metastatic breast cancer in combination with endocrine therapy. The use of CDK4/6 inhibitors in clinics is becoming common for patients with HR+/HER2- metastatic breast cancer and will certainly increase in the near future. However, patients might show de novo or acquired resistance to these drugs. Molecular alterations have been suggested as determinants for de novo resistance to CDK4/6 inhibitors, but have never been validated in a clinical setting. In addition, molecular mechanisms of acquired resistance to palbociclib have been analyzed only in preclinical studies. Here we review the current knowledge on the available preclinical data about the mechanisms of de novo and acquired resistance to CDK4/6 inhibitors in breast cancer, and clinical data about potential biomarkers of response.