Dynamic changes of Receptor activator of nuclear factor-κB expression in Circulating Tumor Cells during Denosumab predict treatment effectiveness in Metastatic Breast Cancer.
Francesco PantanoElisabetta RossiMichele IulianiAntonella FacchinettiSonia SimonettiGiulia RibelliAlice ZoccoliBruno VincenziGiuseppe ToniniRita ZamarchiDaniele SantiniPublished in: Scientific reports (2020)
Receptor-activator of nuclear-factor -κB-ligand (RANKL) and its receptor RANK have been recently identified as key players in breast cancer bone metastases. Since Circulating Tumor Cells (CTCs) are considered a crucial step of metastatic process, we explored RANK expression on CTCs in metastatic breast cancer (MBC), and the predictive value of RANK-positive CTCs in monitoring patients during treatment with denosumab (anti-RANKL antibody). To this purpose, we developed a novel CTC assay to quantify RANK-positive CTCs in forty-two bone MBC patients, candidates to denosumab treatment. Companion algorithms ΔAUC and Slope were developed, and correlated with time to first skeletal-related-events (SRE), time to bone metastasis progression and time to visceral metastasis progression. Twenty-seven patients had at least one CTC at baseline and, among these, nineteen (70%) had one or more RANK-positive CTCs. Notably, the baseline total CTCs, but not the RANK-positive, were associated with Time-to-first-SRE, Time-to-Bone-Metastasis-Progression and Time-to-Visceral-Metastasis-Progression. Conversely, during treatment monitoring, positive ΔAUC value, expression of RANK-positive CTCs persistence, correlated with longer Time-to-first-SRE (p = 0.0002) and Time-to-Bone-Metastasis-Progression (p = 0.0012). Furthermore, the early increase at second day, in RANK-positive CTCs (Positive-Slope) was associated with delay in time-to-first-SRE (p = 0.0038) and Time-to-Bone-Metastasis-Progression (p = 0.0024). We demonstrate, for the first time, the expression of RANK on CTCs in MBC patients and that the persistence of RANK expression determines denosumab effectiveness.
Keyphrases
- circulating tumor cells
- nuclear factor
- end stage renal disease
- bone mineral density
- newly diagnosed
- chronic kidney disease
- prognostic factors
- ejection fraction
- metastatic breast cancer
- randomized controlled trial
- systematic review
- toll like receptor
- adipose tissue
- machine learning
- bone loss
- insulin resistance
- young adults
- patient reported outcomes
- metabolic syndrome
- soft tissue
- body composition
- single cell
- patient reported
- deep learning
- replacement therapy
- childhood cancer