Longitudinally collected CTCs and CTC-clusters and clinical outcomes of metastatic breast cancer.

Journal: Breast Cancer Research And Treatment
Published:
Abstract

Purpose: Circulating tumor cell (CTC) is a well-established prognosis predictor for metastatic breast cancer (MBC), and CTC-cluster exhibits significantly higher metastasis-promoting capability than individual CTCs. Because measurement of CTCs and CTC-clusters at a single time point may underestimate their prognostic values, we aimed to analyze longitudinally collected CTCs and CTC-clusters in MBC prognostication.

Methods: CTCs and CTC-clusters were enumerated in 370 longitudinally collected blood samples from 128 MBC patients. The associations between baseline, first follow-up, and longitudinal enumerations of CTCs and CTC-clusters with patient progression-free survival (PFS) and overall survival (OS) were analyzed using Cox proportional hazards models.

Results: CTC and CTC-cluster counts at both baseline and first follow-up were significantly associated with patient PFS and OS. Time-dependent analysis of longitudinally collected samples confirmed the significantly unfavorable PFS and OS in patients with ≥5 CTCs, and further demonstrated the independent prognostic values by CTC-clusters compared to CTC-enumeration alone. Longitudinal analyses also identified a link between the size of CTC-clusters and patient OS: compared to the patients without any CTC, those with 2-cell CTC-clusters and ≥3-cell CTC-clusters had a hazard ratio (HR) of 7.96 [95 % confidence level (CI) 2.00-31.61, P = 0.003] and 14.50 (3.98-52.80, P < 0.001), respectively.

Conclusions: In this novel time-dependent analysis of longitudinally collected CTCs and CTC-clusters, we showed that CTC-clusters added additional prognostic values to CTC enumeration alone, and a larger-size CTC-cluster conferred a higher risk of death in MBC patients.

Authors
Chun Wang, Zhaomei Mu, Inna Chervoneva, Laura Austin, Zhong Ye, Giovanna Rossi, Juan Palazzo, Carl Sun, Maysa Abu Khalaf, Ronald Myers, Zhu Zhu, Yanna Ba, Bingshan Li, Lifang Hou, Massimo Cristofanilli, Hushan Yang
Relevant Conditions

Breast Cancer